Multi-frequency sensing system and method

Abstract

The sensor device can include an electrochemical (EC) gas sensor, a metal oxide semiconductor (MOS) gas sensor, and control circuitry. The control circuitry can provide an EC excitation signal to the EC gas sensor and at least two MOS excitation signals to the MOS gas sensor to detect at least two gases. The control circuitry can detect the gases based on providing the EC excitation signal, receiving an EC response signal from the at least one EC gas sensor, providing the MOS excitation signal, receiving a MOS response signal from the MOS gas sensor, determining a multivariate response pattern based on the EC response signal and the MOS response signal, and distinguishing between the at least two gases in contact with the sensor device based on the multivariate response pattern.

Description

[Technical Field]

[0001] Government Licensing Rights This invention was made with government support under Contract No. W15QKN-18-9-1004 awarded by ACC-NJ to the CWMD Consortium. The government has certain rights in this invention.

[0002] Field One or more embodiments are disclosed that relate to systems and methods for detecting gases. [Background technology]

[0003] The gas sensors can be based on sensing materials including metal oxide semiconductor (MOS) materials, dielectric polymers, conducting polymers, nanotubes, metal organic frameworks, graphene, supramolecular compounds and some others.

[0004] Conventional MOS sensors have a relatively narrow dynamic range of measurement due to the nature of the interaction mechanism between the MOS sensing material and the surrounding environment. While MOS materials have been commercially successful due to their widespread use for gas alarms in residential and industrial facilities, readout of MOS materials is traditionally achieved by measuring the material's resistance change as a function of gas concentration. Such a relationship follows a well-known power law, with saturation of the sensor response occurring at high concentrations. Conventional single-output sensors that measure value and / or induction changes in response to changes in resistance, capacitance, current, light intensity, and other changes in a single output are known as zero-order analytical instruments. Summary of the Invention

[0005] In one or more embodiments, a sensor device is described. The sensor device may include an electrochemical (EC) gas sensor, a metal-oxide semiconductor (MOS) gas sensor, and control circuitry. The control circuitry may provide a first excitation signal or signals to the EC gas sensor, a second excitation signal or signals to the MOS gas sensor at a first alternating current (AC) excitation frequency, and a third excitation signal or signals to the MOS gas sensor at a second AC excitation frequency. The control circuitry may detect a first gas (or fluid) based on receiving the first excitation signal or signals in response to providing the first excitation signal or signals to the EC gas sensor and receiving the second excitation signal or signals in response to providing the second excitation signal or signals to the MOS gas sensor. Additionally, the control circuitry may detect a second gas based on receiving the first excitation signal or signals and receiving the third excitation signal or signals in response to providing the third excitation signal or signals to the MOS gas sensor.

[0006] In another embodiment, another sensor device is described. The sensor device can include a metal oxide semiconductor (MOS) gas sensor and control circuitry. The control circuitry can provide a first one or more excitation signals to the MOS gas sensor at a first alternating current (AC) excitation frequency, a second one or more excitation signals to the MOS gas sensor at a second AC excitation frequency, and a third one or more excitation signals to the MOS gas sensor at a third AC excitation frequency, and can detect a first gas, a second gas, and a third gas based on excitation signal responses of the MOS gas sensor in response to providing the first one or more excitation signals, the second one or more excitation signals, and the third one or more excitation signals.

[0007] In yet another embodiment, a method is described. The method is implemented by a processor of a sensor device. The method includes receiving a first control signal indicating sensing one or more gas types (or fluid types), providing a second control signal indicating providing a first excitation signal to a metal-oxide semiconductor (MOS) gas sensor and a second excitation signal to an electrochemical (EC) gas sensor, determining a gas response based on receiving the excitation signal response of the MOS gas sensor, determining a baseline response based on receiving the excitation signal response of the EC gas sensor, and providing a third control signal to one or more output devices indicating detecting at least two gas types and a concentration of at least one of the at least two gas types in contact with the sensor device based on the gas response and the baseline response. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 illustrates a sensor system including at least one metal oxide semiconductor (MOS) gas sensor and at least one electrochemical (EC) gas sensor, according to one embodiment. [Figure 2] FIG. 1 illustrates an exemplary position of a wearable sensor system, according to one embodiment. [Figure 3] 2 illustrates a process for determining one or more gas species, the concentration of at least one of the gas species, or both, by the sensor system of FIG. 1, according to one embodiment. [Figure 4] 2 is a graph depicting an exemplary dynamic response of an EC gas sensor of the sensor system of FIG. 1 in response to a number of different fluids, according to one embodiment. [Figure 5] 2 is a graph depicting an exemplary dynamic response of a MOS gas sensor of the sensor system of FIG. 1 in response to a number of different fluids when applying alternating current (AC) excitation at three different AC excitation frequencies, according to one embodiment. [Figure 6]6 is a graph depicting an exemplary dynamic response of the MOS gas sensor of FIG. 5 in response to several different fluids when stimulated with a single direct current (DC) excitation for comparison, according to one embodiment. [Figure 7A] 1 is a first three-dimensional score plot at a first visualization angle depicting a principal component analysis (PCA) result of a combination of the response of an EC gas sensor and the response of a MOS gas sensor when applying multiple stimuli at different AC excitation frequencies, in accordance with an embodiment of the present technology. [Figure 7B] 10 is a second three-dimensional score plot at a second visualization angle depicting PCA results of the combined response of an EC gas sensor and a MOS gas sensor when applying multiple stimuli at different AC excitation frequencies, in accordance with an embodiment of the present technology. [Figure 8A] 1 is a three-dimensional score plot at a first visualization angle depicting PCA results of the combined response of an EC gas sensor and a MOS gas sensor when applying a DC excitation for comparison, in accordance with an embodiment of the present technology. [Figure 8B] 1 is a three-dimensional score plot at a first visualization angle depicting PCA results of the combined response of an EC gas sensor and a MOS gas sensor when applying a DC excitation for comparison, in accordance with an embodiment of the present technology. [Figure 9] 1 is a dendrogram plot depicting hierarchical cluster analysis (HCA) results of the combined response of an EC gas sensor and a MOS gas sensor when applying multiple stimuli having different AC excitation frequencies, in accordance with an embodiment of the present technology. [Figure 10] 10 is a dendrogram plot depicting HCA results of the combined response of an EC gas sensor and a MOS gas sensor when applying a DC excitation for comparison, in accordance with an embodiment of the present technique; DETAILED DESCRIPTION OF THE INVENTION

[0009] One or more embodiments of the subject matter described herein provide sensing systems and methods that allow for differentiation between different gases.

[0010] 1 is a schematic diagram of one embodiment of a gas sensor 10 (e.g., a sensor system) for multi-gas analysis of a fluid sample in accordance with the present technology. In different embodiments, the gas sensor 10 may be a wearable multi-gas sensor, an ingestible gas sensor for personal (e.g., patient) monitoring, etc. In certain embodiments, the gas sensor 10 may be an industrial environmental sensor, a value monitoring sensor, an industrial process monitoring gas sensor, a consumer sensor, a transportation sensor, a security sensor, or any combination thereof. In further embodiments, the sensor may be part of a wireless sensor network.

[0011] The gas sensor 10 may include an array of sensors 11, control circuitry 14, and one or more output devices 16. The control circuitry 14 includes a measurement circuit 32 and a data processing unit 34. In the depicted embodiment, the array 11 includes electrochemical (EC) sensing elements 12 (e.g., EC sensing elements 12) and metal-oxide-semiconductor (MOS) sensing elements 13 (e.g., MOS sensing elements 13). It should be understood that in alternative or additional embodiments, the array 11 may include any number and / or combination of viable sensors. For example, the array 11 may include, among others, multiple EC gas sensing elements 12, multiple MOS gas sensing elements 13, or any combination of both. MOS gas sensing elements 13 are also known as semiconducting metal oxide (SMOX) gas sensors, and are also known as semiconducting metal oxide (MOX) gas sensors.

[0012] In some embodiments, excitation or dielectric excitation of the MOS gas sensing element 13 refers to alternating current (AC) excitation of the MOS gas sensing element 13 at the shoulder of its dielectric relaxation region. The dielectric excitation or AC excitation of the MOS gas sensing element 13 may be based on including the MOS gas sensing material 23 or another non-MOS sensing material such as a dielectric polymer material, a conductive polymer material, a nanotube material, a nanowire material, a nanoparticle material, a metal-organic framework material, a graphene material, a supramolecular compound material, MXene, which is a two-dimensional inorganic material composed of atomically thin layers of transition metal carbides, nitrides, or carbonitrides, and / or other materials.

