A method and device for detecting copper ions based on a single-component bimodal platform

Abstract

The application discloses a kind of copper ion detection method and device based on single-component bimodule platform, belong to heavy metal ion detection, chemical sensing and polydimethylsiloxane microfluidic integrated analysis technical field.The application uses Py-OH as single recognition molecule, and integrates colorimetric detection module and organic single crystal field effect transistor (OSCFETs) electrical detection module by PDMS microfluidic platform.The device utilizes the same coordination event to generate solution color change and transistor current change simultaneously, combined with smartphone image analysis and data fusion algorithm, realizes high sensitivity, high selectivity detection of copper ion.The application has high sensitivity (detection limit 0.39 ng mL ‑1 ) of electrical detection and intuitive portability of colorimetric detection, effectively solves the problem of low reliability of traditional single-mode detection and low integration of multi-probe bimodule system, and has important application value in environmental emergency and on-site screening.

Description

Technical Field

[0001] This invention belongs to the field of heavy metal ion detection, chemical sensing and polydimethylsiloxane (PDMS) microfluidic integrated analysis technology, and particularly relates to a method and device for copper ion detection based on a single-component dual-mode platform. Background Technology

[0002] Copper ions are among the most representative functional metal ions in living and environmental systems. Within organisms, Cu... 2+ Cu participates in energy metabolism, redox regulation, nerve signal transmission, and the maintenance of the activity of various metalloenzymes; in the environment, Cu... 2 + Cu is widely derived from processes such as mining, metallurgy, electroplating, electronics, agricultural application, and metal pipeline corrosion. When its concentration is within a reasonable range, it can maintain normal physiological functions. However, when its concentration is abnormally elevated in drinking water, natural water bodies, biological fluids, or local microenvironments, it can easily cause neurotoxicity, liver and kidney damage, and ecological harm through pathways such as promoting reactive oxygen species generation, inducing oxidative stress, and interfering with protein homeostasis. Therefore, it is necessary to establish a Cu molecule that is both sensitive and accurate, suitable for laboratory quantification, and has the potential for rapid on-site screening. 2+ Detection technology is of great value.

[0003] Currently, standard methods for detecting copper ions mainly include inductively coupled plasma mass spectrometry (ICP-MS), atomic absorption spectroscopy (AAS), and atomic emission spectroscopy (AES). These methods are highly accurate and authoritative, but they generally rely on large instruments, complex pretreatment processes, and specialized personnel, making them difficult to meet the practical needs of on-site real-time detection, rapid assessment in resource-constrained scenarios, and continuous monitoring at multiple locations. Particularly in environmental emergencies, water quality inspections, individual health monitoring, and portable terminal applications, these traditional methods suffer from significant shortcomings such as high cost, bulky equipment, and long detection cycles.

[0004] To compensate for the shortcomings of traditional instrumental analysis, a large number of new copper ion detection platforms based on principles such as fluorescence, colorimetry, electrochemistry, and organic field-effect transistors have emerged in recent years. Colorimetry has the advantages of intuitive color changes, rapid response, simple operation, and low cost, making it easy to judge with the naked eye or through smartphone imaging, suitable for initial screening and rapid on-site analysis; however, single colorimetric modes are often susceptible to the influence of background color, turbidity, light fluctuations, and coexisting components in complex matrices, which may lead to misjudgment or quantitative deviations in real samples. Electrochemical and transistor detection have high sensitivity and signal amplification capabilities, but single electrical modes may also be affected by interface drift, non-specific adsorption, or environmental disturbances during long-term use, requiring auxiliary methods for verification.

[0005] Organic single-crystal field-effect transistors (OSCFETs) possess a natural advantage in converting weak interfacial interactions into significant electrical signals because channel carriers can be efficiently modulated by changes in interface charge. In particular, OSCFETs based on C6-DPA organic single-crystal thin films exhibit high mobility, low noise, and good gate control behavior, making them theoretically well-suited for trace ion detection. However, while the electrical detection mode itself is sensitive, it typically lacks direct, visually perceptible feedback. Furthermore, in complex samples, the absence of a second independent signal for cross-validation makes it difficult to completely avoid false positives or false negatives.

[0006] To improve detection reliability, dual-mode sensing technology has gained increasing attention. Existing dual-mode solutions typically achieve multiple signal outputs through methods such as fluorescence-colorimetry, electrochemical-colorimetry, or transistor-electrochemical methods. However, most existing dual-mode platforms suffer from a fundamental problem: the two signals often originate from different molecular probes, different recognition sites, or even different spatial modules. This leads to low system integration, complex preparation processes, asynchronous response processes, high sample consumption, and difficulty in ensuring that the two modes truly output around the same molecular recognition event. In this situation, although dual-mode detection is superficially achieved, the consistency and comparability between the two signals are not ideal, further increasing the complexity of data interpretation and device implementation.

[0007] Furthermore, real-world sample testing places higher demands on sensing platforms. For example, tap water, artificial sweat, or biological samples typically contain sodium (Na₂O₃). + K + Mg 2+ Zn 2+ Hg 2+ In addition, there are various interfering factors such as organic components, surface-active substances, and trace particles. If the sensing system does not have sufficient coordination selectivity for the target ion, or if its detection process relies too heavily on complex calibration, it will be difficult to achieve stable recovery rates and repeatability in real-world scenarios.

[0008] Therefore, there is an urgent need to provide a highly integrated detection platform that can simultaneously generate optical and electrical signals on the same recognition unit and can be further combined with microfluidics, smartphone analysis and data fusion algorithms. Summary of the Invention

[0009] To address the technical problems of insufficient accuracy of existing single-mode sensors in complex matrices and low integration and poor consistency of existing dual-mode systems due to the separation of multiple probes and modules, this invention proposes a copper ion detection method and device based on a single-component dual-mode platform. Py-OH is used as a single recognition molecule, utilizing its interaction with Cu...2+ The specific coordination of Cu induces both a color change in the solution and a change in the current of the organic single-crystal transistor. Furthermore, the colorimetric module and the OSCFET module are integrated into the same PDMS microfluidic platform, and combined with smartphone image analysis and dual-mode signal fusion, to achieve the specific coordination of Cu. 2+ This invention offers highly sensitive, selective, and reliable detection. It retains the high sensitivity advantage of the electrical mode while also possessing the intuitiveness and portability of the colorimetric mode, demonstrating significant application potential in complex real-world samples.

[0010] To achieve the above objectives, the present invention provides the following technical solution: A copper ion detection device based on a single-component dual-mode platform includes: a PDMS microfluidic platform, wherein the PDMS microfluidic platform integrates a colorimetric detection module and an electrical detection module; The colorimetric detection module and the electrical detection module share the same recognition molecule, Py-OH, which is used to coordinate with copper ions in the test solution to produce color changes and electrical signal changes.

