Diffusion discrimination gas sensor

Abstract

The present invention relates to a gas sensor for detecting one or more volatile compounds in a gas, the sensor comprising a signal transducer comprising a layer containing nanopores, the gas having access to the nanopores in said layer, a heating or cooling element having adjustable temperature settings for heating or cooling the layer containing said nanopores, a means of access of the gas to the layer containing said nanopores, and an electronic circuit for monitoring the time- and temperature-dependent signals generated by the signal transducer upon adsorption or release of compounds from the nanopores in the layer.

Description

[Technical field]

[0001] The present invention relates to a gas sensor, and more particularly to a sensor capable of selectively detecting a gas with high sensitivity. [Background technology]

[0002] Gas sensing is a rapidly developing technology field due to its potential applications in monitoring air pollution levels (indoor, outdoor, or industrial applications), food freshness, healthcare diagnostics (through breath analysis), etc. Currently, gas sensing technology is dominated by metal oxide semiconductor (MOS) sensors, which often lack selectivity and cannot effectively distinguish between gas components, especially volatile organic compounds (VOCs). Therefore, to fully realize their potential in the above applications, novel miniaturized sensor technologies are needed that can distinguish VOCs of interest from complex backgrounds.

[0003] An emerging class of gas sensors is the adsorption-based sensor, which uses a microporous sensing layer composed of metal-organic frameworks (MOFs) or zeolites. Here, MOFs are described in more detail, but the concept can be applied to other microporous or nanoporous materials as well. MOFs are a class of crystalline solids consisting of inorganic nodes connected by organic linkers [Non-Patent Document 1]. Uniform nanopores (typically 0.5 nm to 2 nm) and walls only a single molecule thick are formed via the self-assembly of the MOF crystal lattice, resulting in record internal surface areas (up to 6000 m2). 2 g -1Due to their chemical and structural features, MOFs can uptake analytes such as VOCs, even at trace concentrations, with partition coefficients orders of magnitude higher than established materials (Non-Patent Document 3). Thus far, MOF-based sensing has been based exclusively on equilibrium sensor responses and therefore relied solely on thermodynamic adsorption parameters to achieve selectivity (i.e., the difference between equilibrium uptake isotherms).

[0004] US Patent Publication 2007 / 0133963 discloses a gas sensor comprising a gas-sensing material comprising a metal-organic framework with fcu topology (RE-fcu-MOF), where the ligand of the RE-fcu-MOF is one or more of fumaric acid and 1,4-naphthalenedicarboxylic acid. The sensing signal transduction was based on measuring the capacitance of the sensor in an interdigitated electrode configuration. The sensor showed higher sensitivity to H2S and NH3 vapors when compared to NO2, CH4, H2, and C7H8.

[0005] Non-Patent Document 4 demonstrated a chemiresistive sensor array from conductive 2D metal-organic frameworks. The array consisted of three separate devices, each using a different MOF as the sensing layer. The combined response of the sensor array was processed using principal component analysis to obtain a classification of the data by functional group class (alkanes, alcohols, ketones, amines, aromatics, and aliphatics).

[0006] As an alternative to sensor arrays, multivariate approaches have been used to improve the selectivity of single sensor elements [5]. In contrast to conventional single-output sensors, a single multivariate sensor produces two or more (at least partially) independent outputs. The uncorrelated information in these outputs improves selectivity compared to single-output sensors and allows quantification of individual VOCs in mixtures by using standard methods used in chemometrics (e.g., principal component analysis). Furthermore, because multivariate sensors use a single sensing material, drift in the output (if any) is correlated and can be more easily compensated for.

[0007] Multiparameter sensors based on MOFs have so far only been reported for optical transduction, measuring, for example, the wavelength-dependent adsorption of MOFs [Non-Patent Document 5, supra]. [Prior art documents] [Patent documents]

[0008] [Patent Document 1] US Patent Application Publication No. 2018 / 0195990 [Non-patent literature]

[0009] [Non-Patent Document 1] Kitagawa et al. (2004) Angew. Chem. Int. Ed. 43, 2334-2375 [Non-Patent Document 2] Farha et al. (2012) J. Am. Chem. Soc. 134, 15016-15021 [Non-Patent Document 3] Leidinger et al. (2016) Sensors and Actuators B: Chemical 236, 988-996 [Non-Patent Document 4] Campbell et al. (2015) J. Am. Chem. Soc. 137, 13780-13783 [Non-Patent Document 5] Potyrailo (2016) Chem. Rev. 116, 11877-11923 Summary of the Invention

[0010] In this invention, we describe a multivariate gas sensor that relies on the discrimination of analytes based on diffusion kinetics. The diffusion constants in microporous materials can vary by orders of magnitude for different analytes because their diffusion is controlled by steric hindrance and specific host-analyte interactions. Thus, even molecules with similar uptake properties can often be discriminated based on diffusion kinetics. For example, methanol and ethanol diffuse dramatically faster in ZIF-8 (a microporous MOF material) compared to 1-butanol, by 10 6 Although it provides ideal kinetic selectivity up to 10, the thermodynamic selectivity is moderate at comparable concentrations. Similarly, the uptake of butanol and benzene is comparable, but the diffusion of benzene is 10 4 In the present invention, "kinetic selectivity" is defined as the ratio of the diffusivities of the adsorbates and "thermodynamic selectivity" is defined as the ratio of their equilibrium uptakes.

