Ionic liquids (ILs) have garnered significant interest owing to their distinct physicochemical traits. Nonetheless, their extensive application is curtailed by ecotoxicity concerns. This study aimed to develop a quantitative structure-activity relationship (QSAR) model for predicting the toxicity of ILs in biological cells. Toxicity data of ILs on leukemia rat cell line IPC-81, Escherichia coli (E. coli), and acetylcholinesterase (AChE) were collected from open-source databases, and two integrated models, random forest (RF) and gradient boosted decision tree (GBDT), were used to train the data. The molecular structures of the ILs were represented by three different methods, namely molecular descriptor (MD), molecular fingerprint (MF), and molecular identifier (MI), respectively. The Tanimoto similarity coefficients indicate that MD has a stronger ability to recognize structural similarity. Statistical metrics of model performance showed that the two models (MD-RF and MD-GBDT) with MD as an input feature performed better in the three datasets. The application of the SHapley Additive exPlanations (SHAP) method explains the importance of different features. Specifically, reducing the carbon chain length and the number of fluorine atoms in the structure of ILs can effectively reduce their toxic effects on biological cells. This study employs machine learning to grasp better how the structure of ILs relates to inhibiting biotoxicity, offering insights for crafting safer, eco-friendly IL designs.

Hydrogenation of lignin-derived phenol to KA oil (the mixture of cyclohexanone (K) and cyclohexanol (A)) is attractive yet challenging in the sustainable upgrading of biomass derivatives under mild conditions. Traditional supported metal catalysts have been widely studied but the active components on supports often exhibit low recyclability due to their instability under experimental conditions. Here we show fabricating ultrasmall Pt/NiO in the pores of chromium terephthalate MIL-101 as catalysts for hydrogenation of phenol. Impressively, Pt/NiO@MIL-101 achieves catalytic phenol hydrogenation to KA oils of tunable K/A ratios and good reusability under room temperature and atmospheric hydrogen pressure, superior to contrast Pt@MIL-101 and Pt/NiO samples. Such excellent performance mainly originates from the effective adsorption and activation of phenol by coordinatively unsaturated Cr sites and H₂ activation on ultrasmall Pt/NiO as well as its effective spillover to the adsorbed phenol over Cr sites for hydrogenation reaction. Substantially, such catalyst also displays the excellent performances for hydrogenation of phenol’s derivatives under mild conditions.

Compared with monometallic metal-organic frameworks (MOFs) that are synthesized by reacting inorganic metal ions or clusters with bidentate or multidentate ligands via hydrothermal or solvothermal methods, the construction of heterogeneous frameworks like at least two kinds of metal sites in the individual nodes is proved to be an effective way to modulate their properties for advanced catalysis, especially for selective catalysis and multifunctional catalysis. However, it is still very challenging to precisely characterize their microstructures and reveal the relationship among the composition, structure, and their performances. Therefore, it is necessary to summarize the recent progress on bimetallic MOFs for thermal catalysis. First, we summarize the synthesis strategies and characterization methods of bimetallic MOFs and their derivatives. Second, the application of bimetallic MOFs and their derivatives as catalysts in thermal catalysis is discussed, and the relationship among the active components, structures, and their properties is elucidated. Third, the potential challenges and prospects of bimetallic MOF based nanocatalysts are proposed. This review will bring some insights into the design and preparation of bimetallic MOFs based nanocatalysts in the future.