[0013] The EC gas sensing element 12 may include a substrate 18, an electrode 20 disposed on the substrate 18, and an EC gas sensing material 22 disposed on the substrate 18 in contact with the electrode 20. The sensor 10 may include, among other sensors, one or more temperature sensors, one or more humidity sensors, and one or more pressure sensors. The measurement circuit 32 may include a voltage controller and a current detector electrically coupled to the electrode 20. The voltage controller may include a direct current (DC) voltage source, an AC voltage source, or both. In certain cases, the DC voltage source may provide an excitation signal to the EC gas sensing element 12, and the AC voltage source may provide an excitation signal to the MOS gas sensing element 13. Thus, the measurement circuit 32 can provide one or more excitation signals (e.g., bias voltages) across the electrode 20 during multi-gas analysis of the fluid 26. Furthermore, the measurement circuit 32 can measure the current response and / or DC response of the EC gas sensing material 22 and the impedance response and / or AC response of the MOS gas sensing material 23.

[0014] The response of the EC gas sensing material 22 can indicate the identity and / or concentration of the gas present in the fluid 26. The current responses (e.g., impedance response, DC response, AC response, among others) of the EC gas sensing element 12 can be collectively and / or interchangeably referred to as one or more excitation responses (or excitation signal responses). The measurement circuitry 32 can distinguish between gases in the fluid 26 by analyzing the excitation response of the EC gas sensing element 12 to the fluid 26.

[0015] Similarly, the MOS gas sensing element 13 may include a substrate 19 and electrodes 24 disposed on the substrate 19. The MOS gas sensing element 13 may include a MOS gas sensing material 23 disposed on the substrate 19 between and / or across the electrodes 24. In some cases, each of the electrodes 24 may include multiple interdigitated sensing electrodes. In such cases, the MOS gas sensing material 23 may generally form a gas sensing film together with the electrodes 24. Thus, dielectric excitation of the MOS gas sensing material 23 and measurement of the dielectric excitation response of the gas sensing material 23 are performed via the electrodes 24. The electrodes 24 of the MOS gas sensing element 13 may be electrically coupled to a measurement circuit 32 or any other possible excitation and measurement circuitry. Thus, the measurement circuit 32 can provide one or more excitation signals to the electrodes 24 and measure the excitation response of the electrodes 24 during multi-gas analysis of a fluid 26. Furthermore, in some cases, the substrate 19 may include a different material compared to the substrate 18 discussed above.

[0016] The excitation response may indicate an induced change to the EC gas sensing material 22 and / or the MOS gas sensing material 23 as a function of gas concentration in the fluid 26. In certain cases, such a relationship may follow a well-known power law, with saturation of the excitation response occurring at high concentrations. Upon receiving the excitation response, the control circuitry 14 may measure the induced change to the EC gas sensing material 22 and / or the MOS gas sensing material 23. For example, the control circuitry 14 may measure current, impedance, real part of impedance, imaginary part of impedance, admittance, reactance, susceptance, capacitance, current, light intensity, or a combination thereof, among other excitation responses. As used herein, "impedance" is a non-limiting term for measuring an induced change to an excitation signal when measuring an excitation response.

[0017] The data processing unit 34 can apply transfer functions, multiplication factors, look-up tables, models, among other things, to data collected from the impedance and / or DC responses of the EC gas sensing material 22 to identify one or more gases and / or concentrations of gases present in the fluid 26. In some cases, the control circuitry 14 can include circuitry to detect multiple gases in the fluid 26 by performing measurements under AC and / or DC measurement conditions and / or impedance measurement conditions. Thus, the control circuitry 14 can determine the gases (and / or concentrations of gases) present in the fluid sample 26 based on the measured responses of the EC gas sensing element 12 and the MOS gas sensing element 13 by the measurement circuitry 32.

[0018] With the above in mind, measurement circuitry 32 can provide excitation signals to electrodes 20 of EC gas sensing element 12 and electrodes 24 of MOS gas sensing element 13 simultaneously, relatively closely together, or at different times to perform multi-gas analysis of fluid 26. In some cases, the excitation response of EC gas sensing element 12 may be more stable over time and under various environmental conditions, while MOS gas sensing element 13 can receive excitation signals (e.g., stimuli) and return excitation responses at multiple frequencies (multiple frequency ranges). For example, EC gas sensing element 12 may be less susceptible to corrosion or environmental damage.

[0019] Therefore, in some embodiments, the data processing unit 34 can generate a baseline response (e.g., a relatively constant response, a relatively stable response) based on the excitation response of one or more of the EC gas sensing elements 12. Furthermore, the data processing unit 34 can generate a gas response by correcting the excitation response of one or more of the MOS gas sensing elements 13 at one or more frequencies based on the generated baseline response. For example, the data processing unit 34 can reduce baseline drift of the gas response by correcting the excitation response of the MOS gas sensing element 13 based on the excitation response of the EC gas sensing element 12.

[0020] The measurement circuit 32 can provide AC excitation signals to the MOS gas sensing material 23 at one or more preselected frequencies (e.g., a preselected frequency range). The preselected frequencies can include one or more frequencies selected based on empirical and / or simulated sensor response data to perform multi-gas analysis of the fluid 26. For example, the preselected frequencies can include the frequency of a shoulder of the dielectric relaxation region of the MOS sensing material 23. Furthermore, the measurement circuit 32 can monitor the excitation response (or gas-modulated excitation signal) of the MOS gas sensing material 23 at the preselected frequencies. In certain embodiments, the measurement circuit 32 can additionally or alternatively provide one or more DC excitation signals to the MOS gas sensing material 23 and measure the DC response (e.g., resistance response) of the MOS gas sensing material 23 to these excitations.

[0021] In some embodiments, the measurement circuitry 32 can provide multiple excitation signals at multiple preselected frequencies (e.g., frequency ranges) to the MOS sensing material 23. For example, the excitation response of the MOS sensing material 23 can be monitored at, among other frequencies, a gas-modulated high-frequency shoulder of the dielectric relaxation peak of the MOS sensing material 23 and a gas-modulated low-frequency shoulder of the dielectric relaxation peak of the MOS sensing material 23. In such embodiments, the measurement circuitry 32 can include circuitry for receiving the multiple excitation responses of the MOS sensing material 23 at multiple preselected frequencies.

[0022] Additionally, measurement circuitry 32 may measure one or more parameters of the excitation response at multiple preselected frequencies. The one or more parameters may include changes induced by measuring impedance at different frequencies, changes induced by the temperature of sensing elements 12 and / or 13, and / or changes induced by UV or visible light applied to the sensor (known as photoactivation). Determining such induced changes in the multiple excitation responses can indicate the gas and / or gas concentration in fluid 26.

[0023] For example, measurement circuitry 32 may measure such parameters based on comparing the excitation response to a corresponding excitation signal. Additionally, different operating parameters may be selected for different sensor arrays 10 and / or based on the application of the sensor array 10. Additionally, in different embodiments, measurement circuitry 32 may monitor and / or determine different numbers and / or combinations of operating parameters.

[0024] The gas sensor 10 may represent one or more different versions of the multi-gas sensing system described herein. In one or more embodiments, the measurement circuit 32 may include multiple resistor-capacitor (RC) circuits for measuring induced impedance changes of multiple multiple excitation responses. Each of the RC circuits may include one or more resistors (R) and / or capacitors (C). In certain embodiments, one or more of the RC circuits may include one or more variable resistors and / or capacitors. In such embodiments, the data processing unit 34 may electronically control the values ​​of the variable resistors and / or capacitors of the RC circuits. For example, the data processing unit 34 may control the values ​​of the variable resistors and / or capacitors based on a desired frequency for generating and / or measuring the excitation signal. Additionally, in some cases, the data processing unit 34 may control the values ​​of the variable resistors and / or capacitors based on one or more analyte gases of interest.

[0025] Thus, measurement circuit 32 can generate and provide multiple excitation signals to MOS gas sensing material 23 and measure the multiple excitation responses of MOS gas sensing material 23 at multiple frequencies. In either case, measurement circuit 32 is not designed to be affected by the gas concentration being measured. Rather, only EC sensing element 12 and MOS gas sensing element 13 are designed to be predictably affected by the gas concentration being measured.

[0026] The data processing unit 34 can receive the excitation response (e.g., data bits, digital response (counts), analog response) measured by the measurement circuit 32. The data processing unit 34 can include, among other things, an on-board data processor 36 and a memory 38. The memory 38 can store gas analysis models 40, such as a gas classification model 42 and a gas quantification model 44. These gas analysis models 40 are generally mathematical models that store a relationship between an excitation response (e.g., a dielectric excitation response) and a particular classification or concentration of a gas in the fluid 26. For example, the gas classification model 42 can store a relationship between the excitation response of the EC gas sensing material 22 and / or the MOS gas sensing material 23 and a particular classification of a gas.

[0027] Additionally, the gas quantification model 44 may store a relationship between the excitation response of the EC gas sensing material 22 and / or the MOS gas sensing material 23 and a particular concentration of a gas. In certain embodiments, the gas analysis model 40 may include one or more coefficients having values ​​that are experimentally determined (e.g., empirical data, simulation data, among others) and stored in the memory 38. In some embodiments, the number of analyte gases determined by the gas classification model 42, or the gas quantification model 44, or any combination thereof, for the illustrated gas sensor 10 may range from two analyte gases to fifty analyte gases.

