Selective detection of volatile organic compounds in microfluidic gas detectors based on "like dissolves like"

Unveiling Colorectal Cancer Biomarkers: Harnessing Biosensor Technology for Volatile Organic Compound Detection

Conventional screening options for colorectal cancer (CRC) detection are mainly direct visualization and invasive methods including colonoscopy and flexible sigmoidoscopy, which must be performed in a clinical setting and may be linked to adverse effects for some patients. Non-invasive CRC diagnostic tests such as computed tomography colonography and stool tests are either too costly or less reliable than invasive ones. On the other hand, volatile organic compounds (VOCs) are potentially ideal non-invasive biomarkers for CRC detection and monitoring. The present review is a comprehensive presentation of the current state-of-the-art VOC-based CRC diagnostics, with a specific focus on recent advancements in biosensor design and application. Among them, breath-based chromatography pattern analysis and sampling techniques are overviewed, along with nanoparticle-based optical and electrochemical biosensor approaches. Limitations of the currently available technologies are also discussed with an outlook for improvement in combination with big data analytics and advanced instrumentation, as well as expanding the scope and specificity of CRC-related volatile biomarkers.

Microfluidics in environmental analysis: advancements, challenges, and future prospects for rapid and efficient monitoring

Microfluidic devices have emerged as advantageous tools for detecting environmental contaminants due to their portability, ease of use, cost-effectiveness, and rapid response capabilities. These devices have wide-ranging applications in environmental monitoring of air, water, and soil matrices, and have also been applied to agricultural monitoring. Although several previous reviews have explored microfluidic devices' utility, this paper presents an up-to-date account of the latest advancements in this field for environmental monitoring, looking back at the past five years. In this review, we discuss devices for prominent contaminants such as heavy metals, pesticides, nutrients, microorganisms, per- and polyfluoroalkyl substances (PFAS), etc. We cover numerous detection methods (electrochemical, colorimetric, fluorescent, etc.) and critically assess the current state of microfluidic devices for environmental monitoring, highlighting both their successes and limitations. Moreover, we propose potential strategies to mitigate these limitations and offer valuable insights into future research and development directions.

Highly selective molecularly imprinted polymer nanoparticles (MIP NPs)-based microfluidic gas sensor for tetrahydrocannabinol (THC) detection

A highly selective microfluidic integrated metal oxide gas sensor for THC detection is reported based on MIP nanoparticles (MIP NPs). We synthesized MIP NPs with THC recognition sites and coated them on a 3D-printed microfluidic channel surface. The sensitivity and selectivity of coated microfluidic integrated gas sensors were evaluated by exposure to THC, cannabidiol (CBD), methanol, and ethanol analytes in 300-700 ppm at 300 °C. For comparison, reference signals were obtained from a microfluidic channel coated with nonimprinted polymers (NIP NPs). The MIP and NIP NPs were characterized using scanning electron microscopy (SEM) and Raman spectroscopy. MIP and NIP NPs channels response data were combined and classified with 96.3% accuracy using the Fine KNN classification model in MATLAB R2021b Classification Learner App. Compared to the MIP NPs coated channel, the NIP NPs channel had poor selectivity towards THC, demonstrating that the THC recognition sites in the MIP structure enabled selective detection of THC. The findings demonstrated that the recognition sites of MIP NPs properly captured THC molecules, enabling the selective detection of THC compared to CBD, methanol, and ethanol.

Microfluidic integrated gas sensors for smart analyte detection: a comprehensive review

The utilization of gas sensors has the potential to enhance worker safety, mitigate environmental issues, and enable early diagnosis of chronic diseases. However, traditional sensors designed for such applications are often bulky, expensive, difficult to operate, and require large sample volumes. By employing microfluidic technology to miniaturize gas sensors, we can address these challenges and usher in a new era of gas sensors suitable for point-of-care and point-of-use applications. In this review paper, we systematically categorize microfluidic gas sensors according to their applications in safety, biomedical, and environmental contexts. Furthermore, we delve into the integration of various types of gas sensors, such as optical, chemical, and physical sensors, within microfluidic platforms, highlighting the resultant enhancements in performance within these domains.