[0011] This invention uses Py-OH as the colorimetric response unit in both the colorimetric detection module and the electrical detection module, along with the OSCFETs ion-sensitive membrane, to enable Cu... 2+ The same coordination event is synchronously converted into OSCFET current change and solution color change, fundamentally solving the problem of signal source separation in traditional dual-mode platforms and realizing inherent cross-verification; at the same time, through PDMS microfluidic integration, smartphone imaging and machine learning, combined with data fusion methods, the portability of the system and the reliability of real sample detection are further improved.

[0012] Optionally, the electrical detection module includes, from bottom to top: Substrate: 300nm Si / SiO2 heavily doped silicon wafer; A modified layer modified by phenyltrichlorosilane in the gas phase; A transport layer with a C6-DPA organic single-crystal thin film deposited; Au electrode; An ion-sensitive layer with a Py-OH (2-(pyrene-1-ylmethyleneamino)phenol) film deposited on it.

[0013] Optionally, the colorimetric detection module includes a color detection chamber located on the PDMS microfluidic platform, and the color detection chamber is filled with Py-OH ethanol solution as a colorimetric probe.

[0014] Furthermore, the concentration of the Py-OH ethanol solution is 10. -4 M.

[0015] Optionally, the PDMS microfluidic platform is formed by mixing and curing PDMS prepolymer and curing agent at a mass ratio of 10:1.

[0016] The method for detecting copper ions using the copper ion detection device based on the single-component dual-mode platform described above includes the following steps: The copper ion solution to be tested is introduced into the PDMS microfluidic platform, so that it simultaneously contacts the Py-OH ethanol solution in the colorimetric detection module and the Py-OH ion-sensitive layer in the electrical detection module. Incubate at room temperature to allow Py-OH to complete the coordination reaction with copper ions; The color change information of the solution in the colorimetric detection module is obtained, and the current change information in the electrical detection module is also obtained.

[0017] Optionally, obtaining the color change information of the solution in the colorimetric detection module specifically includes: Use a smartphone to capture an image of the colorimetric detection module after it has reacted; The image is input into a convolutional neural network model for analysis, and the corresponding predicted value of copper ion concentration is output.

[0018] Furthermore, before capturing the image of the colorimetric detection module's reaction using a smartphone, the process further includes: The smartphone is placed inside a fixed imaging box, and parallel LED light sources are used as background light to unify the lighting conditions and shooting distance.

[0019] Optionally, acquiring the current change information in the electrical detection module specifically includes: The transfer characteristic curves of the device before and after the reaction are measured, and the relative change in the on-state current is calculated as the electrical response signal.

[0020] Optionally, the method further includes a step of testing tap water or artificial sweat samples: The samples of tap water or artificial sweat were subjected to ultrasonic treatment and filtration through a 0.22 μm filter membrane; Quantitative results of the filtered samples were obtained in colorimetric and electrical modes, respectively. The combined concentration value of the two models is output through a weighted data fusion method.

[0021] Compared with the prior art, the present invention has the following advantages and technical effects: 1. This invention achieves true single-component dual-mode detection. Compared to traditional schemes that output signals using two different probes or two independent recognition sites, the electrical and optical responses of this invention both originate from Py-OH and Cu. 2+The two modes share the same coordination process, thus maintaining consistency at the signal generation source, which can effectively reduce the result deviation caused by inconsistent probes, asynchronous responses, or errors between modules.

[0022] 2. This invention combines the advantages of high sensitivity and high visibility. The OSCFET electrical module, relying on the high mobility and low noise characteristics of organic single-crystal channels, achieves high sensitivity and visibility for Cu... 2+ The ultrasensitive detection has a theoretical detection limit as low as 0.39 ng / mL. -1 The colorimetric module provides a visual change from yellow to brown, with a theoretical detection limit of 57.78 ng / mL. -1 It can be used for rapid prediction and on-site screening. The two modes complement each other, making the system suitable for both trace analysis and rapid on-site decision-making.

[0023] 3. This invention exhibits excellent selectivity and anti-interference capabilities. Whether in electrical mode or colorimetric mode, Na… + K + Mg 2+ Zn 2+ Hg 2+ Common ions are difficult to generate with Cu 2+ The considerable response signal indicates that Py-OH affects Cu 2+ It possesses a clear and stable selective recognition capability, thereby ensuring the applicability of the present invention in complex ionic backgrounds.

[0024] 4. This invention facilitates device integration and portability. By integrating the colorimetric module and OSCFET module into one unit through the PDMS microfluidic platform, sample and reagent consumption can be significantly reduced, and the operation process can be simplified. Furthermore, by combining smartphone imaging and convolutional neural network analysis, the colorimetric quantification process that originally relied on laboratory equipment can be transferred to a portable terminal, improving the feasibility of the device for point-of-care testing and on-site analysis.

[0025] 5. The detection results of this invention in real samples are reliable. In complex samples such as tap water and artificial sweat, the recovery rate after dual-mode fusion can reach 98%-102%, with a relative standard deviation of less than 1%, and is highly consistent with the results of standard methods. This indicates that this invention is not only effective in standard solutions, but also has good real-world application capabilities. This is particularly important for environmental monitoring, health management, and grassroots testing scenarios.

[0026] In summary, this invention overcomes the technical bottlenecks of insufficient reliability of single-mode platforms, low integration of dual-mode platforms, and limited adaptability to real samples in existing copper ion detection technologies. It provides a feasible technical solution for developing highly sensitive, highly accurate, visualized, and portable heavy metal ion detection systems. Furthermore, the technical approach proposed in this invention has strong scalability. By keeping the OSCFET module, microfluidic chip, and intelligent terminal framework unchanged, and only replacing the single-molecule probes with different recognition sites, it can be further extended to dual-mode detection of other heavy metal ions or specific chemical analytes, providing a foundation for subsequent serialized and modular product development. Attached Figure Description