[0028] A gas sensor that provides two or more excitation responses or outputs is called a multivariable gas sensor. The data processing unit 34 can apply multivariate data processing principles to analyze the output from the multivariable gas sensor. For example, the data processing unit 34 can apply multivariate data processing principles to the output signal to determine one or more multivariate response patterns. Thus, the data processing unit 34 can quantify the diversity of the multivariable sensor's response to different gases. In some cases, a multivariate transfer function can be constructed to quantify the different gases. The constructed multivariate transfer function can be implemented to quantify the different gases in new measurement data from the multivariable gas sensor.

[0029] Non-limiting examples of multivariate data processing principles include methods for performing gas classification / cluster analysis and quantification. Classification / cluster analysis can be performed to accurately determine the type of analyte gas. Quantification can be performed to accurately determine the concentration of the analyte gas. Examples of classification / cluster analysis algorithms include, but are not limited to, principal component analysis (PCA), hierarchical cluster analysis (HCA), independent component analysis (ICA), linear discriminant analysis (LDA), and support vector machine (SVM) algorithms. Non-limiting examples of methods for performing analyte quantification to determine the concentration of a specific analyte gas include principal component regression (PCR), independent component regression (ICR), nonlinear regression analysis (NRA), discriminant function analysis (DFA), support vector regression (SVR), or artificial neural network analysis (ANN). In certain embodiments of the inventive subject matter described herein, a classification algorithm can be followed by a quantification algorithm.

[0030] As discussed below, the onboard data processor 36 can receive the excitation responses measured by the measurement circuitry 32, select a particular excitation response, and provide the selected excitation response as an input to one or more of the stored gas analysis models 40 for analysis. The gas analysis models 40 can return an output that resolves or distinguishes between two or more gases in the fluid 26. As used herein, "resolving" two or more gases in the fluid 26, "providing resolution" between two or more gases in the fluid 26, "distinguishing" two or more gases in the fluid 26, or "providing discrimination" between two or more gases in the fluid 26 refers to determining the respective classification for each of the gases in the fluid 26, determining the respective concentrations of the gases in the fluid 26, or determining both the respective classification and the respective concentrations of the gases in the fluid 26. As used herein, "classifying" or "determining the classification" of a gas refers to determining the chemical identity of a gas (e.g., ethanol, acetone, hydrogen, carbon monoxide, methane, toluene, benzene, among other chemical gas identities) or determining the chemical class to which each gas belongs (e.g., hydrocarbons, oxides, sulfides, ketones, aromatic hydrocarbons, etc.).

[0031] For example, the fluid 26 may be in the form of a fluid container, which may be in the form of a container having a controlled volume, or in the form of an open area such as an indoor facility (e.g., a room, hall, house, school, hospital, confined space, etc.), or in the form of an outdoor facility (e.g., a stadium, gas production site, fuel injection station, gasoline fuel injection station, hydrogen fuel injection station, compressed natural gas fuel injection station, liquefied natural gas fuel injection station, gas distribution site, fuel distribution site, beach, forest, city, urban environment, marine environment, battlefield environment, etc.). In one embodiment, the gas sensor 10 can provide continuous monitoring of the fluid 26 in a reservoir or flow path. In one or more embodiments, the gas sensor 10 may be an impedance gas sensor, an electromagnetic sensor, an electronic sensor, a hybrid sensor, or another type of sensor. The gas sensor 10 may be a sensor array.

[0032] Fluid 26 can include, for example, a gas, a liquid, a gas-liquid mixture, a solid material, particles or particulate matter, etc., including one or more gases, including an analyte gas and / or an interfering gas. In another embodiment, fluid 26 can be a gas or fuel, such as a hydrocarbon-based fuel. For example, fluid 26 can be natural gas or hydrogen gas supplied to a powered system (e.g., a manned vehicle, an unmanned vehicle, an aircraft engine, or a stationary generator set) for consumption. Furthermore, fluid 26 can include gasoline, diesel fuel, jet fuel or kerosene, biofuel, petroleum diesel-biodiesel fuel blends, natural gas (liquid or compressed), and / or fuel oil. In other embodiments, fluid 26 can be a sample of indoor or outdoor ambient air. For example, the sample can be from an industrial, residential, military, construction, urban, or any other known location. Additionally, ambient air samples may contain relatively low concentrations of chemical agents such as benzene, naphthalene, carbon monoxide, ozone, formaldehyde, nitrogen dioxide, sulfur dioxide, ammonia, hydrofluoric acid, hydrochloric acid, phosphine, ethylene oxide, carbon dioxide, hydrogen sulfide, nerve agents, blister agents, blood agents and asphyxiant agents, hydrocarbons and / or other environmental agents.

[0033] In other embodiments, fluid 26 may be a disinfectant such as an alcohol, an aldehyde, chlorine dioxide, hydrogen peroxide, or the like. In other embodiments, fluid 26 may contain relatively low, moderate, and / or high concentrations of flammable gases, such as methane, ethane, propane, butane, hydrogen, and / or other gases, mixed with ambient air from around gas sensor 10. The ambient air may have certain measurable or identifiable characteristics, such as relative humidity, temperature, barometric pressure, concentrations of other gases, or the like. In further embodiments, fluid 26 may include at least one gas dissolved in an industrial liquid, such as transformer oil, bioprocessing media, fermentation media, wastewater, or the like. Fluid 26 may also include at least one gas dissolved in a consumer liquid, such as milk, non-alcoholic beverages, alcoholic beverages, cosmetics, or the like. In other embodiments, fluid 26 may include at least one gas dissolved in a bodily fluid, such as blood, sweat, tears, saliva, urine, feces, bile, or the like.

[0034] In certain embodiments, fluid 26 may include an analyte gas that is a toxic industrial material or a toxic industrial chemical. A non-limiting list of exemplary toxic industrial materials and chemicals includes, but is not limited to, ammonia, arsine, boron trichloride, boron trifluoride, carbon disulfide, chlorine, diborane, ethylene oxide, fluorine, formaldehyde, hydrogen bromide, hydrogen chloride, hydrogen cyanide, hydrogen fluoride, hydrogen sulfide, nitric acid (fume), phosgene, phosphorus trichloride, sulfur dioxide, sulfuric acid, and tungsten hexafluoride.

[0035] Additionally, in certain embodiments, fluid 26 may include an analyte gas that is a toxic material with a moderate hazard quotient. A non-limiting list of exemplary toxic materials with a moderate hazard quotient includes, for example, acetone cyanohydrin, acrolein, acrylonitrile, allyl alcohol, allylamine, allyl chlorocarbonate, boron tribromide, carbon monoxide, carbonyl sulfide, chloroacetone, chloroacetonitrile, chlorosulfonic acid, diketene, 1,2-dimethylhydrazine, ethylene dibromide, hydrogen selenide, methanesulfonyl chloride, methyl bromide, methyl chloroformate, methylchlorosilane, methylhydrazine, methyl isocyanate, methyl mercaptan, nitrogen dioxide, phosphine, phosphorus oxychloride, phosphorus pentafluoride, selenium hexafluoride, silicon tetrafluoride, stibine, sulfur trioxide, sulfuryl chloride, sulfuryl fluoride, tellurium hexafluoride, n-octyl mercaptan, titanium tetrachloride, trichloroacetyl chloride, and trifluoroacetyl chloride.

[0036] Fluid 26 may include an analyte gas that is a "high" hazard quotient toxic material. A non-limiting list of exemplary high hazard quotient toxic materials may include, for example, ammonia, arsine, boron trichloride, boron trifluoride, carbon disulfide, chlorine, diborane, ethylene oxide, fluorine, formaldehyde, hydrogen bromide, hydrogen chloride, hydrogen cyanide, hydrogen fluoride, hydrogen sulfide, nitric acid, fumes, phosgene, phosphorus trichloride, sulfur dioxide, sulfuric acid, and tungsten hexafluoride.

[0037] In certain embodiments, fluid 26 may include an analyte gas that is a toxic material with a low hazard index. A non-limiting list of exemplary toxic materials with a low hazard index includes allyl isothiocyanate, arsenic trichloride, bromine, bromine chloride, bromine pentafluoride, bromine trifluoride, carbonyl fluoride, chlorine pentafluoride, chlorine trifluoride, chloroacetaldehyde, chloroacetyl chloride, crotonaldehyde, cyanogen chloride, dimethyl sulfate, diphenylmethane-4,40-diisocyanate, ethyl chloroformate, ethyl chlorothioformate, ethyl phosphonate dichloride, ethyl phosphonate dichloride, ethyleneimine, and hexachlorocyclopentadiene. Analyte gases include, but are not limited to, hydrogen iodide, iron pentacarbonyl, isobutyl chloroformate, isopropyl chloroformate, isopropyl isocyanate, n-butyl chloroformate, n-butyl isocyanate, nitric oxide, n-propyl chloroformate, parathion, perchloromethyl mercaptan, sec-butyl chloroformate, tert-butyl isocyanate, tetraethyl lead, tetraethyl pyrophosphate, tetramethyl lead, toluene 2,4-diisocyanate, and toluene 2,6-diisocyanate. Analyte gases may also include a range of indoor environmental agents, such as acetaldehyde, formaldehyde, 1,3-butadiene, benzene, chloroform, methylene chloride, 1,4-dichlorobenzene, perchloroethylene, trichloroethylene, naphthalene, and polycyclic aromatic compounds, as well as outdoor environmental agents, such as ozone, nitrogen dioxide, sulfur dioxide, and carbon monoxide. Additionally, analyte gases may include industrial agents, such as flammables, confined space hazards, and the like.

