Non-dispersive Infrared Gas Research Articles

Concentration calculation model for calibration of non-dispersive infrared gas detection system

Non-dispersive infrared (NDIR) gas detection systems have been extensively used for gas monitoring because they are considered the simplest approach with moderate sensitivity and fast response. Concentration calculation models for calibration are particularly important in NDIR gas detection systems because of the nonlinear relationship between the output voltage ratio and concentration. We propose a concentration calculation model with two fitting parameters for non-dispersive infrared gas detection systems, accounting for the fact that not all IR radiation that impinges upon the detector is absorbed by the gas and for the saturation effects in absorption peaks leading to the nonlinear relationship. Despite the small number of fitting parameters of the proposed concentration calculation model, it presents high quality curve fitting to experimental data. The performance of the proposed model is compared to that of other concentration calculation models.

Development of a Compact NDIR CO2 Gas Sensor for a Portable Gas Analyzer

A carbon dioxide (CO2) gas sensor based on non-dispersive infrared (NDIR) technology has been developed and is suitable for use in portable devices for high-precision CO2 detection. The NDIR gas sensor comprises a MEMS infrared emitter, a MEMS thermopile detector with an integrated optical filter, and a compact gas cell with high optical coupling efficiency. A dual-ellipsoid mirror optical system was designed, and based on optical simulation analysis, the structure of the dual-ellipsoid reflective gas chamber was designed and optimized, achieving a coupling efficiency of up to 54%. Optical and thermal simulations were conducted to design the sensor structure, considering thermal management and light analysis. By optimizing the gas cell structure and conditioning circuit, we effectively reduced the sensor’s baseline noise, enhancing the overall reliability and stability of the system. The sensor’s dimensions were 20 mm × 10 mm × 4 mm (L × W × H), only 15% of the size of traditional NDIR gas sensors with equivalent detection resolution. The developed sensor offers high sensitivity and low noise, with a sensitivity of 15 μV/ppm, a detection limit of 90 ppm, and a resolution of 30 ppm. The total power consumption of the whole sensor system is 6.5 mW, with a maximum power consumption of only 90 mW.

Smart mid-infrared metasurface microspectrometer gas sensing system

Smart, low-cost and portable gas sensors are highly desired due to the importance of air quality monitoring for environmental and defense-related applications. Traditionally, electrochemical and nondispersive infrared (IR) gas sensors are designed to detect a single specific analyte. Although IR spectroscopy-based sensors provide superior performance, their deployment is limited due to their large size and high cost. In this study, a smart, low-cost, multigas sensing system is demonstrated consisting of a mid-infrared microspectrometer and a machine learning algorithm. The microspectrometer is a metasurface filter array integrated with a commercial IR camera that is consumable-free, compact ( ~ 1 cm3) and lightweight ( ~ 1 g). The machine learning algorithm is trained to analyze the data from the microspectrometer and predict the gases present. The system detects the greenhouse gases carbon dioxide and methane at concentrations ranging from 10 to 100% with 100% accuracy. It also detects hazardous gases at low concentrations with an accuracy of 98.4%. Ammonia can be detected at a concentration of 100 ppm. Additionally, methyl-ethyl-ketone can be detected at its permissible exposure limit (200 ppm); this concentration is considered low and nonhazardous. This study demonstrates the viability of using machine learning with IR spectroscopy to provide a smart and low-cost multigas sensing platform.

Non-dispersive infrared SF6 sensor with temperature compensation using ISSA_BP neural network

Sulfur hexafluoride (SF6) is a widely used gas in the power industry, and its concentration monitoring is of great importance in power systems. In this study, a non-dispersive infrared (NDIR) gas sensor was developed for monitoring SF6 with a response time (t90) of 3–4 s. A dual-channel structure was designed to minimize the influence of other factors such as light sources. However, the sensor’s output signal is susceptible to temperature drift and non-linear characteristics. To address these challenges, a new compensation algorithm of improved sparrow search algorithm based on the backpropagation neural network (ISSA_BP) is presented to improve the temperature dependence and to correct the nonlinear errors of the sensors. The ISSA_BP algorithm extracts features from sensor-collected signals and predicts the concentration of SF6 gas by the BP neural network. The levy flight strategy and sine-cosine factor are employed within the sparrow search algorithm (SSA) to improve the efficiency and accuracy of the method. The experimental results show that the proposed model outperforms the state-of-the-art approaches, achieving an average relative error of 0.02 within the range of −10°C to 45°C and gas concentrations from 0 ppm to 5000 ppm, which is 3% lower than the industry standard. Compared with traditional approaches, the measurement accuracy is improved approximately by 0.02–0.03, confirming that the proposed algorithm has a high reference value for temperature compensation and nonlinear calibration, which is applicable in the production of infrared sensors for industrial settings.

