In the field of biosensors, polymer thin films such as Nafion, poly(vinyl alcohol) (PVA), chitosan, and cellulose acetate (CA) have been introduced onto electrode surfaces to enhance the stability of catalytic materials and/or impart electrode selectivity. In this study, we investigated indium tin oxide (ITO) electrodes-whose modification with polymer protective layers has been relatively less explored-and evaluated the effects of polymer-layer incorporation in terms of (1) improved stability of the catalytic material and (2) the feasibility of charge-selective electrochemical detection. In addition, by comparing planar ITO with nanoporous-structured ITO electrodes, we aimed to identify the support that more clearly exhibits the protective effect and stability provided by the polymer layer. These findings provide a basis for expanding design and fabrication strategies for ITO-based biosensors.
In this study, CdSe quantum dots (QDs) were grown on mesoporous TiO2 films using the successive ionic layer adsorption and reaction (SILAR) method, and the effect of cationic bath pH on QD growth behavior and photoelectrode performance was systematically investigated. By introducing triethanolamine (TEA) into the Cd2+ precursor solution, the pH was increased above the point of zero charge of TiO2 , inducing a negatively charged surface that enhances electrostatic attraction toward Cd (2+) ions. As a result, the growth rate and surface coverage of CdSe QDs were significantly increased compared to the case without TEA. The accelerated growth and higher QD density were confirmed by visible color evolution, UV-Vis absorption spectroscopy, and transmission electron microscopy. Photoelectrochemical characterization revealed that the increased CdSe loading leads to substantially enhanced photocurrent generation in both quantum dot-sensitized solar cells and photoelectrochemical cells. Notably, the CdSe-sensitized TiO2 electrode prepared under basic conditions exhibited approximately 2.3 times higher photocurrent density during photoelectrochemical oxidation, along with stable and reproducible hydrogen evolution. These results demonstrate that electrostatic control of cation adsorption via pH modulation is a key parameter governing SILAR-grown metal chalcogenide QDs, providing valuable design guidelines for high-performance quantum dot-sensitized photoelectrodes.
Control of the microstructure of photocathodes is a key factor governing the efficiency of organic pollutant degradation in photoelectrochemical (PEC) water purification systems. Cu2O photocathodes were prepared via electrodeposition, and the relationship between applied deposition voltage, crystal structure, and PEC water purification performance was investigated. To promote preferential growth along the (111) crystallographic direction, the electrolyte pH was maintained at 11, and the potential window for stable Cu2O deposition was determined to be 0.3 to 0.7 V by linear sweep voltammetry. The structural properties of the electrodeposited Cu2O films were characterized by X-ray diffraction and scanning electron microscopy, while their PEC performance was evaluated using methyl orange as a model organic pollutant. The Cu2O photocathode deposited at 0.5 V exhibited a pronounced (111) preferred orientation, enlarged grain size, and a uniform film morphology, resulting in the highest photocurrent density and excellent operational stability under simulated 1-sun illumination. These findings demonstrate that precise control of electrodeposition voltage is crucial for optimizing the PEC performance of Cu O photocathodes and highlight their potential for environmentally friendly water purification applications.
Lithium-ion batteries (LIBs) are the dominant energy storage technology for portable electronics, electric vehicles, and grid applications. However, their performance deteriorates significantly at sub-zero temperatures due to sluggish electrochemical kinetics, reduced ion conductivity, and unstable electrode-electrolyte interfaces. This review summarizes the recent progress in low-temperature LIBs, focusing on electrode material design, electrolyte engineering, interface modification, and emerging strategies such as solid-state electrolytes and external thermal management. Challenges and future directions for realizing practical low-temperature LIBs in extreme environments are also discussed.
Anion exchange membranes (AEMs) underpin fuel cells and water electrolyzers, requiring a balance of ionic conductivity, chemical stability, dimensional control, and mechanical robustness. Recent machine learning (ML) studies introduce condition-aware surrogate models that predict anion conductivity and, in some cases, alkaline stability across diverse AEM chemistries. Interpretable pipelines relate structure and test conditions to performance, while unsupervised mapping supports pre-synthesis exploration. Scalable inverse-design workflows combine ML with heuristic search to screen large virtual libraries under conductivity-stability criteria. At the device level, data-driven models highlight membrane and operating parameters that govern anion exchange membrane water electrolysis (AEMWE) performance. This mini review summarizes recent progress and outlines a concise workflow, i.e., condition-aware meta-data, multi-scale featurization, interpretable supervision, unsupervised mapping, and ML-guided screening, for reproducible materials-to-device translation.
