Substrates for surface-enhanced spectroscopy

Abstract

A method for preparing an SES substrate includes preparing the substrate and providing a nanoparticle layer on the substrate. The nanoparticle layer contains metal nanoparticles. The nanoparticle layer is subjected to an oxidation cleaning step, thereby creating an oxide coating on the surface of the nanoparticles. Subsequently, the nanoparticle layer is subjected to a redefinition step, in which the oxide coating is removed in the presence of a scaffolding ligand, the scaffolding ligand is placed between adjacent nanoparticles, and their relative spacing is defined for use in subsequent SES analysis. The SES is either SERS or SEIRA. A method for performing SES analysis is also disclosed.

Description

[Technical Field]

[0001] Acknowledgments for funding The project leading to this application is funded by the EPSRC Sensor Technology Doctoral Training Center for a Healthy and Sustainable Future. Grant number: EP / S023046 / 1 The project leading to this application is funded by the Research Council for Engineering Physics. Grant number: EP / X037770 / 1 The project leading to this application is funded by the Research Council for Engineering and Physical Sciences. Grant number: EP / T517847 / 1

[0002] Field of Invention The present invention relates to a substrate for use in surface-enhanced spectroscopy (SES), a method for manufacturing such a substrate, and a method for preparing such a substrate. [Background technology]

[0003] In this disclosure, indications such as [1] indicate reference disclosures, the complete bibliographic details of which are provided at the end of the description.

[0004] Surface-enhanced spectroscopy (SES) refers to the enhancement of the spectral response of a particular method using a surface. For example, surface-enhanced Raman spectroscopy (SERS) is an optical technique in which the inelastic Raman scattering of light by the analyte is enhanced by electromagnetic field amplification when light is confined to spaces between specific metal nanostructures called "hot spots." [1] Surface-enhanced infrared absorption spectroscopy (SEIRA) is an optical technique that enhances the absorption of infrared light by the same electromagnetic field amplification. Both SERS and SEIRA can provide fingerprint spectra of analyte molecules and hold great potential for low-cost home or clinic applications in healthcare, biofluid analysis, and sensing, especially when using nanoparticle layer-based SES substrates. [Overview of the project] [Problems that the invention aims to solve]

[0005] To effectively utilize SES for sensing applications, it is necessary that the nanoparticle layer-based SES substrate is stable, reproducible, easy to manufacture, and has high reliability for SES enhancement. [1] Accurately defined hot spots can enhance the reproducibility of SES signals, and by selecting the spacing between nanoparticles, the confined plasmon modes can be adjusted to resonate with common laser wavelengths. [1] Due to reproducibility, in addition to identification, the analyte can also be quantified with high sensitivity.

[0006] It is also desirable that the nanoparticle layer-based SES substrate can be reused for continuous measurements without significantly degrading its performance. Such performance enables, for example, effective sensing of the "inflow" of biological fluids, which usually leads to rapid contamination of the substrate.

[0007] Methods utilizing aggregation and self-assembly have been demonstrated to be able to easily manufacture nanoparticle layer-based SES substrates at low cost. [2-16] However, since synthesized nanoparticles often contain additional chemicals and surfactants to enhance storage period and functionality, surface chemistry control can be a problem with these substrates. Surface molecules cannot be completely removed even by ligand exchange, there is a risk of interfering with the binding of target analytes, and SES sensitivity decreases by blocking hot spots.

[17] Variations in surfactants between batches and aging of nanoparticles

[18] can reduce the uniformity and reproducibility of these substrates.

[0008] Attempts have been made to develop methods to make the SES substrate washable and reusable. [19-20] However, in these methods, activity is generally lost, hindering practical application.

[0009] The present invention has been devised in consideration of the above considerations.

Means for Solving the Problems

[0010] The inventors recognized that it would be advantageous to be able to manufacture SES substrates in a way that allows for precise control of the spacing between the nanoparticles. It would also be advantageous to be able to tune the SES substrates for similar purposes. Further, it is advantageous to provide a method for recycling SES substrates with little or limited reduction in activity.

[0011] In a first aspect, the present invention provides a method for tuning an SES substrate, comprising: providing a substrate, providing a layer of nanoparticles on the substrate, wherein the layer of nanoparticles comprises metal nanoparticles, subjecting the layer of nanoparticles to an oxidation cleaning step, thereby generating an oxide coating on the surface of the nanoparticles, and subsequently subjecting the layer of nanoparticles to a redefinition step, wherein the oxide coating is removed in the presence of a scaffolding ligand that is disposed between adjacent nanoparticles and their relative spacing is defined for use in subsequent SES analysis.

[0012] In this case, SES refers to surface enhanced spectroscopy. SES refers to spectroscopy in which the measurement signal is enhanced by amplification by the surface. SES is a result of light field enhancement in the nanogap between adjacent nanoparticles and is known as plasmonic enhancement. SES may refer to surface enhanced Raman spectroscopy (SERS), surface enhanced infrared absorption spectroscopy (SEIRA), or other surface enhanced spectroscopy.

[0013] The layer of nanoparticles is provided on the substrate. The layer of nanoparticles may be provided by a suitable route based on self-assembly of the nanoparticles. The layer of nanoparticles may be provided by evaporation deposition and aggregation, which may include formation of a monolayer of nanoparticles in a two-phase solvent system, formation of droplets containing the monolayer, and transfer thereof onto the substrate. The layer of nanoparticles may be adhered to the substrate. Adhesion of the layer of nanoparticles may be facilitated by providing an adhesion coating (e.g., a metal chromium coating) on the substrate.

[0014] In a second embodiment, the present invention provides a prepared SES substrate obtained by or obtained by a preparation method according to the first embodiment of the present invention.

[0015] A preparation method according to a first aspect of the present invention enables precise control of the nanogap spacing between adjacent nanoparticles through the introduction of a scaffolding ligand. SES substrates prepared according to the first aspect of the present invention exhibit uniform gap spacing regardless of how the nanoparticle layer was initially formed. SES substrates produced by such preparation exhibit highly reliable SES spectra with extremely low relative variation, making them particularly useful for sensing applications and opening up the possibility of use in methods for quantifying the concentration of analytes.

[0016] The nanoparticle gap spacing (nanogap spacing) refers to the size of the nanogap in the nanoparticle layer of this invention. More specifically, a nanogap is the closest gap between adjacent nanoparticles.

[0017] In a third embodiment, the present invention provides a method for carrying out SES, the method comprising providing an SES substrate comprising a substrate and a nanoparticle layer on the substrate, wherein the nanoparticle layer comprises metal nanoparticles, and the method further comprises the following steps: A first SES analysis is performed using the aforementioned SES substrate. The nanoparticle layer is subjected to an oxidation cleaning step. By subjecting the aforementioned nanoparticle layer to a redefinition step, a recycled SES substrate is provided, and A second SES analysis is performed on the recycled SES substrate.

[0018] A third aspect of the present invention, a method for performing SES, namely, using an SES substrate for SES analysis and then reusing it for subsequent analysis, is made possible only by reliable and reproducible SES enhancement achieved by an SES substrate subjected to a combination of an oxidative cleaning step and a subsequent redefinition step.

[0019] The reuse of SES substrates offers significant advantages. The manufacturing costs of these substrates are high, and they may contain rare metals. The ability to reuse SES substrates enables sensing of inflow in various application fields. The ability to readjust SES substrates allows for control over the analytes that can be sensed by altering the bonding of surface analytes and the chemical properties within the nanogap.

[0020] Further optional features of the present invention are described below. Unless otherwise specified in the context, these may be applied individually or in any combination with any aspect of the present invention.

[0021] In some embodiments, the oxidative cleaning step acts to detach molecules bound to the surface of the nanoparticles. Since synthesized nanoparticles often contain additional chemicals and surfactants to enhance shelf life and functionality (whether commercially available or in-house manufactured), controlling the surface chemistry can be a challenge with nanoparticle-based substrates.

[0022] The oxidation cleaning step can completely remove these additional chemicals and surfactants to create a pure nanoparticle surface. The oxidation cleaning step can produce oxide-coated nanoparticles that are substantially free of surface-binding molecules by decomposing, oxidizing, etching, removing, exfoliating, or otherwise changing surface-binding molecules (e.g., reducing their binding affinity to the nanoparticle surface), or a combination thereof.

[0023] The oxidation cleaning step generates an oxide coating on the surface of the nanoparticles. This oxide coating is several molecular layers thick and can spread into the gaps between adjacent nanoparticles, filling the entire volume of the gaps. The oxidation cleaning step may involve comprehensive oxidation of the nanoparticle surface over a long period of time, sufficient to create a stable oxide coating. This oxide coating may be substantially composed of the metals that make up the nanoparticles.

[0024] The oxidation cleaning step creates an oxide coating or layer on the surface of the nanoparticles, thereby stabilizing the nanoparticle layer against sintering or other forms of degradation, which can affect the plasmonic field enhancement effect and ultimately impact the response enhancement of the SES technology.

[0025] In some embodiments, the metal nanoparticles are selected from one or more metals that support surface plasmons at optical or mid-infrared frequencies.

[0026] SES relies on the amplification of electromagnetic radiation (such as laser light) by a local electric field generated by the resonant collective motion of surface electrons called plasmons. SERS and SEIRA use light of optical or mid-infrared frequencies to investigate the vibrational states of analyte molecules present in hot spots on an SES substrate; therefore, in these methods, the metal nanoparticles must be metals that can support plasmons that can resonate at these frequencies.

[0027] In some embodiments, the metal nanoparticles are one or more metals selected from the group consisting of gold (Au), silver (Ag), copper (Cu), and aluminum (Al). The metal nanoparticles may be gold nanoparticles. The metal nanoparticles may be silver nanoparticles. The metal nanoparticles may be copper nanoparticles. The metal nanoparticles may be aluminum nanoparticles. At least the core of the nanoparticles may be formed from one or more nanoparticles selected from the group consisting of gold (Au), silver (Ag), copper (Cu), and aluminum (Al). The oxide layer formed may be an oxide of any of the aforementioned metals.

[0028] The diameter of the metal nanoparticles may be 15 nm or more, or 60 nm or more. In some embodiments, for example in the case of SEIRA, the nanoparticles may have a relatively large diameter, for example, up to 10 μm. The upper limit of the nanoparticle diameter can be, for example, 5 μm, 1 μm, 800 nm, 600 nm, 400 nm, 200 nm, 160 nm, or 120 nm. In some embodiments, the nanoparticle diameter is in the range of 15 to 120 nm. The diameter of the metal nanoparticles may be in the range of 60 to 100 nm. The diameter of the metal nanoparticles may be in the range of 60 to 80 nm. The diameter of the metal nanoparticles may be approximately 80 nm. The shape of the nanoparticles is not particularly limited, but may be substantially spherical. References to the diameter of the nanoparticles usually refer to the average diameter.

[0029] In some embodiments, the surface of metal nanoparticles is coated with palladium (Pd) or platinum (Pt). The thick Pd or Pt coating can be achieved by chemical reduction, electrochemical deposition, or underpotential deposition. In the case of electrochemical underpotential deposition, the thickness can be controlled in the range of 0 to 3 atomic layers (including partial atomic layers).

[0030] In some embodiments, the nanoparticle layer is a single-layer nanoparticle layer, a multilayer nanoparticle layer, or a nanoparticle layer having a single-layer nanoparticle region and a multilayer nanoparticle region. The multilayer nanoparticle region may be a two-layer or three-layer region.

[0031] Because the nanoparticle layer consists of a small number of layers (single, double, or multilayer), good access of the oxygen plasma to the nanogap is possible when oxygen plasma is used to perform oxidative cleaning. It also provides a nanogap for scaffolding ligands during the redefinition step and good access to the analyte being probed during SES analysis.

[0032] In the multilayer region, a stronger electron field enhancement effect is generated, which is thought to result in greater response amplification in SES experiments.

[0033] In some embodiments, the redefinition step includes removing the oxide coating under reducing or acidic conditions in the presence of a scaffolding ligand.

[0034] Reducing conditions can be generated by one or more reducing agents, a scaffolding ligand acting as a reducing agent, or a negative voltage applied to the SES substrate within an electrochemical cell. In other words, reducing conditions are those under which the oxide coating can be removed by reduction.

[0035] Here, an electrochemical cell means that a nanoparticle layer is attached to a conductive substrate that functions as a working electrode, and an ionic solution is immersed in this nanoparticle layer and comes into contact with a counter electrode to which a potential difference is applied. This counter electrode can be controlled via a third reference electrode that measures and controls the potential difference. The conductive substrate may be a metal substrate, or a transparent conductive layer coated on any substrate such as indium tin oxide or fluorine-doped indium tin oxide.

[0036] Acidic conditions can be created by one or more acids or acidic scaffolding ligands. Acidic conditions are generally pH < 7, but more preferably pH < 3.

[0037] In some embodiments, the redefinition step includes removing the oxide coating using an acid or reducing agent in the presence of a scaffolding ligand.

[0038] In some embodiments, the redefinition step includes removing the oxide coating thermally (i.e., by heating) or by ultraviolet light in the presence of a scaffolding ligand.

[0039] In some embodiments, the redefinition step includes removing the oxide coating under acidic or neutral pH conditions in the presence of a scaffolding ligand and halide ions.

[0040] The redefinition step involves removing the oxide coating. This may include reduction, hydrolysis, exfoliation, or a combination thereof of the oxide coating. In the redefinition step, scaffolding ligands are placed between nanoparticles to stabilize the nanogap between nanoparticles and control the size of the nanogap. In this sense, the scaffolding ligands are thought to prevent deformation of the nanoparticles and prevent sintering of the nanoparticles through deformation of the nanoparticles or bridging between adjacent nanoparticles by the flow of gold atoms. Therefore, the scaffolding ligands may act as chemical spacers and have sufficient rigidity to stabilize the nanogap. In this disclosure, “rescafolding” is synonymous with “redefinition”.

[0041] In some embodiments, the scaffolding ligand is one or more molecules having a binding affinity to the surface of metal nanoparticles. The scaffolding ligand may be one or more molecules having a preferred affinity for binding to the surface of metal nanoparticles. The scaffolding ligand may be a hydrophilic molecule or a molecule having at least one hydrophilic moiety, or the scaffolding ligand may be a polar molecule or a molecule having at least one polar moiety. The scaffolding ligand can bind the analyte to the nanogap.

[0042] In some embodiments, the scaffolding ligand is one or more molecules selected from the group consisting of cucurbits[n]uryl, polystyrene molecules, 3-mercaptopropionic acid, citrate, acetic acid, cysteamine, dopamine, paracetamol, ethanol, and methanol.

[0043] After the redefinition step, the nanoparticle layer can be rinsed with deionized water (DI) and blow-dried.

[0044] In some embodiments, the surface of the nanoparticles includes a sensitizer that promotes the binding of molecules to the nanoparticles. The sensitizer may be introduced to the surface of the nanoparticles before the nanoparticle layer is formed, or the sensitizer may be added to the nanoparticle layer after the nanoparticle layer has been formed. The sensitizer may bind the analyte or scaffolding ligand to the nanogap. The sensitizer may be Fe(III).

[0045] In some embodiments, the substrate comprises a dielectric or polymer. The substrate may include glass, silicon nitride, or silicon. The substrate can be a flexible polymer; for example, the substrate may be PMMA. The substrate is transparent to the laser wavelengths used in SES technology (e.g., the substrate is optically transparent), allowing for back-side illumination of the nanoparticle layer. This configuration is particularly useful in sensing applications.

[0046] In some embodiments, the substrate is conductive. The substrate may be a metal, or a dielectric or polymer including a conductive coating. The substrate may be gold-coated silicon.

[0047] In some embodiments, the oxidation cleaning step includes oxygen plasma treatment, in which the nanoparticle layer is exposed to oxygen plasma. Oxygen plasma treatment may include passing oxygen plasma over the nanoparticle layer or exposing the nanoparticle layer to an environment containing oxygen plasma. Here, oxygen plasma refers to atoms, molecules, ions, electrons, free radicals, metastable states, and photons generated by applying a high voltage to oxygen gas.

[0048] In some embodiments, the oxidative cleaning step includes electrochemical oxidation, in which a positive voltage is applied to the entire SES substrate within an electrochemical cell.

[0049] In some embodiments, the redefinition step includes removing the oxide coating by electrochemical reduction, where a negative voltage is applied to the entire SES substrate in an electrochemical cell in the presence of a scaffolding ligand.