Designing an optical gas chamber with stepped structure for non-dispersive infrared methane gas sensor

Compared to traditional semiconductor and electrochemistry gas sensors, the non-dispersive infrared (NDIR) gas detection technology presents notable advantages in terms of stability and selectivity. However, the high-performance NDIR gas sensor generally requires a long optical path, resulting in a large gas chamber. In this short communication, a simple and relatively small stepped optical gas chamber (45 mm × 20 mm × 30 mm) with long optical path (94.92 mm) is designed combining simulation method. Furthermore, the stepped optical gas chamber based on the simulation structure is fabricated by a computer number control technique, and used to fabricate a NDIR gas sensor. The results show that the NDIR gas sensor based on the stepped optical gas chamber can be successfully used for CH4 gas detection with a wide detection range and good repeatability. This work provides an optional reference for developing compact NDIR gas sensor.

Compact, real-time exhaust gas recirculation rate sensor for use in natural gas combustion engine control

Natural gas fueled engines offer a 25% reduction in greenhouse gas emissions compared to diesel. However, achieving similar fuel efficiency to diesel while also minimizing harmful emissions is a challenge. Emissions and efficiency targets can be simultaneously achieved for natural gas by using a three way catalyst and exhaust gas recirculation (EGR), but this requires that the air-fuel ratio and EGR rate be measured and precisely controlled to avoid knocking combustion while maximizing efficiency. Such on-engine control can be achieved with high speed, precise, and robust measurements of EGR rate at a size and cost level compatible with onboard control systems. In this work, we present a compact, real-time laser absorption spectroscopy-based EGR sensor with potential for low-cost, on-engine control. We develop a new, computationally efficient data fitting algorithm called Integral Hashing to enable fully autonomous, low latency, real-time operation of the laser sensor at 954Hz. The complete sensor, including lasers and drivers, data acquisition, and data processing is contained in a single 25 × 25 × 8cm enclosure supplied with 15W of power. We validate the sensor to within 2% EGR rate against an extractive non-dispersive infrared (NDIR) gas sensor on a 250kW 6 cylinder natural gas engine by simultaneously measuring a set of steady state EGR rates between 0% and 25%. Additionally, we measure transient EGR rate fluctuations that are too fast to detect with the NDIR measurement. The sensor system presented here could be used to precisely control the EGR rate, improving the efficiency, emissions, and overall adoption of natural gas engines.

Novel pyroelectric single crystals PIN-PMN-PT and their applications for NDIR gas detectors

Ternary manganese-doped (1−x−y)Pb(In1/2Nb1/2)O3-xPb(Mg1/3Nb2/3)O3-yPbTiO3 (Mn-doped PIN-PMN-PT) single crystals have demonstrated remarkable pyroelectric properties alongside enhanced temperature stability. These attributes hold substantial promise for the advancement of high precision nondispersive IR (NDIR) applications. In this study, Mn-doped 0.21Pb(In1/2Nb1/2)O3-0.49Pb(Mg1/3Nb2/3)O3-0.30PbTiO3 single crystals were introduced and carefully investigated. A compensated structure of pyroelectric IR detector based on Mn-doped PIN-PMN-PT single crystal was designed and fabricated, and a CO2 gas concentration monitoring module was built. Results showed that Mn-doped PIN-PMN-PT single crystals exhibit high pyroelectric coefficient, and better thermal stability than binary (1−x)Pb(Mg1/3Nb2/3)O3-xPbTiO3 system. The compensated pyroelectric IR detectors using Mn-doped PIN-PMN-PT single crystals as element chips showcase a performance that is approximately fourfold higher than that of commercial LiTaO3 pyroelectric detectors. The NDIR CO2 gas sensor module was assembled and exhibited remarkable accuracy along with an impressively low minimum detection concentration. These outcomes underscores its substantial potential for practical utilization in gas monitoring applications.