[0027] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 To demonstrate the effect, Example 1 uses the Job's plot method based on UV-Vis spectroscopy to determine the relationship between Py-OH and Cu. 2+ The binding stoichiometry; Figure 2 In Example 1, the determination of Py-OH and Cu was based on Benesi-Hildebrand analysis. 2+ Binding constant at 382 nm; Figure 3 For the effect, in Example 1, Py-OH and Cu 2+ A schematic diagram of the coordination structure; Figure 4 For Cu in test examples 1-4 2+ Analysis of binding with Py-OH; Figure 5 For the effect of Example 2, the OSCFETs sensor for Cu 2+ Recognition performance analysis; Figure 6 For different concentrations of Cu in test example 5 2+ Combined with Kelvin probe force microscopy (KPFM) potential map of the post-film surface; Figure 7 For Cu in test example 5 2+ Statistical graph of induced membrane potential changes; Figure 8 This is a schematic diagram of the dual-mode integrated sensing platform in Example 3. Figure 9 The diagrams show the CNN model architecture in Examples 4 and 6. Figure 10 For the effect shown in Example 5, the colorimetric module in the dual-mode integrated sensing platform measures Cu. 2+ Color response and detection performance; Figure 11 To demonstrate the performance of the CNN-enhanced colorimetric analysis model in Example 6; Figure 12 To demonstrate the effectiveness of ICP-MS, colorimetry, OSCFETs sensors, and the dual-mode integrated sensing platform in detecting Cu in real samples in Example 7. 2+ Comparison of recovery rates. Detailed Implementation

[0028] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as a limitation of the present invention, but rather as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0029] It should be understood that the terminology used in this invention is merely for describing particular embodiments and is not intended to limit the invention. Furthermore, with respect to numerical ranges in this invention, it should be understood that each intermediate value between the upper and lower limits of the range is also specifically disclosed. Every smaller range between any stated value or intermediate value within a stated range, and any other stated value or intermediate value within said range, is also included in this invention. The upper and lower limits of these smaller ranges may be independently included or excluded from the range.

[0030] Unless otherwise stated, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. While only preferred methods and materials have been described herein, any methods and materials similar or equivalent to those described herein may be used in the implementation or testing of this invention. All references to this specification are incorporated by way of citation to disclose and describe methods and / or materials associated with those references. In the event of any conflict with any incorporated reference, the content of this specification shall prevail.

[0031] Various modifications and variations can be made to the specific embodiments described in this specification without departing from the scope or spirit of the invention, as will be apparent to those skilled in the art. Other embodiments derived from this specification will also be apparent to those skilled in the art. This specification and embodiments are merely exemplary.

[0032] The terms “include,” “including,” “have,” “contain,” etc., used in this article are all open-ended terms, meaning that they include but are not limited to.

[0033] This invention discloses a copper ion detection device based on a single-component dual-mode platform, comprising: a PDMS microfluidic platform, wherein the PDMS microfluidic platform integrates a colorimetric detection module and an electrical detection module; The colorimetric detection module and the electrical detection module share the same recognition molecule, Py-OH, which is used to coordinate with copper ions in the test solution to produce color changes and electrical signal changes.

[0034] The above-mentioned device is described as follows: (1) Single Recognition Unit: This invention uses 2-(pyrene-1-ylmethyleneamino)phenol (Py-OH) as the single recognition molecule. This molecule consists of a pyrene conjugated backbone, a Schiff base imine site, and an ortho-hydroxyl site, which can exhibit a significant optical response in solution and can also form a solid functional layer by vacuum deposition. Solution coordination studies show that Py-OH reacts with Cu 2+ They can form a 1:2 type coordination structure with a high binding constant, indicating a clear and stable specific coordination relationship between the two. It is this unified molecular recognition basis that enables it to serve both colorimetric modules and transistor electrical modules.

[0035] (2) Composition of the electrical detection module: The electrical detection module adopts an organic single-crystal field-effect transistor with a bottom-gate top-contact structure. A 300 nm Si / SiO2 heavily doped silicon wafer is used as the substrate. After cleaning, oxygen plasma activation, and PTS vapor phase modification, a C6-DPA organic single-crystal thin film is deposited on its surface as a transport layer using the Czochralski method. Then, source and drain electrodes are formed using Au electrode transfer. Finally, a Py-OH ion-sensitive layer of approximately 30 nm thickness is vacuum-deposited on the device surface. Since the C6-DPA single-crystal thin film has high mobility and low background noise, the Py-OH layer provides protection against Cu... 2+ The module's selective identification allows it to amplify interface coordination events into measurable current changes.

[0036] (3) Electrical testing method: Place the functionalized OSCFET device on the test platform, and first record the initial transfer curve and the on-state current. I 0; then 20 μL of the Cu to be tested was dropped onto the device surface. 2+ After incubating the solution at room temperature for 20 minutes, remove the residual liquid and gently blow dry. Test the device again to obtain the post-reaction current. I With Δ I SD Alternatively, the relative current change can be used as a response signal for different concentrations of Cu. 2+ Quantitative analysis was performed. Subsequent experimental results indicate that, with the increase of Cu... 2+ Concentration from 1 ng / mL -1 Gradually increase to 100 μg / mL -1The on-state current of the device exhibits a regular decrease, indicating that the interface charge modulation effect caused by the coordination process can be effectively coupled to the P-type channel. This module demonstrates good linear response over a wide concentration range, with a theoretical detection limit as low as 0.39 ng / mL. -1 It achieves nanomolar-level detection capability.

[0037] (4) Selectivity and mechanism of electrical modules: In Na + K + Mg 2+ Zn 2+ Hg 2+ When multiple common ions are present, the electrical module of this invention can react to Cu. 2+ It still maintains a significant response, while showing only minimal or negligible current changes for other ions, indicating that Py-OH reacts with Cu. 2+ There is a prominent selective coordination relationship between them. Mechanistically, Cu... 2+ After binding to the C=N and phenolic oxygen sites on the Py-OH surface, a localized positively charged layer is formed on the sensitive layer surface, which is equivalent to applying an additional positive gate voltage to the P-type organic channel, leading to the depletion of hole carriers and thus causing a decrease in drain-source current. Characterization by X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FT-IR), ultraviolet-visible molecular absorption spectroscopy (UV-Vis), and Kelvin probe force microscopy (KPFM) all indicate that Cu 2+ Coordination and surface potential changes did indeed occur between the functional layer and the sensor, confirming the electrical sensing mechanism at both the molecular and device levels.

[0038] (5) Composition of the colorimetric detection module: The colorimetric module uses Py-OH ethanol solution as a colorimetric probe, which is introduced into the color detection cavity of the PDMS microfluidic chip. Preferably, 32.14 mg of Py-OH is dissolved in 1 L of ethanol to prepare a 10 -4 M probe solution. For detection, take 100 μL of the Cu to be tested. 2+ The solution was mixed with 1 mL of Py-OH probe solution, and then color observation and absorption testing were performed in a colorimetric chamber. When Cu... 2+In its presence, the solution color gradually changes from light yellow to brown, and the original absorption near 382 nm in the absorption spectrum weakens, while a new coordination-related absorption band appears near 500 nm. Using the absorbance at 500 nm as the analytical signal, good linear quantification can be achieved in the 5-50 μM range, with a theoretical limit of detection of 57.78 ng / mL. -1 .

