Humidity Interference Research Articles

Alcohol Sensor Calibration on the Edge Using Tiny Machine Learning (Tiny-ML) Hardware

Introduction Detecting precise concentrations of alcohol by means of a wearable sensor with varying relative humidity and temperature, has been a challenge in gas detection methods. By acquiring sensor data under these varying conditions and analyzing the data, we can better quantify the sensor behavior and extract precise measurements from the sensor. Improved analysis of the system behavior is required to identify decay or drift over a period of time Machine Learning (ML) can be used to improve the sensor calibration by using the collected data. Machine Learning can be leveraged for a reduction in costs and implementation effort for decorrelating the effect of changing humidity and temperature on sensor response. Microcontrollers offer benefits such as low energy consumption, small size and are suitable as a computing device for wearable applications. By running machine learning inference on microcontrollers, dependency on the network connectivity can be reduced, which is generally focused on bandwidth and power limitation and results in higher latency. Since data is processed at the device itself during testing, it can preserve the confidentiality of data under test. Previous studies have implemented decorrelation of temperature and humidity for the gas sensor, where model building and testing of sensor data were done at the remote computer. The goal of this study is to improve the precision of alcohol sensing by decorrelating the effect caused due to change in environmental conditions by applying machine learning at the edge. Methodology We have implemented an alcohol sensor for wearable applications to find the level of alcohol consumed by the subject. An alcohol sensor is interfaced with nRF52480 microcontroller with Bluetooth Low Energy (BLE) being a special feature to send sensor data to other computing devices as shown in Fig. 1. The response of the sensor was assessed under precise test environments to recognize the and compute their relation with the alcohol sensor output. In this study, data from a temperature sensor, humidity sensor and alcohol sensor are collected over a period of a week at the local computer and these are used as a training dataset for building the machine learning model. The received dataset is pre-processed and an ML model is trained to quantify the sensor output. Google Colab is used to build a Tiny Machine Learning (Tiny-ML) model with the help of a tensor-flow lite micro-library. The generated machine learning model is uploaded to the microcontroller for the prediction of data under test to compensates for the influence of ambient situations on an alcohol sensor. The novelty of this study is to quantify the output of an alcohol sensor by applying the ML model on test data at the embedded system itself and to calibrate the sensor response locally. The corrective procedure appears to be effective in refining the sensor response enactment under a variety of thermal and humidity situations. Keyword : Sensor Calibration, Tiny Machine Learning, Edge Computing Reference 1. Huerta, Ramon, et al. "Online decorrelation of humidity and temperature in chemical sensors for continuous monitoring." Chemometrics and Intelligent Laboratory Systems 157 (2016): 169-176. doi: 10.1016/j.chemolab.2016.07.0042. Jalal, A. H.; Umasankar, Y.; Gonzalez, P. J.; Alfonso, A.; Bhansali, S. 2017. Multimodal technique to eliminate humidity interference for specific detection of ethanol, Biosensors and Bioelectronics, 2017Jan 15;87:522-530. doi: 10.1016/j.bios.2016.08.1063. Peng Wei, Zhi Ning, Sheng Ye, Li Sun, Fenhuan Yang, Ka Chun Wong, Dane Westerdahl, and Peter K. K. Louie, Impact Analysis of Temperature and Humidity Conditions on Electrochemical Sensor Response in Ambient Air Quality Monitoring, Sensors (Basel). 2018 Feb; 18(2): 59, doi: 3390/s180200593. Tyagi, V Singh, Decorrelation of Temperature and Humidity Sensor’s by Comparing Classifier’s Performance on Metal Oxide Semiconductor Sensor’s Dataset,2018 International Conference on Bioinformatics and Systems Biology(BSB), doi: 10.1109/BSB.2018.8770589 Figure 1

Microporous Elastomer Filter Coated with Metal Organic Frameworks for Improved Selectivity and Stability of Metal Oxide Gas Sensors

