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.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3812-5
Anaerobic bacterial infections, prevalent in oxygen-deprived tissues, are recalcitrant to conventional antibiotics due to slow bacterial metabolism and the generation of nutrient-rich niches that foster polymicrobial biofilms. Propionibacterium acnes (P. acnes), a skin commensal, exemplifies this challenge, causing acne vulgaris and implant-associated infections, with rising antibiotic resistance. This study introduces an antimicrobial peptide (AMP), WRK (sequence: WRKFRRFKFRW-NH2), which induces endogenous reactive oxygen species (ROS) production in anaerobic bacteria, exploiting their inherent low ROS tolerance. WRK exhibited potent antibacterial activity, with a minimum inhibitory concentration (MIC) of 4 μg mL−1 against planktonic P. acnes and a minimum biofilm eradication concentration (MBEC) of 64 μg mL−1. To enable dermal delivery, WRK was encapsulated in layered dissolving microneedles (MNs), which demonstrated adequate mechanical strength for skin penetration. In a mouse back acne model, AMP MNs significantly reduced P. acnes infection and inflammation, outperforming commercial clindamycin gel. Histological analysis confirmed reduced inflammatory cell infiltration and tissue hyperplasia in the AMP MN group. This strategy offers a promising approach for treating anaerobic infections without promoting drug resistance, addressing a critical unmet need in clinical dermatology and implant surgery.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3908-1
Smart responsive hydrogels have emerged as a promising class of biomaterials in bone tissue engineering, offering dynamic and adaptive therapeutic strategies for complex bone defects. These hydrogels can perceive and respond to microenvironmental cues, such as pH fluctuations, oxidative stress, enzymatic activity, mechanical forces, and thermal or photic changes, to achieve controlled drug release, modulate cellular behavior, and reconstruct the local tissue milieu. This review systematically summarizes recent advances in various categories of smart hydrogels, including enzyme-responsive, reactive oxygen species-responsive, pH-responsive, thermo-/photo-responsive, mechanically responsive, and multi-responsive systems. Emphasis is placed on their mechanisms of action and their roles in immunomodulation, angiogenesis, osteogenesis, and microenvironment remodeling. Furthermore, the review highlights representative design innovations that integrate multi-stimuli sensitivity with intelligent feedback regulation, enhancing clinical adaptability and regenerative efficacy. Despite remarkable progress, challenges such as complex synthesis procedures, limited response precision, biosafety concerns, and translational standardization remain to be addressed. Future research directions are discussed, focusing on logical material design, interdisciplinary integration, and the development of next-generation hydrogels with immunoregulatory, self-adaptive, and programmable regenerative capabilities for clinical translation in bone repair.