SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3633-5
High-temperature interfacial diffusion in Half-Heusler (HH) thermoelectric devices poses significant challenges for practical applications, particularly the diffusion of Ag from conventional solders, which degrades material performance and device stability. This study reveals anomalous Ag diffusion through a Cr powder barrier layer into Ti0.5Zr0.5NiSn0.98Sb0.02, driven by Sn phase penetration. In contrast, employing a Cr foil barrier layer pre-densified the material, effectively preventing Sn phase penetration and eliminating Ag diffusion pathways, thereby preserving junction integrity. After aging at 973 K for 30 days, the Cr foil junction maintained a clean interface with a low contact resistivity of 0.27 μΩ cm2. Benefiting from this interfacial design, a Hf-free HH module achieved a high conversion efficiency of 10.4% at a hot-side temperature of 976 K, alongside long-term stability. This work addresses critical bottlenecks in developing high-performance, low-cost HH modules, facilitating their commercial application in waste heat recovery.
Journal of Fuel Chemistry and Technology•2026•DOI: 10.1016/S1872-5813(25)60620-7
Direct coal liquefaction (DCL) diesel constitutes over 60% of DCL products, yet its cetane number (30–40) falls short of the automotive diesel standard (≥45). Rapid and accurate compositional analysis is essential for optimizing properties via component blending. Traditional gas chromatography offers high accuracy but is unsuitable for online industrial monitoring. Near-infrared (NIR) spectroscopy enables rapid, non-destructive analysis, but spectral interpretation is complex. This study integrates NIR spectroscopy with machine learning (ML) to construct a spectral-composition database for DCL diesel. Feature extraction using correlation coefficient and mutual information methods screened key wavelength variables, reducing dimensionality from ~1800 to ~200 wavelengths. Three ML models—Lasso, SVR, and XGBoost—were compared. Excluding spectral data with absorbance >1 significantly improved model accuracy, increasing test set R² from 0.85 to 0.96. After feature extraction, the optimal variable count was 177, enhancing computational efficiency. Among models, SVR-MI-0.9 (mutual information feature selection) achieved the best performance, with training and test set R² values exceeding 0.98, enabling precise prediction of paraffin, naphthene, and aromatic contents. This research provides a robust methodology for intelligent online quality monitoring. An intelligent NIR spectroscopy data analysis software was independently developed based on the established model. Compared with comprehensive two-dimensional gas chromatography, the software reduced analysis time by over 98%, with absolute prediction error below 0.2%. Thus, rapid analysis of DCL diesel components was successfully realized.
Chinese Journal of Environmental Engineering•2026•DOI: 10.12030/j.cjee.202510029
Low hydrolysis efficiency is a core bottleneck in anaerobic digestion (AD) of lignocellulosic agricultural residues, limiting methane production and resource utilization. This study optimized thermal hydrolysis pretreatment (THP) of corn straw (CS) using response surface methodology (RSM) to enhance methane yield. The optimal conditions were determined as solid-to-liquid ratio of 51.0–57.5 mg·mL−1, pretreatment time of 74–81 min, and temperature of 182.5–197.5 °C. Under the optimal combination (52.3 mg·mL−1, 78.4 min, 191 °C), cumulative methane yield increased from 218.0 to 362.9 mL·g−1 VS, a 66.7% improvement over untreated CS. Characterization via XRD, FTIR, and SEM revealed that THP disrupted the lignocellulosic structure, reducing lignin content from 21.5% to 8.3% and crystallinity index (CrI) from 70.83% to 61.95%. Inhibitory derivatives generated during THP included furfural (1.69 mg·mL−1), 5-methylfurfural (2.44 mg·mL−1), and phenol (23.14 mg·L−1), with a theoretical combined inhibition rate of 7.26%. The promotion effect on methane production (66.7%) far exceeded the theoretical inhibition (7.26%), indicating that THP under optimized conditions is effective and environmentally controllable. This study provides a systematic framework for optimizing THP parameters to maximize methane production from agricultural residues.
Journal of Environmental Engineering Technology•2026•DOI: 10.13205/j.hjgc.202608018
Chlorinated volatile organic compounds (CVOCs) are volatile, difficult to degrade, and highly toxic, posing serious threats to the atmospheric environment and human health. Catalytic oxidation is currently one of the mainstream methods for CVOCs abatement, owing to its high efficiency, safety, and economic feasibility, and its key aspect lies in the design and development of high-performance catalysts. In the catalytic oxidation of CVOCs, the poisoning effect of chlorine species on catalysts severely restricts catalytic performance. Ru-based catalysts, which exhibit excellent catalytic oxidation activity toward CVOCs and favorable chlorine-resistant performance, have been widely studied in recent years. This paper reviews the latest research progress on Ru-based catalysts for the catalytic oxidation of CVOCs. The mechanism of catalytic oxidation of CVOCs by Ru-based catalysts is elucidated through a systematic analysis of the relevant literature. Furthermore, the strategies for the design and structural regulation of Ru-based catalysts are outlined from the perspectives of active components, supports, and surface modification. Finally, novel preparation methods for Ru-based catalysts and the influence of reaction components on catalytic performance are summarized. Future research directions in this field are also prospected, aiming to provide a reference for the subsequent design and development of high-performance Ru-based catalysts suitable for complex operating conditions.