[0039] (6) Advantages of the colorimetric detection module: The colorimetric mode has the advantages of intuitive response, visual visibility, and ease of on-site judgment. Even without relying on precision instruments, the operator can determine the presence of a high concentration of Cu in the sample by observing the color change from yellow to brown. 2+ This allows for rapid judgment; combining it with a small spectrophotometer or image analysis can further enable quantitative measurement. More importantly, since the colorimetric and electrical signals originate from the same Py-OH / Cu... 2+ The coordination event means that the two are inherently consistent, rather than originating from two independent probe systems.

[0040] (7) Dual-mode integrated device: The device of this invention integrates two detection modules using a PDMS microfluidic platform. PDMS prepolymer and curing agent are mixed at a mass ratio of 10:1, degassed, and then injected into a customized mold. The mixture is cured at 70°C for 2 hours and then permanently bonded to a glass substrate after perforation and oxygen plasma treatment. The overall dimensions of the platform are approximately 5.0 cm × 3.5 cm × 1.5 cm. The colorimetric detection module and the OSCFET detection module (electrical detection module) are distributed on both sides of the platform, achieving quantitative delivery and simultaneous detection of the sample solution through microfluidic channels. Compared with the traditional method of assembling the two sensors separately, the structure of this invention is more compact, consumes less sample, and is more convenient for subsequent portability and batch production.

[0041] (8) Smartphone and Machine Learning-Assisted Analysis: To enhance on-site quantitative capabilities, this invention further integrates colorimetric modes with a smartphone imaging system. By setting up a fixed imaging box with parallel LED light sources, uniform lighting conditions and shooting distances are achieved, and Cu samples of different concentrations are collected. 2+ The processed colorimetric image was then standardized to 224×224 pixel RGB format, and subjected to white balance correction, background subtraction, and normalization. The resulting image was then input into a convolutional neural network for training and prediction. Subsequent model training results indicated that within the range of 0-50 μg mL... -1 Within the range, the predicted concentration and the actual concentration showed a high correlation, and the goodness of fit was good. R 2 The result is 0.986, indicating that this strategy can achieve relatively accurate portable quantitative analysis without the need for a professional spectrometer.

[0042] (9) Real sample testing method: To verify the feasibility of this invention in complex matrices, tap water and artificial sweat were used as representative samples, and 0.1 μg mL of each sample was tested. -1 and 1 μg mL -1 Two levels of spiked recovery experiments were conducted. Samples were sonicated for 10 min and filtered through a 0.22 μm filter before being simultaneously analyzed by both colorimetric and electrical modules. Quantitative results were obtained separately in colorimetric and OSCFET modes, and then a weighted data fusion method was used to obtain a combined dual-mode output. Subsequent experimental results showed that the fused recovery rate remained stable between 98% and 102%, with a relative standard deviation of less than 1%, and was highly consistent with results obtained using standard instrument methods, indicating that the present invention maintains excellent accuracy and repeatability even in complex samples.

[0043] (10) Dual-mode data fusion and result judgment: In this invention, the dual-mode results can be output separately or fused according to preset precision weights. When the detection results of the two modes are highly consistent, the confidence in the judgment of the sample can be directly improved; when one mode deviates due to occasional background interference, the other independent mode can play a role in verification and correction. This mechanism distinguishes this invention from the single-mode platform that simply improves sensitivity, but establishes a balance between "sensitivity, visualization and reliability", which is more suitable for complex environments and field applications.

[0044] Unless otherwise specified, "room temperature" in this invention refers to 20-30℃.

[0045] The main raw materials used in the embodiments of this invention can all be commercially available analytical grade or higher purity reagents. 2,6-bis(4-hexylphenyl)anthracene (C6-DPA) was purchased from Shanghai Daran Chemical Co., Ltd. Toluene and isopropanol were purchased from Tianjin Yuanli Chemical Co., Ltd. Chloroform, n-hexane, and acetone were purchased from Shanghai Dibai Chemical Co., Ltd. Copper chloride, potassium chloride, sodium chloride, magnesium chloride, and zinc chloride were purchased from Tianjin Xiens Co., Ltd. Phenylacetyltrichlorosilane (PTS) was purchased from Beijing Bailingwei Technology Co., Ltd. Anhydrous ethanol was purchased from Shanghai Aladdin Co., Ltd. High-purity gold particles were purchased from Beijing Zhongnuo New Materials Co., Ltd. 1-Aminopyrene (purity greater than 98%) and salicylaldehyde (analytical grade) were both purchased from Tianjin Xiens Biochemical Technology Co., Ltd. Si / SiO2 silicon wafers were purchased from the 46th Research Institute of China Electronics Technology Group Corporation. Copper mesh was purchased from Beijing Xinxing Bairui Co., Ltd. Polydimethylsiloxane (PDMS) was purchased from Shanghai Daran Chemical Co., Ltd. Mercury standard solution was purchased from Kaimate Chemical Technology Co., Ltd. Gallium-indium alloy was purchased from Tianjin Jiangtian Chemical Co., Ltd. 2,6-bis(4-ethylphenyl)anthracene (C6-DPA) was used as the organic single-crystal semiconductor transport layer; heavily doped Si / SiO2 silicon wafers were used as the bottom gate and dielectric layer substrate; phenyltrichlorosilane (PTS) was used for substrate surface modification; high-purity gold was used for source / drain electrode fabrication; polydimethylsiloxane (PDMS) and its curing agent were used for the construction of a dual-mode microfluidic platform; and CuCl2 was used to formulate Cu... 2+ The test solution; Py-OH serves as both a colorimetric identification probe and an ion-sensitive membrane for OSCFETs devices. The pyrene derivative Py-OH (CAS No.: 20361-56-2) used in this invention is prepared from 1-aminopyrene and salicylaldehyde.

[0046] Testing and characterization equipment included: UV-Vis spectrophotometry (UV-Vis) obtained using a UV-3600Plus UV-Vis spectrophotometer; Fourier transform infrared spectroscopy (FT-IR) obtained using a Vertex70 Fourier transform infrared spectrometer; X-ray photoelectron spectroscopy (XPS) measurements performed using an Axis Ultra DLD (Kratos, UK) ultra-high vacuum photoelectron spectrometer under Al Kα radiation (1486.6 eV); contact angle measurements using an optical contact angle measuring instrument DSA100 / DSA30; and analysis of the biosensor's electrochemical properties using a Keithley 4200 SCS semiconductor parameter analyzer. Kelvin probe force microscopy (KPFM) was also used.

[0047] The technical solution of the present invention will be further illustrated by the following embodiments.