[0050] When electrochemically oxidatively cleaning and redefining, it is conceivable to use a SERS substrate formed on a conductive substrate as the working electrode in an electrochemical cell. To achieve oxidative cleaning, it is conceivable to oxidize the surface of the gold nanoparticles and remove adsorbed materials by applying a potential of 1-2V (relative to an Ag / AgCl reference electrode) for at least 1 second in an electrolyte solution (e.g., phosphate buffer, NaClO4, H2SO4, etc.).

[0051] To achieve redefinition, the Au oxide layer can be reduced by applying a reduction potential step or sweep in an electrolyte solution containing scaffolding molecules, and the nanogap can be re-scaffolded / redefined with the respective scaffolding ligand. Examples of effective reduction protocols include (a) a potential step at -0.60 V for at least 1 second, or (b) a potential sweep from the open-circuit potential to -1 V and then back to 0 V. Various sweep rates, such as 50 mV / s or 200 mV / s, can be used. The potentials referenced here are specific to Au. For other metals, the oxidation and reduction potentials may differ.

[0052] The method of the first embodiment may further include a cycle of subsequent oxidation-cleaning and redefinition steps. That is, a further “cycle” includes the oxidation-cleaning step and the redefinition step in sequence. The total number of cycles of oxidation-cleaning and redefinition steps may be at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 20, or at least 30. The total number of cycles includes the initial oxidation-cleaning and redefinition steps. The present invention makes it possible to perform multiple (many) cycles without a significant decrease in the uniformity of the nanoparticle layer or the intensity of the SES response.

[0053] In some embodiments, the method for executing SES according to a third aspect of the present invention is a method for executing SERS or a method for executing SEIRA.

[0054] A method for performing SES according to a third aspect of the present invention may include an oxidation cleaning step that generates an oxide coating on the surface of nanoparticles.

[0055] A method for carrying out SES according to a third aspect of the present invention may include a redefinition step of removing the oxide coating in the presence of a scaffolding ligand.

[0056] A method for performing SES according to a third aspect of the present invention may include a redefinition step in which scaffolding ligands are placed between adjacent nanoparticles to define their relative spacing.

[0057] A method for performing SES according to a third aspect of the present invention may include an oxidation cleaning and redefinition step between the first SES analysis and the second SES analysis, corresponding to the adjustment method of the first aspect of the present invention.

[0058] The method of the third embodiment may further include a subsequent oxidation cleaning step, a redefinition step, and an SES analysis cycle. That is, the further “cycle” consists of an oxidation cleaning step, a redefinition step, and an SES analysis step. The total number of cycles of the oxidation cleaning step, the redefinition step, and the SES analysis step may be at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 20, or at least 30. The total number of cycles includes the first cycle of the oxidation cleaning step, the redefinition step, and the SES analysis step. The present invention may enable the execution of multiple (many) cycles without significantly reducing the uniformity of the nanoparticle layer or the intensity of the SES response. The SES response generated in the SES analysis may be generated by the investigation of the analyte or a mixture containing the analyte. The relative standard deviation of the peak area of ​​the analytes investigated by SES analysis may be ≤10%, ≤9%, ≤8%, ≤7%, ≤6%, or ≤5.5% across all oxidation washing steps, redefinition steps, and SES analysis cycles.

[0059] Embodiments and experiments illustrating the principle of the present invention will be described with reference to the attached drawings. [Brief explanation of the drawing]

[0060] [Figure 1] Figure 1 shows the method for preparing and characterizing the nanoparticle layer, specifically the preparation protocol consisting of (i) partial aggregation of gold nanoparticles (AuNPs) in water with a CHCl3 level, (ii) removal of salts by repeatedly replacing the supernatant with DI water ("washing"), and (iii) a final concentration step. [Figure 2] Figure 2 shows the method for fabricating and characterizing the nanoparticle layer. The images show the deposition of droplets onto an Au / Si substrate, the dried nanoparticle layer, and a densely packed layer of AuNPs, as well as an SEM image. [Figure 3] Figure 3 shows the method for creating and characterizing the nanoparticle layer. Dark-field (DF) images, bright-field (BF) images, and SERS map scans show single-layer (1ML) and double-layer (2ML) regions, and the presence of 1ML and 2ML layers (white outlines) is confirmed in close-up SEM. [Figure 4] Figure 4 shows the method for fabricating and characterizing the nanoparticle layer. Dark-field spectra are shown for the 1ML and 2ML regions. [Figure 5] Figure 5 shows the definition, oxidation cleaning, and redefinition of nanogap. Specifically, it is a three-step nanogap redefinition protocol for the nanoparticle layer: (i) an initial surfactant (L1) defines the nanogap, (ii) an oxygen plasma removes the surfactant, and (iii) a scaffolding ligand (L2) is used to stabilize the nanogap. [Figure 6] Figure 6 shows the surface modification associated with the three-step nanogap redefinition protocol in Figure 5 (left = nanogap definition, center = oxidation cleaning, right = redefinition). [Figure 7]Figure 7 shows the stacked (unnormalized) SERS spectra from spatial mapping of nanoparticle layers recorded after each step (i-iii) of the three-step nanogap redefinition protocol in Figure 5 (left = nanogap definition, center = oxidative cleaning, right = redefinition). Shading indicates interquartile variation, and dotted lines indicate baseline shift. [Figure 8] Figure 8 shows the controlled movement of gold atoms. (a) Dark-field spectra of the three ligands (citric acid, MUA, CB[5]) before plasma treatment. Histograms of the mean spectrum and peak wavelength from position 100. (b) Dark-field spectra of the plasma-treated nanoparticle layer after CB[5] redefinition. [Figure 9] Figure 9 shows the movement of gold atoms after O2 plasma treatment, resulting in the formation of sintered or stabilized nanogap with and without scaffolding ligand (top); and also shows corresponding SEM images of nanoparticle sintering (bottom left) after plasma delamination (bottom center) and subsequent direct acid treatment with scaffolding ligand (bottom right) (scale bar is 100 nm). [Figure 10] Figure 10 shows the sensing capability of a nanoparticle layer treated according to the present invention and illustrates a sensing setup for recyclable sensing of hydrophobic toluene. [Figure 11] Figure 11 shows the sensing capability of a nanoparticle layer treated according to the present invention and illustrates the sensing protocol for volatile organic compounds (VOCs) in a sealed container. [Figure 12] Figure 12 shows the toluene signature peak (995 cm⁻¹) extracted from the sensing setup in Figure 10, normalized to the CB[7] scaffold, and exhibiting a low detection limit. [Figure 13] Figure 13 shows the VOCs (methanol, ethanol, toluene, acetone, and dimethyl sulfoxide) used in the experiment using the sensing protocol in Figure 11. [Figure 14]Figure 14 shows the SERS spectrum of the VOC (VOC is shown in Figure 13, with the CB[7] signal subtracted; left) using the sensing protocol shown in Figure 11, and a SERS map showing the CB[7] signal peak intensity (upper right) and the toluene signature peak normalized to CB[7] (lower right). [Figure 15] Figure 15 illustrates the application of nanoparticle layers to flow sensing, specifically showing cycling SERS sensing of paracetamol in a PDMS flow cell. [Figure 16] Figure 16 shows time-resolved SERS measurements of paracetamol (Para) and acid washing (HCl) spectra from a flow sensing experiment (see Figure 15). [Figure 17] Figure 17 shows how the independent components extracted from the flow sensing experiment (see Figure 15) are similar to CB[7], protonated and deprotonated paracetamol. [Figure 18] Figure 18 shows the time evolution of the protonated and deprotonated paracetamol component during cycling in a flow sensing experiment (see Figure 15). [Figure 19] Figure 19 shows the equilibrium times for various paracetamol concentrations during the flow sensing experiment, along with the fitted (lines) and standard errors (see Figure 15). [Figure 20] Figure 20 shows the AuNP colloid phase on chloroform (left) and concentrated AuNP droplets before deposition (right). [Figure 21] Figure 21 shows droplets deposited on a gold-coated substrate during drying. [Figure 22] Figure 22 shows the nanoparticle layer deposited on the cover glass (shown in black) (the chromium layer for improving adhesion is shown in dark gray). [Figure 23] Figure 23 shows direct deposition onto the cover glass. [Figure 24]Figure 24 shows the X-ray photoelectron (XPS) spectrum (C1s scan) of the nanoparticle layer. The layer fabricated using CB[5] shows the C=O and CNC bonds of CB[5] (before plasma treatment), and these bonds are removed after plasma treatment. Redefining with CB[5] restores the characteristic bonds. CC contamination is present throughout the measurement and on the exposed gold surface (Au ref). [Figure 25] Figure 25 shows the XPS spectrum (C1s scan) of the nanoparticle layer generated by NaCl aggregation (citric acid stabilization), indicating that the citrate is completely removed and redefined by CB[5]. [Figure 26] Figure 26 shows evidence of oxygen on the AuNP surface after plasma treatment. [Figure 27] Figure 27 shows evidence of oxygen on the AuNP surface after plasma treatment. [Figure 28] Figure 28 shows the size dependence of sintering on gold nanoparticles (commercially available AuNPs of 60, 80, and 100 nm). At the same HCl concentration, larger AuNPs are more resistant to sintering. SEM images were taken after plasma treatment. [Figure 29] Figure 29 shows (a) a control measurement demonstrating that sintering does not occur when an untreated nanoparticle layer (AuNPs: 80 nm) is exposed to HCl. (b) Sintering of the nanoparticle layer (AuNPs: 80 nm) after plasma treatment and exposure to H2SO4. This indicates that HCl is not the only factor that causes sintering. [Figure 30] Figure 30 shows (a) the chemical structure of toluene; (b) SERS of a CB[7] redefined nanoparticle layer and Raman (top), DFT calculation of toluene (center) and polarized DFT (SERS intensity recalculated in a polarized electric field, bottom). [Figure 31] Figure 31 shows the typical modes of characteristic vibrations of toluene. [Figure 32] Figure 32 shows (a) a toluene experiment using a nanoparticle layer that has not undergone redefinition or plasma cleaning, and (b) a series of toluene concentrations, starting from the highest concentration and followed by repeated HCl cleaning. [Figure 33] Figure 33 shows dark-field scattering of a nanoparticle layer constructed from AuNPs with D=80 and a diameter of 50 nm, which were initially aggregated by CB[7]. Pre = before plasma cleaning, Post = after 45 minutes of plasma cleaning, Rescaffold = after HCl + CB[7] treatment. [Figure 34] Figure 34 shows dark-field scattering of a nanoparticle layer constructed from AuNPs with D=40 and a diameter of 20 nm, which was initially aggregated by CB[7]. Pre = before plasma cleaning, Post = after 45 minutes of plasma cleaning, Rescaffold = after HCl + CB[7] treatment. [Figure 35] Figure 35 shows the SERS of nanoparticle layers constructed from AuNPs with diameters of D=80 and 50 nm and initially aggregated by CB[7]. Pre = before plasma cleaning, Post = after 45 minutes of plasma cleaning, Rescaffold = after HCl + CB[7] treatment. [Figure 36] Figure 36 shows the SERS of a nanoparticle layer constructed from AuNPs with D=40 and a diameter of 20 nm, which was initially aggregated by CB[7]. Pre=before plasma cleaning, Post=after 45 minutes of plasma cleaning, Rescaffold=after HCl+CB[7] treatment. [Figure 37] Figure 37 shows the relationship between the dark-field spectral resonance position and the AuNP diameter (excerpted from Figure 34). [Figure 38] Figure 38 shows (top) the spectral resonances of a single NP, a dimer, and an NP chain under the nearest neighbor approximation, and (bottom) the relationship between the dimer and the mirror-on-nanoparticle (NPoM) mode resonance. [Figure 39] Figure 39 shows the SERS of an 80 nm nanoparticle layer formed by CB[7] aggregation, indicating that the nanogap is gradually oxidized before and after oxygen plasma cleaning for 2-30 minutes. [Figure 40] Figure 40 shows repeated cleaning cycles of two nanoparticle layer samples formed from 80 nm AuNP. Each cleaning cycle involves 30 minutes of oxygen plasma cleaning followed by redefinition with 0.5 M HCl and CB[6]. [Figure 41] Figure 41 shows the SERS of nanoparticle layers cleaned and redefined using various molecular frameworks: (a) 4-aminothiophenol (ATP), (b) 4-mercaptobenzoic acid (MBA). Spectra were measured after exposure to air and after immersion in 1 M HCl for 10 minutes. [Figure 42] Figure 42 shows the SERS of nanoparticle layers after oxygen plasma cleaning and redefinition using various molecular framework examples: (a) 4-mercaptopyridine (MPy), (b) cyclodextrin (CD). Spectra were measured after exposure to air and after immersion in 1 M HCl for 10 minutes. [Figure 43] Figure 43 shows dopamine sensing using an AuNP SERS substrate. Solution aggregation (Solagg) in water using NaCl forms a fractal chain of 60 nm AuNPs. [Figure 44] Figure 44 shows dopamine sensing using an AuNP SERS substrate. It is a schematic diagram of the nanoparticle layer on a glass substrate. The SEM image shows a randomly packed, close-packed arrangement of 60 nm gold nanoparticles. [Figure 45] Figure 45 shows dopamine sensing using an AuNP SERS substrate. The glass substrate allows access from both sides, and the schematic diagram shows Fe(III)-sensitized AuNPs that create gaps of less than 1 nm between NPs on the nanoparticle layer. [Figure 46] Figure 46 shows dopamine sensing using an AuNP SERS substrate. Comparison of dopamine SERS intensity for each probed nanogap in the corresponding SERS substrate. [Figure 47] Figure 47 shows the characterization of dopamine sensing in nanoparticle layers. DA SERS spectra of three nanoparticle layer samples functionalized using different protocols. PreFe(III) shows a signal three times higher than PostFe(III). [Figure 48] Figure 48 shows the characteristics of nanoparticle layer dopamine sensing. DFT calculations were performed for both deprotonated and protonated bisdopamine complexes. [Figure 49] Figure 49 shows the characterization of the nanoparticle layer dopamine sensing. It is a schematic diagram of the complex formation between bisdopamine and Fe. [Figure 50] Figure 50 shows the characterization of dopamine sensing in a nanoparticle layer. The kinetic study (left) shows how DA (added at time t=0) diffuses into the gaps at various concentrations. The delay time τd until the saturation signal reaches 50% and the shown binding rate τr -1 (lines from left to right: 100 μM, 50 μM, 10 μM). The extracted corresponding τd and τr -1 (right) and DA concentrations (circles in each row, from left to right: 10 μM, 50 μM, 100 μM). [Figure 51] Figure 51 shows the cleaning of the nanoparticle layer SERS substrate. SERS spectra after each step of the cleaning process (arrows). Oxygen plasma treatment removes all organic analytes, making the layer reusable. [Figure 52] Figure 52 shows the cleaning of the nanoparticle layer SERS substrate. XPS count (after scaling) shows the formation of Au(III). [Figure 53] Figure 53 shows the cleaning of the nanoparticle layer SERS substrate. SERS uniformity is measured at 50 different locations (average interval of 100 μm) with an extracted relative standard deviation (RSD) of 6%. [Figure 54] Figure 54 shows the detection limit of DA sensing using a nanoparticle layer. The spectrum after 24 hours of immersion. DA peaks below 500 nM are visually identifiable. The vertical offset is shown by the line on the right. The vertical order in the legend corresponds to the vertical order of the line segments. [Figure 55] Figure 55 shows the detection limits of DA sensing using a nanoparticle layer. Principal component analysis (PCA) shows different DA concentration regimes. The dotted line represents the component score of 0M DA, and the shaded area above this line represents the LOQ corresponding to 9σ. The arrows indicate the clinical concentration range of DA contained in human urine. The LOD was calculated for the quantitative region using the Langmuir-Hill formula (inset). [Figure 56]Figure 56 shows the multiple sensing of DA and EPI in the nanoparticle layer. a) Chemical structures of dopamine (DA) and epinephrine (EPI). b) Corresponding SERS spectra when compounded with Fe(III) in the nanoparticle layer. [Figure 57] Figure 57 shows the normalized SERS spectra with varying DA:EPI ratios (left) and the 895 cm⁻¹ SERS peak from the DA-EPI-Fe(III) complex, which appears only with mixed catecholamines (right). [Figure 58] Figure 58 shows the experimental SERS peaks of 10 mM DA, denoted a-j, and assigned to Table S1 based on density functional theory (DFT) calculations. All frequencies are scaled by a factor of 0.9671. [Figure 59] Figure 59 shows the SERS DA signals from the nanoparticle layer before and after multiple cycles of plasma cleaning and DA exposure to test the reproducibility of the cleaning protocol and accumulated damage. In each case, the SERS intensity at 1481 cm⁻¹ was extracted. [Figure 60] Figure 60 shows the XPS spectrum of the nanoparticle layer after exposure to a 10 mM DA solution. [Figure 61] Figure 61(a) shows Au4f before plasma cleaning, and (b) shows that the proportion of Au(III) species was detected after 15 minutes of plasma cleaning. [Figure 62] Figure 62 shows the SERS spectrum after immersion in DA for 10 minutes, where a DA peak greater than 10 μM is observed, and the vertical offset is indicated by the line on the right. The vertical order of the legend corresponds to the vertical order of the lines. [Figure 63] Figure 63 shows the principal component analysis (PCA) illustrating the behavior of a typical Langmuir isotherm model (inset). [Figure 64] Figure 64 shows the eigenvalues ​​obtained from principal component analysis (PCA) of 160 SERS spectra at different analyte concentrations. I-III show the three main components of the PCA and their weights based on the proportion of eigenvalues. [Figure 65]Figure 65 plots the first three PCA component scores for each SERS sample number, along with their corresponding concentrations (bottom). [Figure 66] Figure 66 shows the loading plot of the corresponding component in Figure 65, where I resembles the expected DA:Fe(III)SERS spectrum. [Figure 67] Figure 67 shows a comparison of the expected DA with the measured DA by calculating the ratio of the 100% SERS spectrum that maximizes overlap with each experimental SERS spectrum. [Figure 68] Figure 68 shows (top) the residual area of ​​the new peak at 895 cm⁻¹ and a line representing DA% × (1-DA%), and (bottom) the residual when the peak area at 895 cm⁻¹ is fitted to the DA% × (1-DA%) curve. [Figure 69] Figure 69 shows the preparation using the nanoparticle layer-CB[5] and the detection, washing, and redefinition of the inflow EC-SERS analyte, specifically a schematic diagram of integrating the nanoparticle layer-CB[5] into the EC-SERS flow system. All SERS spectra are collected with a 1 mW 785 nm laser at an integration time of 1 second. [Figure 70] Figure 70 shows the preparation of EC-SERS analytes using a nanoparticle layer CB[5], as well as the detection, washing, and redefinition of the incoming sample, specifically a cross-section of the EC-SERS flow cell (CE=counter electrode, RE=reference electrode, WE=working electrode). All SERS spectra are collected with a 1 mW 785 nm laser at an integration time of 1 second. [Figure 71] Figure 71 shows a schematic diagram of the electrochemical SERS (EC-SERS) flow and optical setup. [Figure 72] Figure 72 shows photographs of the flow and optical setup of the electrochemical SERS (EC-SERS). [Figure 73]Figure 73 shows the voltage-dependent binding of adenine (ADN) on the nanoparticle layer CB[5], specifically the time-series SERS spectrum (top) of the nanoparticle layer CB[5] cycled between +0.5V and -1V with 5 scans at 50mV / s in 10 μM adenine (ADN) and 50 mM potassium phosphate buffer (pH 7.0). The peak intensities of CB[5] (830 cm⁻¹) and ADN (~732 cm⁻¹) are also plotted for each SERS spectrum (center). The applied potential and the corresponding current response are plotted over time (bottom). All SERS spectra were collected with an integration time of 1 second, a 785 nm excitation laser, and an output of 1 mW. [Figure 74] Figure 74 shows the voltage-dependent binding of ADN on the nanoparticle layer-CB[5], specifically the molecular structures of ADN and its acidic and base forms (top), and SERS spectroscopic voltammograms of CV scan 1-2 showing the change in ADN peak intensity when the potential is scanned. The dotted line indicates the applied starting potential (bottom). All SERS spectra were collected with an integration time of 1 second, a 785 nm excitation laser, and an output of 1 mW. [Figure 75] Figure 75 shows the voltage-dependent binding of ADN on the nanoparticle layer CB[5], specifically (left) the open-circuit potential (OCP), various applied step potentials (vsAg / AgCl), and time-series SERS spectra of the nanoparticle layer-CB[5] incubated with 10 μM ADN in 50 mM potassium phosphate buffer (pH 7.0), after relaxation to OCP. (right) shows the ADN peak (νADN ~ 732 cm⁻¹) tracked from the time-series SERS spectrum. All SERS spectra were collected with an integration time of 1 sec, a 785 nm excitation laser, and 1 mW power. [Figure 76] Figure 76 shows the voltage-dependent coupling of ADN on the nanoparticle layer-CB[5], specifically the SERS spectra before coupling (t=0 sec from the time-series SERS spectrum), during coupling (t=30 sec), and after different applied potentials (t=45 sec). All SERS spectra were collected with an integration time of 1 sec, a 785 nm excitation laser, and a power of 1 mW. [Figure 77]Figure 77 shows the voltage-dependent coupling of ADN on the nanoparticle layer CB[5], specifically the normalized intensity of the ADN peak at and after different applied potentials. All SERS spectra were collected with an integration time of 1 second, a 785 nm excitation laser, and 1 mW power. [Figure 78] Figure 78 shows the preparation using the nanoparticle layer CB[5] and the detection, washing, and redefinition of inflow EC-SERS analytes, specifically a schematic diagram of the in-situ electrochemical SERS analyte detection and washing / redefinition protocol. Potentials are for Ag / AgCl. All SERS spectra were measured with a 785 nm laser at an integration time of 1 second and an output of 1 mW. [Figure 79] Figure 79 shows the SERS spectra after preparation and detection of the influent EC-SERS analyte, washing and redefinition using nanoparticle layer-CB[5], specifically, the initial nanoparticle layer-CB[5] (top), after detection of 10 μM adenine (ADN) (second from top), after the oxidation washing step (second from bottom), and after the redefinition step (bottom). The ADN peak at 732 cm⁻¹ is indicated by an asterisk. SERS spectra were collected with a 1 mW 785 nm laser at an integration time of 1 second. [Figure 80] Figure 80 shows the detection, washing, and redefinition cycles of the analyte using CB[5]. Specifically, these are SERS spectra from 30 cycles of 10 μm ADN detection and redefinition using CB[5]. The spectra have been offset for readability, and the redefined spectrum is the lower member of each spectrum pair. [Figure 81] Figure 81 shows the ADN peak area (λADN = 732 cm⁻¹) obtained from the SERS spectra of analyte detection, washing, and redefinition cycles using CB[5], particularly ADN detection and washing / CB[5] redefinition cycles. The dotted horizontal line represents the average of the ADN peak area across all analyte detection cycles. [Figure 82]Figure 82 shows the regional uniformity of the ADN signal on the nanoparticle layer-CB[5] over multiple cycles of analyte detection and cleaning / redefinition by CB[5], particularly the SERS spectrum of the nanoparticle layer-CB[5] before the analyte cycling test. SERS maps were taken using an integration time of 1 second, a 785 nm excitation laser, 2.14 mW power, and a 20x objective lens. [Figure 83] Figure 83 shows the regional uniformity of the ADN signal on the nanoparticle layer CB[5] over multiple cycles of analyte detection and washing / redefinition using CB[5], specifically an optical microscope image of the 465 × 330 μm region of interest used for SERS mapping. [Figure 84] Figure 84 shows the local uniformity of the ADN signal on the nanoparticle layer-CB[5] over multiple cycles of analyte detection and washing / redefinition using CB[5], specifically the SERS spectra of the nanoparticle layer-CB[5] after binding 5 μM ADN at an enhancement potential of -0.60 V in 50 mM potassium phosphate buffer (pH 7.0) and after washing and redefinition with CB[5] (left) in cycle 1 (top), cycle 10 (bottom), and (left). The spectra were acquired in situ using a 40x objective lens, with an integration time of 1 second, a 785 nm laser, and a power of 1 mW. Heatmap of the SERS ADN peak area (νADN = 732 cm⁻¹) on the surface area of ​​the dried nanoparticle layer-CB[5]. Center shows the area after ADN binding and right shows the area after the redefinition cycle with CB[5]. The heatmap was acquired over the region shown in Figure 83 (31 × 11 grid, 15 × 30 μm spacing). The SERS map was acquired with an integration time of 1 second, a 785 nm excitation laser, an output of 2.14 mW, and a 20x objective lens. [Figure 85]Figure 85 shows the local uniformity of the ADN signal on the nanoparticle layer-CB[5] over multiple cycles of analyte detection and washing / redefinition using CB[5], specifically the SERS spectra of the nanoparticle layer-CB[5] after binding 5 μM ADN at an enhancement potential of -0.60 V in 50 mM potassium phosphate buffer (pH 7.0) and after washing and regeneration with CB[5] at cycle 20 (top) and cycle 30 (bottom), (left). The spectra were acquired in situ using a 40x objective lens, with an integration time of 1 second, a 785 nm laser, and a power of 1 mW. Heatmap of the SERSADN peak area (νADN = 732 cm⁻¹) on the surface area of ​​the dried nanoparticle layer-CB[5]. Center shows the area after ADN binding and right shows the area after the redefinition cycle with CB[5]. The heatmap was acquired over the region shown in Figure 83, a 31x11 grid (15×30 μm spacing). The SERS map was acquired using a 1-second integration time, a 785 nm excitation laser, 2.14 mW output, and a 20x objective lens. [Figure 86] Figure 86 shows the detection, washing, and redefinition cycle of the analyte using CB[5], specifically the CB[5] peak area (νCB[5] = 830 cm⁻¹, circle) and the integrated SERS background (square) of the CB[5] regenerated nanoparticle layer. The dotted horizontal line represents the average CB[5] peak area across all redefinition cycles. [Figure 87] Figure 87 shows the superposition of SERS spectra from 15 cycles of analyte detection, washing, and redefinition without CB[5], specifically, 10 μM ADN detection (top) and after redefinition without CB[5] (bottom). A constant background was subtracted from all spectra to facilitate comparison over 15 cycles. [Figure 88] Figure 88 shows the ADN peak region (νADN = 732 cm⁻¹) from the SERS spectra of the analyte detection, washing, and redefinition cycles without CB[5], particularly for each ADN detection and washing / redefinition cycle without CB[5]. [Figure 89]Figure 89 shows the local homogeneity of the ADN signal on the nanoparticle layer-CB[5] after multiple analyte detection and washing / redefinition cycles without CB[5], specifically (left) the SERS spectrum of the nanoparticle layer-CB[5] before the analyte cycling test and (right) an optical microscope image of the 465 × 330 μm region of interest used for SERS mapping. The SERS map was recorded using an integration time of 1 second, a 785 nm excitation laser, a power of 2.14 mW, and a 20x objective lens. [Figure 90] Figure 90 shows the local homogeneity of the ADN signal on the nanoparticle layer-CB[5] over multiple cycles of analyte detection and washing / redefinition without CB[5], specifically cycle 1 (top), cycle 2 (middle), and cycle 10 (bottom): (left) SERS spectrum of the nanoparticle layer-CB[5] after binding 5 μM ADN at an enhancement potential of -0.60 V in 50 mM potassium phosphate buffer (pH 7.0), and SERS spectrum after washing and redefinition without CB[5]. Spectra were acquired in situ with a 40x objective lens, integration time of 1 second, 785 nm laser, and 1 mW power. Heatmap of SERSADN peak area (νADN = 732 cm⁻¹) on the surface area of ​​the dried nanoparticle layer-CB[5]. After ADN binding (middle) and after redefinition without CB[5] (right). The heatmap was acquired over a 465 × 330 μm area, as shown in Figure 89 (right), on a 31 × 11 grid with 15 × 30 μm spacing. The SERS map was recorded using an integration time of 1 second, a 785 nm excitation laser, a power of 2.14 mW, and a 20x objective lens. [Figure 91] Figure 91 shows the SERS spectra from 15 cycles of detection, washing, and redefinition of 10 μM ADN with buffer and 1 mMKCl on the nanoparticle layer CB[5], specifically, detection and washing / redefinition of 10 μM ADN with 1 mMKCl and 50 mM potassium phosphate buffer (pH 7.0). The spectra have been offset for clarity. [Figure 92]Figure 92 shows the detection, washing, and redefinition cycle of 10 μM ADN on the nanoparticle layer CB[5] with buffer and 1 mM KCl, specifically (top) the ADN peak region after analyte detection and washing / regeneration; (bottom left) the dark-field scattering spectra of MLagg-CB[5] before and after 15 cycles and analyte detection and washing / redefinition with 1 mM KCl and buffer; and (bottom right) scanning electron microscope images. [Figure 93] Figure 93 shows the SERS spectra from 15 cycles of detection, washing, and redefinition of 10 μM ADN with buffer on a nanoparticle layer of NaCl, specifically, detection and washing / redefinition of 10 μM ADN with 50 mM potassium phosphate buffer (pH 7.0). The spectra have been offset for clarity. [Figure 94] Figure 94 shows the detection, washing, and redefinition cycle of 10 μM ADN on the nanoparticle layer NaCl with buffer, specifically (top) the ADN peak region after detection and washing / redefinition of the analyte, (bottom left) the dark-field scattering spectrum, and (bottom right) scanning electron microscope images of the nanoparticle layer-NaCl before and after 15 cycles and detection and washing / regeneration with buffer. [Figure 95] Figure 95 shows a schematic diagram of the initial EC cleaning and regeneration of the nanoparticle layer CB[5], specifically, the initial cleaning and redefinition of the newly prepared nanoparticle layer CB[5] using in situ electro-oxidation and reduction. [Modes for carrying out the invention]