[0011] MOFs refer to a class of crystalline solids consisting of inorganic nodes connected by organic linkers.

[0012] The method of the invention can be used, for example, to monitor air pollution levels (indoor, outdoor or industrial applications), food freshness, healthcare diagnostics (by breath analysis).

[0013] Throughout this specification, nanopores or nanoporous are used as synonyms for micropores or microporous.

[0014] The invention is further summarized in the following description.

[0015] 1. A gas sensor for detecting one or more volatile compounds in a gas, the sensor comprising: a signal transducer including a layer including a nanopore, the gas accessing the nanopore in the layer; a heating or cooling element having adjustable temperature settings for heating or cooling the layer containing the nanopores; a means of access for said gas to said layer containing said nanopores; an electronic circuit that monitors the time-dependent and temperature-dependent signals generated by the signal transducer upon adsorption or desorption of a compound from the nanopore in the layer; A gas sensor comprising:

[0016] "Volatile compounds" refers to compounds that exist partially or completely in the gas phase at room temperature. Examples include water, alkanes, ketones, alcohols, aldehydes, and aromatic compounds.

[0017] Herein, water is typically a background component that interferes with the measurement of other volatile components.

[0018] 2. The gas sensor of claim 1, wherein the layer containing nanopores has a thickness of less than 50 μm, or less than 10 μm, or less than 5 μm, for example between 50 nm and 300 nm.

[0019] 3. The gas sensor of claim 1 or 2, wherein the nanopores in the layer containing the nanopores have an average diameter of less than 10 nm, less than 10 nm, or less than 2 nm.

[0020] 4. The gas sensor according to any one of statements 1 to 3, wherein the layer containing nanopores is a zeolite or a porous carbon.

[0021] 5. The gas sensor according to any one of statements 1 to 3, wherein the layer containing nanopores is a MOF (metal-organic framework).

[0022] 6. The gas sensor of any one of statements 1 to 5, wherein the heating element and the nanopore-containing layer are separated by a thermally conductive material.

[0023] 7. The gas sensor of claim 6, wherein the thermally conductive material has a thermal conductivity of at least 0.3 W / mK.

[0024] 8. The gas sensor according to claim 6 or 7, wherein the thermally conductive material is a non-conductive material such as silicon nitride, silicon oxide, silicon carbide, ceramics, or the like.

[0025] 9. The gas sensor according to any one of statements 1 to 8, wherein the heating element is an ohmic heater such as a microhotplate.

[0026] 10. The gas sensor according to any one of statements 1 to 9, wherein the signal converter is an electronic signal converter, a capacitive signal converter, an optical signal converter, or a gravimetric signal converter.

[0027] 11. The gas sensor of claim 10, wherein the capacitive signal converter includes a bottom thermally conductive layer and a top gas-permeable conductive layer, and the nanopore-containing layer is disposed between the bottom layer and the top layer.

[0028] 12. The gas sensor of claim 10, wherein the optical signal converter includes a bottom reflective or semi-reflective layer and a top reflective or semi-reflective gas-permeable layer, and the nanopore-containing layer is disposed between the bottom layer and the top layer.

[0029] 13. The gas sensor of claim 10, comprising a gravimetric signal transducer, wherein the layer containing the nanopores is disposed on and in contact with one or more mechanical resonators capable of monitoring resonant frequency or amplitude.

[0030] 14. The gas sensor of claim 13, wherein the gravimetric transducer operates in a static mode or a resonant mode.

[0031] 15. The gas sensor of claim 13 or 14, wherein the gravimetric transducer is a cantilever resonator or a coupled resonator.

[0032] 16. The gas sensor of any one of statements 1 or 15, wherein the layer containing the nanopore is in direct contact with the transducer.

[0033] 17. A gas sensor according to any one of statements 1 or 15, wherein the layer containing the nanopore and the transducer are spatially separated.

[0034] 18. The gas sensor of claim 17, wherein the transducer is a metal oxide semiconductor sensor.

[0035] 19. A sensor described in any one of statements 1 to 18, wherein the gas sensor comprises multiple layers containing nanopores, the materials of the layers having different affinities for volatile compounds and / or different diffusion properties for volatile compounds, and each of the layers is part of an individual signal transducer.

[0036] 20. The sensor of claim 19, wherein each of the nanopore-containing layers can be subjected to a distinct temperature regime.

[0037] 21. The sensor of claim 19 or 20, wherein each of the multiple layers containing the nanopores has a different thickness.

[0038] 22. A method for determining the presence and / or amount of a plurality of volatile compounds in a gas, comprising: a) introducing a gas into the sensor of any one of statements 1 to 20, and allowing compounds in the gas to adsorb within the nanopores of the layer comprising the nanopores; b) decreasing or increasing the temperature of the layer containing the nanopores, thereby releasing the adsorbed compounds from the nanopores upon heating or adsorbing the compounds in the nanopores upon cooling; c) measuring the temperature- and time-dependent release and / or adsorption of a compound from or to the nanopore from the signal transducer; d) determining the presence and / or concentration of at least two volatile compounds in the gas based on the measurements of the transducer; and A method comprising:

[0039] 23. The method of claim 22, wherein in step b) the temperature of the layer containing the nanopores is increased, thereby releasing adsorbed compounds from the nanopores.