[0038] In certain embodiments, fluid 26 may include an analyte gas that is an indoor pollutant. A non-limiting list of exemplary indoor pollutants includes, but is not limited to, acetaldehyde, formaldehyde, 1,3-butadiene, benzene, chloroform, methylene chloride, 1,4-dichlorobenzene, perchloroethylene, trichloroethylene, naphthalene, and polycyclic aromatic compounds. In certain embodiments, fluid 26 may include an analyte gas that is an outdoor pollutant. A non-limiting list of exemplary outdoor pollutants includes, but is not limited to, ozone, nitrogen dioxide, sulfur dioxide, and carbon monoxide.

[0039] Embodiments of the gas sensor 10 have the ability to distinguish between different concentrations of gas in the fluid 26. For example, the gas sensor 10 can distinguish between analyte gases at regulated vapor exposure limits established by different organizations. In certain embodiments, the gas sensor 10 can degrade analyte gases below the permissible exposure limit (PEL). In some embodiments, the gas sensor 10 can degrade analyte gases below the threshold limit short-term exposure limit (TLV-STEL). In some embodiments, the gas sensor 10 can degrade analyte gases below the threshold limit time-weighted average (TLV-TWA). In some embodiments, the gas sensor 10 can degrade analyte gases below concentrations immediately dangerous to life or health (IDLH). In certain embodiments, the gas sensor 10 can degrade analyte gases below and above the lower explosive limit (LEL). In certain embodiments, the gas sensor 10 may be capable of decomposing gases having concentrations of less than 5%, less than 100 parts per million (ppm), less than 100 parts per billion (ppb), or less than 100 parts per trillion (ppt).

[0040] In either case, in some embodiments, the memory 38 may be integrated into the on-board data processor 36. Furthermore, in some alternative or additional embodiments, the on-board data processor 36 may include a multi-core processor. For example, the on-board data processor 36 may include a multi-core processor on a single integrated circuit having two or more separate processing units (also referred to as cores), each capable of reading and executing program instructions. In further alternative or additional embodiments, the multi-core processor may include only a single central processing device (CPU) and multiple additional cores. In embodiments in which the on-board data processor 36 is a multi-core processor, different gas analysis models and / or different signal processing algorithms may be executed independently by different cores to reduce power consumption of the data processing unit 34 and / or the gas sensor 10.

[0041] In the illustrated embodiment, the gas sensor 10 may also include one or more output devices 16. In some embodiments, the output device 16 includes one or more display devices 46 configured to present information regarding the multi-gas analysis. For example, the display device 46 may display the classification and / or concentration of two or more gases in the fluid 26. In alternative or additional embodiments, the output device 16 may include an alarm 49, such as a visual alarm (e.g., a light-emitting diode (LED)), an audible alarm (e.g., a speaker), and / or a tactile alarm (e.g., a tactile feedback device).

[0042] Alternatively or additionally, the output device 16 may include one or more communication devices 48 (e.g., wired communication interface, wireless communication interface) that may enable the gas sensor 10 to communicate with other computing systems, such as a desktop computer, a mobile computing device (e.g., laptop, smartphone), a remote server (e.g., internet server, cloud server), or other sensors (e.g., gas sensors, temperature sensors, vibration sensors, health monitors) of a multi-sensor monitoring system. For example, in some embodiments, information determined by the on-board data processor 36 regarding the differentiation of two or more gases in the fluid 26 may be provided to an external computing system that acts as a controller for the mesh of sensors that includes the gas sensor 10. In some embodiments, the gas sensor 10 may additionally or alternatively use the communication device 48 to provide excitation-response measurements to the external computing system, which can then use these measurements to calculate one or more coefficient values ​​for one or more of the gas analytical models and return these coefficient values ​​to the gas sensor 10 for storage in the memory 38.

[0043] Additionally, the illustrated gas sensor 10 includes a battery 50 electrically coupled to and powering the various components of the gas sensor 10. In the depicted embodiment, the battery 50 is coupled to the control circuitry 14 and the output device 16. It can be appreciated that the battery 50 should have an electrical energy storage capacity suitable for powering all of the components of the gas sensor 10 coupled thereto. For example, the battery 50 can include sufficient electrical energy storage capacity to heat the gas sensing material 22, provide a DC excitation to the EC gas sensing material 22, provide an inductive / AC excitation to the MOS gas sensing material 23, measure the excitation responses of the gas sensing materials 22 and 23, analyze the measured excitation responses to distinguish between two or more gases in the fluid 26, and present the results of the analysis via the output device 16.

[0044] In certain embodiments, the battery 50 may have a capacity sufficient to operate the gas sensor 10 for at least 6 hours, 10 hours, 15 hours, 24 hours, 48 ​​hours, etc. In some embodiments, the battery 50 may have a battery capacity of 1 milliamp-hour (mAh) to 50,000 mAh, 1 mAh to 10,000 mAh, or 1 mAh to 100 mAh. In certain embodiments, such as embodiments in which the gas sensor 10 is designed to be particularly thin (e.g., for ingestible or tattooed embodiments of the gas sensor 10), the battery 50 may have a thickness of less than about 5 millimeters (mm). In some embodiments, all of the components of the gas sensor 10 may be coupled to, or at least partially disposed within, a package or housing suitable for a particular gas sensing application. For example, for personal monitoring applications, the packaging of the gas sensor 10 may be made of a biocompatible polymer that can be worn externally, injected subcutaneously, or ingested to perform multi-gas analysis of an individual or patient.

[0045] The gas sensor 10 may be a wearable device that can be worn or moved by an operator from one location to another. The gas sensor 10 may be positioned within or be an integrated part of a helmet, hat, glove, or other clothing attribute. For example, the gas sensor 10 may be held within a wearable or non-wearable transportable object, such as a military or industrial eyeglass frame, a wearable pulse oximeter, a safety vest or harness, clothing, a mobile device (e.g., a cell phone, a tablet, etc.). The wearable device may be integrated into the fabric of the clothing, positioned on the clothing, such as on a pocket, in the form of an armband, worn on the wrist or other limb, etc. The wearable device may be worn by a subject, such as a human, animal, or robot. The wearable device may be removably coupled to or integrated with an article worn by the subject (e.g., a shirt, pants, safety vest, protective clothing, glasses, hat, helmet, hearing device, etc.), or may be any alternative device that may be stationary or substantially stationary, that may be transportable so that the sensor can be moved between different locations, etc.

[0046] The wearable device may be worn or carried by different subjects or individuals, such as, but not limited to, soldiers, medical professionals, athletes, system operators, students, and other active or inactive individuals. Optionally, the wearable sensing system may be coupled to, integrated with, disposed on, or the like, an object of value, such as a mobile system such as a drone, a stationary system, or the like. The wearable system may be positioned on an item worn by the subject, such as a helmet, a pocket (e.g., of a shirt, pants, bag, etc.), a glove, an armband, an earpiece, or the like, or may be directly attached to or otherwise coupled to the object or object of value, such as around the wrist, ankle, or the like. The wearable device may be fabricated using manufacturing techniques based on complementary metal-oxide semiconductor electronics, flexible electronics, flexible hybrid electronics, and other known approaches to providing conformal and flexible design, implementation, and use. Optionally, the gas sensor 10 may be a stationary device, independently movable (e.g., detachable from and capable of moving independently of the operator), airborne, or the like.

[0047] In one or more embodiments, the gas sensor 10 may be a handheld sensor system. In one or more embodiments, the gas sensor 10 may be a wearable sensor system, may be held within a wearable and / or non-wearable transportable object (e.g., the frame of military or industrial eyeglasses), etc. A wearable device may be worn by a subject, such as a human or animal, may be removably coupled to or integrated with an article worn by the subject (e.g., a shirt, pants, safety vest, protective clothing, glasses, hat, helmet, hearing device, etc.), or may be any alternative device that may be stationary or substantially stationary, that may be transportable so that the sensor can be moved between different locations, etc. FIG. 2 illustrates exemplary locations of different wearable gas sensors 10. In the illustrated embodiment of FIG. 2, the subject is a human subject, but the subject may also be a mammalian subject, a plant subject, etc.

[0048] 2 illustrates exemplary locations of different gas sensors 10. In the exemplary embodiment of FIG. 2, several exemplary implementations of the gas sensor 10 are illustrated relative to a human subject and a drone. However, FIG. 2 depicts only some implementations of the gas sensor 10, and in alternative cases, the subject may be different, such as a mammalian subject, a plant subject, etc.