Development of a compact NDIR CO2 gas sensor for harsh environments

We present a compact non-dispersive infrared (NDIR) gas sensor that can be adopted in high-moisture and low temperature environments. The NDIR gas sensor was formed by a Micro-Electro-Mechanical Systems (MEMS) emitter working at 400℃ with a broadband radiation spectrum, a MEMS thermopile detector that integrated with an optical filter, a compact gas-cell with high optical coupling efficiency of ∼ 48 %, and an imbedded miniature thermostat. The footprint of the sensor is 24 mm × 8 mm × 8 mm (length × width × height), making it just 30 % of the size of conventional NDIR gas sensors with equivalent detection resolution, and its heat capability is around 7.29 J/K that promise a cost-effective thermoregulation. The sensor is capable of accurately detecting gas, such as Carbon dioxide, within a concentration range spanning from 0.5 % to 20 % with a reading error of ± 0.1 % covering a working temperature from −20 ℃ to 60 ℃. Because the sensor is equipped with a waterproof breathable film at the air hole, the sensor can operate in the humidity range from 0 to 100 %RH, and the maximum detection reading error is 0.1 % ± 230 ppm. It is possible to be applied for both low temperature environments (e.g. food preservation cabinet, biological cabinet, etc) and high-moisture environments (e.g. greenhouse, humidity chambers, etc.).

Hydrofluoroolefins Leakage Detection by Nondispersive Infrared Gas Sensor Using InAsSb Light Emitting Diodes and Photodiodes

Hydrofluoroolefins Leakage Detection by Nondispersive Infrared Gas Sensor Using InAsSb Light Emitting Diodes and Photodiodes

Fluid Dynamics Analysis in NDIR Gas Sensor Capsule Designed with Convergent Nozzles

Non-dispersive infrared (NDIR) gas sensor capsules have holes for gas inlet-outlet. The volumetric flow rate of the target gas into the sensor capsule is a significant factor affecting the fast and accurate measurement of gas concentration. The structure and dimensions of the holes in the capsule affect the volumetric flow rate of the target gas. If cylindrical holes are preferred in sensor capsules, it is necessary to enlarge the hole diameter to increase the volumetric flow rate of the gas. However, enlarging the hole diameter in NDIR gas sensors increases IR rays exiting the sensor capsule. This energy loss reduces the light concentration reaching the detector and adversely affects sensor performance. One of the ways to increase the volumetric flow of gas passing through the barrier without enlarging the hole diameter is the use of a convergent nozzle structure. Convergent nozzles increase the gas inlet velocity by increasing the pressure difference between the inner and outer points of the barrier, thanks to their structure. In this study, fluid dynamics analysis was conducted in a sensor capsule with cylindrical holes of different diameters 1mm and 1.5 mm, and convergent nozzles of two different sizes 1.5 mm to 1mm and 2 mm to 1 mm. According to the results obtained, when 1.5 mm to 1 mm convergent nozzles are used, the gas’s volumetric flow rate is approximately the same as when using cylindrical holes with a diameter of 1.5 mm. Thus, the same result is obtained without increasing the hole area in the capsule by 2.25 times by using convergent nozzles, and additional IR rays are prevented from exiting the sensor capsule. Even higher volumetric flow rate values have been achieved using 2 mm to 1 mm convergent nozzles. With this study, the importance of the structure of the holes where the gas enters the capsule is emphasized for the fast and accurate operation of NDIR gas sensors.

Research on the Seed Respiration CO2 Detection System Based on TDLAS Technology

The traditional detection method of CO2 concentration in seed respiration has defects such as low detection accuracy, low detection efficiency, and inability to monitor in real time. In order to solve these problems, we report a seed respiration CO2 detection system based on wavelength modulation spectroscopy (WMS) techniques in tunable diode laser absorption spectroscopy (TDLAS). This system uses a 2004 nm distributed feedback (DFB) laser as the light source, and a double-layer seed respiration device (about 1.5 L) is designed based on Herriott cell with an effective optical path of about 21 meters. Then, the second harmonic (2f) signal is extracted by the wavelength modulation method for CO2 concentration inversion. When the ambient temperature and pressure changes greatly, the corrected 2f signal is used for CO2 concentration inversion to improve the accuracy. A series of verification and comparison experiments have proved that the seed respiration CO2 detection system has the advantages of strong stability, high sampling frequency, and high detection accuracy. Finally, we used the developed system to measure the respiration intensity and respiration rate of 1 g corn seeds. The respiration intensity curves and respiration rate change details show that the seed respiration CO2 detection system is more suitable for a small amount of seeds than nondispersive infrared (NDIR) CO2 sensor and gas chromatography in real-time monitoring of the breathing process.