An electrochemical aptasensor for Δ9-tetrahydrocannabinol detection in saliva on a microfluidic platform

We present a novel "on-off", cost-effective, rapid electrochemical aptasensor combined with a microfluidics cartridge system for the detection of Δ⁹-THC (Δ⁹-tetrahydrocannabinol) in human saliva via differential pulse voltammetry. The assay relied on the competitive binding between the Δ⁹-THC and a soluble redox indicator methylene blue, using an aptamer selected via FRELEX. We found that the aptasensor can detected 1 nM of Δ⁹-THC in PBS in a three-electrode cell system, while the sensitivity and both the dissociation constant (K_d) and association constant (K_b) were dependent on the aptamer density. The aptamer also showed great affinity towards Δ⁹-THC when tested against cannabinol and cannabidiol. The same limit of detection of 1 nM in PBS was achieved in small volume samples (∼60 μL) using the aptamer-modified gold screen-printed electrodes combined with the microfluidic cartridge setup, however, the presence of 10% raw human saliva had a negative effect which manifested in a 10-fold increase in the LOD due to interfering elements. Filtering the saliva, improved the tested volume to 50% and the LOD to 5 nM of Δ⁹-THC which is lower than the concentrations associated with impairment (6.5-32 nM). The aptasensor showed a good storage capability up to 3 days, however, the reusability significantly dropped from 10 cycles (freshly prepared) to 5 cycles. The results clearly demonstrate the feasibility of the aptasensor platform with the microfluidics chamber towards a point-of-care testing application for the detection of Δ⁹-THC in saliva.

Microfluidic Gas Sensors: Detection Principle and Applications

With the rapid growth of emerging point-of-use (POU)/point-of-care (POC) detection technologies, miniaturized sensors for the real-time detection of gases and airborne pathogens have become essential to fight pollution, emerging contaminants, and pandemics. However, the low-cost development of miniaturized gas sensors without compromising selectivity, sensitivity, and response time remains challenging. Microfluidics is a promising technology that has been exploited for decades to overcome such limitations, making it an excellent candidate for POU/POC. However, microfluidic-based gas sensors remain a nascent field. In this review, the evolution of microfluidic gas sensors from basic electronic techniques to more advanced optical techniques such as surface-enhanced Raman spectroscopy to detect analytes is documented in detail. This paper focuses on the various detection methodologies used in microfluidic-based devices for detecting gases and airborne pathogens. Non-continuous microfluidic devices such as bubble/droplet-based microfluidics technology that have been employed to detect gases and airborne pathogens are also discussed. The selectivity, sensitivity, advantages/disadvantages vis-a-vis response time, and fabrication costs for all the microfluidic sensors are tabulated. The microfluidic sensors are grouped based on the target moiety, such as air pollutants such as carbon monoxide and nitrogen oxides, and airborne pathogens such as E. coli and SARS-CoV-2. The possible application scenarios for the various microfluidic devices are critically examined.

Selective monitoring of natural gas sulphur-based odorant mixture of t-butyl mercaptan and methyl ethyl sulphide using an array of microfluidic gas sensors

A natural gas (NG) odorization system requires continuous monitoring as well as an optimal injection to satisfy the odorization guidelines, minimize over-odorization, and prevent hazardous gas leaks. NG consists of hydrocarbons such as methane, odorants such as tert-butyl mercaptan, and other sulphur-based VOCs such as hydrogen sulphide; therefore, selectivity is paramount for the reliable and accurate monitoring of odorants. In this study, we developed a portable device integrated with an array of five different sensors to detect a mixture of tert-butyl mercaptan and methyl ethyl sulphide for a concentration range of 1 ppm to 10 ppm. A machine learning model was developed to predict the presence and concentration of NG odorants from the sensor data. The best-performing sensors in the array achieved high sensitivity and selectivity indicators (measured using the Davies-Bouldin index) of 0.3667 (1⁄ppm) and 0.125, respectively. The sensor system achieved a classification accuracy of 98.75% between NG odorants and hydrogen sulphide, with an overall Mean Squared Error (MSE) and R² error (for the regression model) of 0.50 and 95.16%. These results indicate that the developed portable device and the machine learning model have promising applications for the selective monitoring of NG odorants.