[0061] Aspects and embodiments of the present invention will be described below with reference to the accompanying drawings. Further aspects and embodiments will be obvious to those skilled in the art. All documents referenced herein are incorporated herein by reference.

[0062] In particular, the following description focuses on SERS as an SES technology, but aspects and embodiments of the present invention illustrated in the context of SERS can be applied to any suitable SES technology (e.g., SEIRA). The following description relates to two embodiments of the present invention, namely a gold nanoparticle-based SERS substrate and a Fe(III)-sensitized gold nanoparticle-based SERS substrate.

[0063] Gold nanoparticle SERS substrate The inventors demonstrate that a randomly close-packed gold nanoparticle layer with sub-nanometer gaps can be reliably fabricated as a highly sensitive SERS substrate. By using oxygen plasma etching as an oxidative cleaning tool, all original molecules forming nanogaps between adjacent nanoparticles within the nanoparticle layer can be removed and replaced with scaffolding ligands, achieving very precise nanogap sizes of less than 1 nm. This allows for the modification of the nanogap chemical environment, which is crucial for practical Raman sensing applications. The resulting nanoparticle layer is easily accessible from the opposite side by fluid and light, enabling high-performance fluid sensing cells. The ability to periodically remove analytes and reuse these nanoparticle layers has been demonstrated, with sensing of toluene, volatile organic hydrocarbons, and paracetamol being examples.

[0064] Surface-enhanced Raman scattering (SERS) is a promising optical sensing technique that enhances inelastic Raman scattering from an analyte by billions of times through electromagnetic field amplification when light is confined in nanogaps (hot spots) between suitable metal nanostructures.

[0065] To fabricate nanoparticle layer SERS substrates for applications such as sensing, nanostructure nanoassembly, growth, functional coupling, hotspot control, and surface chemistry are essential. Sensing depends on the substrate being stable, reproducible, easy to fabricate, and having reliable SERS enhancement. [1] Precisely defined hotspots enhance the reproducibility of the SERS signal, and the choice of gap size tunes confined plasmon modes to resonate with common Raman laser wavelengths.

[0066] Top-down approaches such as electron beam lithography [21-23], deep ultraviolet lithography

[24] , focused ion beam milling [25-26], and nanoimprint lithography [27-29] have been used to fabricate SERS substrates with pure metallic surfaces that offer high reproducibility and scalability. However, these lithography-based strategies are time-consuming, require expensive infrastructure, and can only reliably reach gap dimensions greater than 5 nm. [30,31]

[0067] Alternatively, a bottom-up approach based on nanoparticle self-assembly has been demonstrated to enable the low-cost and easy production of nanoparticle layer-based SERS substrates. By utilizing template-assisted[2-4], evaporation[5-9], and interfacial[10-16] self-assembly, densely packed nanoparticle structures with high spatial uniformity can be prepared. By selecting nanoparticle surfactants[6,12,14] and carefully controlling the self-assembly process[5,7,8], the gap spacing between nanoparticles can be adjusted to the sub-nanometer level.

[32]

[0068] Because synthesized nanoparticles often contain additional chemicals and surfactants to enhance shelf life and functionality (whether commercially available or in-house manufactured), controlling surface chemistry can be problematic with nanoparticle-based substrates. Surface molecules cannot be completely removed even by ligand exchange, causing interference with the binding constant of the target analyte

[17] and reducing sensitivity to trace analytes by blocking the region of maximum SERS enhancement. Variations in surfactants between batches and aging of gold nanoparticles (AuNPs; involving morphological changes of adsorbed atoms on metal surfaces

[18] ) can reduce the uniformity and reproducibility of these substrates.