Despite various advantages and usefulness of semiconductor metal oxide gas sensors, low selectivity and humidity interference have limited their practical applications. In order to resolve these issues, we propose a new concept of a selective gas filtering structure that increases the gas selectivity and decreases the moisture interference of metal oxide gas sensors by coating metal organic frameworks (MOFs) on a microporous elastomer scaffold. Cu(BTC) with an excellent selective adsorption capacity for carbon monoxide (CO) compared to hydrogen (H2) and MIL-160 with an excellent moisture adsorption capacity were uniformly coated on the microporous polydimethylsiloxane (PDMS) structure through a squeeze coating method, resulting in a high content of MOFs with a large effective surface area. A Cu(BTC)-coated microporous PDMS filter showed an excellent adsorption efficiency (62.4%) for CO, thereby dramatically improving the selectivity of H2/CO by up to 2.6 times. In addition, an MIL-160 coated microporous PDMS filter showed a high moisture adsorption efficiency (76.2%).

Study on Dust Measurement Technology by Oscillating Balance Method

By comparing the advantages and disadvantages of various dust measurement methods, the oscillating balance method is chosen to measure dust. According to the measuring principle of the oscillating balance method, a particle weighing device based on the oscillating balance method is developed. The device avoids the interference of temperature, humidity and mutual inductance to the magneto-electric speed sensor, improves the amplitude of the magneto-electric speed sensor to receive the oscillation signal, and improves the signal-to-noise ratio of the system as much as possible. According to the phase-frequency characteristics of the oscillating system, an overall structure of the system is designed. The system consists of a drive module, harmonic oscillator, measurement module, and phase-locked loop automatic phase modulation circuit and frequency measurement module. These five modules constitute a system that can automatically adjust the natural frequency. And the list confirms the accuracy of the frequency that is measured by FPGA and STM32 processor. The dust mass is calculated according to the formula. Finally, the reliability of the device is confirmed by a parallel comparison with the internationally recognized filter membrane weighing method. The reliability of the device is confirmed.

Humidity independent hydrogen sulfide sensing response achieved with monolayer film of CuO nanosheets

Detection of ppm and sub-ppm level airborne hydrogen sulfide (H2S) is critical to both environmental monitoring and medical diagnosis. However, conductometric gas sensors based on semiconducting metal oxides are usually susceptible to humidity interference, which limits their performance in those applications. Typically, the hydroxyl groups formed by the chemisorption of water vapor on the surfaces of metal oxides prevent any further redox reaction, and in turn, passivate the sensing material. Departing from the traditional strategy of alleviating humidity interference with moisture adsorbents, we propose to explore the possible surface reactions between H2S and hydroxyl groups on the surface of copper (II) oxide (CuO) in this work. With a monolayer film of CuO nanosheets, we observe an unprecedented humidity independent H2S sensing performance. In addition, the sensor also shows excellent sensitivity and selectivity to H2S and high stability in dry and wet conditions. The mechanism underlying the stable sensing response regardless of humidity variations is investigated with X-ray photoelectron spectroscopy.

A Low-Power PEDOT: PSS/EB-PANI for CO2 Sensing Material Integrated With a Self-Powered Sensing Platform

The Internet of Things (IoT) has inspired key directions for next-generation sensor development. These directions include low power and good selectivity to promote IoT applications. To address this point, in this work, we developed a low-power and room-temperature-operation CO2 sensing material with high selectivity to humidity. The sensing material was developed based on (emeraldine-based polyaniline)/(poly(3,4-ethylenedioxythiophene)-poly(styrene sulfonate) composites, i.e. EB-PANI/PEDOT:PSS. Its selectivity to humidity was experimentally verified from 55% RH to 85% RH. In brief, the sharing of PSS between PEDOT and EB-PANI improved the conductivity and CO2 sensing characteristics of the composite sensing material. At the same time, the opposite humidity-sensing responses of PEDOT and PANI counteracted to each other and resulted in a high selectivity to humidity. In this work, the optimal weight ratio of an EB-PANI/PEDOT:PSS sensing film for CO2 monitoring and immunity to humidity interference was also discussed. To demonstrate the feasibility of integrating the developed sensing material into an IoT system, a self-sustained system-on-chip (SoC) platform for expiration CO2 detection was implemented and experimentally operated with indoor illuminance conditions.