Physicochemical Parameters and Microbial Community in Anaerobic Digestion of Organic Wastes

The demand for an alternative source of energy and challenge of increase in wastes pollution initiates the need for renewable energy and management of waste using anaerobic digestion (AD). Anaerobic digestion is an effective and efficient method of waste treatment and energy generation. The study focused on investigating the physicochemical parameters and microbial community in anaerobic digestion of organic wastes and was conducted using chicken wastes and food wastes as organic substrate under semi-continuous conditions at hydraulic retention time (HRT) of forty-two (42) days in fifteen liter (15L) fabricated digesters labeled D1, D2 and D3 at 37OC. The pH, volatile fatty acid (VFA), moisture content (MC), total ammonia, total solid, volatile solid, alkalinity was assessed before and after digestion while the microbial community diversity was analyzed using 16S rRNA amplicon-based nextgeneration sequencing (NGS). The results indicated a pH value of 6.65 ± 0.12, 7.27 ± 0.13, 6.43 ± 0.27, volatile fatty acid of 72.17 ± 1.42, 58.35 ± 2.58, 40.56 ± 0.38 and moisture content of 98.9 ± 2.65, 92.3 ± 1.81, 96.4 ± 3.60 at day 42 for D1 (Chicken waste and food wastes), D2 (Chicken wastes+), D3 (control) respectively. A collective biogas yield of 686±17.00 kpa for D1, 700±11.00kpa for D2 and 521±21.00 kpa for D3 were recorded. The characterization of biogas analyzed with nondispersive infrared (NDIR) gas analyzer (gas board 3100p) revealed a percentage methane content of 46.11±1.11, 52.4±1.05, 50.31±1.33 for D1, D2 and D3 respectively. The microbial community identified phylum Bacteroidetes, Firmicutes, proteobacteria, Tenericutes, Verrucomicrobia, Actinobacteria, Euryarchaeota among others. The study shows that physicochemical properties and microbial community diversity are useful tools to indicate digester performance and also to enhance anaerobic digestion process.

Identification and characterization of microbial community of anaerobic digested poultry litter

Livestock farming have resulted in the release of excessive wastes which, contains abundant organic matter and microbial population. The need to develop an alternative and sustainable methods to minimize the waste generated and it effects on the environment led to the application of anaerobic digestion (AD) for the treatment of waste and generation of methane gas. The study focused on investigation of the microbiome involve in AD of poultry litter and was conducted using poultry litter as organic substrate under batch conditions at hydraulic retention time (HRT) of fifty-six (56) days in fifteen (15) liter fabricated digesters at 37OC. The pH, total solid (TS), moisture content (MC) total ammonia nitrogen, volatile solid (VS) was assessed before and after digestion while the microbial community diversity was analyzed using 16S rRNA amplicon-based next-generation sequencing (NGS). The results indicated a pH of 7.91±0.04 before digestion and 7.33±0.06 after digestion and a TS value of 56.40±0.6% before digestion and 6.30±0.34% after digestion. A collective biogas yield of 5.21±21.00 bars were recorded. The characterization of biogas analyzed with non-dispersive infrared (NDIR) gas analyzer (gas board 3100p) revealed a percentage methane content of 50.31±1.33. The microbial community indicate Bacteroidetes (46.37%), Firmicutes (48.37%), Proteobacteria (8.17%), as the most dominant phylum. This study suggests the importance of molecular analysis as a fundamental tool to gain insight and deeper understanding of anaerobic digester performances.

Actively variable-spectrum optoelectronics with black phosphorus.

Room-temperature optoelectronic devices that operate at short-wavelength and mid-wavelength infrared ranges (one to eight micrometres) can be used for numerous applications1-5. To achieve the range of operating wavelengths needed for a given application, a combination of materials with different bandgaps (for example, superlattices or heterostructures)6,7 or variations in the composition of semiconductor alloys during growth8,9 are used. However, these materials are complex to fabricate, and the operating range is fixed after fabrication. Although wide-range, active and reversible tunability of the operating wavelengths in optoelectronic devices after fabrication is a highly desirable feature, no such platform has been yet developed. Here we demonstrate high-performance room-temperature infrared optoelectronics with actively variable spectra by presenting black phosphorus as an ideal candidate. Enabled by the highly strain-sensitive nature of its bandgap, which varies from 0.22 to 0.53 electronvolts, we show a continuous and reversible tuning of the operating wavelengths in light-emitting diodes and photodetectors composed of black phosphorus. Furthermore, we leverage this platform to demonstrate multiplexed nondispersive infrared gas sensing, whereby multiple gases (for example, carbon dioxide, methane and water vapour) are detected using a single light source. With its active spectral tunability while also retaining high performance, our work bridges a technological gap, presenting a potential way of meeting different requirements for emission and detection spectra in optoelectronic applications.

