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[Display omitted] • Machine learning was used to predict the yields of ionic liquids catalyzed CO 2 cyclization reaction for the first time. • Density function theory calculations were conducted to obtain reaction descriptors with high-precision. • The strategy of refining the database quality improves the predictive ability of RF model significantly. • The ML model was interpreted well by the shapely additive explanation method. Ionic liquids are one of the excellent catalysts for the CO 2 cycloaddition reaction, which is an effective means to realize CO 2 utilization and alleviate environmental problems. However, the design of ionic liquids catalysts has great blindness due to the diversity of their anion and cation structures. Herein, we collected a database of 866 samples for CO 2 cyclization with ionic liquids as catalysts and established the yield prediction model with various machine learning regression algorithms. Together with density function theory (DFT) calculated molecular electronic properties and the experimental conditions as the input descriptors, random forest (RF) model has better prediction accuracy than support vector regression (SVR) and multilayer perceptron (MLP) for the whole data. When the dataset was subdivided into different subsets based on substrates and ionic liquids, the prediction accuracy of the model was also improved. For the imidazole subset with no additional solvent or additive added, the RF model achieves good accuracy with the R2 of 0.80 for the test data. Moreover, the shapely additive explanation (SHAP) method was used to interpret the ML models. The strategy of refining the descriptors and dataset used in our work provides guidance for establishing highly reliable machine learning models in the chemistry reactions. [ABSTRACT FROM AUTHOR]

• The mechanism of title reaction catalyzed by AgNO 3 /[C 2 C 1 mim][OAc] is elucidated. • The contributions of anions and cations are discussed in detail. • The differences between different catalysts are discussed in depth. The chemical fixation of CO 2 has attracted elevated attentions since it is a promising pathway to solve the serious environmental pollution and fuel shortage. The three-component reaction of CO 2 , propargyl alcohols, and 2-aminoethanols is one of the most attractive candidates due to the wide applications and extreme importance of products. However, the reaction mechanism is desired to explore due to the complicated catalytic components and substrates. In addition, contribution of each catalytic component and actual catalytic component are still not clear. The mechanism of title reaction catalyzed by AgNO 3 /[C 2 C 1 mim][OAc] is elucidated by the density functional theory (DFT). In addition, the catalytic routes of AgNO 3 /[C 4 C 1 mim][OAc], AgNO 3 /[DBUH][OAc], AgNO 3 /[C 2 C 1 mim][NO 3 ], and AgNO 3 /[C 2 C 1 mim][ClO 4 ] are also considered to unfold the contribution of cation and anion. The atoms in molecule (AIM) and noncovalent interactions (NCI) are calculated for some important configurations to deeply understand the difference among various catalysts. To elucidate these issues is favorable to explore the more robust catalysts for this reaction. [Display omitted] [ABSTRACT FROM AUTHOR]

[Display omitted] • Suitable transition metals are selected for CO 2 RR on the defective g-C 3 N 4. • Machine learning builds a bridge between catalytic activity and various features. • Selected transition metals are coordinated on other carbon supporter. • The 25% doped amount of uncoordinated N is suitable. Electrocatalysis of CO 2 reduction reaction (CO 2 RR) has attracted elevated attentions since it is favorable to prompt the carbon cycle in a sustainable pathway. However, the applications of this technology is obstructed by the low activity and selectivity due to the inert of CO 2 and favored hydrogen evolution reaction. Development of robust catalysts is the most feasible method to decrease the overpotential and suppress the competitive side reaction. Single-atom-catalysts (SACs) is one of the most promising catalysts with the satisfied activity. However, the clear and popular rules are still absence to explore the SACs with the desired properties due to the complicated items related with the overall performance. The suitable transition metals (TMs) are screened out based on the defective g-C 3 N 4 (V N -C 3 N 4) supporter by the first principle. Among 24 screened transition metals, the Ni-V N -C 3 N 4 exhibits the better performance as compared to others. Later, the machine learning (ML) algorithm builds a bridge between catalytic activity and intrinsic structural and atomic features. Then, the same coordination environment is constructed on the graphene to explore the possibility to replace the V N -C 3 N 4 with other carbon substrate. When the doped amount of uncoordinated N reaches 25 wt%, the catalytic activity of Ni N C SAC based on the graphene is close to that based on the V N -C 3 N 4. This work introduces a method to construct the SACs by regulating the N -doped amount on the supporter. [ABSTRACT FROM AUTHOR]

[Display omitted] • The catalyzed mechanism of propargylic alcohol and H 2 O is investigated. • CO 2 could be absorbed by the [Bu 4 P+] cation to form [Bu 4 P -H -CO 2 ] complex. • A novel mechanism is proposed with the [Bu 4 P -H -CO 2 ][Im +H ] complex employed as the actual catalytic species. Hydration of propargylic alcohols is one of the most important pathways to synthesize α-hydroxy ketones. However, its mechanism is still obscure in the presence of multiple catalytic species. The mechanism of catalysis for the hydration of propargylic alcohols in the presence of [Bu 4 P+][Im-] is investigated along with the carbon dioxide (CO 2) as the co-catalyst by the density functional theory (DFT) with the aim to elucidate the role of [Bu 4 P+] cation and [Im-] anion. The CO 2 could be absorbed by the [Bu 4 P+] cation to form [Bu 4 P -H -CO 2 ] complex after the hydrogen atom in [Bu 4 P+] cation transfers to the [Im-] anion. Then, both [Bu 4 P -H -CO 2 ] and [Im +H ] are employed as the actual catalytic species to construct a new pathway. It is the more favorable as compared with the previously reported pathways. In previous reported pathway, the [Im-] anion is regarded as the real catalytic species, while [Bu 4 P+] cation plays the auxiliary role to stabilize the substrate by the hydrogen bond. The mechanism of the same reaction catalyzed by other four different ionic liquids is also investigated to further testify the contribution of [Bu 4 P+] cation and [Im-] anion in the catalysis. This work not only provides a new insight into the cation-regulated pathway for the hydration of propargylic alcohols but also points out a new strategy to design the ionic liquids achieving the improved catalytic efficiency. [ABSTRACT FROM AUTHOR]