[0040] 24. The method of claim 22 or 23, further comprising determining in step d) the presence and concentration of water in the gas.

[0041] 25. The method of any one of statements 22-24, wherein the temperature of the nanopore-containing layer is periodically perturbed.

[0042] 26. The method of any one of statements 22-25, wherein the adsorption or release of a compound is monitored on a plurality of layers comprising nanopores.

[0043] 27. The method of any one of statements 22 to 26, wherein the gas introduced in step a) comprises 50% (v / v), up to 75% (v / v), or up to 100% (v / v) water vapor.

[0044] 28. The method of any one of statements 22 to 27, wherein the gas introduced in step a) is outside air or air within the building.

[0045] 29. The method of any one of statements 22 to 28, wherein the gas introduced in step a) is animal or human exhaled breath.

[0046] 30. The method of any one of statements 22-29, wherein the method measures the presence and / or concentration of one or more of 1-propanol, 1-butanol, acetone pentane, and hexane in a gas.

[0047] 31. The method of any one of statements 22-30, wherein the method measures the presence and / or concentration of one or more of 1-propanol, 1-butanol, acetone pentane, and hexane in a gas containing water vapor. [Brief description of the drawings]

[0048] [Figure 1] (a) Simplified structure of a diffusion discrimination gas sensor. (b) Time domain detection concept. A sensor with a microporous active layer is rapidly heated from T1 to T2 at time t0. As a result, analyte molecules diffuse out of the microporous layer, which is detected as a signal S by the sensor transducer. The signal follows an exponential decay function from S2 to S1 upon desorption of the analyte. (c) Frequency domain detection concept. A periodic temperature perturbation with amplitude T and frequency ν modulates the diffusion in the microporous layer. The sensor signal follows the temperature perturbation with amplitude S and phase Φ. Sweeping the frequency of the temperature perturbation results in a stepwise amplitude decrease and a phase-lagging peak in the sensor signal, which is characteristic of analyte diffusion. All examples in the figures are for the ideal case of single analyte diffusion. [Diagram 2] Possible configurations of the sensor transducer: (a) top projection and (b) cross-section of the sensing element in metal-insulator-metal (MIM) configuration, (c) top projection and (d) cross-section of the sensing element in interdigitated electrode (IDE) configuration. 1: heater, 2: insulator / substrate, 3: microporous sensing layer, 4: electrode. [Diagram 3] Possible configurations of a heat converter. 1: heating element, 2: electrical shield, 3: insulation. [Figure 4] Calculated desorption profiles for (a) a 50 nm thick film and (b) a 1000 nm thick film of microporous material. Discrimination power for binary mixtures of analytes with diffusion constant differences of (c) 10-fold, (d) 100-fold, and (e) 1000-fold (calculated for a 50 nm thick film of microporous material). A1 / A2 is the concentration ratio of both analytes. [Diagram 5](a-e) MIM capacitive sensor with a 260 nm thick ZIF-8 layer. (a) Dependence of the diffusion signal amplitude on the concentration of 1-butanol at a temperature step of 16 °C. (b) Dependence of the diffusion signal time constant on the concentration of 1-butanol at a temperature step of 16 °C. (c) Dependence of the diffusion signal amplitude on the temperature step amplitude for ethanol at p / p0 = 0.1% (24 °C). (d) Temporal response of the sensor to methanol (p / p0 = 1% at 24 °C), 1-propanol (p / p0 = 0.1% at 24 °C), 1-butanol (p / p0 = 0.1% at 24 °C), and hexane (p / p0 = 0.05% at 24 °C) at a temperature step of 16 °C. (e) Temporal response of the sensor to a mixture of methanol (p / p0 = 8% at 24 °C) and 1-butanol (p / p0 = 0.5% at 24 °C) at a temperature step of 16 °C. (f) Calculated temporal response of a sensor with a 50 nm thick ZIF-8 layer to a mixture consisting of 40% relative humidity (water), 200 ppm acetone, and 10 ppm 1-hexane. [Figure 6] Multivariate VOC classification using diffusion discrimination sensing technique with MIM capacitive sensors. Measurement of single component and binary mixtures of (a) 1-propanol:1-butanol, (b) acetone:hexane, and (c) water:acetone:hexane. Next to the data points, the concentrations of the single components are shown in ppm. Measurements were performed at 24 °C using a MIM capacitive sensor with a 180 nm thick ZIF-8 layer and a 12 nm thick gold top electrode. [Figure 7]Separated adsorption and measurement elements and sampled measurement method. A. Open-top embodiment of the separation element concept. Dark element (1): heater with nanoporous material coated on top. Light element (2): conversion element. Top: plan view. Bottom: cross-sectional side view. B and C. Semi-closed embodiment of the separation element concept. Dark element (1): heater with nanoporous material coated on top. Light element (2): conversion element. Top: plan view. Bottom: cross-sectional side view. D Sampled measurement method. The temperature of the adsorbent jumps from T1 to T0 (T0 < T1) and molecules start to diffuse into the adsorbent (due to the adsorbed amount n0 > n1). Before the equilibrium at T0 is established, the temperature jumps back to T1 after a well-defined residence time t1 and the molecules that may diffuse are desorbed. The desorbed fraction is quantified downstream using a mass spectrometer. By systematically varying the time t, adsorbed amount versus time curves can be constructed and fitted to an appropriate diffusion model to extract the diffusivity at T0. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0049] The invention presented herein devise a method for selectively detecting analytes and measuring their concentrations by gas sensors or sensor arrays that exhibit kinetic selectivity.