[0069] The inventors have discovered a simple and reproducible method for efficiently constructing nanoparticle layers with uniform nanogap spacing through a tuning method that can be used to isolate and detect small molecules with high levels of specificity. These nanoparticle layers consist of densely packed monolayers (or bilayers) of spherical gold nanoparticles with precisely controlled nanogap spacing defined by molecular backbone ligands such as cucurbit[n]uryl. [17,18]AuNPs form a densely packed, disordered network, but the packing density is clearly defined, and consistent sub-nanometer (<1 nm) gap spacing control results in excellent optical properties. The presence of a monolayer of AuNPs in the nanoparticle layer allows the analyte to diffuse uniformly across the nanogap, enabling reproducible back illumination.

[0070] The inventors also discovered that metal nanoparticle layers can be directly deposited onto various substrates such as glass, Si, PDMS, or Au-coated silicon wafers and integrated into a flow system. Once the nanoparticle layer is fixed, contaminants (citrates, stabilizers, coagulants) can be removed from the nanoparticle layer during the oxidative cleaning stage using oxygen plasma etching, which is known to remove / decompose molecules bound to the surface.

[33]

[0071] The inventors discovered that by washing away the analyte from the nanogap using oxygen plasma cleaning or HCl, the nanoparticle layer can be reused as part of the SERS substrate, enabling a continuously reusable flow sensing system that is not feasible with solution aggregates. Here, liquid, vapor, and flow sensing are demonstrated, highlighting its excellent compatibility for integration with other devices in a variety of applications, from environmental monitoring to healthcare monitoring.

[0072] Fabrication and characterization of nanoparticle layers The nanoparticle layer can be easily prepared in less than 5 minutes by partially agglomerating AuNPs (80 nm in diameter unless otherwise specified; 15-120 nm has also been tested) in a two-phase chloroform-water system (Figure 1). Upon addition of a flocculant (salt or other ligand), AuNPs are pressed against the water-air interface and the water-chloroform interface (Figure 1(i)). After removing the supernatant, the AuNPs are concentrated at the interface and become visible to the naked eye as a reflective reddish-gold film. Repeating this washing procedure three times further increases the AuNP density (Figure 1(ii)), and small AuNP droplets and approximately 10 μL of residual supernatant are suspended in the chloroform phase (Figure 1(iii); see Figure 20 for a photograph).

[0073] These droplets are deposited on various substrates such as gold, glass, silicon, and PDMS (Figure 2) and directly integrated into microfluidic systems (see Figures 21 and 22). As the residual supernatant evaporates, the AuNPs form a dense, disordered arrangement, creating a layer of metal nanoparticles approximately 5 mm in diameter (Figure 2, SEM).

[0074] These metal nanoparticle layers show distinct regions of single (1 ML) or double (2 ML) layers of AuNP (Figure 3, bottom). The second layer is formed because, due to surface fixation, the surface area of ​​the droplet (composed of a single layer of AuNP) during drying is larger than the area occupied on the substrate. The inventors note that the relative area of ​​the single / double nanoparticle layers can be controlled by a predetermined surface pattern of the substrate.

[0075] The 1ML and 2ML regions are clearly visible in bright-field and dark-field images, as well as in SERS map scans (Figure 3, top). The plasmon-active nanogap generates a strong SERS signal from trapped molecules (see below) and exhibits stronger emission in the 2ML region. This enhanced optical interaction is confirmed by dark-field spectra showing different resonance modes from the 1ML and 2ML regions (Figure 4). In both cases, the precisely controlled gap spacing (see below) generates distinct plasmonic modes from the 1ML and 2ML gold nanoparticle layers, which become redshifted and stronger as the number of layers increases.

[0076] Defining, oxidative cleaning, and redefining nanogap A key feature of these densely packed nanoparticle layers is the extremely precise control of gap spacing. Because the nanoparticle layers are supported on the substrate with access to all spaces between adjacent nanoparticles, the inventors can introduce processes of the embodiments of the present invention that transform gap scaffolding and control the spacing between nanoparticles. This is in contrast to solution aggregation, where such molecular replacement is not feasible.

[0077] This three-stage process (Figures 5 and 6) separates (i) defining the nanogap size by initial scaffolding, (ii) oxidative cleaning, and (iii) redefining the gap using an arbitrary scaffolding ligand. This allows for complete control and fine-tuning of the spacing between nanoparticles and the chemical reactions of the facets.

[0078] The initial gap spacing is defined by the chemistry of the flocculant, which acts as a ligand defining the gap. By using various flocculants that bind to the 80 nm diameter AuNP surface, gaps ranging from 0.9 to 3 nm can be formed. If the selected ligand is not water-soluble, it can be dissolved in an organic chloroform phase and bound to the AuNP surface by vigorously shaking the two-phase system. To illustrate the definition of the nanogap, a comparison is made using 11-mercaptoundecanoic acid (MUA), sodium chloride (NaCl), and cucurbituryl[5](CB[5]) as initial flocculants (Figure 5, upper left).

[0079] The SERS spectra recorded after the deposition and drying of the nanoparticle layers (Figure 7, left) reveal the nanogap chemistry of the initially prepared nanoparticle layer. The NaCl salt layer ("citrate") shows the citrate surface chemistry of the AuNPs used. A characteristic vibration at 995 cm⁻¹ indicates that the citrate anion defines the gap

[34] , which is estimated to be 1.0 ± 0.2 nm (shaded area shows the interquartile range in a 200 μm × 200 μm region, with a laser spot size of approximately 1 μm).

[0080] When the nanoparticle layer is aggregated with CB[5] (Figure 7 left, "CB[5]"), a SERS spectrum similar to that of the NaCl salt film is obtained, but with an even stronger CB[5] mode, particularly at 829 cm⁻¹. -1 A ring-breathing mode appears. This indicates that CB[5] does not completely replace the citrate anion from the AuNP surface, resulting in a mixed chemical environment. The gap spacing here is limited to the inter-portal height of CB[5], 0.9 nm (see below). The SERS spectrum of the MUA aggregate layer (Figure 7 left, "MUA") shows even higher relative dispersion than the NaCl or CB[5] nanoparticle layers. The longer, more flexible alkane chains (compared to the smaller citrate or rigid CB[5]) likely lead to larger gap sizes (compare DF spectra in Figure 8) and gap size variability.

[0081] In the subsequent oxidation cleaning step, oxygen plasma cleaning (90% power, 30 sccm, 30 min) of the nanoparticle layer is used to completely remove all molecules bound to the surface from the AuNP nanogap. Surprisingly, the plasma-treated AuNP nanogap remains stable, and no sintering is initially observed (see dark-field view in Figure 8b). The SERS spectrum (Figure 7, center) confirms that the molecules bound to the surface have been completely detached and all molecular vibrations have disappeared (see Figures 24 and 25 for XPS spectra). Oxygen plasma cleaning introduces several monolayers of gold oxide to the AuNP surface, resulting in ν(Au-O) ≈ 600 cm⁻¹. -1 A broad peak

[35] is obtained, which is clearly shown in XPS measurements (Figures 26 and 27). The formation of the Au2O3 phase doubles the volume per Au atom, meaning that the three surface layers expand into the gap until they are completely oxidized, and then fill the entire gap volume. The nanoparticle layer can maintain this metastable state for many hours if stored at low temperatures (below 4°C)

[29] and away from direct sunlight. In aqueous solution, the nanoparticle layer remains stable for several days.

[0082] In the final step, the scaffolding ligand is reintroduced to the oxidatively clean AuNP surface by immersing the nanoparticle layer in a suitable solution. The inventors have successfully tested a wide range of small ligands (including L-cysteine, cysteamine, CB[5], CB[7], etc.). It has been shown that L1 can be replaced with L2=CB[5], which has very favorable scaffolding properties, regardless of the initial ligand L1.

[0083] After adding three types of L1 surfactants (MUA, CB[5], and NaCl) as described above, the layers were immersed in a CB[5] solution (approximately 1 mM). At pH 7, the gold oxide layer is inert, so it takes several days for CB[5] to penetrate all nanogaps. However, at low pH levels such as pH < 3, CB[5] binds to the surface of the gold nanoparticles within seconds, using 1 M HCl or H2SO4 to remove the gold oxide. All three nanoparticle layers exhibit very clean CB[5]SERS spectra (Figure 7, right), with minimal relative variation (1 / 100th of before replacement). This confirms that after the oxidative washing and redefinition procedure, the gap nanostructures have become more consistent, meaning they have been reconstructed into a reliable shape and unwanted molecules have been removed.

[0084] Controlled reconstruction of nanogap Because quantitative and reliable characterization of sub-nm scale gaps by transmission electron microscopy (TEM) is difficult, a more suitable tool for analyzing these changes is dark-field (DF) spectroscopy. Spectra were collected in the same region across three nanoparticle layers both before oxygen plasma treatment and immediately after redefining the gap with CB[5] (Figure 8). Histograms for each nanoparticle layer sample record the peak wavelengths of coupled plasmon modes, and the mean dark-field spectra are also displayed. These peak wavelengths are determined by the gap size and the effective refractive index within each nanogap.

[36]

[0085] The DF spectra of different initial ligands L1 before plasma treatment show distinctly different peak locations and distributions. The MUA layer (Figure 8, left, "MUA") exhibits the shortest wavelength plasmon (approximately 740 nm) and the broadest peak distribution. Since the MUA molecule is longer and more flexible compared to citrate and CB[5], this supports a larger average gap size with greater variability (estimated to be 1.2 ± 0.4 nm

[37] ). In contrast, the CB[5] and citrate nanoparticle layers show narrower peak distributions. The CB[5] peak is blueshifted (approximately 780 nm) compared to the nanogap defined for citrate (approximately 800 nm), and assuming similar refractive indices, this difference suggests a smaller average gap size (0.1 nm smaller) for the nanoparticle layer defined for citrate.

[0086] Despite the initial differences in gap sizes, after oxygen plasma treatment and redefinition of the nanogap with CB[5] / HCl, the same peak wavelength of approximately 790 nm was observed in all three nanoparticle layers. This means that the gap sizes of all three layers are nearly identical, explaining why the SERS (Figure 7, right) is so consistent. The MUA layer also produced a small additional peak of approximately 735 nm after plasma treatment and redefinition, and although the SERS spectrum (Figure 7, right) shows no signs of residual MUA molecules, it suggests the presence of several larger gaps.

[0087] Further experiments confirmed the stabilization of the nanogap by various scaffolding ligands after oxygen plasma treatment. Molecules such as 3-mercaptopropionic acid (MPA), citrate, acetic acid, cysteamine, dopamine, paracetamol, ethanol, and methanol all provided a robust structure. In contrast, molecules that do not normally bind to gold, such as acetone and glucose, did not function as stabilizers.

[0088] Surface gold atoms that "flow" at room temperature DF and SERS data demonstrate atomic-level reconstruction of the gold surface within the plasma-treated nanogap, enabling controlled redefinition of the nanogap. Exfoliation of surface-binding molecules from the gold nanoparticle surface during oxygen plasma treatment forms an oxide coating, which seals the nanogap and stabilizes the metastable state (Figure 9, top center). Even when immersed in a CB[5] solution (pH 7), the oxide coating prevents CB[5] from binding within the nanogap, resulting in only very weak CB[5] SERS peaks appearing over several days.

[0089] When a small amount of 0.5 M HCl (pH 0.3) is added, the oxide groups are hydrolyzed, and the AuNP structure immediately becomes unstable. The inventors have observed two pathways for this process: (1) When the nanoparticle layer is exposed to HCl in the absence of a scaffolding ligand, individual gold atoms in the nanogap flow toward adjacent AuNP facets (Figure 9, upper left), forming bridges between AuNPs, and all SERS are lost (within a few seconds). Sintering of AuNPs usually requires heating the substrate to overcome the activation barrier against the movement of gold atoms [38-41], but the chemical sintering process here occurs at room temperature. The inventors have found that this process is irreversible, and the nanoparticle layer is not reactivated by subsequent plasma treatment. (2) Conversely, in the presence of a scaffolding ligand and HCl (Figure 9, upper right), the scaffolding ligand binds to the nanogap, effectively preventing the sintering of AuNPs. Therefore, the inventors suggest that a key element of the present invention is the loss of oxides and the rescaffolding of nanoparticles by scaffolding ligands that precisely reconstruct the nanogap and facets.

[0090] The results of HCl-induced sintering of newly plasma-treated AuNPs can be observed in SEM images (Figure 9, bottom left). These images clearly show that gold atoms on adjacent AuNP facets flow to each other, forming bridges. In large AuNPs with large initial facets (100 nm in diameter)

[42] , this sintering is less pronounced than in smaller AuNPs (80 nm and 60 nm; Figure 28). Most importantly, sintering does not occur in the non-plasma-treated nanoparticle layer exposed to the same concentration of HCl (Figure 29a) or in the plasma and ligand / HCl-treated nanoparticle layer (Figure 9, bottom right). Similar results are obtained when the sintering experiment is repeated using sulfuric acid instead of the same molar concentration of HCl (Figure 29b). The observed size dependence suggests that curvature, in conjunction with the liquid-solid surface energy, can drive this process.

[0091] Nanoparticle layer as a molecular sensor Plasma-treated nanoparticle layers offer a wide range of possibilities for molecular sensing applications. Below, we demonstrate that the nanoparticle layer improves spatial reproducibility after oxygen plasma cleaning, and, combined with complete control of the scaffolding ligand, allows for the removal of unwanted compounds (such as citrates) from metal surfaces. The inventors discovered that CB[n] can be used as the scaffolding ligand and the substrate can be reused multiple times by immersing it in a 1M HCl solution.

[0092] Liquid sensing To demonstrate these sensing and cleaning functions, the inventors first show that toluene, a highly hydrophobic and volatile compound, can be detected at concentrations below 10 ppm. To simplify handling and better control toluene concentration, they first detect a range of concentrations in aqueous solutions. Despite its hydrophobic nature, it is possible to obtain concentrations up to 5 mM in water, which is sufficient to cover the required range.

[0093] The experimental protocol (Figure 10) involves repeating a cycle of (I) exposing the nanoparticle layer sample to toluene (20 minutes), followed by washing with HCl and blow-drying with N2. The nanoparticle layers used in this experiment are fixed to thin glass slides, plasma-cleaned, and redefined with CB[7] molecules. SERS signals are collected through coverslips. This is a major advantage of these nanoparticle layers, which combine simple optics with immersion in a liquid or vapor cell.

[0094] Toluene ring breathing mode (995cm) -1 ) and CB[7] Signature Peak (833cm -1 Extracting the ratio of HCl to toluene clearly demonstrates the cleanability with HCl and a detection limit of less than 11 ppm (Figure 12). This is below the ACGIH 8-hour threshold of 20 ppm. It is important to emphasize that in this experiment, we started with the highest concentration (180 ppm) of toluene and the same nanoparticle layer was used throughout the experiment. The small background signal ratio after each wash remained almost constant, increasing only after the first exposure, which is probably due to slight reconstruction of gold. Surprisingly, the strongest response was not obtained even at the highest concentration. This is thought to be because toluene dimerizes within the nanogap at high concentrations. In the nanoparticle layer that was not plasma-washed, this effect was not observed and the detection limit deteriorated significantly (Figure 32).

[0095] Steam sensing To demonstrate the sensitivity of the nanoparticle layer to various volatile compounds, the layer was exposed to the vapors of five molecules (Figures 11 and 13), plasma-cleaned again, and exposed to the nanoparticle layer redefined with a CB[7]. Sensing was performed in a glass container sealed with a coverslip, where the vapors accumulated to saturation concentrations (acetone 611 ppm, methanol 120 ppm, toluene 1.8 ppm, ethanol 172 ppm, DMSO 109 ppm). The SERS intensity after subtracting background (Figure 14, left) confirms that the nanoparticle layer can detect methanol, ethanol, toluene, acetone, and dimethyl sulfoxide (DMSO). Here, a CB[7] is used because it has sufficient internal volume to capture each of these molecules. DMSO produced the strongest SERS signal at a very low saturation concentration of only 1.8 ppm. This is thought to be because DMSO interacts most strongly with the gold surface.