A design of an ultra-compact infrared gas sensor for respiratory quotient (qCO2) detection

We present an integrated non-dispersive infrared (NDIR) gas sensor for respiratory quotient (qCO2) detection with ultra-compact size and low-power consumption. The NDIR gas sensor consists of a MEMS emitter with broadband radiation, a special designed gas-cell with high optical coupling efficiency, and a MEMS thermopile detector. The minimum size of the sensor is 10 mm × 10 mm × 4 mm (length × width × height) which is only 10 % of the size of conventional NDIR gas sensors with the same gas detection resolution of around 65 ppm. The sensor is suitable for detecting gas (e.g. CO2) with concentrations in the range of 0.5 – 20 %. This sensor has potentials to be adopted by portable breath analyzers and indoor air quality monitoring systems, etc.

Development of a MEMS hotplate-based photoacoustic CO2 sensor

Instead of the conventional use of micro-electro-mechanical system (MEMS) hotplate for metal oxide semiconductor (MOS) or nondispersive infrared (NDIR) gas sensing, it was used for photoacoustic (PA) gas sensing. A low-cost MEMS microphone was used for the development of this MEMS hotplate PA carbon dioxide (CO2) sensor. To the knowledge of the authors, this is the first time that a MEMS hotplate and a MEMS microphone are combined for use in gas sensing with high modulation frequency. NDIR sensors use much more expensive photodetectors compared to the MEMS microphone used in this work. The MEMS hotplate and MEMS microphone have the desired characteristics of low power consumption, small size and low cost. The hotplate as a blackbody is a good infrared emitter which is suitable for CO2 detection around the 4.26 µm absorption band. Despite the significant radiation power loss due to high modulation frequency, the remaining/reduced power radiation power was still sufficient to excite CO2 molecules for PA signal generation. Temperature analysis on the sensor showed that PA signal decreases with an increase in temperature, which implies that compensation must be provided for such temperature effects. This work provides alternative optical gas sensing that is comparatively inexpensive compared to the conventional NDIR sensors and by using components that can be easily mass-produced, thereby making a valuable contribution to the fight against air pollution and global warming.

Chamberless NDIR CO2 Sensor Robust against Environmental Fluctuations.

Accuracy of CO2 measurement is affected by ambient air fluctuations, making the compensation of such variations in drift-like sensor response essential for concentration level assessment. Here, a series of experiments were carried out with a chamberless approach in a nondispersive infrared (NDIR) gas sensor to examine the combined effect of environmental temperature and relative humidity fluctuations on sensor responses at different concentrations of CO2. To eliminate the drift-like terms caused by environmental fluctuations, the behavior of the sensor was modeled to include ambient temperature, relative humidity, the measured responses as the inputs, and the concentration level as the output. The sensor was fabricated by a light source with an embedded parabolic reflector, a thermopile detector, and two reflective walls that are exposed to the applicable range of CO2 gas. The predicted concentration level was determined by analyzing the system and acquiring a heuristic function based on an ensemble regression model. The created model's reliability and sensor's performance were evaluated by the test and validation data, and the respective accuracies of 99.83 and 98.90% demonstrated the model effectiveness. The chamberless structure of the sensor provides reduction in diffusion time, improves the linearity of responses accompanied by eliminating drift-like variation of responses in varying ambient conditions, and prepares the sensor for industrial applications.