Atomic-scale structure and chemical sensing application of ultrasmall size-selected Pt nanoparticles supported on SnO2

SnO2-based chemoresistive sensors integrated in complementary metal-oxide-semiconductor technology were functionalized with ultrasmall Pt nanoparticles, resulting in carbon monoxide sensing properties with minimized humidity interference.

Flexible wearable graphene/alginate composite non-woven fabric temperature sensor with high sensitivity and anti-interference

The development of a sensitive flexible wearable temperature sensor has extraordinary significance in the field of human vital signs detection. Herein, we demonstrate a flexible temperature sensor (FTS) fitting on human skin based on non-woven fabric, and it has been systematically characterized and tested for performance. The resistor-type FTS integrated sodium alginate with graphene, behaved as negative temperature coefficient feature and exhibited excellent sensing performance of good sensitivity (TCR = − 1.5 °C−1), high accuracy of 0.1 °C, short response time (26.3 s), high stability and repeatability at the temperature range of 20.0–45.0 °C. Specially, the FTS eliminated strain and humidity interference, so that can be attached to the human body to detect skin temperature changes continuously and stably.

Nanohybrids of Pt-Functionalized Al2O3/ZnO Core-Shell Nanorods for High-Performance MEMS-Based Acetylene Gas Sensor.

Metal oxide nanostructures are the most promising materials for the fabrication of advanced gas sensors. However, the main challenge of these gas sensors is humidity interference and issues related to the selectivity and high operating temperature, which limits their response in real-time applications. In this study, we proposed nanohybrids of Pt-functionalized Al2O3/ZnOcore-shell nanorods (NRs) for a real-time humidity-independent acetylene gas sensor. The core ZnO NRs have been fabricated on microelectromechanical system (MEMS) microheater, followed by a coating of a thin nanoscale moisture-blocking conformal Al2O3 shell by atomic layer deposition (ALD) and decoration of Pt NPs using photochemical deposition and e-beam evaporation. Prior to the fabrication, a COMSOL simulation was performed to optimize the microheater design and moisture-blocking layer thickness. A comparative study of the decoration of Pt NPs on the ZnO surface by photochemical (s-Pt/ZnO) and e-beam evaporation (e-Pt/ZnO) and a Al2O3 thin moisture-blocking shell layer (Pt/Al2O3/ZnO) in sensor response has been conducted. The fabricated sensors (s-Pt/ZnO) and (e-Pt/ZnO) showed a high response ΔR/R (%) of 96.46% and 68.15% to 200 ppm acetylene at 120 °C and detect trace concentrations of acetylene down to 1 ppm, but the response is influenced by humidity. Moreover, the sensor (Pt/Al2O3/ZnO) exhibited nearly the same sensing characteristics and high acetylene selectivity despite the wide range of humidity variation from 20% RH to 70% RH. The Pt-functionalized Al2O3/ZnOcore-shell NR-based sensor showed better sensing and stable performance than other sensors (s-Pt/ZnO and e-Pt/ZnO) under humidity conditions.

Highly Sensitive and Selective PbTiO3 Gas Sensors with Negligible Humidity Interference in Ambient Atmosphere.