Gas Selectivity Enhancement Using Serpentine Microchannel Shaped with Optimum Dimensions in Microfluidic-Based Gas Sensor

A microfluidic-based gas sensor was chosen as an alternative method to gas chromatography and mass spectroscopy systems because of its small size, high accuracy, low cost, etc. Generally, there are some parameters, such as microchannel geometry, that affect the gas response and selectivity of the microfluidic-based gas sensors. In this study, we simulated and compared 3D numerical models in both simple and serpentine forms using COMSOL Multiphysics 5.6 to investigate the effects of microchannel geometry on the performance of microfluidic-based gas sensors using multiphysics modeling of diffusion, surface adsorption/desorption and surface reactions. These investigations showed the simple channel has about 50% more response but less selectivity than the serpentine channel. In addition, we showed that increasing the length of the channel and decreasing its height improves the selectivity of the microfluidic-based gas sensor. According to the simulated models, a serpentine microchannel with the dimensions W = 3 mm, H = 80 µm and L = 22.5 mm is the optimal geometry with high selectivity and gas response. Further, for fabrication feasibility, a polydimethylsiloxane serpentine microfluidic channel was fabricated by a 3D printing mold and tested according to the simulation results.

A non-porous Fe(II) complex for the colorimetric detection of hazardous gases and the monitoring of meat freshness

Food quality monitoring and freshness assessment are critical for ensuring food safety at a large scale. Ammonia is used as an important indicator of protein rich food spoilage state. However, current ammonia gas sensors suffer from insufficient sensitivity and selectivity, or sophisticated instrumentation, hindering their practical application in in-situ and real-time food quality monitoring. To overcome such limitations, an innovative nonporous colorimetric complex 1 has been synthesized and investigated for the detection of NH_3(g) and its volatile organic derivatives including aliphatic amines, 1,2-diaminopropane_(g), isobutylamine_(g) and ethylenediamine_(g), etc. The sensor operates colorimetrically at room temperature without energy input, with a detection limit to ammonia_(g) of 105 ppb, and show excellent reusability. The colorimetric detection mechanism involves a partial spin state change of Fe(II) ions upon exposure to amines in the gas phase. In addition, the complex was utilized as real-time monitoring of meat freshness using a smartphone. Thus, chemosensor 1 is considered as a ground breaking new-generation portable electronic nose for vapors of volatile organic compounds discrimination at room temperature.

Sensors for Volatile Organic Compounds

This paper provides an overview of recent developments in the field of volatile organic compound (VOC) sensors, which are finding uses in healthcare, safety, environmental monitoring, food and agriculture, oil industry, and other fields. It starts by briefly explaining the basics of VOC sensing and reviewing the currently available and quickly progressing VOC sensing approaches. It then discusses the main trends in materials' design with special attention to nanostructuring and nanohybridization. Emerging sensing materials and strategies are highlighted and their involvement in the different types of sensing technologies is discussed, including optical, electrical, and gravimetric sensors. The review also provides detailed discussions about the main limitations of the field and offers potential solutions. The status of the field and suggestions of promising directions for future development are summarized.

Emerging Methods of Monitoring Volatile Organic Compounds for Detection of Plant Pests and Disease

Each year, unwanted plant pests and diseases, such as Hendel or potato soft rot, cause damage to crops and ecosystems all over the world. To continue to feed the growing population and protect the global ecosystems, the surveillance and management of the spread of these pests and diseases are crucial. Traditional methods of detection are often expensive, bulky and require expertise and training. Therefore, inexpensive, portable, and user-friendly methods are required. These include the use of different gas-sensing technologies to exploit volatile organic compounds released by plants under stress. These methods often meet these requirements, although they come with their own set of advantages and disadvantages, including the sheer number of variables that affect the profile of volatile organic compounds released, such as sensitivity to environmental factors and availability of soil nutrients or water, and sensor drift. Furthermore, most of these methods lack research on their use under field conditions. More research is needed to overcome these disadvantages and further understand the feasibility of the use of these methods under field conditions. This paper focuses on applications of different gas-sensing technologies from over the past decade to detect plant pests and diseases more efficiently.

Lab-on-a-Chip Platforms for Airborne Particulate Matter Applications: A Review of Current Perspectives

Lab-on-a-Chip (LoC) devices are described as versatile, fast, accurate, and low-cost platforms for the handling, detection, characterization, and analysis of a wide range of suspended particles in water-based environments. However, for gas-based applications, particularly in atmospheric aerosols science, LoC platforms are rarely developed. This review summarizes emerging LoC devices for the classification, measurement, and identification of airborne particles, especially those known as Particulate Matter (PM), which are linked to increased morbidity and mortality levels from cardiovascular and respiratory diseases. For these devices, their operating principles and performance parameters are introduced and compared while highlighting their advantages and disadvantages. Discussing the current applications will allow us to identify challenges and determine future directions for developing more robust LoC devices to monitor and analyze airborne PM.