[0048] Example 1 A copper ion detection device based on a single-component dual-mode platform includes the following structure: 1. Overall Architecture and Foundation The overall dimensions of the detection device are preferably 5.0 cm × 3.5 cm × 1.5 cm. The device uses a glass plate as the bottom support substrate, on which a polydimethylsiloxane (PDMS) microfluidic platform is bonded. The PDMS microfluidic platform is formed by mixing PDMS prepolymer and curing agent at a mass ratio of 10:1, degassing, injecting into an acrylic mold, curing at 70°C for 2 hours, and then permanently bonding to the glass substrate after oxygen plasma treatment (70W power, 10min) to form a sealed microfluidic cavity.

[0049] 2. Layered structure of the electrical detection module The electrical detection module is integrated on one side of the PDMS microfluidic platform, and its specific layered structure from bottom to top includes: Substrate: Selected with a capacitance of 10.5 nF / cm 2 A 300 nm thick Si / SiO2 wafer was used as the substrate material for OSCFETs devices, with heavily doped silicon serving as the gate and a thermally oxidized SiO2 layer as the insulating layer. During sample pretreatment, the wafer was cut into 1 cm × 1 cm squares, initially purged with nitrogen, and then placed in a PTFE cleaning rack. It was then ultrasonically cleaned sequentially with ultrapure water, acetone, and isopropanol (40% ultrasonic power, 10 minutes). After cleaning, the substrate was dried with nitrogen and transferred to a clean petri dish. To further enhance surface chemical activity, an oxygen plasma treatment system was used to activate the substrate surface (80 Hz power, 30 minutes). The hydroxyl density on the SiO2 surface significantly increased after treatment, which is beneficial for subsequent molecular layer self-assembly.

[0050] Modification Layer: After cleaning and oxygen plasma activation of the substrate surface, the SiO2 surface was modified. Phenyltrichlorosilane (PTS) vapor deposition was used for interface modification. The pretreated SiO2 / Si substrate was placed in a vacuum drying oven, where PTS was slowly volatilized and deposited onto the substrate surface at 60 °C under vacuum for 12 hours. After modification, the substrate was placed in a cleaning rack and ultrasonically cleaned sequentially with n-hexane, chloroform, and isopropanol (40% ultrasonic power, 10 minutes) to remove any physically adsorbed modification agent residues. Finally, it was dried with nitrogen for later use. This vapor-phase modification process effectively controlled the interfacial energy level and surface energy, laying the foundation for the subsequent transfer of high-quality crystalline thin films and the formation of good interfacial contacts.

[0051] Transport Layer: A C6-DPA organic single-crystal thin film was deposited on the modified substrate surface using the Czochralski method to serve as a charge transport channel. The C6-DPA organic single-crystal thin film was prepared using the Czochralski method. The specific steps are as follows: First, 0.5 mg of C6-DPA powder was dissolved in 1 mL of toluene and then sonicated in deionized water at a frequency of 100 Hz for 30 minutes to ensure complete dissolution. Subsequently, 45 µL of this solution was dropped onto the surface of a clean glass petri dish containing deionized water. Utilizing the self-assembly effect at the liquid-gas interface, the solute molecules spread and formed a film on the water surface.

[0052] n modified by PTS gas phase + A silicon wafer (1 cm × 1 cm, with a thermally oxidized SiO2 layer on its surface) is fixed on an dip-coating device and immersed in a solution, then vertically dipped into the liquid film at a constant speed of 6 µm / s. During the 30-minute dipping process, C6-DPA molecules undergo ordered assembly at the water-toluene interface and are deposited layer by layer on the SiO2 surface as the substrate is slowly pulled, ultimately forming a continuous, dense crystalline film with a well-defined molecular orientation. This method combines interfacial self-assembly with controlled dipping technology, which is beneficial for the fabrication of large-area, high-quality organic semiconductor thin films.

[0053] Electrodes: To ensure a good ohmic contact between the C6-DPA crystal film and the electrodes, the work function of the electrode material must match its energy level. Au was selected as the source / drain electrode, as its work function is close to that of C6-DPA, which is beneficial for efficient hole injection. To avoid thermal radiation damage to the organic crystal during traditional evaporation processes, a transfer method was used to fabricate the electrodes. First, an Au film was deposited on a clean silicon wafer using a copper mesh mask (rate 1.0 Å / s, thickness 150 nm). Then, using a gallium-indium alloy as the adhesion medium, a microprobe was used to precisely transfer the pre-fabricated gold film to a designated area of ​​the C6-DPA film. This method achieves work function matching while effectively avoiding damage to the organic semiconductor structure during the heating process.

[0054] Fabrication of the sensitive layer: The OSCFETs device (the integral device obtained after electrode fabrication as described above) was fixed on a glass substrate and placed on the sample stage of an organic evaporation system. An appropriate amount of Py-OH powder was placed in the ceramic boat containing the evaporation source. The system was evaporated to a vacuum of 1×10⁻⁶. − 6 After setting the evaporation rate, target film thickness, and substrate temperature (specifically 25°C (room temperature)) in sequence, start the heating program and slowly raise the temperature to the predetermined evaporation temperature and stabilize it. Once the evaporation rate has stabilized, zero the film thickness monitor, turn on the evaporation baffle and rotate the sample stage for deposition. Maintain a constant evaporation rate during the evaporation process. After reaching the target thickness, close the baffle and allow the system to cool naturally to below 50°C. Then, purge with nitrogen to atmospheric pressure, remove the sample, and complete the preparation of the sensitive layer.

[0055] Evaporation parameters were controlled as follows: the evaporation deposition rate was 0.1 Å / s and the film thickness was 0.3 kÅ (30 nm).

[0056] 3. Fluid structure of the colorimetric detection module The colorimetric detection module is located on the other side of the PDMS microfluidic platform and is connected to the electrical detection module via a microchannel. The colorimetric detection module includes a color detection chamber (colorimetric cell) formed on the PDMS block and a probe (Py-OH ethanol solution, concentration 10) located within the detection chamber. -4 M). The cavity is designed as a channel structure that facilitates optical observation, and is physically isolated from the electrical detection module but fluidly connected to it, ensuring that the same sample solution can flow through the two detection areas simultaneously.

[0057] 4. External auxiliary components To enable portable quantitative analysis, the device is equipped with external auxiliary components, including: Imaging system: A smartphone, in conjunction with a fixed imaging box (photo booth) with a parallel LED light source, to eliminate ambient light interference.

[0058] Data processing terminal: A computer or mobile app running a convolutional neural network (CNN) model, used to receive image data and output concentration results.