[0050] Features disclosed in the specification or claims, or in the accompanying drawings, may, where appropriate, be presented in a specific form, or in terms of means for performing a disclosed function, or in terms of a method or process for obtaining a disclosed result, and may be utilized separately or in any combination of such features to realize the invention in various of its forms.

[0051] Although the present invention has been described in conjunction with the above exemplary embodiments, numerous equivalent modifications and variations will become apparent to those skilled in the art when given this disclosure. Accordingly, the exemplary embodiments of the present invention set forth above should be considered as illustrative and not limiting. Various modifications can be made to the described embodiments without departing from the spirit and scope of the present invention.

[0052] For the avoidance of doubt, the theoretical explanations provided herein are provided for the purpose of enhancing the understanding of the reader, and the inventors do not wish to be bound by any of these theoretical explanations.

[0053] The section headings used herein are for organizational purposes only and are not to be construed as limiting the subject matter described.

[0054] Throughout this specification, including the claims which follow, unless the context requires otherwise, the words "comprise" and "include", as well as variations such as "comprises", "comprising" and "including", will be understood to imply the inclusion of a stated integer or step or group of integers or steps but not the exclusion of any other integer or step or group of integers or steps.

[0055] It should be noted that, as used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. Ranges may be expressed herein as from "about" one particular value, and / or to "about" another particular value. When such a range is expressed, another embodiment includes from the one particular value and / or to the other particular value. Similarly, when values ​​are expressed as approximations, by use of the antecedent "about," it will be understood that the particular value forms another embodiment. The term "about" with respect to numerical values ​​is arbitrary and may mean, for example, + / - 10%.

[0056] Detection principle Measurement of diffusion requires non-equilibrium conditions of adsorption. The adsorption equilibrium can be adjusted by changing the analyte concentration, gas pressure or sensor temperature. While the analyte concentration and gas pressure are difficult to adjust in real-world applications, temperature adjustment is easily achieved by introducing a heating element into the sensor. Thus, the diffusion discrimination sensor comprises a heating element that provides a rapid temperature perturbation to the sensing element that measures the amount of adsorbed gas (FIG. 1a). The temperature perturbation creates thermodynamic non-equilibrium conditions of adsorption, which drives the diffusion of the analyte until equilibrium at a given temperature is reached.

[0057] Ideally, the microporous layer has a geometry that ensures a fast diffusion time constant and a single exponential diffusion event for a single analyte. Possible geometries are thin films and particles with a narrow particle size distribution. A particularly preferred geometry is a thin film. For simple signal interpretation, the sensor signal is linearly proportional to the number of adsorbed molecules. All examples here assume a thin film geometry and a linear relationship between the signal and the amount of adsorbed molecules. In such a case, diffusion of one analyte results in an exponential decay function (Equation 1).

number

[0058] In the first example, a heating element provides a step-like temperature perturbation from temperature T1 to T2 (Fig. 1b). The time dependence of the amount of adsorbed molecules is monitored by the signal of the sensing element. In most microporous materials, an increase in temperature leads to desorption of gas molecules. For a single analyte, the sensor signal follows the temperature step with an exponential decay function. The time constant of the exponential decay function is proportional to the diffusion constant of the analyte at temperature T2. Furthermore, by performing diffusion measurements at different temperatures, the heat of diffusion can be measured.

[0059] In a second example, the heating element provides a periodic temperature perturbation, for example in the form of a sinusoid (Figure 1c). The frequency of the temperature perturbation is swept over a frequency range and the sensor signal at each frequency is monitored. At frequencies much lower than the analyte diffusion time constant, the sensor signal follows the temperature perturbation without phase lag. The amplitude of the signal is related to the amount of adsorbed analyte. As the temperature perturbation frequency approaches the diffusion time constant, the phase lag of the sensor signal increases until it reaches a peak and the amplitude decreases in steps. At frequencies much higher than the diffusion time constant, the sensor signal follows the temperature perturbation, also without phase lag, but the sensor amplitude corresponds to the response of an empty sensing layer (i.e., the signal is related to the temperature dependence of the dielectric properties of the sensing layer). The main advantage of using a periodic temperature perturbation is that phase-sensitive detection methods can be used, such as detection of the diffusion signal using a lock-in amplifier. If necessary, by using a sufficiently small temperature perturbation amplitude, the nonlinear contribution due to the thermal activation of diffusion can be avoided. Phase-sensitive detection methods can significantly improve the signal-to-noise ratio and improve the detection limit of the sensor.

[0060] Configuring the Sensor The sensor transduction mechanism converts the amount of adsorbed analyte into a measurable signal. Possible transduction mechanisms include those with electrical, optical or gravimetric readout. Particularly useful are electrical and optical readouts, as they can be easily integrated with the heater element. Since most microporous materials are dielectric, a possible transduction mechanism for adsorption sensors with electrical readout is the measurement of capacitance (or complex impedance). When an analyte molecule is adsorbed in a microporous material, its effective dielectric constant increases in proportion to the amount adsorbed and the dielectric constant of the adsorbed phase. Similarly, the refractive index increases upon adsorption of the analyte, which is exploited in sensors with optical readout. Here, capacitive sensors are described in more detail, but the same principles apply to sensors with other transduction mechanisms.