Three PbTiO3 nanostructures were synthesized using a one-step hydrothermal reaction with different TiO2 powders as Ti sources, and their gas-sensing properties were investigated. The sensor comprising PbTiO3 nanoplates (NPs) exhibited a high response (resistance ratio = 80.4) to 5 ppm ethanol at 300 °C and could detect trace concentrations of ethanol down to 100 ppb. Moreover, the sensor showed high ethanol selectivity and nearly the same sensing characteristics despite the wide range of humidity variation from 20 to 80% RH. The mechanism for humidity-independent gas sensing was elucidated using diffuse reflectance infrared Fourier transform spectra. PbTiO3 NPs are new and promising sensing materials that can be used for detecting ethanol in a highly sensitive and selective manner with negligible interference from ambient humidity.

UV-light-activated H2S gas sensing by a TiO2 nanoparticulate thin film at room temperature

A UV-light-activated TiO2 thin film gas sensor composed of nanoparticles is reported for H2S detection at room temperature. TiO2 nanoparticulate thin films were fabricated by bar coating of a mixture of TiO2 powder and acetic acid. The morphology and structural properties of the films were examined by scanning electron microscopy, X-ray diffraction, photoluminescence spectroscopy, and absorption spectroscopy. The nil response to H2S was significantly enhanced by UV light irradiation in the response levels and response/recovery kinetics. The effect of the sensor conductance and light intensity towards sensor optimization was discussed. The sensor exhibited high gas selectivity, repeatability, and linearity for practical applications of the sensor, but the interference of humidity on the sensing process needs to be solved. The results exhibited a simple way to detect parts per million concentrations of H2S at room temperature.

Portable ozone calibration source independent of changes in temperature, pressure and humidity for research and regulatory applications

Abstract. A highly portable ozone (O3) calibration source that can serve as a U.S. EPA level 4 transfer standard for the calibration of ozone analyzers is described and evaluated with respect to analytical figures of merit and effects of ambient pressure and humidity. Reproducible mixing ratios of ozone are produced by the photolysis of oxygen in O3-scrubbed ambient air by UV light at 184.9 nm light from a low-pressure mercury lamp. By maintaining a constant volumetric flow rate (thus constant residence time within the photolysis chamber), the mixing ratio produced is independent of both pressure and temperature and can be varied by varying the lamp intensity. Pulse width modulation of the lamp with feedback from a photodiode monitoring the 253.7 nm emission line is used to maintain target ozone mixing ratios in the range 30–1000 ppb. In order to provide a constant ratio of intensities at 253.7 and 184.9 nm, the photolysis chamber containing the lamp is regulated at a temperature of 40 ∘C. The resulting O3 calibrator has a response time for step changes in output ozone mixing ratio of < 30 s and precision (σp) of 0.4 % of the output mixing ratio for 10 s measurements (e.g., σp=±0.4 ppb for 100 ppb of O3). Ambient humidity was found to affect the output mixing ratio of ozone primarily by dilution of the oxygen precursor. This potential humidity interference could be up to a few percent in extreme cases but is effectively removed by varying the lamp intensity to compensate for the reduced oxygen concentration based on feedback from a humidity sensor.

Fully Stretchable and Humidity-Resistant Quantum Dot Gas Sensors.

Stretchable gas sensors that accommodate the shape and motion characteristics of human body are indispensable to a wearable or attachable smart sensing system. However, these gas sensors usually have poor response and recovery kinetics when operated at room temperature, and especially suffer from humidity interference and mechanical robustness issues. Here, we demonstrate the first fully stretchable gas sensors which are operated at room temperature with enhanced stability against humidity. We created a crumpled quantum dot (QD) sensing layer on elastomeric substrate with flexible graphene as electrodes. Through the control over the prestrain of the flexible substrate, we achieved a 5.8 times improvement in NO2 response at room temperature with desirable stretchability even under 1000 stretch/relax cycles mechanism deformation. The uniformly wavy structural configuration of the crumpled QD gas-sensing layer enabled an improvement in the antihumidity interference. The sensor response shows a minor vibration of 15.9% at room temperature from relative humidity of 0 to 86.7% compared to that of the flat-film sensors with vibration of 84.2%. The successful assembly of QD solids into a crumpled gas-sensing layer enabled a body-attachable, mechanically robust, and humidity-resistant gas sensor, opening up a new pathway to room-temperature operable gas sensors which may be implemented in future smart sensing systems such as stretchable electronic nose and multipurpose electronic skin.