[0059] The following mechanism analysis and detection effect verification are now performed based on the detection device in Example 1: Example 1 Cu 2+ Coordination mechanism with pyrene derivative Py-OH: Step 1: Solution UV-Vis study at a constant total concentration (10 −4 Draw the Job's Plot under M conditions ( Figure 1 As can be seen from the figure, at λCu 2+ A significant peak appears at 0.33, confirming that Cu... 2+ It forms a 1:2 complex with Py-OH (i.e., each Cu... 2+ (Coordinated with two Py-OH molecules).

[0060] Step 2: Further thermodynamic analysis of the titration data was performed using the Benesi-Hildebrand method. Figure 2 The binding constant K = 9.91 × 10⁴ M was obtained from the fitted curve. −1 / 2 This indicates that the two have a strong coordination affinity.

[0061] Step 3: Based on the above results and combined with coordination chemistry theory analysis, the stable structure of this complex can be deduced as follows: Each Cu2+ The ion coordinates simultaneously with the Schiff base nitrogen atom (C=N) and the deprotonated phenoloxy atom (C–O–) in both Py-OH molecules through its empty orbital, forming a stable coordination mode. Figure 3 This well-defined coordination structure and high binding constant, at the molecular level, facilitate the pairing of Py-OH with Cu. 2+ This provides a crucial theoretical basis for the highly selective identification of Cu based on Py-OH, and also lays the foundation for subsequent construction of highly sensitive and accurate Cu based on Py-OH. 2+ The sensing platform laid an important foundation.

[0062] Example 2 Based on Py-OH functionalized OSCFETs sensors (the electrical detection module in Example 1), Cu 2+ Analysis of detection performance: Step 1: First, measure the initial transfer characteristic curve of the functionalized OSCFETs sensor and record the initial current. I 0.

[0063] Step 2: Drop 20 μL of Cu at different concentrations onto the device surface. 2+ An aqueous solution was incubated at room temperature for 20 minutes to allow Cu to... 2 + It undergoes a coordination reaction with the Py-OH functional layer.

[0064] Step 3: After incubation, gently rinse the device surface with deionized water and then dry it with argon gas.

[0065] Step 4: Remeasure the device transfer curve and record the current after the reaction. I And calculate Δ I DS =( I - I 0) / I 0×100% is used as the electrical response signal.

[0066] Step 5: With Cu 2+ Concentration from 1 ng / mL -1 Gradually increase to 100 μg / mL -1 The on-state current of the device decreases regularly. Figure 5 (a) explains Cu 2+ After coordination, a localized positive charge layer is formed at the sensing interface. This positive charge layer is equivalent to an additional positive gate voltage, which depletes the holes in the P-type channel, thereby causing a decrease in drain-source current.

[0067] Step 6: The calibration curve shows that this electrical mode operates at 100 μg / mL. -1 up to 1 ng mL-1 It exhibits good linear response over a wide concentration range, with a theoretical detection limit as low as 0.39 ng / mL. -1 ( Figure 5 in (b)); in Na + K + Mg 2+ Zn 2+ and Hg 2+ The electrical response changes very little in the presence of common interfering ions, indicating that the device is responsive to Cu. 2+ It has high selectivity and anti-interference ability. Figure 5 (c)-(d)).

[0068] The electrical detection module in Example 1 will now be tested as follows (Test Examples 1-5): Test Example 1: X-ray photoelectron spectroscopy (XPS) measurements were performed using an Axis Ultra DLD (Kratos, UK) ultra-high vacuum photoelectron spectrometer under Al Kα radiation (1486.6 eV). XPS confirmed the presence of C, O, N, and Cu elements on the film surface, and the characteristic peaks at 932.1 eV and 951.8 eV in the Cu 2p fine spectrum, along with their satellite peaks (ΔE ≈ 8 eV), clearly confirmed the presence of Cu. 2+ The existence of ( Figure 4 (a)-(b)). High-resolution N 1s and O 1s spectra ( Figure 4 (c) shows a redshift in the peak positions of C=N–C and C–O–H, confirming that coordination leads to a redistribution of electron density in N and O atoms.

[0069] Test Example 2: Infrared characterization: Fourier transform infrared (FTIR) spectra were obtained using a Vertex 70 Fourier transform infrared spectrometer. Approximate amounts of dried 1-aminopyrene (5 mg), Py-OH powder (approximately 5 mg), and salicylaldehyde reagent (approximately 1 mL) were placed on the sample stage, ensuring full contact between the sample and the diamond crystal. FTIR spectra were obtained using a Fourier transform infrared spectrometer in the range of 400–4000 cm⁻¹. −1 Within the wavenumber range at 4 cm −1 Transmission spectra were acquired at high resolution. Blank correction was performed against an air background before testing, and the instrument surface was cleaned with anhydrous ethanol after testing. The obtained spectral data were processed using OMNIC software, including automatic baseline correction and smoothing, and the characteristic absorption peaks of major functional groups were analyzed. Figure 4 (d)

[0070] Test Example 3: Ultraviolet characterization: Ultraviolet-visible spectrophotometry (UV-Vis) was obtained using a UV-3600Plus UV-Vis spectrophotometer. A suitable amount of dried Py-OH powder sample was taken and uniformly packed into a dedicated sample cell. The sample was scanned within the wavelength range of 200–800 nm using a UV-Vis spectrophotometer, with high-reflectivity barium sulfate powder as the reference background, to obtain the optical absorption characteristic spectrum of the sample. Figure 4 The absorption band position and intensity of the sample (e) are analyzed to study its light absorption properties and related electronic transition behavior in the solid state.

[0071] Test Example 4: Contact angle measurements were obtained using an optical contact angle meter DSA100 / DSA30. The water contact angle at the membrane surface is determined by the Cu bonding. 2+ The previous 80° increased to Cu 2+ 100° after combination ( Figure 4 (f) indicates that coordination causes molecular rearrangement and reduces the exposure of hydrophilic groups, thereby increasing the contact angle of water.