[0061] Suitable capacitor architectures are the metal-insulator-metal (MIM) configuration (Figures 2a, 2b) and the interdigitated electrode (IDE) configuration (Figures 2c, 2d), both of which are described in detail below.

[0062] The MIM configuration consists of a microporous sensing layer sandwiched between two electrodes. The capacitance of the MIM sensor is determined by the area of ​​electrode overlap, the thickness of the sensing layer, and the dielectric constant of the sensing layer. The bottom electrode is deposited on a substrate and covered by the microporous sensing layer. The top electrode is deposited on top of the sensing layer and is gas permeable. In some embodiments, the top electrode is in the form of a thin layer composed of a noble metal (Au, Pt, or Ag) with a thickness of 7 nm to 100 nm. In the MIM configuration, the top electrode can, in some cases, introduce additional resistance to the diffusing gas molecules, which increases the apparent diffusion time constant. The diffusion resistance of an electrode is proportional to its denser morphology (or the absence of pinholes in the electrode) and, consequently, its thickness. In some embodiments, the thickness of the electrode is used to shift the diffusion time constant of fast diffusing analytes into the operating range of the sensor by increasing the diffusion path length through the microporous material.

[0063] The IDE configuration consists of in-plane electrodes in the form of interdigitated fingers separated by a certain distance. The sensing layer is deposited on top of the electrodes or the electrodes are deposited on top of the sensing layer. Due to the in-plane configuration of the electrodes, the IDE sensor can accommodate sensing layers with various morphologies, including rough layers with pinholes and particle coatings. Diffusion in the sensing layer is not hindered by the top electrode, which can benefit the detection of analytes with slow diffusion. However, the IDE sensor has inferior sensitivity compared to the MIM sensor due to the large stray contribution from the underlying substrate and the surrounding atmosphere to the measured capacitance.

[0064] The heater provides a thermal perturbation to the sensing element, resulting in the non-equilibrium conditions necessary for diffusion detection. The heater must provide a fast heat input (either a pulse, step change, or cyclic temperature change) relative to the time constant of the diffusion of the fastest gas molecules to be detected. If the frequency of the cyclic temperature change is swept over a range, at least the fastest frequency in that range must meet this criterion. The thermal time constant of the entire sensor determines the lower detection limit for the diffusivity and depends on the heater configuration, thermal properties, and thickness of the layers that make up the sensor.

[0065] In some embodiments, the heater is deposited on the backside of a thin substrate (Figure 3a). In this configuration, the thickness of the substrate is significantly larger than the thickness of the individual layers and dominates the thermal response of the sensor. The time constant is inversely proportional to the thermal conductivity of the substrate and proportional to its thickness. Therefore, an electrical insulator with high thermal conductivity and mechanical properties suitable for miniaturization is desirable. An alumina substrate with a thickness of 0.1 mm has a thermal time constant of approximately 0.001 s -1 The thermal time constant of a glass substrate of the same thickness is approximately 0.02 s -1 It is.

[0066] Ultra-low thermal time constants can be achieved by using suspended thin films (Figure 3b). Sub-micrometer thick membranes can be easily fabricated using microelectromechanical systems (MEMS) fabrication processes. A 1 μm thick silicon nitride membrane has a thermal time constant of about 10 -7 s -1 It was.

[0067] The detection limit at long times (low frequencies) is determined by the maximum measurement time allowed for the sensing application. Ideally, the measurement time should not exceed a few tens of seconds, e.g., 10 seconds. The bandwidth of the sensor is determined by the range between the lower and upper time limits of the sensor. A typical bandwidth for a diffusion discrimination sensor is 10 3 ~10 7 and the larger the value, the more preferable.

[0068] According to Equation 1, the specific time response of the sensor depends on the diffusion constant of the VOC and the thickness of the nanoporous layer. The thickness of the nanoporous layer can be adjusted depending on the sensing application, for example, less than 5 μm, suitably about 50 nm to 300 nm thick.

[0069] Variations of the embodiment with separated elements and sampled measurements The heater and the transducer element with the nanoporous material on top do not have to be stacked on top of each other. Instead, both elements can be spatially separated inside an open-top or semi-closed sensor package (Figures 7a-7c). In this embodiment, the measurement is performed in a sampling manner. An example of this measurement method is shown in Figure 7d. In this example, the nanoporous material is first equilibrated with the gas flow at temperature T1. Then, the adsorbent temperature is changed abruptly to T0 (T0< T1). At this point, the molecules start to diffuse into the nanoporous material (because the adsorbed amount n0> n1). Before the equilibrium at T0 is established, the temperature jumps back to T1 after a well-defined residence time t1 and the molecules that could diffuse are desorbed. The desorbed fraction is quantified by the transducer element. By systematically varying the adsorption time t, the amount adsorbed for each residence time is determined and an adsorbed amount vs. time curve can be created and fitted to an appropriate diffusion model to extract the diffusivity of the adsorbed molecules at T0 (Figure 7d).