[43]

[0096] The spatial distribution and reproducibility of toluene vapor sensing within nanogaps on a nanoparticle layer defined by CB[7] are tracked through a high-resolution 50×50 μm SERS map (Figure 14, right). The vibrational response of CB[7] clearly images the monolayer region (weak), the bilayer region (strong), and the mixed monolayer and bilayer region on the nanoparticle layer. Essentially, this maps the number of nanogaps beneath the laser spot and can be used as a normalized signal. Comparing the toluene signal normalized to CB[7] (Figure 14, bottom right), a much more uniform response is revealed, regardless of the number of nanoparticle layers or gap density. This suggests that when the nanoparticle layer has a bilayer structure, toluene vapor penetrates equally deeply into the nanogaps of both layers. Therefore, in quantitative measurements, reliable measurements can be achieved by calibrating the detection signal using normalization to the CB[7] vibrational component. To investigate the detection limit of VOCs in the nanoparticle layer, experiments are needed to systematically investigate the optimal scaffolding ligand L2 for each analyte. However, the excellent reproducibility and sensitivity of these technologies in VOC sensing suggest their future potential.

[0097] Flow sensing and cleaning A further application of the nanoparticle layer of the present invention is its direct integration into a flow cell for sensing the inflow of an analyte (Figure 15). For liquid and vapor sensing, the nanoparticle layer is fixed to a glass coverslip (coated with a 5 nm Cr layer to enhance adhesion; see "Gold Nanoparticle SERS Substrate - Detailed Method") and plasma-coupled to a PDMS fluid tip. The nanoparticle layer is again plasma-cleaned and redefined with CB[7]. Two syringe pumps connected to the PDMS tip initiate and control the flow rate of the analyte at approximately 10 μL / s. SERS pump lasers are incident through the coverslip, and the light is collected along the same path, directly separating the optical system from the fluid system.

[0098] The inventors used this flow cell to investigate the kinetics of analyte isolation and nanogap washing. This is demonstrated in flow by switching the liquid flowing over the nanoparticle layer between the selected analyte and HCl for washing. Here, paracetamol is selected as the analyte. In this experiment, after a 20-second washing cycle with HCl, paracetamol (1.5 mM) is flowed for another 20 seconds. Dynamic SERS scanning with an integration time of 0.5 seconds clearly separates the switching between flowing paracetamol and HCl (Figure 16). It was found that a consistent signal was maintained even after dozens of wash and sensing cycles.

[0099] To extract different component spectra from such dynamic measurements, independent component analysis (ICA) is optimal for obtaining three independent spectra (Figure 17) (see "Gold Nanoparticle SERS Substrate - Detailed Method"). These spectra are similar to those of CB[7] and paracetamol. The latter shows two distinct spectra related to the protonated and deprotonated states (by density functional theory simulations). The corresponding time-dependent ICA scores (Figure 18) indicate that washing with HCl occurs within seconds and is fully reproducible between cycles. Furthermore, it is clear that the time-dependent isolation of paracetamol into the sensing gap follows an exponential function (Figure 19), which is consistent with a simple theoretical model based on Langmuir isotherms. This confirms that equilibrium is obtained with a simple, open, layered nanoparticle shape despite the small gap size used to obtain a strong SERS for sensing.

[0100] Surprisingly, the profile of protonated paracetamol shows sharp spikes immediately after the start of paracetamol inflow and at the start of HCl inflow. During the transition from HCl to paracetamol, a significant portion of the protonated paracetamol enters the nanogap. Protonation occurs by the backflow of acid into the tube carrying paracetamol while HCl is flowing. As more paracetamol flows through the nanoparticle layer, the pH returns to equilibrium and the ratio of protonation to deprotonation signals becomes constant. During the transition from paracetamol to HCl, the acid flow first protonates the paracetamol in the nanogap before releasing it, leading to the second observed spike. This clearly indicates that protonation is faster than the removal of paracetamol from the nanogap, as expected from the dependence of the diffusion rate from protons on the molecular weight of paracetamol. Thus, this high-speed SERS flow sensing device is very promising for distinguishing a variety of small molecule analytes.

[0101] The above demonstrates that a nanoparticle layer, composed of one (or more) layers of randomly and densely packed gold nanoparticles, provides a sensing platform with superior optical and fluid access. The inventors demonstrate that the chemical reactions of the nanogap can be controlled with far greater precision than before, which is crucial for practical sensing applications. By treating the layer with oxygen plasma, all organic compounds are removed from the surface while preserving the gold facets. The oxide layer remaining on the surface prevents and stabilizes the nanoparticles. If removed by acid in the absence of ligands, gold atoms migrate between opposite faces, forming bridges and destroying the sensor properties. However, in the presence of ligands, the gold facets are reconfigured, new scaffolding is accommodated within the nanogap, and the local chemical environment is altered. Even if the nanogap is initially heterogeneous, defined by various molecules, oxygen plasma and acid treatment allows for successful integration of CB[5] molecules into the nanogap. The newly redefined layer provides a highly reproducible SERS spectrum with a robust and precise gap (similar to solution aggregation, but attached to a solid substrate).

[0102] This simple protocol yields a reconfigurable, highly sensitive SERS substrate with excellent sensing capabilities for compounds in solution (such as toluene) and vapor. Washing of the nanoparticle layer between sensing cycles is performed by flowing HCl through it. The plasma-treated CB[7] nanoparticle layer detects many volatile organic compounds, including DMSO, toluene, acetone, methanol, and ethanol. VOCs penetrate both layers of the bilayer nanoparticle layer, providing a calibrated analyte response using normalization with the CB[7] signal. The nanoparticle layer is highly suitable for integration into flow cells due to its optical accessibility from the back surface, enabling repeatable sensing and washing cycles. Therefore, this study demonstrates the potential for continuous monitoring in many applications, from environmental monitoring to healthcare monitoring, including water quality, urine, and saliva sensing.

[0103] Gold nanoparticle SERS substrate - detailed method Preparation of the nanoparticle layer Equal volumes (500 μL) of chloroform (CHCl3) and commercially available AuNP are added to a standard 2 mL centrifuge tube (Eppendorf) to form a two-phase system in which the AuNP suspension floats on top of the chloroform phase. Unless otherwise specified, the size of AuNP in SERS measurements at 785 nm excitation is 80 nm. In the agglutination step using CB[n], 5 μL of approximately 1 mM CB[n] solution is mixed with the AuNP phase. For NaCl agglutination, a high volume of 150 μL of 0.5 mM NaCl solution is added. Agglutination using 11-mercaptoundecanoic acid (MUA) is achieved by saturating the chloroform phase with MUA and then vigorously shaking the centrifuge tube. This method allows for the agglutination of AuNP with molecules that are insoluble in water but soluble in chloroform (such as MUA).

[0104] After vigorously shaking the AuNP / chloroform system, carefully pipette to remove approximately 80% of the supernatant containing the newly aggregated AuNP. Following this step, replenish the centrifuge tube with deionized water. Repeat the exchange of supernatant with deionized water three times to remove large aggregates and significantly reduce the salinity. During this process, a monolayer of AuNP forms between the liquid-air interface and the liquid-chloroform interface (extending to the inner wall of the centrifuge tube). Finally, remove as much of the supernatant as possible (>80%) to concentrate the AuNP monolayer into small droplets (1-5 μL). Transfer these droplets onto a substrate such as a gold-coated Si wafer or coverslip (for flow and vapor sensing experiments). Allow the droplets to dry for several hours.

[0105] Once dry, rinse lightly with DI water to remove excess salt, then dry with N2. Plasma treatment is performed using a commercially available oxygen plasma cleaner (Dienerelectronic GmbH + Co.KG) at an oxygen mass flow rate of 30 sccm and RF power of 90% for 30 minutes. Redefinition of CB[n] is achieved by first dropping a CB[n] solution (approximately 20-50 μL, 1 mM) onto the nanoparticle layer, and then adding a small amount (1-5 μL) of HCl (1 M) to the CB[n] droplets. After 10 minutes, rinse the nanoparticle layer with DI water and finally carefully blow dry.

[0106] Dark-field and SERS measurements SERS spectra are acquired using a commercially available Raman spectrometer (Renishaw inVia) with 785 nm excitation (laser line profile) at a laser power of ~150 μW (0.1% setting) and a 20x objective lens to avoid damage to the nanoparticle layer. High-resolution maps of MUA, CB[5], and NaCl are recorded using the accompanying Renishaw software.

[0107] In map scanning, the nanoparticle layer is deposited on a single large gold-coated coverslip (with a 5 nm chromium bonding layer), with each layer having a diameter of 2–4 mm. SERS spectra are acquired with a 200 μm grid size (10–20 rows and columns depending on the layer diameter), and the sample is exposed for 1 second per spectrum.

[0108] Dark-field reflectance spectra are acquired using a custom microscope setup consisting of an Olympus BX51 microscope, a 20x Zeiss objective lens, and an OceanOptics QE-Pro spectrometer (integration time 0.5 seconds). All spectra are referenced to a white scatterer (Labsphere). The grid size is consistent with SERS measurements (200 μm). The substrate is spatially normalized to ensure consistency between SERS and dark-field spectra.

[0109] SEM measurement Nanoparticle layer samples were prepared according to the standard protocol (see Nanoparticle Layer Preparation) and deposited onto Au-coated silicon wafers cut into small pieces. SEM measurements were performed using an FEI Philips Dualbeam Quanta3D instrument (dwell=100ns, HV=5kV, current=25pA, WD approximately 4mm). Magnification was varied between 150k, 200k, and 250k.

[0110] Steam sensing experiment A droplet of the volatile compound (approximately 50 μL) is pipetted into a glass vial of approximately 5 mL. The ends and neck of this vial (inside and outside) are wrapped with a single layer of Parafilm M. Next, a layer of CB[n]-redefined nanoparticles deposited on a thin borosilicate coverslip is placed on top of the class vial so that the nanoparticle layer faces inward. To seal the setup, the coverslip is lightly pressed against the Parafilm-backed surface. The setup is left for approximately 20 minutes before the SERS measurement to allow sufficient time for the saturation concentration to rise. The SERS spectrum was obtained through the coverslip. During the experiment, the droplet never completely evaporated. This indicates that there is enough analyte to reach saturation concentration even without knowing the exact volume.

[0111] Liquid sensing experiment Sensing of aqueous toluene is performed in a manner similar to that of vapor sensing. The nanoparticle layer redefined in CB[7] is again deposited onto a thin borosilicate coverslip, which is then placed on a droplet of toluene solution for 20 minutes (±10 seconds), after which the SERS spectrum is immediately acquired. In this experiment, only one layer is used and recycled between measurements by HCl treatment, water washing, and nitrogen blow drying. The experiment starts with the highest concentration of toluene and decreases in concentration with each cycle.

[0112] Flow sensing experiment Paracetamol / HCl sensing and cleaning experiments are performed on a nanoparticle layer deposited on a coverslip. The nanoparticle layer is prepared according to a standard protocol, but redefined with CB[7] molecules instead of CB[5]. The layer on the coverslip is then plasma-coupled to the PDMS chip (the layer facing the inside of the chip's channels) by exposing it to oxygen plasma for a short time (several seconds). Briefly, the PDMS chip is manufactured from a template master mold by standard soft lithography. In this process, SU-82100 negative photoresist is uniformly spin-coated onto a silicon wafer to achieve a layer height of approximately 150 μm. After additional baking and exposure to ultraviolet light (via a photomask), the wafer is immersed in PGMEA (1-methoxy-2-propanol acetate) to develop the photoresist and hard-bake it. The chips were fabricated using a PDMS kit (SYLGARD184, Sigma-Aldrich) with a 1:10 (curing agent to PDMS monomer base) mixture ratio (after degassing, fired at 120°C for 30 minutes). For flow experiments, the PDMS chips were drilled with two inlets and one outlet (1 mm in diameter). The inlets were connected to custom syringe pumps containing HCl (1 M) and paracetamol (1.5 mM) solutions. Kinematic SERS measurements were performed using a 63x (numerical aperture, NA=1.2) water immersion objective lens with an integration time of 0.5 seconds. The liquid flow was circulated for 20 seconds each of paracetamol and HCl.

[44]

[0113] Additional Information [Table 1]

[0114] In the plasma-cleaned film shown in Figure 12, the toluene peak is shown at a different spectral position (the same position as pure toluene) at the highest concentration (180 ppm). At lower concentrations, the peak shifts slightly to lower wavenumbers, as is known from the interaction between toluene and water. Therefore, the disappearance of the signal at high concentrations is thought to be due to the dimerization of toluene and the resulting weakening of the SERS cross-section.

[0115] The peak positions of the dark-field spectra in the nanoparticle layer fractal mode are closely related to the plasmons on the 1D chain. Their resonance wavelengths can be estimated through an electrical coupling model (similar to the tight-binding interaction model),

Number

[0116] In a simple estimation comparing the dimer and the nanoparticle-on-mirror mode (inserting a ground plane (i.e., a mirror) between the two NPs of the dimer), a scaling factor of 2 between their coupling capacities is used.

[0117] Combining these, the NpoM resonance is obtained from the perspective of the nanoparticle layer resonance, which is

Number

[37] and https: / / www.np.phy.cam.ac.uk / npom-calculator [accessed March 30, 2023]). Using the data in Fig. 37, for the gap spanning the CB, it is suggested that d~0.9 nm and n g ~1.1 (as expected for non-polar molecules). When these are oxidized, a significant red shift is due to the expected refractive index n gIt matches ~1.8 and is compatible with d~1.8nm, which has twice the gap size.

[0118] SERS substrate containing sensitizing gold nanoparticles The inventors discovered that by utilizing a self-assembled nanoparticle layer of 60 nm gold nanoparticles within a closely packed array fixed on a glass substrate, it is possible to sense neurotransmitters down to nM concentrations. Multiplicative SERS enhancement is achieved by integrating Fe(III) sensitization into a precisely defined sub-1 nm nanogap targeted for dopamine sensing. The transparent glass substrate allows efficient access of fluid and light from both sides of the nanoparticle layer, enabling repeated sensing with different analytes. Repeated reuse after analyte sensing is possible by returning the nanogap to its original state through oxygen plasma oxidation cleaning and redefinition. Investigating binding competition in multiple sensing of two catecholamine neurotransmitters, dopamine and epinephrine, reveals their bidentate binding and interactions. These systems enable the integration of a wide range of microfluidics, allowing for extensive and continuous biofluidic monitoring in personalized medicine applications.

[0119] While continuous monitoring, diagnostic equipment, and precision medicine have garnered significant social interest, there is a need to improve the detection of meaningful target biomarkers. Neurotransmitters are important biomarkers because, as chemical mediators that transmit electrochemical signals, they control a wide range of biological and physiological processes.[50,51] Imbalances or dysregulations of certain neurotransmitters, such as dopamine (DA), are associated with a variety of neurological and psychiatric disorders, including Parkinson's disease

[52] , schizophrenia

[53] , Alzheimer's disease, depression

[54] , and attention deficit hyperactivity disorder (ADHD)

[52] . DA also affects cognitive behaviors such as mood, concentration, and motivation, as well as metabolism and immune function.[55,56]

[0120] To understand the complex changes in neurochemistry and to comprehensively grasp the effects of DA on physiological processes, a highly sensitive, selective, and accurate quantitative sensing platform is needed that can frequently utilize nanomolar-level detection.

[57] Conventional techniques for detecting neurotransmitters include classical electrophysiological methods that measure changes in membrane current [57,58], or more technically demanding high-performance liquid chromatography, mass spectrometry

[59] , fluorescence detection

[50] , ELISA, capillary electrophoresis

[60] , and microdialysis [51,61]. Nevertheless, all techniques face the same fundamental challenges imposed by the inherently low concentrations of neurotransmitters in biological fluids, reduced selectivity due to the similarity of chemical structures between different neurotransmitters, and consequently, very limited sampling intervals.

[62] Furthermore, these conventional techniques are limited by long operating times, large sample volumes, the need for large equipment, labor-intensive operations, and the need for highly trained personnel, and are all costly. [50,63]

[0121] To innovate next-generation personalized point-of-care medical sensors, key challenges must be addressed, including integration, improved analyte sensitivity, reproducibility, reusability, and multiplexing. A promising emerging technology addressing these challenges is based on optical sensing using surface-enhanced Raman spectroscopy (SERS). SERS utilizes the plasmonic properties of metal nanostructures, allowing light to couple to collective electron vibrations (plasmons) within the metal. These plasmons can focus the optical field to below the diffraction limit, to dimensions close to the molecular length scale.