FFT analysis of temperature modulated semiconductor gas sensor response for the prediction of ammonia concentration under humidity interference

The increasing environmental contamination forces the need to design reliable devices for detecting of the volatile compounds present in the air. For this purpose semiconductor gas sensors, which have been widely used for years, are often utilized. Although they have many advantages such as low price and quite long life time, they still lack of long term stability and selectivity. Namely, environmental conditions have significant effect on the sensing accuracy. That is caused by the fact that sensors also respond to interfering molecules coexisting in ambient gas (e.g. humidity) and their response is highly dependent on the temperature and the gas delivery rate. Among the different strategies used to overcome those shortcomings, the modulation of the sensors' operating temperature has been reported. To perform the interpretation and extraction of useful information from dynamic nonlinear response of temperature modulated sensor, the feature extraction and data processing methods are required. In this article the method of determination the concentration of ammonia in the presence of relative humidity is presented. For this purpose the operating temperature of a single commercial SnO2 gas sensor is modulated using sinusoidal voltage applied to the heater. The measurements are performed for different concentrations of ammonia at specified levels of relative humidity. The validation data set was obtained 100 days after the set used for the calibration data. Several features from the dynamic measurements are extracted. Qualitative and quantitative analysis of the selection of the signal features containing useful and relevant information for prediction of target gas are performed. The assessment of the impact of the input vector length of the Fast Fourier Transform method on the resulting signal features is examined. The selected features are utilized as an input for Partial Least Squared regression. The calibration is performed and the prediction error of the ammonia concentration is calculated based on the validation data.

Influence of sample temperature and environmental humidity on measurements of benzene in ambient air by transportable GC-PID

Abstract. Calibration of in situ analysers of air pollutants is usually done with dry standards. In this paper, the influence of sample temperature and environmental humidity on benzene measurements by gas chromatography coupled with a photoionisation detector (GC-PID) is studied. Two reference gas mixtures (40 and 5 µg m−3 nominal concentration benzene in air) were subjected to two temperature cycles (20/5/20 °C and 20/35/20 °C) and measured with two identical GC-PIDs. The change in sample temperature did not produce any significant change in readings. Regarding ambient humidity, the chromatographs were calibrated for benzene with dry gases and subjected to measure reference standards with humidity (20 and 80 % at 20 °C). When measuring a concentration of 0.5 µg m−3 benzene in air, the levels of humidity tested did not produce any significant interference in measurements taken with any of the analysers. However, when measuring a concentration of 40 µg m−3, biases in measurements of 18 and 21 % for each respective analyser were obtained when the relative humidity of the sample was 80 % at 20 °C. Further tests were carried out to study the nature of this interference. Results show that humidity interference depends on both the amount fractions of water vapour and benzene. If benzene concentrations in an area are close to its annual limit value (5 µg m−3), biases of 2.2 % can be expected when the absolute humidity is 8.6 g cm−3 – corresponding to a relative humidity of 50 % at 20 °C. This can be accounted for in the uncertainty budget of measurements with no need for corrections. If benzene concentrations are above the annual limit value, biases become higher. Thus, in these cases, actions should be taken to reduce the humidity interference, as an underestimation of benzene concentrations may cause a mismanagement of air quality in these situations.