[0070] Diffusion Measurements and Performance The diffusion transport of analyte molecules in microporous materials is largely controlled by steric interactions between the host and the analyte. Therefore, the diffusion kinetics strongly depends on the diameter of the diffusing molecule relative to the micropore size. Depending on the size of the analyte molecules, their diffusion constants can span several orders of magnitude. Figure 4 shows the diffusion constants of analyte molecules in microporous materials for a 50 nm thick film (Figure 4a) and a 1000 nm thick film (Figure 4b). -9 m 2 s -1 ~10 -16 m 2 s -1Figure 1 shows the desorption profiles of analyte molecules with diffusion constants in the range of 100 nm to 100 nm. Thinner films are preferred for detecting analytes with smaller diffusion constants to reduce the time required for measurement. Sensor arrays consisting of two or more sensing elements of different thicknesses can be used to extend the bandwidth of the measurement.

[0071] The discrimination power of the diffusion-based sensor is tested by examining the desorption profiles of binary mixtures of analytes with a difference in diffusion constants of 10-fold (Figure 4c), 100-fold (Figure 4d), and 1000-fold (Figure 4e). Different concentrations of both analytes are illustrated by comparing scenarios where the response due to desorption of analyte 2 is (i) equal, (ii) 9-fold, (iii) 99-fold, and (iv) 999-fold lower than the response due to desorption of analyte 1. In these examples, "A1 / A2" corresponds to the concentration ratio of both analytes. In the case of a 10-fold difference in the diffusion constants of the analytes, a biexponential fit can separate the mixture with an A1 / A2 = 1 ratio within 5% error and an A1 / A2 = 9 ratio within 50% error for analyte 2. When the diffusion constants of the analytes differ by a factor of 100, the accuracy of the sensor improves and A1 / A2=1 and A1 / A2=9 for analyte 2 can be separated within 5% error, and A1 / A2=99 within 50% error. When the diffusion constants of the analytes differ by a factor of 1000, all A1 / A2 ratios except A1 / A2=9999 can be separated within 5% error.

[0072] The proof of concept is demonstrated using a MIM capacitance sensor that uses a prototype microporous material, ZIF-8, as the sensing material. The diffusion constants of various analytes in ZIF-8 are shown in Table 1. Typical interfering compounds in the atmosphere, namely, nitrogen, oxygen, carbon dioxide, and water, are 2×10 -11 m 2 s -1Analytes considered as biomarkers in the human body, such as ethanol and acetone, have diffusion constants approximately 100-fold and 4000-fold lower than background compounds, respectively. 1-hexane and trichloromethane, analytes of interest in monitoring indoor air quality, have diffusion constants more than 100,000-fold lower than background. These large differences in diffusion kinetics between background compounds and analytes of interest allow selective detection of the analytes even at low concentrations of the latter.

[0073] Furthermore, some MOFs show large differences in the equilibrium uptake of certain analytes, which can be beneficial for the discrimination power of the sensor. The sensitivity of sensors with MIM-configured ZIF-8 layers to different analytes is shown in Table 2. The ZIF-8 capacitive sensor shows higher sensitivity to 1-butanol and 1-hexane, which is beneficial for the detection limit of these analytes. On the other hand, the sensitivity of the sensor to water is small, which is an advantage since water is often an interfering compound.

[0074] Table 1: Diffusion constants of different analytes in ZIF-8 at 24 °C. [Table 1] [6: Hu et al. (2020) Inorg. Chem. Front. 7, 1598-1632] [7: Zhang et al. (2012) J. Phys. Chem. Let. 3 2130-2134] [8: Zhang et al. (2013) J. Phys. Chem. Let. 4, 3618-3622] [10: Measured using spectroscopic ellipsometry]

[0075] Table 2: Sensitivity (ΔC / C0) of MIM-configured ZIF-8 sensors towards different analytes at 24 °C. The values ​​are measured in the dilute regime before the characteristic sigmoidal uptake occurs. [Table 2]

[0076] Supporting data for the above is the MIM configured capacitance sensor and the ability to measure capacitance up to 150 K min -1 The measurements were collected using a commercial hotplate setup capable of reaching a heating rate of ΔC / C0 = 2×10 per degree Celsius due to the inherent temperature dependence of the dielectric properties of ZIF-8. The sensor consists of a 260 nm thick layer of ZIF-8 with a 20 nm thick silver top electrode. Capacitance measurements were performed at a frequency of 100 kHz. In pure nitrogen, the sensor exhibits a capacitance of ΔC / C0 = 2×10 per degree Celsius due to the inherent temperature dependence of the dielectric properties of ZIF-8. -4 shows a weak temperature dependence of the capacitance in . The change in capacitance upon application of a temperature step (as described in Fig. 1b) is instantaneous on the time scale achieved here and can be explained if the diffusion signal (S2-S1) is relatively small.

[0077] In a first example, the behavior of the diffusion signal at different concentrations of 1-butanol was tested (Figure 5a). The magnitude of the diffusion signal scales linearly with the concentration of the analyte. Importantly, the ratio of sensitivities (ΔC / C0) for the different analytes (Table 2) is equal when comparing the equilibrium and diffusion signals, indicating that the intrinsic selectivity of ZIF-8 is preserved in the diffusion measurements. In the dilute regime, i.e. before the characteristic sigmoidal uptake occurs, the diffusion time constant is concentration independent (Figure 5b).

[0078] In the second example, the temperature step amplitude (T2-T1) was varied in the range from 6 °C to 36 °C (Figure 5c) and the diffusion signal (S2-S1) was monitored. The diffusion signal increased with the temperature step amplitude and showed an exponential decay dependence.