[64] Spatially localized optical fields, known as hotspots, typically form in gaps and edges of self-assembled nanostructures. [65,66] The resulting plasmonic fields greatly enhance the incident light and the resulting Raman scattering from molecules. Characteristic vibrational SERS fingerprints recorded from different molecules (no analyte labeling required) enable multiplexing, and excellent sensitivity, down to real-time single-molecule specificity [67-69,30], could provide a low-cost solution for sensing bioanalytes. However, realizing a suitable flow-based, reusable, and reproducible SERS platform has been challenging. Simultaneously, a lack of precise knowledge regarding molecular bonding, surface chemistry, nanoscale geometry, and their interactions has hindered a detailed understanding of the SERS sensing process.

[0122] SERS Platform This section describes a multi-purpose SERS platform and its use for quantifying catecholamine neurotransmitters, revealing analyte binding and competition and enabling effective reuse. While signal enhancement is relatively easy to obtain with SERS substrates, there is little detailed control over precise hotspot shape, and the use of anything other than simple thiolated targets or dyes results in unreproducible / unpredictable signals.

[70] When self-assembled Au nanoparticles (AuNPs) optimally aggregate to form nanogap hotspots, a typical substrate is obtained in terms of reproducibility, ease of manufacture, scalability, low cost, and accuracy (Figures 43, 44, 45, 46).

[70] However, when AuNPs in solution are aggregated using molecules or salts that define the gap as a coagulant ("Solagg," Figure 43), a suspended SERS-active substrate undergoing Brownian motion is generated, requiring a large focal volume to allow for averaging of the SERS signal, resulting in interference from the coagulant and limiting the scope of system reuse or cleaning. Furthermore, the detection limit is limited because it is difficult to control the number of active nanogaps compared to the concentration of the bulk analyte.

[0123] Here, the inventors aggregate AuNPs into a two-dimensional random close-packed array and immobilize them on a substrate that fixes the position and spacing of the nanogaps, allowing for further processing. These nanoparticle layers (Figure 44) are reliably formed through a liquid-liquid interface assembly

[71] and transferred to any substrate (here, Raman-grade glass). The resulting low flexibility of molecular access to the nanogaps allows for efficient access to the analyte from a liquid, vapor, or gas flowing over the nanoparticle layer. Simultaneously, light directly examines the same nanogaps from the opposite side (Figure 45). This results in a preferred device shape compared to, for example, optically opaque electrochemically roughened Ag or colloidally precipitated nanoparticles. Another important feature of using nanogaps immobilized as layers on a substrate is that they can be cleaned and reused, which is ideal for applications of such sensors in point-of-care technology. Both acid (HCl) and oxygen plasma treatments are used to thoroughly remove all organic molecules from the nanogap surface and restore the surface's chemical properties. [72,73] This greatly helps maintain the consistency and reproducibility of sensor performance, removing not only capping agents such as citric acid but also any potentially interfering flocculants.

[34] Finally, the nanogap immobilized on the substrate can be integrated into microfluidic systems, such as SES substrates suitable for fraction monitoring or in-situ washing and calibration against standards for quantification.

[0124] However, the affinity between neurotransmitters (NTs) and such SES substrates is too low for the nanoparticle layer to sense NTs at clinically relevant concentrations (Figure 47, "without Fe"), and this is addressed in this study. The inventors outline a method using the nanoparticle layer to optimize NT sensing by utilizing complex formation between Fe(III) and catecholamines [74-79] and demonstrate nanomolar sensitivity. The inventors found that the nanoparticle layer was 5000 times superior to the Solagg colloid in terms of SERS intensity and performed a cleaning process for repeated flow sensing through a highly reproducible plasma cleaning protocol. The inventors elucidated factors that play a crucial role in the surface chemistry of analyte binding affecting quantitative measurements. Finally, the inventors are studying competitive binding mechanisms and oscillatory coupling between different NTs (dopamine (DA), epinephrine (EPI)) for multiple sensing.

[0125] result Sensitization of Fe(III) in nanoparticle layers Recent studies have demonstrated that incorporating Fe(III) ions into SERS substrates makes tholaxx more specifically sensitized to catecholamine NTs.

[79] It is thought that Fe(III) adheres to the Au surface and binds NTs to hotspots. Two protocols for introducing Fe(III) were investigated: one is to introduce Fe(III) simultaneously with DA after the AuNP aggregation process (PostFe), and the other is to pre-incubate the AuNP components in Fe(III) solution before AuNP aggregation (PreFe). Here, it was shown that the presence of Fe(III) is important for NT detection, and that the PreFe protocol yielded the best results, enabling nanomolar level NT detection. This suggests that individual NTs diffuse more easily into nanogaps (compared to when they initially form a large Fe complex), where they bind to Fe(III) bound to the surface.

[0126] The same protocol was applied to the nanoparticle layer, with the addition of an additional initial pre-cleaning process using plasma (see “Sensitized Metal Nanoparticle SERS Substrate – Detailed Method”). The PreFe protocol was found to be 3 times more sensitive than the PostFe protocol and 30 times more sensitive than without Fe(III) sensitization (Figure 47). This supports the idea that the nanoparticle layer behaves similarly to previously observed tholaxx.

[79] In both PreFe and PostFe sensing, DA peaks were observed at 812, 1269, 1324, 1425, and 1482 cm⁻¹, which can be attributed to well-known iron catechol complexes of DA [74, 75, 77, 80-83] and are consistent with density functional theory (DFT) calculations regardless of the NT protonation state (Figure 48).

[0127] Furthermore, comparing the sensitized nanoparticle layer with the sensitized SOLAG (Figure 46), the inventors discovered that, when power, time, and the number of hotspots were normalized, a signal 5000 times stronger per hotspot was achieved in the nanoparticle layer system. This indicates that the PreFe nanoparticle layer system provides the highest SERS response among these protocols and will be used for the remaining characterization and optimization. This also allows for lower laser power excitation (<1mW), enabling the implementation of cheaper and safer laser products (such as Class 2 lasers), thus facilitating the transition to miniaturization technologies.

[0128] 450-600cm -1 The three SERS peaks in the range are thought to be due to iron-catechol complex (Fe-O) bond vibrations [74, 75, 77, 84, 85], and the changes with ambient pH are thought to be due to the formation of mono, bis, or tris complexes between DA and Fe(III). These peaks make it possible to distinguish between different metal-ligand complexes.

[75] In particular, 585 cm -1 and 633cm -1 The peak is attributed to the interaction of Fe-O(C3) and Fe-O(C4) stretching of the Fe-catechol bond [77,85], confirming the formation of the DA:Fe(III) complex. 530 cm-1 The peak is attributed to the charge transfer interaction of the bidentate iron-catecholamine complex (Figure 58, peak a). 530 cm -1 The integral peak and 585 cm -1 and 633cm -1 The relative ratio of the peaks indicates the coordination of the DA:Fe(III) complex formation state. [75,77,85] This analysis shows that bis-complex formation of NT is dominant in the Fe(III) sensitized nanoparticle layer system (Figure 49).

[0129] To determine the sensitivity of these sensors and optimize their performance, it is crucial to determine the diffusion and binding kinetics of the analytes and elucidate the key surface chemistry involved. The kinematic behavior of nanoparticle layer sensing is first tracked over time using the primary SERS peak intensity of 1482 cm⁻¹ for various DA concentrations from 10 to 100 μM (Figure 50, left). This shows that the SERS signal initially increases at a nearly linear rate, but then exhibits a characteristic offset delay (τ) corresponding to the exfoliation of the protective molecular coating within the nanogap. d This indicates that it increases only after (see explanation below). It can be seen that the lower the DA concentration, the longer the offset time and the slower the diffusion of the analyte to the hotspot (τ r -1 These parameters are extracted by fitting the concentration data to a Langmuir isotherm model

[86] (Figure 50, left). The observed unexpected offset delay suggests that there is a surface protection that must be overcome before DA can bind to Fe(III) and be detected. To understand this, we analyzed the surface chemistry at several stages of the nanoparticle layer fabrication process.

[0130] Characteristics of the cleaning process After the AuNPs initially aggregate into the nanoparticle layer, a bare nanoparticle layer containing the surfactant is exposed. This is seen in the initial SERS spectrum (Figure 61, bottom row) at 1100–1600 cm⁻¹. -1It has multiple broad peaks. This highlights one of the major confounding factors in actual SERS sensing from surfactants and contaminants that alter surface bonding and introduce undesirable vibration lines. To keep the surface clean, the nanoparticle layer is treated with oxygen plasma for 15 minutes. The oxygen plasma removes any organic deposits, including AuNP stabilizers / capping agents such as citric acid.

[71] After oxygen plasma treatment, all organic peaks disappear and 600 cm -1 A broad gold oxide peak remains nearby (Figure 51, top row and second row from the bottom). If the processing time is insufficient, residual oxidized citric acid reaches 1050 cm³. -1 This shows a peak. The substrate primed by this repeated washing protocol opens up new possibilities for reusing nanoparticle layer sensors even after the analyte has been packed into the nanogap. This reuse enables key characteristics for versatile sensors, such as increased sustainability, improved reproducibility, and greater accessibility for a wider range of target users.

[0131] To demonstrate the effectiveness of this cleaning protocol, when DA was flowed over the plasma-cleaned nanoparticle layer, a large signal was obtained as before (Figure 51, second row from the top) (Figure 47). To further emphasize this control, no trace of DA was found after subsequent plasma cleaning cycles (Figure 51, top line).

[71] This oxygen plasma cleaning treatment and re-exposure to the analyte can be repeated many times (Figures 60 and 61), and the SERSDA signal remains stable after initially decreasing slowly in the first 11 cycles. No changes in vibration fingerprints or uniformity were observed throughout the sample, and statistical variability was observed to decrease as the gap morphology reached a stable configuration. The inventors noted that Fe(III) was not returned, suggesting that Fe(III) was strongly incorporated and remained active. The stability of these SERS substrates is significantly improved compared to substrates that are quickly damaged when exposed to cleaning protocols such as ultraviolet irradiation or other gas plasmas. [73, 87, 88] The inventors note that although the literature claims that SERS substrates are reusable, [89, 90] thorough statistical analysis has not been quantified. Cleaning here is only possible if the inventors utilize a nanoparticle layer that allows plasma ions to access the nanogap, and is ineffective for substrates with large nanoscale curvature.

[0132] In both the "plasma cleaning" and "re-cleaning" samples (Figure 51, top row and second row from the bottom), 600 cm² -1The large peak observed is attributed to the formation of Au oxide. [91,92] To investigate this further, X-ray photoelectron spectroscopy (XPS) was used to map the various elements and their charge states in the nanoparticle layer. Relative XPS intensities under different sample conditions (Figure 52) were extracted. After plasma cleaning, a metastable Au(III) oxide layer

[38] is clearly present on the gold surface (Figure 52, center, Au(III); see "Gold-sensitized nanoparticle SERS substrate - detailed method, characterization by X-ray photoelectron spectroscopy" for details). This oxide layer (estimated thickness 0.3 nm, Gold-sensitized nanoparticle SERS substrate - detailed method, characterization by X-ray photoelectron spectroscopy) is important for maintaining the gap when molecular spacers are removed by oxygen plasma and preventing the Au facets from sintering. [71,38] Upon re-exposure to the DA solution, the Au(III) XPS peak disappears as expected, as the Au oxide has been removed. The DA powder used here is dopamine hydrochloride in a 1:1 ratio with hydrochloric acid (HCl), which is necessary for crystallization. The inventors discovered that this HCl exfoliates the oxide layer. If the oxide is not removed, DA cannot bond with Fe(III), and therefore, as the DA concentration decreases, the HCl concentration also decreases, which explains why the offset time is longer (Figure 50 left).

[92]

[0133] Another important element of a SERS substrate is uniformity and reproducibility, which can be quantified from the relative standard deviation (RSD).

[70] RSD is defined as the standard deviation of the SERS peak intensity relative to the mean intensity (often reported as a %). Substrates with an RSD of 5–15% are considered to perform well, but excellent reproducibility is achieved when the RSD drops to 1–3%. This usually occurs when the nanogap spacing is precisely controlled, for example, when defining a 0.9 ± 0.05 nm gap using a robust scaffold such as ququbit[n]uryl (CB[n]). [17,18] Electric field enhancement (E / E0) from gap plasmons is such that the SERS signal ∝ |E / E 0| 4 ∝d -4It is highly sensitive to changes in the gap spacing, as shown above. [70,93] When 50 SERS spectra are recorded from the entire substrate (Figure 53), the RSD uniformity is 6%, similar to that of a nanoparticle layer substrate defined as CB[n]. The variation is due to the non-uniform coating of Fe(III) and the local domains of the two-layer stacked AuNPs, which vary the number of hotspots probed at each measurement location. Based on the XPS data, a Fe(III) coating of 40±5% per AuNP is calculated (see Gold Sensitized Nanoparticle SERS Substrate - Detailed Method, Characterization by X-ray Photoelectron Spectroscopy). However, this may vary depending on the hotspot. Overall, the sensitized nanoparticle layer has proven to be a highly reproducible and accurate SERS platform.

[0134] Time-resolved detection limits To determine the detection limit (LOD) of the sensitized nanoparticle layer, the nanoparticle layer was immersed in DA solutions of various concentrations for extended periods, ensuring equilibrium bonding even at the lowest concentration (24 hours). SERS spectra were obtained from 10 points for each sample. The resulting average spectrum (Figure 54) clearly shows a peak characteristic of DA in the region below 500 nM. Principal component analysis (PCA) was performed, and the observed nonlinear response (Figure 55) indicates the presence of competitive bonding or inhibition (SERS substrate with sensitized nanoparticles - detailed method, principal component analysis). In practice, two different behaviors are observed. The inventors hypothesize that excess HCl in the DA solution, at high concentrations, accelerates the exfoliation rate of the oxide layer via the nanogap at different rates. Between 10 and 100 μM, the HCl concentration appears to bottleneck the rate of DA adhesion to Fe(III) and oxide removal, but below 10 μM, it is limited by the concentration of HCl present.

[0135] Therefore, the quantitative range of the PCA calculation is limited here to 5 nM to 100 μM, and the first principal component is fitted to the Langmuir-Hill model (Inset 55, Intensifying Nanoparticle SERS Substrate - Detailed Method, Langmuir-Hill Model). The LOD is determined as the intersection of the Langmuir-Hill fit and the 3σ confidence band of the noise level. The LOD of this system is 13.8 nM (the LOD of unwashable Solagg is 1.3 nM), and since the mean concentration of DA in human urine is 4 μM, the nanoparticle layer is suitable for clinical application.

[94] Furthermore, the limit of quantification (LOQ) is 49 nM at a 9σ confidence level. The inventors also note that other studies have claimed that extracellular DA levels are in the range of 0.5 to 100 nM. [55,95] The Hill coefficient extracted from the fitting was 1.3 (SERS substrate with sensitized nanoparticles - detailed method, Langmuir-Hill model), indicating that DA is actively and cooperatively bonded to Fe(III), clearly suggesting that further understanding of the diverse surface chemistry present in various SERS platforms is necessary to fully identify the available application areas.

[0136] In contrast, when the layer was exposed to the DA concentration for only 10 minutes (Figures 62 and 63), the observed LOD was only 22.8 μM. This is also thought to be because, at low concentrations of [HCl], the exfoliation of oxides from the nanogap within this time is limited. At low concentrations, the longer start time (Figure 50, left) hinders the immediate detection of DA. Therefore, the inventors emphasize that LOD specifications should always take into account Langmuir equilibrium time (which is usually not considered in assay specifications) and other effects such as the opening of hotspot sites and binding to Fe(III). One advantage of these nanoparticle layer sensors is that they can automatically filter out only small analytes that fit within the nanogap, excluding larger proteins and cellular components. However, in practical applications, it is clear that improved binding affinity is desirable to shorten the assay timescale.

[0137] Multiple neurotransmitter sensing In clinical applications of sensing neurotransmitters from bodily fluids such as urine, sensor selectivity is crucial, but it is also necessary to measure multiple analytes simultaneously. Therefore, the inventors studied the multiple sensing of DA and epinephrine (EPI), characterizing the distinction between the two similar species and investigating whether their interactions affect their signals. EPI is also a catecholamine with a structure very similar to DA, except for different functional groups (Figure 56a). Therefore, EPI also forms an Fe-catechol complex, similarly producing a highly enhanced SERS signal (Figure 56b). Consequently, their SERS spectra are similar in both the Fe-catechol and catechol ring vibrational regions. Nevertheless, as the inventors demonstrate, characteristic differences in peak ratios and additional peaks allow for the faithful extraction of independent molar concentrations.