Breath emulator for simulation and modelling of expired tidal breath carbon dioxide characteristics

BackgroundIn this work we describe a breath emulator system, used to simulate temporal characteristics of exhaled carbon dioxide (CO2) concentration waveform versus time simulating how much CO2 is present at each phase of the human lung respiratory process. The system provides a method for testing capnometers incorporating fast response non-dispersive infrared (NDIR) CO2 gas sensing devices - in a clinical setting, capnography devices assess ventilation which is the CO2 movement in and out of the lungs. A mathematical model describing the waveform of the expired CO2 characteristic and influence of CO2 gas sensor noise factors and speed of response is presented and compared with measured and emulated data. ObjectiveA range of emulated capnogram temporal waveforms indicative of normal and restricted respiratory function demonstrated. The system can provide controlled introduction of water vapour and/ or other gases, simulating the influence of water vapour in exhaled breath and presence of other gases in a clinical setting such as anaesthetic agents (eg N2O). This enables influence of water vapour and/ or other gases to be assessed and modelled in the performance of CO2 gas sensors incorporated into capnography systems. As such the breath emulator provides a means of controlled testing of capnometer CO2 gas sensors in a non-clinical setting, allowing device optimisation before use in a medical environment. MethodsThe breath emulator uses a unique combination of mass flow controllers, needle valves and a fast acting switchable pneumatic solenoid valve (FASV), used to controllably emulate exhaled CO2 temporal waveforms for normal and restricted respiratory function. Output data from the described emulator is compared with a mathematical model using a range of input parameters such as time constants associated with inhalation/ exhalation for different parts of the respiratory cycle and CO2 concentration levels. Sensor noise performance is modelled, taking into account input parameters such as sampling period, sensor temperature, sensing light throughput and pathlength. ResultsThe system described here produces realistic human capnographic waveforms and has the capability to emulate various waveforms associated with chronic respiratory diseases and early stage detection of exacerbations. The system has the capability of diagnosing medical conditions through analysis of CO2 waveforms.Demonstrated in this work the emulator has been used to test NDIR gas sensor technology deployed in capnometer devices prior to formal clinical trialling.

Non-dispersive infrared multi-gas sensing via nanoantenna integrated narrowband detectors

Non-dispersive infrared (NDIR) spectroscopy analyzes the concentration of target gases based on their characteristic infrared absorption. In conventional NDIR gas sensors, an infrared detector has to pair with a bandpass filter to select the target gas. However, multiplexed NDIR gas sensing requires multiple pairs of bandpass filters and detectors, which makes the sensor bulky and expensive. Here, we propose a multiplexed NDIR gas sensing platform consisting of a narrowband infrared detector array as read-out. By integrating plasmonic metamaterial absorbers with pyroelectric detectors at the pixel level, the detectors exhibit spectrally tunable and narrowband photoresponses, circumventing the need for separate bandpass filter arrays. We demonstrate the sensing of H2S, CH4, CO2, CO, NO, CH2O, NO2, SO2. The detection limits of common gases such as CH4, CO2, and CO are 63 ppm, 2 ppm, and 11 ppm, respectively. We also demonstrate the deduction of the concentrations of two target gases in a mixture.

Near-field resonant photon sorting applied: dual-band metasurface quantum well infrared photodetectors for gas sensing

Abstract Two photodetectors for measuring transmission and two bulky, separated narrowband filters for picking a target gas absorption line and a non-absorbing reference from broadband emission are typically required for dual-band non-dispersive infrared (NDIR) gas sensing. Metal-dielectric-metal (MDM) metasurface plasmon cavities, precisely controllable narrowband absorbers, suggest a next-generation, nanophotonic approach. Here, we demonstrate a dual-band MDM cavity detector that consolidates the function of two detectors and two filters into a single device by employing resonant photon sorting-a function unique to metasurfaces. Two MDM cavities sandwiching a quantum well infrared photodetector (QWIP) with distinct resonance wavelengths are alternately arranged in a subwavelength period. The large absorption cross section of the cavities ensures ~95% efficient lateral sorting of photons by wavelength into the corresponding detector within a near-field region. The flow of incident photons is thus converted into two independent photocurrents for dual-band detection. Our dual-band photodetectors show competitive external quantum efficiencies up to 38% (responsivity 2.1 A/W, peak wavelength 6.9 5m) at 78 K. By tailoring one resonance to an absorption peak of NO2 (6.25 5m) and the other to a non-absorbing reference wavelength (7.15 5m), NDIR NO2 gas sensing with 10 ppm accuracy and 1 ms response times is demonstrated. Through experiment and numerical simulation, we confirm near-perfect absorption at the resonant cavity and suppressed absorption at its non-resonant counterpart, characteristic of resonant photon sorting. Dual-band sensing across the mid-infrared should be possible by tailoring the cavities and quantum well to desired wavelengths.