[0079] In a third example, a temperature step with an amplitude of 16 °C was applied in the presence of a single analyte (either methanol, water, ethanol, 1-propanol, 1-butanol, or hexane) and the sensor signal (capacitance) was monitored over time (Figure 5d). The temporal response of the sensor to methanol, water, and ethanol is similar and follows the temperature perturbation. This indicates that these analytes diffuse too rapidly to be detected with the commercial hotplate setup. The other analytes show a stepwise response that is characteristic of diffusion-driven desorption. Fitting of the temporal sensor response reveals that the apparent diffusion constants for 1-propanol, 1-butanol, and 1-hexane are 6 × 10, respectively. -17 m 2 s -1 , 3×10 -17 m 2 s -1 , and 2 × 10 -17 m 2 s -1 These apparent diffusion constants are approximately ten times smaller than those measured in thin films without a top electrode (measured optically by tracking the refractive index during thermal desorption of the analytes). Importantly, the general trends in diffusion kinetics for different analytes are preserved.

[0080] In the fourth example, methanol (p / p at 24°C) 0 = 8%) and 1-butanol (p / p at 24 °C 0 A temperature step with an amplitude of 16 °C was applied in the presence of a binary mixture of 1,2-dichloro-1,3-trimethylsilyl alcohol (C = 0.5%). The temporal response of the sensor signal shows two desorption events occurring at characteristic times (Figure 5e). The first desorption event occurs at a short time and follows the temperature perturbation, similar to the pure methanol desorption in Figure 5d. The second reaction occurs at a much longer time and is comparable to the diffusion of pure 1-butanol in Figure 5d.

[0081] In the fifth example, 10 -5 s to 10 2The desorption response of the sensor with an extended measurement bandwidth up to 100 s is calculated for a ternary mixture of analytes. This scenario mimics a sensor fabricated on a suspended thin film with an ultra-low thermal time constant. The assumed mixture consisted of 40% relative humidity, 200 ppm acetone, and 10 ppm 1-hexane. The sensor response is calculated using the single component sensor response values ​​listed in Tables 1 and 2. No interactions between the adsorbed analytes are assumed, which is a reasonable assumption due to the high dilution of the analytes. Due to the large difference in the diffusion constants of each analyte, three diffusion events are clearly observed in the calculated temporal response of the sensor. Each event can be fitted separately using a single exponential decay function to obtain the diffusion time constant and diffusion signal amplitude. Using this method, the mixture composition can be fully reconstructed, i.e., the concentrations and diffusion constants of the individual analytes are measured within an error of 5%.

[0082] Another important feature of the diffusion discrimination sensor is that the diffusion constant of the analyte is intrinsic to the microporous material, which should simplify the transfer of calibration models between sensors, assuming the morphology and thickness of the microporous layer are constant.

[0083] Additional measurements were performed on single components and their mixtures to evaluate the selectivity of the diffusion discrimination sensor in the parts per million VOC concentration range. Classification of VOCs is possible by plotting the diffusion constant (which gives the selectivity) versus the amplitude of the desorption curve (which gives the concentration).

[0084] Figure 6a shows the corresponding plots for pure 1-propanol and 1-butanol (filled symbols) and for a binary mixture of the two components (open symbols). The ratio of the diffusion constants of 1-propanol and 1-butanol ranges from 3 to 4. The two components can be clearly separated at all concentrations tested.

[0085] Figure 6b shows the corresponding plots for pure acetone and hexane (filled symbols) and for binary mixtures of the two components (open symbols). The ratio of the diffusion constants of 1-propanol and 1-butanol ranges from 34 to 37. The two components can be clearly separated at all concentrations tested.

[0086] Figure 6c shows the corresponding plots for pure acetone and hexane (filled symbols) and a ternary mixture of the two components in the presence of 10%, 30% or 50% relative humidity. The analyzed ternary mixtures are similar to the theoretical mixture in Figure 5f. Both acetone and hexane can be reliably detected in the presence of interfering humid atmospheres.

[0087] Drawing translation Figure 1(a) Microporous Sensor Heater Figure 1(b) Temperature Time Sensor signal Time Figure 1(c) Temperature Time Sensor signal Phase Amplitude Frequency Figure 3 Substrate Sensor element Membrane Substrate Figure 4(a) R (au) R (arbitrary unit) Figure 4(b) R (au) R (arbitrary unit) Figure 4(c) R (au) R (arbitrary unit) Analyte 1: Analyte 1 : Analyte 2: Analyte 2 : Figure 4(d) Analyte 1: Analyte 1 : Analyte 2: Analyte 2 : Figure 4(e) Analyte 1: Analyte 1 : Analyte 2: Analyte 2 : Figure 5(a) 1-butanol Figure 5(b) 1-butanol Figure 5(c) Ethanol Figure 5(d) Normalized capacitance Methanol 1-Propanol 1-Butanol 1-Hexane Figure 5(e) Normalized capacitance Methanol+1-Butanol Figure 5(f) Normalized capacitance Component A Component B Component C Figure 6(a) Single components Mixtures 1-propanol 1-butanol Amplitude Figure 6(b) Single components Mixtures Acetone Hexane Amplitude Figure 6(c) Single components Mixture Acetone Hexane Amplitude Figure 7 Temperature Sensor signal Quantity adsorbed Time

Claims

1. 1. A gas sensor for detecting one or more volatile compounds in a gas, the sensor comprising: a signal transducer including a layer including a nanopore, the gas accessing the nanopore in the layer; a heating or cooling element having adjustable temperature settings for heating or cooling the layer containing the nanopores; a means of access for said gas to said layer containing said nanopores; an electronic circuit that monitors the time-dependent and temperature-dependent signals generated by the signal transducer upon adsorption or desorption of a compound from the nanopore in the layer; A gas sensor comprising:

2. The gas sensor of claim 1 , wherein the layer containing the nanopores has a thickness of less than 5 μm, for example between 50 nm and 300 nm.