[0072] Test Example 5: OSCFETs sensing mode, Cu 2+ Specific recognition mechanism between Py-OH molecules In OSCFETs sensing mode, Cu 2+ The specific recognition between Cu and Py-OH molecules directly modulates the semiconductor conductive channel through a field-effect mechanism. 2+ After the ion-sensitive membrane is functionalized, a coordination reaction occurs at the sensing interface, forming a localized positive charge layer. This layer is equivalent to applying an additional positive gate voltage, effectively depleting the hole carriers in the P-type channel and causing a decrease in device current. This charge modulation mechanism was directly verified using Kelvin probe force microscopy (KPFM). Figure 6 Different concentrations of Cu 2+ Combined with the KPFM potential map of the back film surface, Figure 6 (a) and (g) are 0 ng / mL respectively. −1 1 ng mL −1 10 ng mL −1 100 ng mL −1 1 μg mL −1 10 μg mL −1 100 μg mL −1 Cu 2+ KPFM potential diagram on the surface of the Py-OH ion-sensitive membrane after functionalization. Figure 6 (a) is unbonded Cu2+ Characterization of KPFM potential on the film surface. The overall potential distribution on the surface is uniform, with no obvious potential anomalies or regional differences. The potential range corresponding to different color intensities is approximately -50 to 100 mV. Figure 6 (b) Low concentration of Cu 2+ After introduction, the baseline of the membrane surface potential shifted slightly upward, increasing the potential range to 50–200 mV. The surface remained predominantly uniformly distributed, with only slight localized potential fluctuations, indicating that Cu at extremely low concentrations… 2+ The adsorption amount was relatively small, and it did not cause a significant redistribution of the charge on the film surface, only generating preliminary charge interactions; with the increase of Cu... 2+ Concentration increases, such as Figure 6 (c) Obvious transverse potential stripe distribution appears on the film surface, with the potential range further increasing to 0–250 mV. The potential in the stripe region is significantly higher than that of the surrounding substrate, indicating that Cu… 2+ Regional enrichment begins on the film surface, and the non-uniformity of charge distribution becomes apparent with increasing concentration, reflecting the film surface's response to Cu. 2+ The adsorption effect begins to increase; Figure 6 In (d), when the concentration is increased to 100 ng·mL −1 At this time, the overall surface potential of the film increased significantly, reaching 200–350 mV, and multiple diffuse high-potential regions appeared. The number and area of ​​high-potential regions were significantly increased in the lower concentration group, indicating that Cu… 2+ The adsorption amount on the membrane surface is greatly increased, and the charge aggregation effect is enhanced; Figure 6 In (e), at this concentration, a significant, dot-shaped high-potential bright spot appears on the film surface, with a potential range of 450–600 mV. The potential at the bright spot is much higher than that of the surrounding substrate, forming a strong potential contrast. At high concentrations, Cu… 2+ Localized specific enrichment or aggregation occurred on the membrane surface, forming localized high charge density sites; Figure 6 In (f), multiple diffusely distributed high-potential regions appear on the membrane surface, with a potential range of 650~800 mV. The number of high-potential regions increases and their distribution becomes more widespread. Figure 6 In (g), at the highest concentration, the overall potential of the film surface reaches a maximum level of 800~950 mV, with multiple diffuse high-potential bright spots distributed simultaneously. With Cu... 2+ As the concentration increases, the surface potential of the device exhibits a systematic positive shift (e.g. Figure 6 and Figure 7 As shown in the figure, the quantitative correlation between the identified event and the electrical signal was experimentally confirmed.

[0073] Example 3: Construction of a Dual-Mode Integrated Sensing Platform Step 1: Mix the polydimethylsiloxane (PDMS) prepolymer and curing agent thoroughly at a mass ratio of 10:1, stir evenly, degas, and inject into a custom acrylic mold.

[0074] Step 2: Place the mold in a 70℃ environment to cure for 2 hours. After curing, demold and punch holes in the predetermined positions to form sample injection and discharge channels.

[0075] Step 3: Perform oxygen plasma treatment on the PDMS plate and glass slide at a power of 70 W for 10 min to activate their surfaces and permanently bond them together to form a microfluidic cavity.

[0076] Step 4: Integrate the aforementioned Py-OH functionalized OSCFETs devices onto one side of the platform, and set a colorimetric sensing module as the colorimetric reaction area on the other side, ultimately obtaining a dual-mode integrated sensing platform with an overall size of approximately 5.0 cm × 3.5 cm × 1.5 cm. Figure 8 ).

[0077] Step 5: During actual testing, 10 -4 M Py-OH ethanol solution is injected into the colorimetric module, while the Cu to be measured is introduced into both the electrical module and the colorimetric module. 2+ The solution allows both to share the same recognition molecule and the same target analyte reaction process.

[0078] Example 4: Build a CNN intelligent analysis model Step 1: Use a smartphone to photograph different Cu samples in a light-controlled imaging box. 2+ Colorimetric images at different concentrations were analyzed, and a CNN intelligent analysis model was established. Figure 9 ).

[0079] Step 2: The image is first uniformly converted to 224×224 pixel RGB format, for each Cu... 2+ Concentration gradient (0-50 µg / mL) −1 Collect 200 images.

[0080] Step 3: Then, white balance correction, background subtraction, and pixel normalization are performed to form a standardized image dataset. The preprocessed image is converted into a feature matrix carrying RGB three-channel information, which is used as input data for CNN training and learning.

[0081] Step 4: The dataset is randomly divided into training and validation sets to ensure the objectivity of model evaluation.

[0082] Step 5: Through layer-by-layer convolution and feature learning, this algorithm can autonomously extract features related to Cu. 2+Concentration-related visual discrimination features significantly improve the accuracy and prediction precision of colorimetric quantitative analysis within the target dynamic range.

[0083] Example 5: Cu 2+ The colorimetric detection method includes the following steps: Step 1: Weigh 32.14 mg of Py-OH and dissolve it in 1 L of ethanol to prepare a solution of 10 -4 M probe solution.

[0084] Step 2: Inject 1 mL of probe solution into the colorimetric module using a syringe, and then inject Cu solutions of different concentrations into the two sensing modules respectively. 2+ Aqueous solution.

[0085] Step 3: In colorimetric mode, add 100 µL Cu 2+ Mix the solution with 1 mL of probe solution (to form a probe to analyte volume ratio of 10:1).

[0086] Step 4: OSCFETs module directly contacts Cu 2+ After incubation for 20 minutes, the sensor surface was rinsed with deionized water and dried under gentle argon purging. Electrical characterization was then performed using a Keithley 4200 semiconductor parameter analyzer.

