Chemosensors

We propose a unique moisture sensing element (including humidity sensor) using carbon nanotube (CNT) composite paper. The CNT composite paper is a composite material consisting of CNTs and cellulose paper, which can be easily produced using a method based on the Japanese washi papermaking process. Since this composite paper contains CNTs, it is a conductive paper. In addition, the cellulose fibers that make up the paper are known to show a volume change of up to 35% with humidity. The proposed moisture sensing element uses this volume change and the electrical resistance derived from the CNT network contained in the composite paper. Through various experiments, it was confirmed that the electrical resistance of the CNT composite paper changes in response to moisture of various sizes, such as water droplets and vapors (humidity). It was concluded that these changes were the result of the volume change of paper fibers due to moisture, which greatly affected the structure of the CNT network contained within the composite paper. The results of this study will be useful for the practical application of simple and flexible paper-based moisture sensing elements in the near future.

A novel airborne pathogen detection method, based on Flashing Ratchet Potential (FRP) and Electric Current Spectroscopy (ECS), is presented. The system employs a precisely engineered asymmetric electrode array to generate controlled directional transport of oxygen ions (O₂⁻•), produced via thermionic emission and three-body electron attachment. As these ions interact with airborne particles in the detection zone, measurable perturbations in the ECS profile emerge, yielding distinct spectral signatures that indicate particle presence. Proof-of-concept experiments, using standardized talcum powder aerosols as surrogates for viral-scale particles, established optimal operating parameters of 6 V potential and 600 kHz modulation frequency, with reproducible detection signals showing a relative shift of 4.5–13.4% compared to filtered-air controls. The system’s design concept incorporates humidity-resilient features, intended to maintain stability under varying environmental conditions. Together with the proposed size selectivity (50–150 nm), this highlights its potential robustness for real-world applications. To the best of our knowledge, this is the first demonstration of an open-air electro-ratchet transport system coupled with electric current spectroscopy for bioaerosol monitoring, distinct from prior optical or electrochemical airborne biosensors, highlighting its promise as a tool for continuous environmental surveillance in high-risk settings such as hospitals, airports, and public transit systems.

This study explores the application of Mid-Infrared (MIR) and Near-Infrared (NIR) spectroscopy combined with various multivariate calibration techniques to detect the presence of cannabis in tobacco samples and tobacco in herbal smoking products. Both MIR and NIR spectra were recorded for self-prepared samples, followed by data exploration using Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA), and the calculation of binary classification models with Soft Independent Modelling of Class Analogy (SIMCA) and Partial Least Squares-Discriminant Analysis (PLS-DA). PCA demonstrated a clear differentiation between tobacco samples containing and not containing cannabis. On the other hand, based on PCA, only NIR was able to distinguish herbal smoking products adulterated and not adulterated with tobacco. HCA further clarified these results by revealing distinct clusters within the data. Modelling results indicated that MIR and NIR spectroscopy, particularly when paired with preprocessing techniques like Standard Normal Variate (SNV) and autoscaling, demonstrated high classification accuracy in SIMCA and PLS-DA, achieving correct classification rates of 90% to 100% for external test sets. Comparison of MIR and NIR revealed that NIR spectroscopy resulted in slightly more accurate models for the screening of tobacco samples for cannabis and herbal smoking products for tobacco. The developed approach could be useful for the initial screening of tobacco samples for cannabis, e.g., in a night life setting by law enforcement, but also for inspectors visiting shops selling tobacco and/or herbal smoking products.