3. 3. The gas sensor of claim 1 or 2, wherein the nanopores in the nanopore-containing layer have an average diameter of less than 10 nm, less than 10 nm, or less than 2 nm.

4. The gas sensor according to any one of claims 1 to 3, wherein the layer containing nanopores is a zeolite or a porous carbon.

5. The gas sensor according to any one of claims 1 to 3, wherein the layer containing nanopores is a MOF (metal-organic framework).

6. The gas sensor according to any one of claims 1 to 5, wherein the heating element and the nanopore-containing layer are separated by a thermally conductive material.

7. 7. The gas sensor of claim 6, wherein the thermally conductive material has a thermal conductivity of at least 0.3 W / mK.

8. 8. The gas sensor according to claim 6, wherein the thermally conductive material is a non-conductive material such as silicon nitride, silicon oxide, silicon carbide, or ceramic.

9. The gas sensor according to any one of claims 1 to 8, wherein the heating element is an ohmic heater such as a microhotplate.

10. The gas sensor according to any one of claims 1 to 9, wherein the signal converter is an electronic signal converter, a capacitive signal converter, an optical signal converter or a gravimetric signal converter.

11. 11. The gas sensor of claim 10, wherein the capacitive signal transducer comprises a bottom thermally conductive layer and a top gas-permeable conductive layer, the nanopore-containing layer being disposed between the bottom layer and the top layer.

12. 11. The gas sensor of claim 10, wherein the optical signal converter comprises a bottom reflective or semi-reflective layer and a top reflective or semi-reflective gas-permeable layer, and the nanopore-containing layer is disposed between the bottom layer and the top layer.

13. 11. The gas sensor of claim 10, comprising a gravimetric signal transducer, wherein the layer containing the nanopores is disposed on and in contact with one or more mechanical resonators capable of monitoring a resonant frequency or amplitude.

14. 14. The gas sensor of claim 13, wherein the gravimetric transducer operates in a static mode or a resonant mode.

15. 15. The gas sensor according to claim 13 or 14, wherein the gravimetric transducer is a cantilever resonator or a coupled resonator.

16. 16. The gas sensor of claim 1, wherein the layer containing the nanopore is in direct contact with the transducer.

17. 16. The gas sensor of claim 1, wherein the layer containing the nanopore and the transducer are spatially separated.

18. 20. The gas sensor of claim 17, wherein the transducer is a metal oxide semiconductor sensor.

19. 19. The sensor of claim 1, wherein the gas sensor comprises a plurality of layers containing nanopores, the materials of the layers having different affinities for volatile compounds and / or different diffusion properties for volatile compounds, each of the layers being part of an individual signal transducer.

20. 20. The sensor of claim 19, wherein each of the multiple layers containing the nanopores can be subjected to a distinct temperature regime.

21. 21. The sensor of claim 19 or 20, wherein each of the multiple layers containing the nanopores has a different thickness.

22. 1. A method for determining the presence and / or amount of a plurality of volatile compounds in a gas, comprising: a) introducing a gas into the sensor of any one of claims 1 to 20, allowing compounds in the gas to adsorb within the nanopores of the nanopore-containing layer; b) decreasing or increasing the temperature of the layer containing the nanopores, thereby releasing the adsorbed compounds from the nanopores upon heating or adsorbing the compounds in the nanopores upon cooling; c) measuring the temperature- and time-dependent release and / or adsorption of a compound from or to the nanopore from the signal transducer; d) determining the presence and / or concentration of at least two volatile compounds in the gas based on the measurements of the transducer; A method comprising:

23. 23. The method of claim 22, wherein in step b) the temperature of the layer containing the nanopores is increased, thereby releasing the adsorbed compounds from the nanopores.

24. 24. The method of claim 22 or 23, wherein in step d) the presence and concentration of water in the gas is determined.

25. The method of any one of claims 22 to 24, wherein the temperature of the nanopore-containing layer is periodically perturbed.

26. The method of any one of claims 22 to 25, wherein the adsorption or release of compounds is monitored on a plurality of layers comprising nanopores.

27. 27. The method according to any one of claims 22 to 26, wherein the gas introduced in step a) comprises no more than 50% (v / v), no more than 75% (v / v), or no more than 100% (v / v) water vapour.

28. 28. The method according to any one of claims 22 to 27, wherein the gas introduced in step a) is outside air or building air.

29. 29. The method according to any one of claims 22 to 28, wherein the gas introduced in step a) is animal or human exhaled breath.

30. 30. The method according to any one of claims 22 to 29, wherein the method measures the presence and / or concentration of one or more of 1-propanol, 1-butanol, acetone pentane and hexane in a gas.

31. 31. The method according to any one of claims 22 to 30, wherein the method measures the presence and / or concentration of one or more of 1-propanol, 1-butanol, acetone pentane and hexane in a gas containing water vapour.

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