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/s40843-025-3900-8
Memristors, which leverage ion migration for resistance switching, offer breakthroughs in bionic perception, information security, and edge computing but face bottlenecks in functional integration and stability. Herein, we explore all-inorganic Cu3SbI6 nanocrystals (NCs) & PMMA composite memristors (Ag/PMMA&Cu3SbI6/ITO) regulated by NCs doping (0–15 wt%). The devices operate via electric field-induced Ag+ ion migration and conductive filament dynamics, where NCs act as local electric field enhancers. At a doping concentration of 4 wt%, stable bipolar switching (Ron/Roff > 2 × 10^3, cycling endurance > 700 cycles) enables the simulation of biological nociception/Pavlovian reflexes and the construction of basic logic gates. At 2 wt%, sparse NCs induce random filament formation for encryption key extraction, which integrates with 4 wt% logic gates to enable efficient encryption/decryption of text/image data. This work provides a strategy for designing multifunctional memristors by regulating ion transport through nanocrystal concentration, offering references for related functional integration and cross-disciplinary applications.
SCIENCE CHINA Materials•2025•DOI: 10.1007/s40843-024-3281-x
Carbon monoxide (CO) therapy has emerged as a promising approach in cancer treatment. Selecting suitable nanocarriers for delivering manganese carbonyl (MnCO), a CO donor, while simultaneously regulating CO release and compensating for hydrogen peroxide (H2O2) and acidity in the tumor microenvironment is crucial for enhancing the effectiveness of CO therapy. In this study, a tumor microenvironment-responsive core-shell structured cascade nanoreactor was designed and synthesized using mesoporous polydopamine (MPDA) as a nanocarrier, followed by loading of MnCO and glucose oxidase-encapsulated zeolite imidazolate framework-8 (GOx@ZIF-8) nanoparticles. Upon entering cancer cells, the protective shell of GOx@ZIF-8 degrades in response to the acidic tumor environment, releasing GOx. GOx catalyzes the conversion of endogenous glucose into gluconic acid and H2O2, accelerating energy starvation in tumor cells. This process, in turn, promotes the reaction between MnCO and H2O2, resulting in in-situ amplified release of CO. Additionally, the excellent photothermal properties of MPDA enable photothermal therapy. This comprehensive antitumor strategy represents a promising advancement in the field of CO-based cancer therapy.