[0049] In one or more embodiments, the gas sensor 10 may be a wearable device worn by a subject, such as a human or animal. Specifically, FIG. 2 illustrates non-limiting examples of positions for a gas detection system for detecting a combustible gas or any other target gas or vapor using a single gas sensor 10. FIG. 2 demonstrates various positions in which the wearable gas sensor 10 may be worn. For example, the wearable gas sensor 10 may be worn directly on the subject's body. Alternatively, the wearable gas sensor 10 may be removably coupled to or integrated into an article worn by the subject. For example, as illustrated in FIG. 2, the wearable gas sensor 10 may be worn on military or industrial headgear, on a shirt sleeve, or on the front of a shirt, jacket, or vest.

[0050] Additionally, the wearable gas sensor 10 may be worn on the hand or wrist, either directly on the body or integrated into a glove, as depicted in FIG. 2 . Alternatively, the wearable gas sensor 10 may be removably coupled to or integrated with a non-wearable, transportable object, such as an unmanned vehicle, e.g., on an unmanned ground or airborne or other vehicle. In this manner, the wearable gas sensor 10 may be coupled to or integrated with any alternative object or device that may be transportable, such that the gas sensor 10 can be moved between different locations, may be stationary or substantially stationary, etc. Although not shown in FIG. 2 , the wearable sensor may also be removably coupled to or integrated with eyeglasses, pants, safety vests, safety suits, hats, hearing devices, or any other wearable device or garment. In the illustrated embodiment of FIG. 2 , the subject is a human subject, but the subject may also be a mammalian subject, a plant subject, a robotic subject, etc.

[0051] 3 illustrates a process 80 for multi-gas detection operation of a gas sensor 10 including at least one EC gas sensing element 12 and at least one MOS gas sensing element 13. While the process 80 is described in a particular order, the process blocks may be performed in any other operable order. Furthermore, the process 80 is provided as an example, and it should be understood that in alternative or additional embodiments, the gas sensor 10 may perform additional, reduced, and / or different operations. Furthermore, although operations are described as being performed by an onboard data processor 36, hereafter processor 36, the operations may be performed by any other onboard or external executable processing circuitry. While the operation of one MOS gas sensing element 13 and one EC gas sensing element 12 is described, the processor 36 may provide similar control signals to, receive responses from, and / or perform operations differently on multiple MOS gas sensing elements 13 and / or multiple EC gas sensing elements 12.

[0052] At block 82, processor 36 may receive a control signal indicating detection of one or more gas types (or fluid types) and gas concentrations of at least one of the gas types in fluid 26. In some cases, processor 36 may receive the control signal stored in memory 38 (e.g., one or more look-up tables) or from any other possible source. In some embodiments, the control signal may indicate detection of each gas type or different gas types by providing stimulus signals at different frequencies to MOS gas sensing element 13. For example, each gas type may be associated with performing measurements by providing stimulus within one or more particular frequency ranges.

[0053] In block 84, the processor 36 may receive a control signal indicating context information. For example, the context information may indicate one or more operating parameters of the gas sensor and one or more values ​​of each of the operating parameters. The operating parameters may include measuring / monitoring changes in one or more dependent and / or independent parameters of the sensor response. For example, the gas sensor 10 may include a temperature controller (e.g., a heater) for varying the temperature of the MOS gas sensing element 13 (e.g., sweeping the temperature, scanning the temperature) during operation. Additionally, the operating parameters may include, among others, the real and / or imaginary parts of the impedance of the sensor response, frequency, and temperature. In some embodiments, the MOS gas sensing element 13 may monitor each of the operating parameters at multiple frequencies or frequency ranges.

[0054] In some embodiments, upon receiving data bits (or analog signals) from the measurement circuit 32, the processor 36 can apply context inputs to select an expected application scenario based on the gas response. Non-limiting examples of context inputs may include the intended use of the sensor as a particular wearable device or permanent installation. The context inputs may also include the expected gas concentration in a particular environment, or the concentration of an analyte gas that an operator may need to detect to ensure the environment is safe for occupancy. Other context inputs may include the geographic area of ​​sensor use, its location based on global positioning system coordinates, the location of a particular region or city, and the altitude at a particular location. Other context inputs may include the type of sensing material used or the type of analyte gas being measured. For example, a first set of operating parameters may be selected based on the context input. The first set of operating parameters may include a selected operating voltage of the heating element of the gas sensor 10, two or more frequencies of dielectric excitation, and a selected capacitance of one or more capacitors of the measurement circuit 32.

[0055] The context information may also include one or more preselected (e.g., known) values ​​for one or more of the selected operating parameters. In some embodiments, the preselected values ​​may include a range of variation for one or more of the operating parameters for determining a gas type (or class) and / or gas concentration. In alternative or additional embodiments, the preselected values ​​may include a threshold gas concentration value for performing a subsequent action. For example, the subsequent action may include issuing an alarm above / below a threshold concentration of one or more particular gas types. It should be understood that such context information may be application-specific, and the gas sensor 10 may include / receive different context information for different applications of the gas sensor 10.

[0056] In block 86, the processor 36 may provide control signals for operating one or more MOS gas sensing elements 13 and one or more EC gas sensing elements 12. As previously discussed, operating the MOS gas sensing elements 13 at multiple frequencies may provide the processor 36 with additional information for determining multiple gas types with a single sensor (or array of sensors). Thus, in some embodiments, the processor 36 may provide control signals to one or more MOS gas sensing elements 13 at multiple frequencies, as will be appreciated.

[0057] The baseline response of the sensor 10 is the response in a clean environment (e.g., in contact with a clean carrier gas) without the presence of the measured gas(es) (e.g., fluid 26). The baseline response of the sensor 10 is composed of the baseline response of one or more EC gas sensing elements 12 and the baseline response of one or more MOS gas sensing elements 13. During operation, the baseline response values ​​of the EC gas sensing element 12 and the MOS gas sensing element 13 may undesirably change. Such changes in the baseline response may result in reduced accuracy of the classification and quantification results. Therefore, the baseline response of the EC gas sensing element 12 can be used to correct the baseline response of the MOS gas sensing element 13.

[0058] For example, the processor 36 may correct the baseline response of the MOS gas detection element 13 by tracking deviations of the baseline response of the MOS gas detection element 13 from the baseline response of the EC gas detection element 12. Further, the processor 36 may apply a correction factor to eliminate such deviations of the baseline response of the MOS gas detection element 13. For example, the processor 36 may retrieve a correction factor from a plurality of correction factors stored in the memory 38 based on tracking deviations of the baseline response of the MOS gas detection element 13 from the baseline response of the EC gas detection element 12. Alternatively or additionally, the processor 36 may determine (e.g., calculate) the correction factor based on tracking deviations of the baseline response of the MOS gas detection element 13 from the baseline response of the EC gas detection element 12. Illustrative examples of the correction factor may include, among others, univariate baseline subtraction between the response of the EC gas detection element 12 and the response of the MOS gas detection element 13, multivariate baseline subtraction between one or more responses of the EC gas detection element 12 and the response of the MOS gas detection element 13.

[0059] With the above in mind, in block 88, the processor 36 may determine a gas response based on receiving responses from one or more MOS gas sensing elements 13 and may determine a baseline response based on receiving responses from one or more EC gas sensing elements 12. For example, the processor 36 may determine a baseline response based on receiving responses from one or more auxiliary environmental sensors, such as a temperature sensor, a humidity sensor, or a pressure sensor, among other sensors. Additionally, the processor 36 may determine the gas response based on receiving data bits (or analog signals) from the measurement circuit 32. Furthermore, in different embodiments, the processor 36 may determine the gas response of the MOS gas sensing element 13, the EC gas sensing element 12, or both at a specific time (e.g., an instance), consecutive instances (e.g., periodically), or continuously. For example, the EC gas sensing element 12 may collect data over a period of time using amperometry, cyclic voltammetry, chronoamperometry, or any other viable EC sensor measurement method.

[0060] In block 90, the processor 36 may monitor one or more operating parameters of the gas response based on the baseline response to reduce baseline drift of the gas response. As previously described, the EC gas detection element 12 may be prone to drifting responses over time. Therefore, the processor 36 may reduce baseline drift of the MOS gas detection element 13 (at one or more frequencies) based on the baseline response of the EC gas detection element 12. It should be further understood that monitoring may include, among other things, determining or calculating based on the received formula and comparing with respect to one or more of the received operating parameters and their respective values. In either case, as previously described, the processor 36 may correct the baseline response of the MOS gas detection element 13 by tracking deviations of the baseline response of the MOS gas detection element 13 from the baseline response of the EC gas detection element 12.