[0087] Step 5: On the other side, take 1 mL of the reaction solution from the colorimetric area and dilute it with 2 mL of anhydrous ethanol. Place it in a 10 mm quartz cuvette for UV-Vis measurement. Perform 30 replicate measurements for each concentration to ensure statistical reliability. Figure 10 (b)

[0088] Step 6: Colorimetric module for Cu 2+ It exhibits a distinct color response, with Cu 2+ As the concentration increases, the color of the reaction solution gradually changes from light yellow to dark brown. Figure 10 In (a), this change is consistent with the systematic shift in the UV-Vis spectrum. Figure 10 (b)

[0089] Step 7: Spectral data show that Cu 2+ After addition, the absorption at 382 nm decreased, while the absorption at 500 nm increased, indicating that Py-OH reacts with Cu. 2+ Significant charge transfer occurs after coordination ( Figure 10 (b) Step 8: When the absorbance at 500 nm is used as the detection signal, a good linear relationship can be obtained in the range of 5-50 μM. R 2= 0.990), the theoretical limit of detection is 57.78 ng / mL. -1 ( Figure 10 (c) Step 9: Selective test results show that in Na + K + Mg 2+ Hg 2+ and Zn 2+ Even with multiple interfering ions coexisting, this colorimetric module still detects Cu. 2+ Maintains specific response and has good anti-interference ability. Figure 10 (d)

[0090] Example 6: A smartphone colorimetric analysis system based on CNN Step 1: Combine smartphone imaging with machine learning to build a portable analysis system. The system includes a simple photo booth composed of parallel LED lights to fix the shooting environment, ensuring consistent lighting conditions for each image acquisition, thereby improving image stability and comparability.

[0091] Step 2: Image data is processed by a CNN. The network extracts data layer by layer through the input layer, convolutional layer, pooling layer, fully connected layer, and output layer (see DOI: 10.1038 / s41467-022-31236-0; DOI: 10.1021 / acs.analchem.4c04817) and learns (…). Figure 9 Establish the relationship between solution color change and Cu 2+ A quantitative relationship model between concentrations.

[0092] Step 3: The smartphone colorimetric analysis system based on CNN is applied to Cu 2+ It exhibits excellent performance in quantitative detection. Figure 11 (a) This model can accurately identify 0–50 μg mL −1 The color change pattern of the solution within a concentration range was studied, and a concentration-response calibration curve with high fitting degree was established. R 2 = 0.986); Step 4: Regarding model optimization and training, the entire dataset was randomly divided into training and validation sets. Throughout the training process, the loss functions of both the training and validation sets decreased synchronously and steadily, eventually converging to below 0.1, indicating that the model was sufficiently trained and did not exhibit overfitting. Figure 11 (b) Step 5: During training and validation, the coefficient of determination between predicted and true values. R 2All gradually increased from an initial value of approximately 0.1 to over 0.9. Figure 11 In (c), the model demonstrates strong feature learning and generalization capabilities; Step 6: Further verification showed that the predicted concentration and the actual concentration were highly clustered near the 45° ideal reference line. Figure 11 (d) Step 7: The predicted residuals exhibit a symmetrical distribution centered at zero, and more than 95% of the residuals fall within ±0.5 μg / mL. −1 Within the range ( Figure 11 (e) indicates that the model has good predictive consistency and accuracy.

[0093] Step 8: In addition, the model adopted an adaptive learning rate scheduling strategy during training. The initial learning rate was set to 0.001 and gradually decreased with each training round, effectively improving the model's convergence efficiency and stability. Figure 11 (f)

[0094] Example 7 Dual-mode fusion detection in real samples Step 1: Select tap water and artificial sweat as complex sample matrices, and prepare 0.1 μg mL solutions respectively. -1 and 1 μgmL -1 Two concentrations.

[0095] Step 2: After the sample was sonicated for 10 min and filtered through a 0.22 μm filter membrane, Cu was independently measured using both colorimetric and electrical modes. 2+ Concentration was tested repeatedly for each sample.

[0096] Step 3: The results from the two modes are weighted and fused to obtain the dual-mode output value. Experiments show that the dual-mode platform achieves a recovery rate of 98%–102% in tap water and artificial sweat, with a relative standard deviation of less than 1%, which is highly consistent with the results of the standard method, indicating that the platform has high accuracy and reliability in complex matrices.

[0097] Step 4: When the detection results of the colorimetric module and the electrical module deviate, the risk of false positives in a single mode can be reduced by weighted fusion and cross-validation.

[0098] Step 5: Comparison was performed using ICP-MS as a reference method. The results showed that the recovery rate of the dual-mode platform was closer to the theoretical value and highly consistent with the ICP-MS results. Figure 12 This confirms the platform's reliability in detecting complex matrices.

[0099] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A copper ion detection device based on a single-component dual-mode platform, characterized in that, include: A PDMS microfluidic platform, which integrates a colorimetric detection module and an electrical detection module; The colorimetric detection module and the electrical detection module share the same recognition molecule, 2-(pyrene-1-ylmethyleneamino)phenol (Py-OH). The electrical detection module comprises, from bottom to top: Substrate; A modified layer modified by phenyltrichlorosilane in the gas phase; A transport layer with a C6-DPA organic single-crystal thin film deposited; Au electrode; An ion-sensitive layer with a Py-OH thin film deposited on it; The colorimetric detection module includes a color detection chamber located on a PDMS microfluidic platform, and the color detection chamber is filled with Py-OH ethanol solution as a colorimetric probe.

2. The copper ion detection device based on a single-component dual-mode platform according to claim 1, characterized in that, The concentration of the Py-OH ethanol solution is 10. -4 M.

3. The copper ion detection device based on a single-component dual-mode platform according to claim 1, characterized in that, The PDMS microfluidic platform is formed by mixing and curing PDMS prepolymer and curing agent at a mass ratio of 10:

1.

4. A method for detecting copper ions using the copper ion detection device based on a single-component dual-mode platform as described in any one of claims 1-3, characterized in that, Includes the following steps: The copper ion solution to be tested is introduced into the PDMS microfluidic platform, so that it simultaneously contacts the Py-OH ethanol solution in the colorimetric detection module and the ion-sensitive layer with Py-OH film deposited in the electrical detection module. Incubate at room temperature to allow Py-OH to complete the coordination reaction with copper ions; The color change information of the solution in the colorimetric detection module is obtained, and the current change information in the electrical detection module is also obtained.

5. The method for detecting copper ions using the copper ion detection device based on a single-component dual-mode platform according to claim 4, characterized in that, The specific steps of acquiring the color change information of the solution in the colorimetric detection module include: Use a smartphone to capture an image of the colorimetric detection module after it has reacted; The image is input into a convolutional neural network model for analysis, and the corresponding predicted value of copper ion concentration is output.

6. The method for detecting copper ions using the copper ion detection device based on a single-component dual-mode platform according to claim 5, characterized in that, Before capturing the image of the colorimetric detection module's reaction using a smartphone, the process also includes: The smartphone is placed inside a fixed imaging box, and parallel LED light sources are used as background light to unify the lighting conditions and shooting distance.

7. The method for detecting copper ions using the copper ion detection device based on a single-component dual-mode platform according to claim 4, characterized in that, The acquisition of current change information from the electrical detection module specifically includes: The transfer characteristic curves of the device before and after the reaction are measured, and the relative change in the on-state current is calculated as the electrical response signal.

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