A critical research direction for solid oxide cells (SOCs), such as solid oxide fuel cells (SOFCs) and solid oxide electrolyser cells (SOECs), is to smoothly transition between fuel-cell and electrolyser modes to achieve high energy conversion efficiencies and flexible operation. To overcome current obstacles, related to conductivity, oxidation resistance, and durability, it is imperative to design strong, high-performance electrode materials. Recent developments have relied heavily on nickel (Ni), cobalt (Co), and iron (Fe). Ni-based electrodes provide remarkable electrical conductivity, mechanical strength, and catalytic activity, allowing for effective operation at lower temperatures while, Fe-based materials offer robust, affordable, and thermally stable solutions for high-temperature applications, in symmetrical SOCs, like in perovskite structures. The special redox behaviour of Fe–O bonds and Fe substitution in fuel electrodes enhance superior performance under various operational conditions. Innovative development of extremely active electrocatalysts employing Fe-nano metal or alloy on oxide-based electrode through infiltration process as well as in situ exsolution, protective coatings to suppress degradation in SOECs, are some examples of recent progress. Here, recent advancements in metal-based electrodes for SOCs are analysed, with regard to durability increment and efficiency, and potential research directions and limitations for further enhancing these materials toward sustainable energy technology.
Nitrogen oxide (NOx) emissions from industrial selective catalytic reduction (SCR) units are shaped by complex time-delay dynamics. However, existing studies rarely identify which process variables matter at which lags, or distinguish autoregressive channels from process-driven predictors. This paper presents a lag-aware attribution framework built on a non-autoregressive feature design. ElasticNet and XGBoost form the primary attribution pair on a common (variable, lag) grid, while an Attention-LSTM serves as an auxiliary sequential verification. The framework is applied to five years of hourly data from three independent SCR units (Clean 1, 2, and 3) at a steelworks sintering plant with forecast horizons h ∈ {0, 1, 2, 3}. Under these conditions, the SCR and Damper/Flow groups consistently emerge as the strongest recurring predictor families across the primary ElasticNet–XGBoost pair and all three units. Their predictive contributions peak several hours before the target measurement, whereas a subset of pressure-related variables exhibits lower consistency across units and models. Three lines of evidence — cross-model convergence, cross-unit recurrence, and variable-level attribution faithfulness — collectively substantiate these groups as recurring predictor families. Quarter-level persistence provides an auxiliary consistency verification, constrained by the limited number of quarterly transitions. Taken together, these analyses reduce hundreds of process variables to a small set of recurring predictor families, providing a prioritized basis for follow-up diagnosis in high-dimensional industrial settings.
Metal-organic frameworks (MOFs) have emerged as promising adsorbents for wastewater treatment because of their exceptionally high surface areas, tunable pore architectures, and abundant accessible active sites. Nevertheless, most conventional MOFs are produced as fine powders, which are prone to agglomeration during practical operation and are further constrained by difficult recovery and insufficient mechanical stability, thereby limiting their large-scale engineering application. Hydrogels, as polymeric materials with three-dimensional network structures, offer excellent processability together with tailorable functional-group chemistry, making them ideal matrices for MOF immobilization. Consequently, hydrogel-modified MOF composites represent an effective strategy for enhancing the practical applicability of MOF adsorbents in water decontamination. This review critically summarizes recent advances in hydrogel-modified MOF composites for water treatment, with a classification of the matrix materials, support selection strategies, modification methods, adsorption mechanisms, and recent applications. Distinct from previous reviews, this article provides an integrated overview of current MOF adsorbents by classifying them according to their metal nodes and organic ligands and examining hydrogel support selection, modification strategies, mechanistic understanding, and application scenarios. It also reviews applications in removing different classes of water pollutants, including pharmaceuticals, heavy metals, dyes, and emerging contaminants, thereby offering both a theoretical foundation and a practical reference for the design and development of highly efficient, stable, and recyclable adsorbent materials.
Environmental policies promoting resource recycling have been implemented worldwide to achieve goals such as carbon neutrality and reducing greenhouse gas emissions. The Republic of Korea has set targets to reduce waste and increase recycling rates to 70
Indoor CO2 concentrations over 1000 ppm can negatively impact human health. In this work, KOH/AC (KOH impregnated on activated carbon), as a cost-effective CO2 adsorbent, was used to further investigate the CO2 adsorption performance based on our previous study. In addition, the effect of moisture on adsorption performance is the main focus of this study. Although successful impregnation with KOH greatly reduced the surface area, KOH-impregnation significantly altered the surface chemistry (e.g., basic active sites). In-situ FTIR analysis showed that the CO2 adsorption mechanism on KOH/AC involved chemisorption (mainly by KOH-impregnation) and physisorption (mainly by activated carbon). CO2 isotherms combined with TGA analyses indicated that moisture strongly influenced the occurrence of chemisorption, with higher moisture content leading to improved CO2 adsorption performance. Also, the fixed bed adsorption experiments showed that adsorption performance is positively correlated with the moisture content, and KOH/AC had good adsorption performance for CO2 in the indoor concentration range (1.93 mmol/g for 1000 ppm, 2.80 mmol/g for 2000 ppm). Adsorption kinetic study showed that CO2 adsorption well fitted the linear driving force (LDF) mass transfer model, and the rate of adsorption was influenced by the moisture content. Finally, the current study suggested that KOH/AC has great potential as an adsorbent for indoor CO2 removal.