[0061] In block 92, processor 36 may provide a control signal indicating one or more gas types and / or one or more concentrations of at least one of the gas types based on responses received from sensing elements 12 and / or 13 and from the contextualized input. Additionally, or alternatively, processor 36 may generate a control signal indicating implementing one or more response actions. The response actions may include generating one or more alerts, initiating specific treatment or decontamination of the object having the sensor device, optimizing logistics steps after learning about the detected concentration of the gas, minimizing logistics steps after learning about the detected concentration of the gas, initiating an emergency response, or a combination thereof. Furthermore, the response actions may respond, among other things, to the detection of higher / lower threshold concentrations of one or more of the gas types. Furthermore, in some embodiments, processor 36 may provide a control signal indicating one or more gas types and / or one or more concentrations of at least one of the gas types at a specific time (e.g., instance), consecutive instances (e.g., periodically), or continuously.

[0062] For example, information from the readings of the MOS gas sensing element 13 and the EC gas sensing element 12 can be implemented for informational purposes. Informational purposes can include visual, acoustic, and / or tactile alarms, or any other known alarms. The MOS gas sensing element 13 and the EC gas sensing element 12 can be used to generate or trigger an alarm for the gas sensor 10. The alarm can be transmitted to a central station or to another gas sensor 10 having a similar or different MOS gas sensing element 13 and / or EC gas sensing element 12. The alarm can be in the form of quantitative information, such as the concentration of the detected gas. The alarm can be in the form of semi-quantitative information, such as a binned level of the detected gas, e.g., three bins, such as yellow, orange, and red alarm levels. The alarm can be in the form of qualitative information, such as an alarm regarding the detected gas exceeding a predetermined threshold concentration of the gas.

[0063] With the above in mind, FIG. 4 illustrates a graph 100 depicting a first EC response signal 102 of a first EC gas sensing element 12-1 and a second EC response signal 104 of a second EC gas sensing element 12-2. For example, the array 11 of FIG. 1 may include a first EC gas sensing element 12-1 and a second EC gas sensing element 12-2. Furthermore, the measurement circuit 32 described above may generate a stimulus signal over time 106. Furthermore, the first EC response signal 102 and the second EC response signal 104 may represent the current response of the EC gas sensing elements 12-1 and 12-2. The EC gas sensing elements 12-1 and 12-2 may generate a current proportional to the concentration of the gas being detected. The gas is measured at the respective electrodes 20. In some embodiments, the EC gas sensing elements 12-1 and / or 12-2 may include a counter electrode to complete the electrical circuit of their respective sensor cells. The processor 36 may apply (or provide control signals to apply) voltages (e.g., one or more stimulus signals) to each electrode 20 to provide a bias voltage or bias potential for the EC gas sensing elements 12-1 and / or 12-2.

[0064] The first EC response signal 102 and the second EC response signal 104 may each include different responses to different gases (e.g., fluid patterns 108, 110, 112, and 114). For example, the first EC gas sensor sensing element 12-1 and the second EC gas sensing element 12-2 may be exposed to a first fluid for a first period 116, a second fluid for a second period 118, a third fluid for a third period 120, and a fourth fluid for a fourth period 122. Fluids 1-4 in FIG. 4 may include, among other fluids, nitrogen dioxide (NO), carbon monoxide (CO), diesel exhaust, and hydrogen sulfide (HS). As shown in FIG. 4, each fluid may be presented to the sensor at three increasing concentrations. The analyte gases of interest were nitrogen dioxide (Fluid 1), carbon monoxide (Fluid 2), and hydrogen sulfide (Fluid 4). The interferent was diesel exhaust (Fluid 3). The purpose of sensor 10 was to distinguish between the analyte gases (Fluids 1, 2, and 4) and the interferent gas (Fluid 3).

[0065] In either case, as previously described, the EC gas sensing elements 12, such as the first EC gas sensing element 12-1 and the second EC gas sensing element 12-2, may provide more stable response signals 102 and 104 based on their lower susceptibility to drift over time. Therefore, in some embodiments, the measurement circuit 32, the data processing unit 34, or both, may determine the response signals 102 and 104 of the first EC gas sensing element 12-1 and the second EC gas sensing element 12-2 in the absence of fluids 1-4 as baseline signals. Therefore, the measurement circuit 32, the data processing unit 34, or both, may correct the baseline response of the MOS gas sensing element 13 based on the response signals 102 and 104 of the first EC gas sensing element 12-1 and the second EC gas sensing element 12-2.

[0066] 5 illustrates a graph 140 depicting multiple MOS response signals of each of the first MOS gas sensing element 13-1 and the second MOS gas sensing element 13-2 of the array 11. In particular, the graph 140 includes a first MOS response signal 142, a second MOS response signal 144, and a third MOS response signal 146 of the first MOS gas sensing element 13-1. The graph 140 also includes a fourth MOS response signal 148, a fifth MOS response signal 150, and a sixth MOS response signal 152 of the second MOS gas sensing element 13-2. For example, one or more of the MOS response signals 142, 144, 146, 148, 150, and 152 may include the impedance responses of the first MOS gas sensing element 13-1 and the second MOS gas sensing element 13-2 of the array 11. It should be appreciated that each of the MOS response signals 142, 144, 146, 148, 150 and 152 may represent, among other parameters, the real or imaginary part of the impedance response at a particular frequency.

[0067] The multivariate response pattern may include the analysis results of graphs 100 and 140. In particular, the multivariate response pattern may include a first EC response signal 102 of the first EC gas sensing element 12-1, a second EC response signal 104 of the second EC gas sensing element 12-2, and a plurality of MOS response signals of each of the first MOS gas sensing element 13-1 and the second MOS gas sensing element 13-2 of the array 11. Based on the multivariate response pattern, the control circuitry 14 can determine improved discrimination between gases in contact with the array 11 compared to unselected responses from the MOS gas sensing element 13. In some cases, the control circuitry 14 can determine one or more gases in contact with the EC gas sensing element 12 and the MOS gas sensing element 13 by one or more multivariate statistical analysis tools, such as PCA and / or HCA (e.g., unsupervised, supervised, etc.), as will be appreciated. For example, performing a multivariate statistical analysis of one or more EC response signals 102 and / or 104 and at least two MOS response signals 142, 144, 146, 148, 150 and / or 152 may provide improved discrimination between gases compared to using unselected responses from sensor 10. The unselected responses from sensor 10 may include the DC resistance response of the MOS gas sensor (e.g., MOS gas sensing element 13) compared to the AC impedance response of the MOS gas sensing element 13.

[0068] In the depicted example, the first MOS gas sensing element 13-1 and the second MOS gas sensing element 13-2 may each be exposed to the same fluid patterns 108, 110, 112, and 114 for the same respective periods 116, 118, 120, and 122 as the EC gas sensing elements 12-1 and 12-2. For example, the results of graphs 100 and 140 may be the result of simultaneous, sequential, or other correlated operations. Moreover, the measurement circuit 32 may generate stimulus signals at different excitation frequencies for each of the MOS response signals 142, 144, and 146 of the first MOS gas sensing element 13-1 and the MOS response signals 148, 150, and 152 of the second MOS gas sensing element 13-2.

[0069] 5, the MOS gas sensing elements 13-1 and 13-2 can each provide different responses to the different fluid patterns 108, 110, 112, and 114 when receiving excitation signals at different frequencies and providing corresponding response signals 142, 144, 146, 148, 150, and 152. The MOS gas sensing material 23 of each of the MOS gas sensing elements 13-1 and 13-2 can provide different responses to the different fluid patterns 108, 110, 112, and 114 at different frequencies. For example, the fifth MOS response signal 150 and the sixth MOS response signal 152 of the second MOS gas sensing element 13-2, each associated with an excitation signal having a particular frequency, can provide measurable responses to the first fluid pattern 108 and the fourth fluid 114.

[0070] Similarly, a fourth MOS response signal 148 associated with a different stimulation frequency may provide a measurable response only to the first fluid pattern 108. In some embodiments, the processor 36 may use information stored in the memory 38 (e.g., a look-up table) to determine the excitation frequency for providing a stimulation signal for detecting the fluid patterns 108, 110, 112, and 114 and / or the concentration of each of the fluid patterns 108, 110, 112, and 114. The processor 36 or any other executable circuitry may determine the fluid patterns 108, 110, 112, and 114 and / or the concentration of each of the fluid patterns 108, 110, 112, and 114 by a classification / cluster analysis and quantification algorithm. Examples of classification / cluster analysis algorithms may include, but are not limited to, principal component analysis (PCA), hierarchical cluster analysis (HCA), independent component analysis (ICA), linear discriminant analysis (LDA), and support vector machine (SVM) algorithms. Non-limiting examples of methods for performing analyte quantification to determine the concentration of a particular analyte gas include principal component regression (PCR), independent component regression (ICR), non-linear regression analysis (NRA), discriminant function analysis (DFA), support vector regression (SVR) or artificial neural network analysis (ANN), among other possible processes.

[0071] For comparison, FIG. 6 depicts a graph 160 illustrating the MOS resistance responses 162 and 164 of the MOS gas sensing elements 13-1 and 13-2 to fluid patterns 108, 110, 112, and 114 when providing a direct current (DC signal) excitation signal (e.g., relatively close to 0 Hz).