Selective detection of VOCs using microfluidic gas sensor with embedded cylindrical microfeatures coated with graphene oxide

Volatile organic compounds (VOCs) are major environmental pollutants. Exposure to VOCs has been associated with adverse health outcomes. The monitoring of hazardous VOCs is a vital step towards identifying their presence and preventing the risk of acute or chronic exposure and polluting the environment. One of the challenges associated with monitoring VOCs is selectivity of the sensor. Microfluidic gas sensors offer selective and sensitive detection capabilities that have been recently applied for detection of VOCs. In this study, we achieve improved selectivity for detection of a range of VOCs by adding micro- and nanofeatures to the microchannel of microfluidic gas sensors. First, microfeatures are embedded into the microchannel and their geometries are optimized using Taguchi design of experiment method. In the next step the microfeatures embedded microchannel is coated with graphene oxide, to increase the surface to volume ratio by introducing nanofeatures to the surfaces. The nano- and microfeatures are characterized by SEM, XPS, and water contact angle measurement. Finally, the changes in the sensor response are compared to plain microfluidic gas sensor, the results show an average of 64.4% and 120.9% improvement in the selectivity of the sensor with microfeatures and both nano- and microfeatures, respectively.

Noninvasive real-time breath test for controlling hormonal background of the human body: detection of serotonin and melatonin with quantum point-contact sensors

Significant progress in development of noninvasive diagnostic tools based on breath analysis can be expected if one employs a real-time detection method based on finding a spectral breath profile which would contain some energy characteristics of the analyzed gas mixture. Using the fundamental energy parameters of a quantum system, it is possible to determine with a high accuracy its quantitative and qualitative composition. Among the most efficient tools to measure energy characteristics of quantum systems are sensors based on Yanson point contacts. This paper reports the results of serotonin and melatonin detection as an example of testing the human hormonal background with point-contact sensors, which have already demonstrated their high efficiency in detecting carcinogenic strains ofHelicobacter pyloriand selective detection of complex gas mixtures. When comparing the values of serotonin and melatonin with the characteristic parameters of the spectral profile of the exhaled breath of each patient, high correlation dependences of the concentration of serotonin and melatonin with a number of characteristic parameters of the response curve of the point-contact sensor were found. The performed correlation analysis was complemented with the regression analysis. As a result, empiric regression relations were proposed to realize in practice the new non-invasive breath test for evaluation of the human hormonal background. Registration of the patient's breath profile using point-contact sensors makes it possible to easily monitor the dynamics of changes in the human hormonal background and perform a quantitative evaluation of serotonin and melatonin levels in the human body in real time without invasive interventions (blood collection) and expensive equipment or reagents.

Simulation of gas sensing mechanism of porous metal oxide semiconductor sensor based on finite element analysis

In recent years, finite element analysis is increasingly adopted to simulate the mechanism of metal oxide semiconductor (MOS) resistive gas sensors. In this article, the chemical reaction engineering module in the COMSOL Multiphysics tool is used to describe the dynamic equilibrium process of oxygen ions in the sensor. The boundary conditions of temperature transfer, conductivity model, and mass transfer are applied to simulate the convection, diffusion, and penetration processes. The response of the sensor at different temperatures (445 K-521 K) and different target gas concentrations (1-500 ppm) is simulated. In this paper, the dynamic model of oxygen ions is used creatively as a bridge between gas concentration and sensor response instead of the traditional direct parameter fitting method. The simulated result of the surface oxygen ion control and permeability control model of the MOS gas sensor shows a good agreement with the real sensor. For explaining the principle of metal oxide semiconductor gas sensors simulations has been performed on COMSOL Multiphysics software. The proposed method in this paper is based on the underlying transfer logic of the sensor signal, it is expected to predict the sensor signal and assist the sensor design.

