Chieh-Ming Hsieh

Deep eutectic solvents (DESs) are promising for CO2 capture, yet rapid screening remains challenging because of their chemical diversity. This study develops an interpretable machine learning framework integrating experimental conditions with compact molecular descriptors derived from COSMO solvation calculations and the resulting σ-profiles. A data set of 2,398 CO2 solubility measurements across 114 unique DESs was used to develop tree-based machine learning models. XGBoost achieved the highest testing accuracy (R2 = 0.990, RMSE = 0.070, MAE = 0.043, AARD = 10.05%) using only nine input features. Benchmark comparisons showed performance comparable to or better than models using full σ-profiles or larger feature sets. SHAP analysis identified pressure as the dominant predictor and highlighted contributions from molecular geometry and hydrogen-bonding-related descriptors. The proposed framework therefore provides an accurate, efficient, and interpretable approach for screening DESs within chemically related design spaces and supports future data-driven solvent design.

The pursuit of high-performance anode materials for Li-ion batteries is crucial for portable electronic devices and electric vehicles. Blue phosphorene (BP) and silicene, with their graphene-like layered structures, exhibit high theoretical specific capacity and good conductivity. In this study, the potential of the BP/Si heterostructure as an anode material for Li-ion batteries was systematically explored based on vdW corrected density functional theory (DFT). The results demonstrated that Li exhibits the most stable adsorption energy of −1.82 eV on BP/Si, significantly lower than that on the pristine monolayers of BP and silicene, indicating good structural stability. The BP/Si heterostructure showed a minimum diffusion barrier of only 0.2 eV for Li diffusion and a high diffusion coefficient of 3.21 × 10⁻⁶ cm² s⁻¹ at room temperature, indicating excellent rate performance. With an increasing Li concentration, the BP/Si heterostructure achieved a high theoretical specific capacity of 472 mA h g⁻¹. Furthermore, the BP/Si heterostructures retained their respective electronic properties, including a low band gap of 0.26 eV and direct semiconductor characteristics, providing good conductivity.