[0072] 5, each of the MOS gas sensing elements 13-1 and 13-2 may provide a different response to different fluid patterns 108, 110, 112, and 114 when an excitation signal is provided at a different frequency. However, in some cases, when an excitation signal is provided at a single zero frequency (e.g., a DC signal), each of the MOS gas sensing elements 13-1 and 13-2 may provide a different response (e.g., a resistance response) to different fluid patterns 108, 110, 112, and 114. For example, in FIG. 6, in the example graph 160, the MOS gas sensing element 13-1 may provide MOS resistance responses 162 and 164 that are different from the MOS response signals 142, 144, 146, 148, 150, and 152 discussed above. In particular, the MOS resistance responses 162 and 164 depict the change in the resistance response of the MOS gas sensing elements 13-1 and 13-2 when in contact with the fluids 110 and 112 during periods 118 and 120. Therefore, in such cases, it may be more desirable to provide multiple excitation signals of different frequencies to the MOS gas sensing elements 13-1 and 13-2, as shown in graph 140 of FIG. 5 above.

[0073] 7A is a first three-dimensional score plot 170 at a first visualization angle depicting the PCA results of the combined responses of the EC gas sensing elements 12-1 and 12-2 and the MOS gas sensing elements 13-1 and 13-2 when stimuli are applied at different AC excitation frequencies. Additionally, FIG. 7B is a first three-dimensional score plot 172 at a second visualization angle depicting the PCA results of the combined responses of the EC gas sensing elements 12-1 and 12-2 and the MOS gas sensing elements 13-1 and 13-2 when stimuli are applied at different AC excitation frequencies.

[0074] 8A is a three-dimensional score plot 174 at a first visualization angle depicting the PCA results of the combined responses of the EC gas sensing elements 12-1 and 12-2 and the MOS gas sensing elements 13-1 and 13-2 when a DC excitation is applied for comparison. Additionally, FIG. 8B is a three-dimensional score plot 176 at a second visualization angle depicting the PCA results of the combined responses of the EC gas sensing elements 12-1 and 12-2 and the MOS gas sensing elements 13-1 and 13-2 when a DC excitation is applied for comparison.

[0075] In some cases, processor 36 can correct the baseline response of MOS gas sensing elements 13-1 and / or 13-2 by tracking the deviation of the baseline response of MOS gas sensing element 13 from the baseline response of EC gas sensing elements 12-1 and 12-2, as discussed above. The PCA results of score plots 170 and 172 provide more characteristic results based on fluid patterns 108, 110, 112, and 114 compared to the PCA results of score plots 174 and 176. In one non-limiting example, the principal component (PC) results of score plots 170 and 172 show PC1 equal to 55.1%, PC2 equal to 24.04%, and PC3 equal to 18.64%, while the principal component (PC) results of score plot 176 show PC1 equal to 73.99%, PC2 equal to 22.41%, and PC3 equal to 3.21%.

[0076] 9 is a dendrogram plot 180 illustrating the results of a hierarchical cluster analysis (HCA) of the combined responses of the EC gas sensing elements 12-1 and 12-2 and the MOS gas sensing elements 13-1 and 13-2. For example, the EC gas sensing elements 12-1 and 12-2 and the MOS gas sensing elements 13-1 and 13-2 may provide responses in response to the processor 36 applying stimuli at different AC excitation frequencies to the MOS gas sensing elements 13-1 and 13-2. The dendrogram plot 180 may illustrate the hierarchical relationships among the multivariate responses of the sensor 10 to fluids 1-4 (of FIGS. 4-6) at their respective concentrations (e.g., the three concentrations depicted in FIGS. 4-6).

[0077] The dendrogram plot 180 in Figure 9 assigns the multivariate responses of sensor 10 to fluids 1-4 to different clusters based on fluid type (or gas type). The vertical axis in Figure 9 can represent the hierarchical relationship of samples within an analyzed dataset, which may include the responses of sensor 10 sensing fluids 1-4. For example, one or more clusters can be grouped to identify each of fluids 1-4 based on fluid clusters 200, 202, 204, and 206, as well as blank cluster 208. Blank cluster 208 can be the baseline response of sensor 10 in the absence of fluids 1-4 in clean air.

[0078] 9 depicts the distance between response clusters 200, 202, 204, and 206 generated by fluids 1-4 (and blank cluster 208). Horizontal axis 188 may depict the magnitude of dissimilarity of one or more datasets associated with response clusters 200, 202, 204, and 206 generated by fluids 1-4 (and blank cluster 208). Thus, dendrogram plot 180 may provide a hierarchical structure of datasets associated with responses generated by fluids 1-4 and blank cluster 208.

[0079] 9, clusters 200, 202, 204, and 206 may depict the response to fluids 1-4 at each concentration (e.g., three concentrations) with one or two data points for each concentration. In alternative or additional embodiments, clusters 200, 202, 204, and 206 may depict the response to fluids 1-4 at each concentration (e.g., three concentrations) with a different number of data points for each concentration.

[0080] In the depicted embodiment, the depicted cluster of the data set for fluid cluster 200 associated with fluid 1 may include the longest distance 189 compared to the clusters for fluid clusters 202, 204, and 206. For example, the response clusters for fluids 4, 2, and 3 are depicted with shorter respective distances 190, 192, and 194 in hierarchical order. The response cluster for blank 186 may have the shortest distance.

[0081] Thus, the dendrogram plot 180 in FIG. 9 demonstrated that sensor 10 successfully distinguished between fluids 1-4. For example, different fluids may contain nitrogen dioxide (e.g., fluid 1), carbon monoxide (e.g., fluid 2), and hydrogen sulfide (fluid 4). Sensor 10 also successfully distinguished between its medium and highest concentrations of diesel exhaust (e.g., fluid 3), and considered it to be the same cluster while analyzing low concentrations of diesel exhaust (e.g., fluid 3) and blank cluster 208. Therefore, the response of sensor 10 analyzed by the HCA dendrogram plot in FIG. 9 demonstrated the desired discrimination between analyte gases (e.g., fluids 1, 2, and 4) and interference gases (e.g., fluid 3).

[0082] FIG. 10 is a dendrogram plot 220 depicting hierarchical cluster analysis (HCA) results of the combined responses of EC gas sensing elements 12-1 and 12-2 and MOS gas sensing elements 13-1 and 13-2 when DC excitation is applied for comparison, according to an embodiment of the present technology. The results demonstrate that sensor 10 may produce a false cluster of diesel exhaust (e.g., fluid 3) and carbon monoxide (e.g., fluid 2). The results may also demonstrate that sensor 10 produced another false cluster of hydrogen sulfide (e.g., fluid 4), diesel exhaust (e.g., fluid 3), and a blank cluster 208. Thus, the response of sensor 10 analyzed by dendrogram plot 220 of FIG. 10 demonstrated lower discrimination between the analyte gas (e.g., fluid 2) and the interference gas (e.g., fluid 3), and lower discrimination between the analyte gas (e.g., fluid 4) and the interference gas (e.g., fluid 3), compared to dendrogram plot 180 of FIG. 9.

[0083] 10, the depicted cluster of the data set for fluid cluster 200 associated with fluid 1 may include the longest distance 221 compared to the clusters for fluid clusters 202, 204, and 206. For example, the response clusters for fluids 4, 2, and 3 are depicted with shorter respective distances 190, 192, and 194 in hierarchical order. The response cluster for blank 208 may have the shortest distance.

[0084] However, compared to the response clusters for fluids 4, 2, and 3 depicted in Figure 9, the response clusters for fluids 4, 2, and 3 in Figure 10 have a somewhat less regular structure, given the shorter distances 190, 192, and 194, respectively, in hierarchical order. Fluids 2 and 3 are separated by a distance 222. The cluster of fluids 2 and 3 is separated from fluid 4 by a distance 223. The two concentrations of fluid 4 are separated by a distance 224 from a cluster containing one concentration of fluid 4, one concentration of fluid 3, and a blank 208.

[0085] As used herein, elements or steps listed in the singular and preceded by the word "a" or "an" should be understood as not excluding a plurality of such elements or steps, unless such exclusion is expressly stated. Furthermore, references to "one embodiment" of the subject matter described herein are not intended to be interpreted as excluding the existence of additional embodiments that also incorporate the recited features. Moreover, unless expressly stated to the contrary, embodiments "comprising," "including," or "having" (or similar terminology) an element having a particular characteristic or multiple elements having a particular characteristic can include additional such elements that do not have the specified characteristic.

[0086] As used herein, terms such as "system" or "controller" may include hardware and / or software that operates to perform one or more functions. For example, a system or controller may include a computer processor or other logic-based device that performs operations based on instructions stored in a tangible, non-transitory, computer-readable storage medium, such as a computer memory. Alternatively, a system or controller may include a hardwired device that performs operations based on the device's hardwired logic. The systems and controllers shown in the figures may represent hardware that operates based on software or hardwired instructions, software that instructs hardware to perform operations, or a combination thereof.

[0087] As used herein, terms such as "operably connected," "operably connected," "operably coupled," "operably coupled," "operably contacted," "operable contact," and the like indicate that two or more components are connected in a manner that enables or permits at least one of the components to perform a specified function. For example, when two or more components are operably connected, there may be one or more connections (electrical and / or wireless connections) that enable the components to communicate with each other, enable one component to control another, enable each component to control the other, and / or enable at least one of the components to operate in a specified manner.