A Fuel Cell Sensing Platform for Selective Detection of Acetone in Hyperglycemic Patients

In this work, a three-electrode fuel cell sensor is integrated with a miniaturized potentiostat (LMP91000) and a microcontroller (nRF51822) for selective detection of acetone. Elevated level of acetone in breath or sweat is an indication of systemic ketosis, hyperglycemia or type-I diabetes [1]. Rise of ketone concentrations leads to an increase in acid levels in the blood, called ‘Ketoacidosis’. Ketoacidosis is a serious hyperglycemic condition in patients with type-I diabetes. Among the conventional sensing methods (e.g. breathalyzer for lung ketone analysis, chemical strips, laboratory blood test and urine test), continuous monitoring is a challenge [2]. Also, though real time detection of acetone from different biofluids is promising, interference from other biomarkers remains an issue [3]. To address the above in non-invasive detection, we have developed a statistical model and algorithm which enable separation of signals and eliminate interference from other associated biomarkers. In the developed sensing platform, our fabricated sensor comprises an electrolyte membrane, nafion and monel mesh, as electrodes. Catalytic oxidation of acetone occurs on the working electrode in presence of moisture while oxygen is reduced on the counter electrode. Applying a constant potential across the working and reference electrodes, current is measured between the working and counter electrodes. With the change of concentrations of acetone, the current varies linearly. From this study, it is observed that the sensor is capable to detect as low as 1 ppm of acetone with the sensitivity of 60 nA ppm-1 cm-2. The developed platform has been based on the pre-calibrated data to interpret precise measurement of acetone. Reference: Matzeu, G.; Florea, L.; Diamond, D. 2015. Advances in wearable chemical sensor design for monitoring biological fluids, Sensors and Actuators B, 211:403–418.Tricoli, A.; Nasiri, N.; De, S. 2017. Wearable and Miniaturized Sensor Technologies for Personalized and Preventive Medicine, Advanced Functional Materials, 27(15): 1-19.Jalal, A. H.; Umasankar, Y.; Gonzalez, P. J.; Alfonso, A.; Bhansali, S. 2017. Multimodal technique to eliminate humidity interference for specific detection of ethanol, Biosensors and Bioelectronics, 87(15): 522–530.

Formaldehyde passive sampler using an optical chemical sensor: how to limit the humidity interference.

The behaviour of a new formaldehyde diffusive sampler usingan optical chemical sensor with respect to high humidity conditions is examined in controlled atmospheres. Five prototypes ofthe radial diffusion sampler having the same chemical sensor and different designs were tested. In addition, a set of experiments were performed on the chemical sensor to characterise its efficiency of trapping water vapour in the absence and in the presence of the reactants, Fluoral-P and formaldehyde. Differences in humidity interference between the five diffusive sampler prototypes were studied and discussed. From all the results obtained, it was shown that the prototype LDE1.4 combining a small diffusion slot, a reduced internal volume and a sensor shifted upwards from the diffusion slot provided formaldehyde measurements least affected by humidity up to 80% RH at 20°C. This new type of diffusive sampler with on-site direct reading is intended to ultimately replace conventional passive samplers with DNPH requiring offset laboratory analyses.

Impact of reduced graphene oxide on the ethanol sensing performance of hollow SnO2 nanoparticles under humid atmosphere

The interference of humidity is a key factor to be considered in metal oxide semiconductors gas sensing performance. However, an efficient gas detection under humid conditions is a challenge. Herein, we report the effect of reduced graphene oxide (RGO) on volatile organic compounds (VOCs) sensing performance of hollow SnO2 nanoparticles (NPs) under wet atmosphere. For this purpose, RGO-SnO2 nanocomposite was obtained by a one-pot microwave-assisted solvothermal synthesis. The sensing tests for VOCs were conducted under dry air and at a relative humidity (RH) between 24 and 98%. The samples exhibited better response toward ethanol than to other VOCs such as acetone, benzene, methanol, m-xylene, and toluene, at the optimum operating temperature of 300°C. Furthermore, RGO-SnO2 nanocomposite showed an enhanced ethanol response in comparison with pure hollow SnO2 NPs. Even under 98% of RH, the RGO-SnO2 nanocomposite showed a response of 43.0 toward 100ppm of ethanol with a response time of 8s. The excellent sensor performance is related to the hollow structure of SnO2 NPs, and the heterojunction between RGO and SnO2. Therefore, the RGO content can be a promising approach to minimize the humidity effect on SnO2 ethanol sensing performance.

