This work presents the recent development of a fiber-coupled multipass near-infrared (NIR) gas sensor used to monitor water vapor desorption of small material coupons. The gas sensor design employs a White cell topology to maximize the optical path length over a compact, hand-size footprint. Water vapor concentrations are quantified over a large dynamic range by simultaneously applying wavelength modulation and tunable diode laser absorption spectroscopy techniques. A custom headspace optimized for material desorption experiments is assembled using commercially available vacuum chamber components. We provide in situ measurements of water vapor desorption from two geometries of the industrially important silicone elastomer Sylgard-184 as a case study for sensor viability. To corroborate the results, the gas sensor data are compared to numerical simulations based on a triple-mode diffusion–sorption model, consisting of Henry, Langmuir, and Pooling modes.

Conventional detection schemes for nucleic-acid based electrochemical sensors involve a layer of single-stranded DNA (ssDNA) capture probe that is attached to the working electrode at one end and labeled with a redox reporter at the opposite end. Upon electrochemical interrogation, the probe layer produces a current, which is attenuated upon hybridization with the target DNA or RNA biomarker due to conformational change of the ssDNA. The decrease in current, referred to as percent signal suppression (%SS), indicates successful hybridization. Since the probe and target signals need to be successively acquired for accurately determining %SS, this method is not suitable for sample collection at a site without electrochemical analysis capabilities. Here, we introduce a new approach, where the sample can be blotted onto an electrode that is pre-functionalized with probe DNA. In this scheme, post-hybridization current is obtained first, followed by melting the hybridized DNA duplex in warm deionized water for subsequent acquisition of the post-melt current. The increase in cur-rent upon melting, which we refer to as percent signal enhancement (%SE), similarly indicates presence of tar-get DNA with comparable performance to a standard electrochemical detection technique at representative 2 µM and 100 nM target concentrations. The performance of planar and nanoporous gold (np-Au) electrodes are compared for DNA detection in complex biological samples where np-Au exhibits biofouling-resilient sensing. Finally, remote sample collection is simulated by blotting the complex sample on np-Au electrodes for %SE de-termination, where target DNA is successfully detected.

This work introduces a new electrochemical sensing approach, where the liquid sample containing nucleic acid targets can be blotted onto an electrode that is pre-functionalized with probe DNA for offline analysis.

Vanadium oxides (VOxs) are technologically important materials because of their versatile properties, including a reversible metal-insulator transition. However, the complex vanadium-oxygen phase diagram includes numerous stable stoichiometries and metastable polymorphs, making material identification challenging. This work presents a data-driven, nondestructive characterization workflow that combines Raman spectroscopy and principal component analysis (PCA) to provide rapid and intelligent feedback during VOx thin-film fabrication. Although Raman spectroscopy provides ultrasensitive chemical information, conventional spectral interpretation requires specialized expertise and extensive reference data. An in-house fabrication protocol based on spin-casting chemical precursors and thermal annealing was developed to produce thin-film standards of VO₂, V₂O₅, V₃O₇, and V₆O₁₃. Raman fingerprints from these standards were used to construct two- and three-dimensional PCA models that distinguish stoichiometric variation and provide interpretable feedback during fabrication-process development. The standards also serve as references for evaluating thermally corroded samples. These results demonstrate that PCA-enabled Raman analysis can serve as an adaptive sensing approach for rapid assessment of VOx stoichiometry, simplified spectral interpretation, and fabrication optimization.