A highly selective electron affinity facilitated H2S sensor: the marriage of tris(keto-hydrazone) and an organic field-effect transistor

Conjugated polymers (CPs) are emerging as part of a promising future for gas-sensing applications. However, some of their limitations, such as poor specificity, humidity sensitivity and poor ambient stability, remain persistent. Herein, a novel combination of a polymer-monomer heterostructure, derived from a CP (PDVT-10) and a newly reported monomer [tris(keto-hydrazone)] has been integrated in an organic field-effect transistor (OFET) platform to sense H₂S selectively. The hybrid heterostructure shows an unprecedented sensitivity (525% ppm^-1) and high selectivity toward H₂S gas. In addition, we demonstrated that the PDVT-10/tris(keto-hydrazone) OFET sensor has the lowest limit of detection (1 ppb), excellent ambient stability (∼5% current degradation after 150 days), good response-recovery behavior, and exceptional electrical behavior and gas response reproducibility. This work can help pave the way to incorporate futuristic gas sensors in a multitude of applications.

A nanoscale paper-based near-infrared optical nose (NIRON)

Electronic noses (e-nose) and optical noses (o-nose) are two emerging approaches for the development of artificial olfactory systems for flavor and smell evaluation. The current work leverages the unique optical properties of semiconducting single-wall carbon nanotubes (SWCNTs) to develop a prototype of a novel paper-based near-infrared optical nose (NIRON). We have drop-dried an array of SWCNTs encapsulated with a wide variety of peptides on a paper substrate and continuously imaged the emitted SWCNTs fluorescence using a CMOS camera. Odors and different volatile molecules were passed above the array in a flow chamber, resulting in unique modulation patterns of the SWCNT photoluminescence (PL). Quartz crystal microbalance (QCM) measurements performed in parallel confirmed the direct binding between the vapor molecules and the peptide-SWCNTs. PL levels measured before and during exposure demonstrate distinct responses to the four tested alcoholic vapors (ethanol, methanol, propanol, and isopropanol). In addition, machine learning tools directly applied to the fluorescence images allow us to distinguish between the aromas of red wine, beer, and vodka. Further, we show that the developed sensor can detect limonene, undecanal, and geraniol vapors, and differentiate between their smells utilizing the PL response pattern. This novel paper-based optical biosensor provides data in real-time, and is recoverable and suitable for working at room temperature and in a wide range of humidity levels. This platform opens new avenues for real-time sensing of volatile chemical compounds, odors, and flavors.

Advancements in Microfabricated Gas Sensors and Microanalytical Tools for the Sensitive and Selective Detection of Odors

In recent years, advancements in micromachining techniques and nanomaterials have enabled the fabrication of highly sensitive devices for the detection of odorous species. Recent efforts done in the miniaturization of gas sensors have contributed to obtain increasingly compact and portable devices. Besides, the implementation of new nanomaterials in the active layer of these devices is helping to optimize their performance and increase their sensitivity close to humans' olfactory system. Nonetheless, a common concern of general-purpose gas sensors is their lack of selectivity towards multiple analytes. In recent years, advancements in microfabrication techniques and microfluidics have contributed to create new microanalytical tools, which represent a very good alternative to conventional analytical devices and sensor-array systems for the selective detection of odors. Hence, this paper presents a general overview of the recent advancements in microfabricated gas sensors and microanalytical devices for the sensitive and selective detection of volatile organic compounds (VOCs). The working principle of these devices, design requirements, implementation techniques, and the key parameters to optimize their performance are evaluated in this paper. The authors of this work intend to show the potential of combining both solutions in the creation of highly compact, low-cost, and easy-to-deploy platforms for odor monitoring.

Robust and Rapid Detection of Mixed Volatile Organic Compounds in Flow Through Air by a Low Cost Electronic Nose

This work aims to detect volatile organic compounds (VOC), i.e., acetone, ethanol and isopropyl alcohol (IPA) and their binary and ternary mixtures in a simulated indoor ventilation system. Four metal-oxide-semiconductor (MOS) gas sensors were chosen to form an electronic nose and it was used in a flow-through system. To speed up the detection process, transient signals were used to extracted features, as opposed to commonly used steady-state signals, which would require long time stabilization of testing parameters. Five parameters were extracted including three in phase space and two in time space. Classifier and regression models based on backpropagation neural network (BPNN) were used for the qualitative and quantitative detection of VOC mixtures. The VOCs were mixed at different ratios; ethanol and isopropyl alcohol had similar physical and chemical properties, both being challenging in terms of obtaining quantitative results. To estimate the amounts of VOC in the mixtures, the Levenberg–Marquardt algorithm was chosen in network training. When compared with the multivariate linear regression method, the BPNN-based model offered better performance on differentiating ethanol and IPA. The test accuracy of the classification was 82.6%. The concept used in this work could be readily translated for detecting closely related chemicals.