Multimodal technique to eliminate humidity interference for specific detection of ethanol

Multimodal electrochemical technique incorporating both open circuit potential (OCP) and amperometric techniques have been conceptualized and implemented to improve the detection of specific analyte in systems where more than one analyte is present. This approach has been demonstrated through the detection of ethanol while eliminating the contribution of water in a micro fuel cell sensor system. The sensor was interfaced with LMP91000 potentiostat, controlled through MSP430F5529LP microcontroller to implement an auto-calibration algorithm tailored to improve the detection of alcohol. The sensor was designed and fabricated as a three electrode system with Nafion as a proton exchange membrane (PEM). The electrochemical signal of the interfering phase (water) was eliminated by implementing the multimodal electrochemical detection technique. The results were validated by comparing sensor and potentiostat performances with a commercial sensor and potentiostat respectively. The results suggest that such a sensing system can detect ethanol at concentrations as low as 5ppm. The structure and properties such as low detection limit, selectivity and miniaturized size enables potential application of this device in wearable transdermal alcohol measurements.

Development and Characterization of Fuel Cell Sensor for Potential Transdermal Ethanol Sensing

Existing fuel cell alcohol sensors suffer from humidity interference and signal instability which renders them useless for transdermal ethanol detection in a non-ideal environment. To address these insufficiencies in fuel cell sensors, various electrode designs, along with the catalysts that would best improve response, were explored in this work. The designs include both two and three electrode setups with Nafion as the proton exchanging membrane. The three-electrode setup provided a more stable signal compared to the two-electrode setup. Considering the development of a potential transdermal ethanol sensor, the ethanol exposed area of the working electrode was optimized to be 1cm2. Catalysts such as Cu, stainless steel, and Ni were studied in these experiments and it was determined that Ni demonstrated the best catalytic activity for ethanol oxidation and oxygen reduction; providing 300 times greater current response than Fe and 3 times greater than Cu. The lower detection limit of the sensor is 1 part per million (ppm) and the sensitivity of the fuel cell sensor using the Ni catalyst was found to be 0.02 nAppm-1 in this study.

Development and Characterization of Fuel Cell Sensor for Potential Transdermal Ethanol Sensing

The existing fuel cell alcohol sensors [1-3] suffer severely with humidity interference and signal instability. This interference and instability renders the existing sensors useless for transdermal ethanol detection in non-ideal environment. To address these issues of the fuel cell alcohol sensor, various electrode designs along with the catalysts were explored in this work. The design includes both two and three electrode setups with the Nafion as proton exchange membrane, where the three electrode setup provided stable signal compared to two electrode setup. Considering the development of a potential transdermal ethanol sensor, the ethanol exposed area of the working electrode was optimized to 1cm2and reference and counter electrode were placed on the other side of the Nafion membrane. For the ethanol measurements in the three electrode system, a fixed potential was applied between working and reference electrode and the change in current due to ethanol concentration was measured between working and counter electrode. To eliminate the interference due to humidity the applied potential for measurement was same as that of the open circuit potential (OCP) of the fuel cell in presence of humidity. Catalysts such as Ni, Cu, Fe and Au were studied, where Ni has better catalytic activity for ethanol oxidation and oxygen reduction [4] providing almost 600, 300 and 3 times greater current response than Au, Fe and Cu respectively (Figure 1). The sensitivity for the sensor was found 0.062 nA/ppm in vapor phase for this Ni catalyst. Figure 1: Amperometric responses of fuel cell sensor for ethanol (a) Fe, (b) Au, (c) Ni and (d) Cu catalysts. Acknowledgements: This work is funded by the ASSIST NSF ERC and NSF I-Corps Teams.