Ion transport is a significant concept that underlies a variety of technologies including membrane technology, energy storages, optical, chemical, and biological sensors and ion-mobility exploration techniques. These applications are based on the concepts of capacitance and ion transport, so a prior understanding of capacitance and ion transport phenomena is crucial. In this review, the principles of capacitance and ion transport are described from a theoretical and practical point of view. The review covers the concepts of Helmholtz capacitance, diffuse layer capacitance and space charge capacitance, which is also referred to as quantum capacitance in low-dimensional materials. These concepts are attributed to applications in the electrochemical technologies such as energy storage and excitable ion sieving in membranes. This review also focuses on the characteristic role of channel heights (from micrometer to angstrom scales) in ion transport. Ion transport technologies can also be used in newer applications including biological sensors and multifunctional microsupercapacitors. This review improves our understanding of ion transport phenomena and demonstrates various applications that is applicable of the continued development in the technologies described.

Hyperspectral imaging (HSI) is an effective technique for material identification and classification, utilizing spectral signatures with applications in remote sensing, environmental monitoring, and allied disciplines. Despite its potential, the broader adoption of HSI technology is hindered by challenges related to compactness, affordability, and durability, exacerbated by the absence of standardized protocols for developing practical hyperspectral cameras. This study introduces a comprehensive framework for developing a compact, cost-effective, and robust hyperspectral camera, employing commercial off-the-shelf (COTS) components and a volume phase holographic (VPH) grism. The use of COTS components reduces development time and manufacturing costs while maintaining adequate performance, thereby improving accessibility for researchers and engineers. The incorporation of a VPH grism enables an on-axis optical design, enhancing compactness, reducing alignment sensitivity, and improving system robustness. The proposed framework encompasses spectrograph design, including optical simulations and tolerance analysis conducted in ZEMAX OpticStudio, alongside assembly procedures, performance assessment, and hyperspectral image acquisition via a pushbroom scanning approach, all integrated into a structured, step-by-step workflow. The resulting prototype, housed in an aluminum enclosure, operates within the 420–830 nm wavelength range, achieving a spectral resolution of 2 nm across 205 spectral bands. It effectively differentiates vegetation, water, and built structures, resolves atmospheric absorption features, and demonstrates the ability to distinguish materials in low-light conditions, providing a scalable and practical advancement in HSI technology.

This study presents a custom-built, portable multispectral imaging (MSI) system integrated with computer vision for sodium nitrite detection via the Griess reaction on paper-based substrates. The MSI system was used to investigate the absorption characteristics of sodium nitrite at concentrations from 0 to 10 ppm across nine spectral bands spanning 360–940 nm on para-aminobenzoic acid (PABA) and sulfanilamide (SA) substrates. Upon forming azo dyes with N-(1-naphthyl) ethylenediamine (NED), the PABA and SA substrates exhibited strong absorption near 545 nm and 540 nm, respectively, as measured by a spectrometer. This agrees with the 550 nm MSI images, in which higher sodium nitrite concentration regions appeared darker due to increased absorption. A concentration-correlation analysis was conducted for each spectral band. The normalized difference index (NDI), constructed from the most and least correlated bands at 550 nm and 940 nm, showed a stronger correlation with sodium nitrite concentration than the single best-performing band for both substrates. The NDI increased the coefficient of determination (R²) by approximately 19.32% for PABA–NED and 19.89% for SA–NED. This improvement was further confirmed under varying illumination conditions and through comparison with a conventional smartphone RGB imaging approach, in which the MSI-based NDI showed substantially superior performance. The enhancement is attributed to improved contrast, illumination normalization by the NDI, and the narrower spectral bands of the MSI compared with RGB imaging. In addition, the NDI framework enabled effective image segmentation, classification, and visualization, improving both interpretability and usability and providing a practical guideline for developing more robust models with larger training datasets. The proposed MSI system offers strong advantages in portability, sub-minute acquisition time, and operational simplicity, enabling rapid, on-site, and non-destructive chemical analysis.