[0088] It is to be understood that the subject matter described herein is not limited in its application to the details of construction and the arrangement of elements set forth in the description herein or illustrated in the drawings herein. The subject matter described herein is capable of other embodiments and of being practiced or carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein are for purposes of description and should not be regarded as limiting. The use of "including," "comprising," or "having," and variations thereof, herein means to encompass the items listed thereafter and equivalents thereof, as well as additional items.

[0089] It should be understood that the above description is intended to be illustrative, not limiting. For example, the above-described embodiments (and / or aspects thereof) may be used in combination with each other. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the subject matter described herein without departing from its scope. While the dimensions, material types, and coatings described herein are intended to define the parameters of the disclosed subject matter, they are by no means limiting and are exemplary embodiments. Many other embodiments will be apparent to those skilled in the art upon reviewing the above description.

[0090] The scope of the subject matter should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. In the appended claims, the terms "including" and "in which" are used as the plain-English equivalents of the terms "comprising" and "wherein," respectively. Moreover, in the following claims, terms such as "first," "second," and "third" are used merely as labels and are not intended to impose numerical requirements on their subject matter. Moreover, the limitations of the following claims are not written in means-plus-function form and are not intended to be construed under 35 U.S.C. § 112(f) unless and until such claim limitations expressly use the phrase "means for" followed by a description of a function without further structure.

[0091] This specification uses examples to disclose some embodiments of the present subject matter and to enable those skilled in the art to practice embodiments of the disclosed subject matter, including making and using any device or system, and performing any incorporated methods. The patentable scope of the subject matter is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they contain equivalent structural elements that do not differ substantially from the literal language of the claims.

Claims

1. A sensor device, at least one electrochemical (EC) gas sensor; at least one metal oxide semiconductor (MOS) gas sensor; A control circuit unit, providing one or more EC excitation signals to the at least one EC gas sensor; providing at least two MOS excitation signals to the at least one MOS gas sensor; At least two gases, receiving one or more EC response signals from the at least one EC gas sensor based on providing the one or more EC excitation signals; receiving at least two MOS response signals from the at least one MOS gas sensor based on providing the at least two MOS excitation signals; determining a multivariate response pattern based on the one or more EC response signals and the at least two MOS response signals; distinguishing between the at least two gases in contact with the sensor device based on the multivariate response pattern; a control circuit configured to detect based on A sensor device comprising:

2. 2. The sensor device of claim 1, wherein the multivariate response pattern comprises the one or more EC response signals from the at least one EC gas sensor and the at least two MOS response signals from the at least one MOS gas sensor.

3. The sensor device of claim 1 , wherein the EC gas sensor comprises an EC gas sensing material and the at least one MOS gas sensor comprises a MOS gas sensing material.

4. The control circuit unit a controller coupled to the EC gas sensor and the MOS gas sensor and configured to generate the one or more EC excitation signals and the at least one at least two MOS excitation signals; a detector configured to receive the one or more EC response signals and the at least two MOS response signals, the detector including a current detector, a resistance detector, an impedance detector, or a combination thereof; The sensor device of claim 1 , comprising:

5. 10. The sensor device of claim 1, wherein detecting a first gas of the at least two gases is by correcting baseline drift of the at least two MOS response signals based on the one or more EC response signals.

6. 10. The sensor device of claim 1, wherein the control circuitry distinguishes between the at least two gases based on the multivariate response patterns by applying one or more supervised multivariate statistical analysis tools, one or more unsupervised multivariate statistical analysis tools, or both.

7. 10. The sensor device of claim 1, comprising a memory storing one or more gas classification models for detecting a first gas and a second gas based on distinguishing between the at least two gases.

8. The sensor device of claim 7 , wherein the memory stores one or more gas quantification models associated with detecting concentrations of the first gas, the second gas, or both.

9. A sensor device, a first metal oxide semiconductor (MOS) gas sensor; a second MOS gas sensor; A control circuit unit, providing a first excitation signal at a first frequency to the first MOS gas sensor and the second MOS gas sensor; providing a second excitation signal to the first MOS gas sensor and the second MOS gas sensor at a second frequency; providing a third excitation signal to the first MOS gas sensor and the second MOS gas sensor at a third frequency; receiving excitation signal responses of the first MOS gas sensor and the second MOS gas sensor in response to providing the first excitation signal, the second excitation signal, and the third excitation signal; control circuitry configured to detect at least a first gas and a second gas based on determining a multivariate response pattern of the excitation signal responses of the first MOS gas sensor and the second MOS gas sensor; and A sensor device comprising:

10. The control circuit unit 10. The sensor device of claim 9, comprising a processor configured to perform multivariate response pattern analysis by applying one or more supervised multivariate statistical analysis tools, one or more unsupervised multivariate statistical analysis tools, or both, to the excitation signal responses of the first MOS gas sensor and the second MOS gas sensor to determine the first gas and the second gas.

11. 11. The sensor device of claim 10, wherein the processor is configured to determine the concentration of at least one of the first gas and the second gas based on performing at least one supervised multivariate statistical analysis tool, one or more unsupervised multivariate statistical analysis tools, or both.

12. The sensor device of claim 9 further comprising an electrochemical (EC) gas sensor.

13. The control circuit unit providing an excitation signal to the EC gas sensor; receiving an excitation signal response of the EC gas sensor; and The sensor device of claim 12 , configured to determine and remove baseline drift of the excitation signal response of the MOS gas sensor based on the excitation signal response of the EC gas sensor.

14. 1. A method comprising: receiving, by a processor of the sensor device, a first control signal indicating detection of one or more gas types; providing, by the processor, a first excitation signal to a metal oxide semiconductor (MOS) gas sensor and a second excitation signal to an electrochemical (EC) gas sensor; determining, by the processor, a gas response based on receiving an excitation signal response of the MOS gas sensor; determining, by the processor, a baseline response based on receiving an excitation signal response of the EC gas sensor; determining, by the processor, at least two gas types in contact with the sensor device and a concentration of at least one of the at least two gas types based on the gas response and the baseline response; providing, by the processor, an indication of the at least two gas types and the concentration of the at least one of the at least two gas types to one or more output devices; A method comprising:

15. Determining the at least two gas species, the concentration of at least one of the at least two gas species, or both, comprises: providing the first excitation signal having at least two frequencies to the MOS gas sensor; receiving an excitation signal response of the EC gas sensor based on providing the first excitation signal having the at least two frequencies; 15. The method of claim 14, comprising:

16. The method of claim 14 , further comprising correcting a baseline drift of the excitation signal response of the MOS gas sensor based on the excitation signal response of the EC gas sensor.

17. 15. The method of claim 14, further comprising, before providing the first excitation signal to the MOS gas sensor and providing the second excitation signal to the EC gas sensor, receiving, by the processor, a second control signal indicative of one or more operating parameters of the MOS gas sensor, the EC gas sensor, or both, and one or more values ​​of each of the operating parameters.

18. 20. The method of claim 17, wherein the one or more operating parameters include a real part of the impedance of the excitation signal response, an imaginary part of the impedance, a frequency, or a combination thereof.

19. 20. The method of claim 18, comprising displaying an alert in response to determining a particular gas type, a concentration of a gas type above a threshold concentration, a concentration of a gas type below a threshold concentration, or a combination thereof based on the one or more operating parameters and the one or more values ​​of each of the operating parameters.

20. A sensor device, at least one electrochemical (EC) gas sensor; at least one metal oxide semiconductor (MOS) gas sensor; A control circuit unit, providing one or more EC excitation signals to the at least one EC gas sensor; providing at least two MOS excitation signals to the at least one MOS gas sensor; At least two gases, receiving one or more EC response signals from the at least one EC gas sensor based on providing the one or more EC excitation signals; receiving at least two MOS response signals from the at least one MOS gas sensor based on providing the at least two MOS excitation signals; performing a multivariate statistical analysis of the one or more EC response signals and the at least two MOS response signals with improved discrimination between gases compared to unselected responses from the sensor device; a control circuit configured to detect based on A sensor device comprising:

21. 21. The sensor device of claim 20, wherein the unselected responses from the sensor device include a DC resistance response of the MOS gas sensor.

22. 21. The sensor device of claim 20, wherein the control circuitry comprises one or more processors, the one or more processors configured to determine one or more gas types and at least one gas concentration of at least one of the one or more gas types.

23. 23. The sensor device of claim 22, wherein the one or more processors are configured to generate a control signal indicating performing at least one response action based on determining the one or more gas types and the at least one gas concentration.

24. 24. The sensor device of claim 23, wherein the response action comprises generating one or more alerts, initiating an emergency response, initiating specific treatment or decontamination of an object having the sensor device, optimizing logistics steps following knowledge of the detected concentration of the gas, minimizing logistics steps following knowledge of the detected concentration of the gas, or combinations thereof.

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