[0138] When the DA:EPI ratio is swept from 0 to 100%, the measured SERS spectrum (Figure 57, left) can be reconstructed primarily using the linear superposition of the individual 100% DA and EPISERS spectra (Figure 67). However, an interesting additional effect is also observed, which appears only in the mixture and is strongest at 60:40% DA:EPI at 895 cm⁻¹. -1 This is a new SERS peak (Figure 57 right, Figure 68). This suggests that bis-complex formation with Fe(III) within the nanogap is the most stable, generating previously unseen vibrational transitions. The inventors found that hydrogen bonding between the NH2 terminal group of DA and the OH tail group of EPI results in approximately 940 cm² in each 100% complex. -1 This suggests that the weak vibrational modes are shifted and strengthened (due to the oscillation of the NH2 tail). DFT calculations for individual complexes fail to reproduce this mixing line (regardless of the protonation and hydration state of the clusters; see "Sensitizing Nanoparticle SERS Substrate - Detailed Method"). This suggests that these are intercomplex interactions rather than intracomplex interactions, thus supporting the separation of catechol ends within each complex.

[0139] As a result of these investigations, the inventors achieved a more detailed nanoscale understanding of how the Fe(III)-sensitized nanoparticle layer substrate generates a strong SERS signal for catechols. When other organic substances are removed by oxidation, a high coverage of Fe(III) remains within the nanogap hotspot. Upon removal of the oxides, these Fe(III) particles become active on the Au surface and can bind to catechols as bis-complexes (Figure 45). The inventors discovered that similar binding activity is observed for different catechols, and as a result, they found that faithful extraction of multiple concentrations can be achieved with a detection limit of less than 13 nM.

[0140] The inventors demonstrated that neurotransmitters can be sensed using Fe(III)-sensitized AuNPs on a highly sensitive and reproducible nanoparticle layer SERS substrate. These nanoparticle layers are deposited on a transparent glass substrate, enabling efficient access and sensing from both fluid and light, achieving RSD of 6% and LOD of DA less than 13 nM, exceeding clinical limits. By using oxygen plasma cleaning, all analytes can be completely removed, allowing the layer to be reused and providing a reproducible, pure hotspot for sensing. Such cleaning is only possible for nanoparticle layer samples where plasma ions can access the gaps. During oxygen plasma cleaning, the formation of gold oxides and subsequent reduction before DA detection can be directly observed by SERS and XPS. Multiplex sensing of neurotransmitters revealed excellent mixing and competition at the same site, as well as anomalous complex formation and vibrational coupling suggesting interactions between complexes. These devices are highly promising for microfluidic integration and translational implementations such as "smart toilets" for continuous monitoring and drug compliance. Simplified forms of plasma cleaning are available and should be studied as alternative methods for removing organic matter from nanogaps.

[0141] SERS substrate with sensitizing nanoparticles - detailed method Manufacturing of nanoparticle layers Standard 60 nm spherical AuNPs stabilized with citrate were purchased from BBI Solutions (UK). 500 μL of these 60 nm AuNPs were added to an Eppendorf tube containing 500 μL of chloroform and pipetted using a Pasteur pipette to form a two-phase system. This allowed for the aggregation of AuNPs by adding 150 μL of 0.5 M NaCl. The tube was then shaken for approximately 1 minute, allowing the color to change from clear red to opaque grayish-purple. Upon standing, the aggregated AuNPs precipitated at the interface between the chloroform and the aqueous phase. This aqueous phase was washed three times by adding and removing 300 μL of DI water, with excess citrate and salts being diluted and removed in each round. The remaining liquid was slowly removed from the aqueous phase until small, dense droplets of aggregated AuNPs were formed. The droplet is carefully transferred to a glass slide (Fisherbrand borosilicate glass, 16 mm) that has been washed before use with ethanol and DI water. The droplet is dried to form a nanoparticle layer, and after drying, the nanoparticle layer is washed away with DI water and then dried using a nitrogen gas stream. The surfactant on the AuNP surface is removed by oxygen plasma treatment by exposing the nanoparticle layer to oxygen plasma for 15 minutes (30 sccm, 90% RF power) using a Diener electronic GmbH & Co. KG plasma etcher. The substrate is carefully removed from the plasma etching apparatus, and the layer is immersed in 355 μL of dopamine hydrochloride solution (10 nM-10 mM), which is dispensed into a 96-well microplate made of black polypropylene (Greiner Bio-One Ltd). All reagents were purchased from Sigma-Aldrich.

[0142] Raman measurement The nanoparticle layer is measured using a Renishaw inVia confocal Raman microscope equipped with a 20x objective lens (NA=0.40) and a 785 nm laser. Unless otherwise specified, spectra are typically collected with an integration time of 1 second and laser power of 0.5% (incident power approximately 2.2 mW).

[0143] Characterization of nanoparticle layers Scanning electron microscope images were acquired using an FEI Philips Dualbeam Quanta3D with an acceleration voltage of 5kV and a current of 25pA. X-ray photoelectron spectroscopy (ThermoFisher Escalab250Xi) was performed using a monochromatic AlKα X-ray source.

[0144] Density Functional Theory (DFT) DFT calculations were performed using the B3LYP[96,97] hybrid generalized gradient approximation exchange-correlation function and Grimm's D3 variance correction (GD3BJ) with Becke-Johnson decay

[98] . The Def2SVP

[99] basis set was used for all atoms. All DFT calculations were performed using the Gaussian09Rev.E hyperfine integration grid.

[0100]

[0145] Calculation of hot spots probed with SERS substrate A simple calculation is implemented to estimate the number of hotspots investigated in both SolAgg and nanoparticle layer systems. Both substrates have λ=785nm and the NA of the 5x objective lens used is 0.12. For the nanoparticle layer, assuming a diffraction-limited spot on the sample, the laser irradiation spot size can be calculated as follows:

number

[0146] Considering that the AuNP is uniformly covered with a single layer of Fe(III), the effective diameter is estimated to be 61.9 nm thick, which illuminates the following region.

number

[0147] Assuming that each nanoparticle layer consists of 1.5 probed AuNPs and each AuNP supports 1.6 surrounding hotspots, we can see that N ~ 6700 gaps are being probed.

[0148] In the case of SolAgg, the laser spot diameter (A) is 1250 μm 2 It can be approximated as follows, with Rayleigh length z r The volume being probed can be calculated using this method.

number

[0149] Aggregation does not change the average particle density, and commercially available AuNP from BBI Solutions has a density of 2.6 × 10⁶ per mL. 10 Because it contains AuNP, the AuNP tested will be approximately 1.03 × 10⁶ 7 This results in approximately 1.7 × 10¹⁶ hotspots. Furthermore, assuming that each AuNP has 1.6 hotspots (with similar fractal dimensions), the total would be approximately 1.7 × 10¹⁶. 7 It will become a hotspot for individuals.

[0150] DA:DFT calculation of Fe(III) complex As described above, DFTs were calculated for both protonated and deprotonated DA. When calculating the bis-complex DA:Fe(III), the simulations correlated well with the experimental spectra, as shown in Figure 48. As can be seen in Figure 48 and Table 2, the protonated and deprotonated DFT spectra are almost identical, indicating that the presence and influence of different protonation states due to the presence of HCl in the DA solution can be ignored. Based on the literature, Raman modes can be assigned as shown in Table 2.

[0151] [Table 2]

[0152] Langmuir isotherm model The Langmuir model

[86] is based on the assumption that only a monolayer of non-interacting solute is dynamically formed on the adsorbent surface. The proportion of occupied hotspots is

number

number

number

number

[0153] Reproducibility testing using oxygen plasma treatment In the cleaning protocol used for post-manufacturing and reuse, each nanoparticle layer was cleaned with oxygen plasma at 30 sccm and 90% power for 15 minutes. To test the reproducibility and stability of the nanoparticle layers, the cleaning process was repeated as shown in Figure 59. After each plasma cleaning (PC), the sample was immersed in a 10 mMDA solution for 5 minutes before measurement. Five individual measurements were performed each time, and the standard deviation of the SERS count was obtained. In this reproducibility test, 1481 cm⁻¹ was obtained. -1 The peak intensity was analyzed. During the test, the SERS count returned to baseline, clearly indicating that the DA was completely detached from the substrate after each PC. This means that structural damage was minimal. However, as the number of repetitions increased, the SERS count decreased, saturating over time to about half of the initial value. The inventors concluded that SERS is E 4Since this is proportional to the difference, it is noted that this corresponds to a mere 20% decrease in the nanogap field E, i.e., a reduction in the accessible gap. Such a decrease in the field can easily occur through slight changes in the nanogap facets that redshift the resonance, resulting from changes in the input coupling of the pump optics.

[0154] Characterization by X-ray photoelectron spectroscopy The nanoparticle layer was characterized by X-ray photoelectron spectroscopy (XPS), and the results were analyzed using CasaXPS. All spectra were calibrated against the Au4f7 / 2 peak (83.9 eV) and the investigative spectrum of the nanoparticle layer after exposure to dopamine (Figure 60).

[0155] Before plasma cleaning, native Au4f with binding energies of 83.9 eV and 87.6 eV were present as expected (Figure 61a). However, after oxygen plasma cleaning (Figure 61b), new species with binding energies of 85.8 eV and 89.5 eV were present. The 1.9 eV shift compared to the untreated sample is consistent with literature values ​​for Au2O3 formation [101,102]. The 1.8–2.1 eV shift corresponds to the formation of Au(III) [103–105], supporting the formation of new oxide species.

[0156] These XPS results can be used to calculate the packing density of a specific element and the coverage of Fe(III) per AuNP. First, λ Au The mean free path from a universal XPS probe depth calibration at 2.2 nm means that approximately three layers of gold surface can be probed.

[0157] By using the relative sensitivity coefficients of Fe and Au, 9.976 and 11.593 (values ​​specific to the equipment used), the inventor can calibrate the XPS intensity ratio and calculate the surface coverage of Fe(III).

number

number

[0158] As a result, the surface coverage ratio is as follows:

number

[0159] The thickness of the Au(III) layer can also be approximated using the Au(III):Au(0) ratio of 0.137 in Figure 61b. Using the mean free path of gold here as well, we obtain the following equation as expected.

number

[0160] Principal component analysis Principal component analysis (PCA) is a powerful tool for considering the entire spectrum, examining correlations, and extracting spectral changes. This is advantageous because it eliminates the need to perform background subtraction or fitting to an already complex SERS background. Importantly, each principal component represents a linearly transformed eigenspectr with a different level of correlation with the original SERS spectrum.

[0161] PCA was used to extract the correlation between concentration and system sensitivity, and then to calculate the LOD. Next, eigenvectors (components) and eigenvalues ​​were calculated (Figure 64). The higher the weight of an eigenvalue, the lower the weight of the component, and the trend of only the first three components is analyzed (labeling). Ten measurements were taken for each concentration (bottom of Figure 65), and the eigenvalues ​​corresponding to each sample number are plotted in Figure 65. This closely follows the concentration of the analyte, considering that 99% of the eigenvalues ​​originate from component 1.

[0162] To remove contributions from other loads, the following equation is used:

[44]

number

[0163] Langmuir–Hill model The inset in Fig. 55 was fitted according to the standard Langmuir–Hill equation:

[44] [Number] Where K a is the concentration of the analyte that occupies half of the binding sites (also called the dissociation constant), n is the Hill coefficient, [C] is the concentration of the analyte, and A and b are constants. These were fitted to Figs. 55 and 63 in the quantitative region (inset), and the fitting coefficients and details of LOD and LOQ are shown in Table 3.

[0164] [Table 3]

[0165] Multisensing statistical analysis) By further analyzing the multisensing of DA and EPI and performing a simple statistical analysis, it is possible to determine whether a significant chemical interaction occurs between the two analytes. This is performed by maximizing the spectral overlap between the experimental spectrum and the linear superposition of the 100% DA and EPI spectra, and the measured DA ratio is extracted. For non-interacting analytes, the data are expected to be linear (Fig. 67). To reconstruct the measured spectrum, the range of 588–1375 cm -1 is used. From Fig. 67, most of the data points follow the expected line, but not all. This is especially true at 895 cm -1The presence of complex - to - complex interactions is supported by the new peaks that appear (Figure 68). This also confirms the 1:1 complex formation between DA:EPI.

[0106] When a Gaussian distribution is fitted to the residual between the measured spectrum and the predicted spectrum, it is found that this peak is maximized when DA:EPI is 60:40%. However, when this curve is fitted to the red curve (representing DA%×(1 - - DA%)), a simple relationship can be further established and supported by the minimum residual as shown in the second half of Figure 68.

[0166] Reproducibility of analyte detection and cycling The following oxidative cleaning is electrochemically realized, providing a strategy for in - situ control of the surface properties of the SERS substrate (e.g., for flow - sensing applications). By setting the SERS substrate as the working electrode in a three - electrode electrochemical cell, a potential is applied, the surface charge is controlled, and a local reaction is directly induced on its surface.

[0107] ,

[0108] In the Au - based SERS substrate, upon application of an anodic potential, not only is Au oxidized, but the analyte is also oxidized and / or desorbed. This process is rapid (within seconds) even in the case of nanogaps because the oxidation process is directly driven at the Au surface.

[0109] The electrochemical reduction of the Au oxide layer in the re - definition step occurs upon application of a cathodic potential. Apart from analyte removal, electrochemically enhanced SERS (EC - SERS) can regulate the binding of the analyte and increase the SERS signal by up to 10 - fold by enhancing the adsorption of the analyte.

[0107] The inventors investigated multiple analyte detection, cleaning, and re - definition cycles to evaluate both the reproducibility of the stripping ability and the re - definition (also referred to as "regeneration" in this specification).

[0167] To enable electrochemical control of the surface potential, the nanoparticle layer is deposited on a glass slide coated with fluorine-doped tin oxide (FTO) and assembled as a working electrode in an EC-SERS flow cell (Figures 69-72). The SERS spectrum is recorded by irradiating the nanoparticle layer with a 785 nm laser through a transparent FTO-coated glass, facilitating in-situ monitoring of the nanogap while simultaneously controlling the applied potential.

[0168] Adenine (ADN) is selected as the model analyte for the recycling experiment. This is because its voltage-dependent binding and SERS spectrum have been well studied

[0110] ,

[0111] and tested with EC-SERS on a roughened Ag electrode

[0112] . At pH 7.0, adenine mainly binds to neutral Au

[0113] , but in electrolyte solutions, adenine competes with ions for binding sites within the nanogap

[0114] . Negative potential enhances adenine binding, and at a step potential of -0.60 V, ν adenine = 732cm -1 The peak SERS enhancement is maximized (Figures 73-77). When adenine binds to the nanoparticle layer CB[5] hotspot, desorption of adenine does not occur even when this applied potential is removed, nor when a moderate positive potential (maximum +0.60V before oxidation of Au begins) is applied. Thus, adenine is strongly bound and does not desorb even when washed with buffer (pH 2.0, 7.0, or 12.0), 0.1M HCl, or 0.1M NaOH. Since adsorbed adenine is not removed by simple rinsing, it is an ideal analyte for testing the detection, cleaning, and redefinition of in-situ analytes (Figure 78).

[0169] The SERS spectrum of the initial nanoparticle layer CB[5] in the buffer-filled EC-SERS flow cell shows a clean nanoparticle layer with only the spectral fingerprint of the CB[5] molecular scaffolding visible (Figure 79, top). To detect adenine, the analyte solution is injected into the flow cell using a syringe pump and a potential of -0.6V is applied for 15 seconds. The spectrum is then recorded at the open-circuit potential (Figure 79, second from the top). After the analyte has bound, the nanogap is washed by flowing buffer at a constant rate of 500 μL / min while applying +1.5V for more than 10 seconds. This oxidizes / desorbs adenine, forming Au oxide on the AuNP surface, which can be directly confirmed in the SERS spectrum (Figure 79, second from the bottom) as a broad peak of approximately 590 cm⁻¹ due to Au-O stretching.

[0109] ,

[35] After applying the oxidation potential, the buffer is flowed for another 5 seconds to wash away the decomposition products and desorbed analyte from the nanoparticle layer and sample chamber. After washing, 1 mMCB[5] is passed through a buffer solution and -0.8V is applied for 5 seconds to redefine the nanogap, rapidly reduce the Au oxide, and promote the binding of CB[5] to the Au surface. The resulting SERS spectrum of the redefined nanoparticle layer-CB[5] (bottom of Figure 79) is almost identical to the initial spectrum, with no trace of the adenine α peak, indicating how effectively the nanogap in the nanoparticle layer is washed.

[0170] The detection, oxidation cleaning, and redefinition cycle of this in-situ analyte was performed 30 times, and its reproducibility was evaluated (Figure 80). Tracking the α-adenine peak area after each cleaning cycle revealed that not only was the analyte successfully removed each time, but the nanoparticle layer was also regenerated in the same way, with a relative standard deviation (RSD) of 5.5% across all iterations (Figure 81). This variability in analyte detection is comparable to the 5.7% RSD previously observed when paracetamol was detected and cleaned from the nanoparticle layer with multiple HCl cleaning cycles.