Towards Highly Efficient Polymer Fiber Laser Sources for Integrated Photonic Sensors

Lab-on-a-Chip (LoC) devices combining microfluidic analyte provision with integrated optical analysis are highly desirable for several applications in biological or medical sciences. While the microfluidic approach is already broadly addressed, some work needs to be done regarding the integrated optics, especially provision of highly integrable laser sources. Polymer optical fiber (POF) lasers represent an alignment-free, rugged, and flexible technology platform. Additionally, POFs are intrinsically compatible to polymer microfluidic devices. Home-made Rhodamine B (RB)-doped POFs were characterized with experimental and numerical parameter studies on their lasing potential. High output energies of 1.65 mJ, high slope efficiencies of 56%, and 50%-lifetimes of ≥900 k shots were extracted from RB:POFs. Furthermore, RB:POFs show broad spectral tunability over several tens of nanometers. A route to optimize polymer fiber lasers is revealed, providing functionality for a broad range of LoC devices. Spectral tunability, high efficiencies, and output energies enable a broad field of LoC applications.

Topical review on monitoring tetrahydrocannabinol in breath

Legalization of cannabis for recreational use has compelled governments to seek new tools to accurately monitor Δ9-tetrahydrocannabinol (Δ9-THC) and understand its effect on impairment. Various methods have been employed to measure Δ9-THC, and its respective metabolites, in different biological matrices. Recently, breath analysis has gained interest as a non-invasive method for the detection of chemicals that are either produced as part of biological processes or are absorbed from the environment. Existing breath analyzers function by analyzing previously collected samples or by direct real-time analysis. Portable hand-held devices are of particular interest for law enforcement and personal use. This paper reviews and compares both commercially available and prototype devices that proclaim Δ9-THC detection in exhaled breath using methods such as Field Asymmetric Ion Mobility Spectrometry, Semiconductor-Enriched Single-Walled Carbon Nanotube chemiresistors, Liquid Chromatography Tandem-mass Spectrometry, microfluidic-based artificial olfaction, and optical-based gas sensing.

A Nanostructured Microfluidic Artificial Olfaction for Organic Vapors Recognition

Selective and sensitive detection of volatile organic compounds (VOCs) is of great importance in applications involving monitoring of hazardous chemicals or non-invasive diagnosis. Here, polymethyl methacrylate nanoparticles with acetone recognition sites are synthesized and integrated into a 3D-printed microfluidic platform to enhance the selectivity of the device. The proposed microfluidic-based olfaction system includes two parylene C-coated microchannels, with or without polymer nanoparticles. The two channels are exposed to 200, 400, 800, 2000, and 4000 ppm of VOCs (methanol, ethanol, acetone, acetonitrile, butanone, and toluene), and sensor responses are compared using a 2D feature extraction method. Compared to current microfluidic-based olfaction systems, responses observed between coated and uncoated channels showed an increased recognition capability among VOCs (especially with respect to acetone), indicating the potential of this approach to increase and fine-tune the selectivity of microfluidic gas sensors.

Quantitative Assessment of Vapor Molecule Adsorption to Solid Surfaces by Flow Rate Monitoring in Microfluidic Channels

Measuring parameters related to gas adsorption on the effective surfaces of solid samples is important in catalyst studies. Further attention on the subject has appeared due to the materials and methods required to concentrate the gaseous biomarkers for detection. The conventional methods are mainly based on the volumetric and gravimetric analyses, which are applicable to bulk samples. No standard method has yet been provided for such measurements on thin films, which are the most commonly used samples for material screening. Here, a novel method is presented for the adsorption coefficient measurement on thin-film samples. This method comprises coating of the inner walls of a microfluidic channel with the thin film under test. The recorded diffusion rates for a trace gas along this microchannel are compared with the solutions of the adsorption-diffusion equation of the channel for determining the adsorption coefficient of the gas molecule to the inner walls of the channel. The high ratio of surface-to-volume in such channels magnifies the gas sorption effects and improves accuracy. The method is fast, versatile, and cost-effective, allowing measurements at different temperatures and atmospheric pressures. The adsorption coefficients of different isomers of butanol on poly(methyl methacrylate) sheets, zinc oxide thick films, and gold thin films are determined as examples.