[0115] SERS mapping of the adenine signal in cycles 1, 10, 20, and 30 also showed consistent regional uniformity between the analyte signal and the substrate, meaning that all hotspots across the entire SERS substrate surface region were redefined in an effective and reproducible manner (Figures 82-85). The SERS spectra from the regenerated nanoparticle layer were also consistent throughout the cycle (Figures 80, 86). On the other hand, SERS mapping shows that the analyte is effectively removed across the entire probe area of ​​the SERS substrate (Figures 82-85). In terms of the number of cycles demonstrated and %RSD, the reproducibility of this level of recycling is superior to any known method. It should be noted that the nanoparticle layer can withstand at least 100 discontinuous analyte detection cycles, even when removed from the cell and dried intermittently. Under flow conditions, effective adhesion of the nanoparticle layer to the FTO-coated glass is necessary to ensure robustness in continuous long-term use.

[0171] For control, the detection, oxidation washing, and redefinition cycles of the same analyte were repeated on a new nanoparticle layer-CB[5]SERS substrate, but without using a scaffolding ligand during the redefinition step (Figure 87). Specifically, after the formation of the Au oxide, only buffer was introduced into the EC-SERS flow cell, and -0.80V was applied for 5 seconds to reduce the oxide. In this protocol, the analyte signal fluctuated initially for each cycle, then gradually decreased (Figure 88), with the intensity dropping to 12% by cycle 15. SERS maps of the analyte signal for cycles 1, 2, and 10 show similar fluctuations in the analyte signal across the probe region and a degradation of local homogeneity from 6% RSD in cycle 1 to 12% and 29% RSD in cycles 2 and 10, respectively (Figures 89, 90). In the second cycle control using 1 mMKCl and buffer in the redefinition step, the effect of chloride ions in the CB[5] solution was characterized, showing similar fluctuations in the analyte signal and a 21% decrease by cycle 15 (Figures 91 and 92). Similar results were obtained with further control using a nanoparticle layer prepared from NaCl-aggregated AuNPs (without CB[5]) (Figures 93 and 94).

[0172] Reproducibility of analyte detection and cycling - detailed method material All chemicals were used as received. Citric acid-stabilized 80nm AuNP (optical density 1.0 at 555nm) was purchased from BBI Solutions. Analytical grade chloroform (≧99.8%) was obtained from Merck. HCl (37%) was obtained from Fisher Scientific. NaCl (≧99%), K2HPO4 (≧98%), and KH2PO4 (≧98%) were obtained from Alfa Aesar. Cucurbituryl[5] hydrate (≒20% water) and adenine (≧99%) were obtained from Sigma-Aldrich. Polydimethylsiloxane (PDMS) was prepared using the DOWSIL SYLGARD 184 kit. Fluorine-doped tin oxide (FTO) coated glass slides (TEC10) were purchased from Ossila Ltd., washed before use, and cut into 10x15mm slides. All aqueous solutions are deionized water (DI) (>18.2 MΩcm) from the Purelab Ultra Scientific water purification system. -1 Prepared using ).

[0173] Preparation of the nanoparticle layer The nanoparticle layer SERS substrate was first prepared by adding 500 μL of 80 nm AuNPs to an equal volume of chloroform in an Eppendorf tube

[0115] ,

[0116] . Aggregation of AuNPs was initiated by adding 1 m MCB[5] or 50 μL of 1 M NaCl and promoted by vigorously shaking for 1 minute. The aggregates then settled at the water-organic phase interface. Excess ligands and salts were removed by replacing the aqueous supernatant with fresh deionized water. This washing step was repeated three times. Next, the aggregates were transferred by carefully reducing the volume of the aqueous phase to approximately 5 μL and depositing the droplets onto a pre-washed FTO glass slide. After deposition, the nanoparticle layer was air-dried, rinsed with DI, and dried with compressed nitrogen.

[0174] To remove residual native AuNP ligands from the surface of the nanoparticle layer, oxygen plasma washing was performed for 45 minutes using 90% RF power and 30 sccm (Henniker Plasma, HPT-100) to remove all surface ligands. Next, the plasma-washed nanoparticle layer was incubated in a 1 mM ligand solution prepared in 0.5 M HCl to introduce the desired scaffolding ligand (e.g., CB[5]). After 5 minutes, the nanoparticle layer was washed with DI and dried with N2. Alternatively, the initial nanoparticle layer was also washed by in-situ electrochemical washing using the redefinition protocol described below (Figure 95).

[0175] SERS and dark-field measurement SERS measurements were recorded using a custom Raman setup (Figures 71 and 72) with a 785 nm diode laser (Matchbox) set to ≤1 mW power. Excitation and acquisition were performed via an Olympus LUMPlanFl / IR40×W0.80-NA water immersion objective lens (inverted configuration), and spectra were recorded with an AndorNewton970EMCCD camera connected to a Shamrock168 spectrometer at an integration time of 1 second.

[0176] SERS mapping measurements were performed using a commercially available Raman spectrometer (RenishawinVia) with an integration time of 1 second, an excitation wavelength of 785 nm (laser line profile), a laser power of 2.1 mW, and a 20x 0.40 NA objective lens. Map scanning was performed on a 465 × 330 μm area on a 31 × 11 grid with 15 × 30 μm spacing.

[0177] Dark-field (DF) scattering spectra were recorded with a modified Olympus B×51 equipped with an OceanOptics QE-Pro spectrometer at an integration time of 0.5 seconds. Excitation and acquisition were performed via an Olympus MPLanFLN20×BD0.45-NA objective lens. DF scattering spectra of nanoparticle layer samples were collected over a 600×400 μm area (10×15 point grid) and averaged. White light scattering was normalized using a white light scattering target (Labsphere) as the reference.

[0178] SEM measurement SEM measurements of nanoparticle layers deposited on FTO-coated glass slides were performed using either an FEI Philips Dualbeam Quanta3 SEM (dwell 3-10 μs, HV 2 kV, current 50 pA, WD ≈ 2.0 mm) or an FEI Helios NanoLab650 SEM (dwell 100 ns-1 μs, HV 20 kV, current 100 pA, WD ≈ 4.0 mm). Magnification ranged from 80,000 to 200,000x.

[0179] EC-SERS Flow Setup A compact EC-SERS flow cell was designed and manufactured to accommodate a standard three-electrode electrochemical system: a leak-free Ag / AgCl reference electrode (LF-1-45, Innovative Instruments Ltd), a Pt wire (Sigma-Aldrich) counter electrode, and a removable nanoparticle layer SERS substrate on FTO-coated glass were used as the working electrode (Figure 70). The flow cell had an internal volume of 26 μL. The EC-SERS flow cell and the three-inlet, one-outlet mixer module were manufactured from PDMS using 3D-printed molds. The EC-SERS flow cell was sealed and mounted on a stage in an inverted Raman setup using a custom 3D-printed holder and base.

[0180] A custom-made syringe pump was used (Figs. 71 and 72) to control the flow rate of the solutions (buffer, CB[5] in buffer, analyte in buffer) passing through the EC-SERS flow cell. Electrochemical measurements were carried out using a portable potentiostat (CompactStat) from Ivium Technologies. All potentials were referenced to an Ag / AgCl reference electrode. The syringe pump, electrochemical measurements, and SERS spectrum collection were all controlled and synchronized with a Python script.

[0181] Detection of the analyte The analyte aqueous solution was prepared with 50 mM potassium phosphate buffer (pH 7.0, conductivity 0.5 mS cm -1 ) as the background electrolyte and injected into the EC-SERS flow cell. Under static conditions, an electrochemical enhancement potential (-0.60 V) was applied for 15 s if necessary. Then, the SERS spectrum was measured at the open circuit potential.

[0182] For the detection of thiol, the nanoparticle layer was removed from the EC-SERS flow cell and immersed in a 100 μM thiol solution in EtOH for 1 h. Then, the nanoparticle layer was washed with EtOH and dried with a stream of N2. Then, the nanoparticle layer was reinstalled in the EC-SERS flow cell, and washing, redefinition, and calibration of the reference for adenine detection were performed. Since the nanoparticle layer is periodically removed from the cell, it is difficult to accurately probe the same spot on the surface of the nanoparticle layer. Therefore, the spectra were acquired at multiple random spots (n = 10) across the substrate and averaged. Thus, the spectral changes in this case also include spatial variations across the entire nanoparticle layer.

[0183] Cleaning and redefinition To clean and redefine the nanoparticle layer, 50 mM potassium phosphate buffer (pH 7.0) was fed into the EC-SERS flow cell, and a continuous buffer flow (flow rate = 500 μL min -1Under static conditions, a potential of +1.5V relative to Ag / AgCl was maintained for 5–60 seconds. Initial washing of the nanoparticle layer typically required 60 seconds, but 15–30 seconds was sufficient for washing the analyte. After washing, 1 mMCB[5] in 50 mM potassium phosphate buffer (pH 7.0) was injected into the flow cell. Under static conditions, a potential of -0.80V relative to Ag / AgCl was maintained for 5 seconds. Next, the buffer was flowed into the cell to remove excess scaffold molecules. If traces of previously detected analytes were revealed from the SERS spectrum, further washing / redefinition was performed.

[0184] During the detection / wash cycle experiment, the solution syringe was replenished every 12–15 cycles. Before resuming measurements, we waited for the flow system to stabilize. During the cycling experiment, care was taken to record the SERS spectrum from the same substrate spot. However, the continuous operation of the flow system was occasionally stopped to replenish water droplets on the immersion objective lens, which tend to dry out with prolonged use. This required moving the EC-SERS flow cell, which may result in some variation in the probed substrate spot.

[0185] Data Analysis Here, 1400 cm² is obtained from back-facing optical measurements. -1 The SERS spectra are shown with minimal data processing, except for background correction to remove the broad glass background signal centered around . The analyte peak area was determined by iteratively fitting a polynomial to correct for the SERS background, followed by fitting a Gaussian curve to the target narrow analyte peak. Gaussian curves were fitted to each DF scattering spectrum to determine the peak wavelength of the nanoparticle layer-coupled plasmon mode from the DF scattering spectrum. The peak wavelength was determined from the center of the fitted Gaussian curve.

[0186] The features disclosed in the preceding description, the following claims, or the accompanying drawings may be expressed as appropriate in their specific forms, or in terms of means for performing the disclosed functions, or methods or processes for obtaining the disclosed results, and such features may be used individually or in any combination to realize the present invention in a variety of forms.

[0187] While the present invention has been described in relation to the exemplary embodiments described above, many equivalent modifications and changes will be apparent to those skilled in the art upon reading this disclosure. Therefore, the exemplary embodiments of the present invention described above are illustrative and not limiting. Various modifications can be made to the described embodiments without departing from the spirit and scope of the invention.

[0188] To avoid any ambiguity, the theoretical explanations provided herein are intended to enhance the reader's understanding. The inventors do not wish to be bound by any of these theoretical explanations.

[0189] The section headings used herein are for organizational purposes only and should not be interpreted as limiting the subject matter being discussed.

[0190] Throughout this specification, including in subsequent claims, unless otherwise specifically required by context, the words “include” and “equip,” and variations such as “include,” “contain,” and “equip,” shall be understood to mean that a specified integer or step, or group of integers or steps, is included, but not that other integers or steps, or groups of integers or steps, are excluded.

[0191] It should be noted that the singular forms “a,” “an,” and “the” used herein and in the appended claims include multiple referents unless the context clearly indicates otherwise. In this specification, ranges may be expressed as “approximately” from one particular value and / or “approximately” to another particular value. Where such ranges are expressed, another embodiment includes one particular value and / or the other particular value. Similarly, where values ​​are expressed as approximations, the use of the antecedent “approximately” is understood to mean that a particular value forms another embodiment. The term “approximately” with respect to numbers is optional and means, for example, + / - 10%.

[0192] The above references numerous publications to provide a more detailed explanation and disclosure of the present invention and the relevant state of the art. All of these references are incorporated herein by reference.

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Claims

1. A method for preparing an SES substrate, Prepare the base material. A nanoparticle layer is prepared on the substrate, wherein the nanoparticle layer includes metal nanoparticles. The nanoparticle layer is subjected to an oxidation cleaning step, thereby generating an oxide coating on the surface of the nanoparticles, and Next, the nanoparticle layer is subjected to a redefinition step, where the oxide coating is removed in the presence of a scaffolding ligand, the scaffolding ligand is positioned between adjacent nanoparticles, and their relative spacing is defined for use in subsequent SES analysis. Methods that include...

2. The method according to claim 1, wherein the oxidative cleaning step acts to detach molecules bound to the surface of the nanoparticles from the surface.

3. The method according to claim 1 or 2, wherein the metal nanoparticles are selected from one or more metals that support surface plasmons at optical frequencies or mid-infrared frequencies.

4. The method according to any one of claims 1 to 3, wherein the metal nanoparticles are one or more metals selected from the group consisting of gold (Au), silver (Ag), copper (Cu), and aluminum (Al).

5. The method according to any one of claims 1 to 4, wherein the surface of the metal nanoparticles is coated with palladium (Pd) or platinum (Pt).

6. The method according to any one of claims 1 to 5, wherein the nanoparticle layer is a single-layer nanoparticle layer, a multilayer nanoparticle layer, or a nanoparticle layer having a single-layer nanoparticle region and a multilayer nanoparticle region.

7. The method according to any one of claims 1 to 6, wherein the redefinition step includes removing the oxide coating under reducing or acidic conditions in the presence of a scaffolding ligand.

8. The method according to any one of claims 1 to 6, wherein the redefinition step includes removing the oxide coating using an acid or reducing agent in the presence of the scaffolding ligand.

9. The method according to any one of claims 1 to 6, wherein the redefinition step includes removing the oxide coating by heat or ultraviolet light in the presence of a scaffolding ligand.

10. The method according to any one of claims 1 to 6, wherein the redefinition step includes removing the oxide coating under acidic or neutral pH conditions in the presence of a scaffolding ligand and halide ions.

11. The method according to any one of claims 1 to 10, wherein the scaffolding ligand is one or more molecules having binding affinity to the surface of the metal nanoparticles.

12. The method according to any one of claims 1 to 11, wherein the scaffolding ligand is one or more molecules selected from the group consisting of cucurbits[n]uryl, polystyrene molecules, 3-mercaptopropionic acid, citrate, acetic acid, cysteamine, dopamine, paracetamol, ethanol, and methanol.

13. The method according to any one of claims 1 to 12, wherein the surface of the nanoparticles contains a sensitizer that promotes the binding of molecules to the nanoparticles.

14. The method according to any one of claims 1 to 13, wherein the substrate is conductive.

15. The method according to any one of claims 1 to 14, wherein the oxidation cleaning step includes oxygen plasma treatment, and the nanoparticle layer is exposed to oxygen plasma.

16. The method according to claim 14, wherein the oxidation cleaning step includes electrochemical oxidation, and a positive voltage is applied to the SES substrate in an electrochemical cell.

17. The method according to claim 14, wherein the redefinition step includes removing the oxide coating by electrochemical reduction, wherein a negative voltage is applied to the SES substrate in an electrochemical cell in the presence of a scaffolding ligand.

18. The method according to any one of claims 1 to 17, further comprising a cycle of subsequent oxidation cleaning and redefinition steps.

19. The method according to claim 18, wherein the total number of cycles of the oxidation cleaning step and the redefinition step is at least 3.

20. A prepared SES substrate obtained or obtainable by the preparation method described in any one of claims 1 to 19.

21. A method for performing SES, comprising preparing an SES substrate comprising a substrate and a nanoparticle layer on the substrate, wherein the nanoparticle layer comprises metal nanoparticles, and further comprising the following steps: Perform a first SES analysis using the aforementioned SES substrate. The nanoparticle layer is subjected to an oxidation cleaning process. By subjecting the aforementioned nanoparticle layer to a redefinition process, a recycled SES substrate is provided, and A second SES analysis is performed on the recycled SES substrate.

22. The method according to claim 21, wherein SES is SERS or SES is SEIRA.

23. The method according to claim 21 or 22, further comprising a subsequent oxidation cleaning step, a redefinition step, and an SES analysis cycle.

24. The method according to claim 23, wherein the total number of oxidation cleaning steps, redefinition steps, and SES analysis cycles is at least three.

25. The method according to claim 24, wherein the relative standard deviation of the peak areas of the analytes investigated in each SES analysis is 10% or less across all oxidation washing steps, redefinition steps, and SES analysis cycles.

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