Reorganization energy(RE)is closely related to the charge transport properties and is one of the important parameters for screening novel organic semiconductors(OSCs).With the rise of data-driven technology,accurate a...Reorganization energy(RE)is closely related to the charge transport properties and is one of the important parameters for screening novel organic semiconductors(OSCs).With the rise of data-driven technology,accurate and efficient machine learning(ML)models for high-throughput screening novel organic molecules play an important role in the boom of material science.Comparing different molecular descriptors and algorithms,we construct a reasonable algorithm framework with molecular graphs to describe the compositional structure,convolutional neural networks to extract material features,and subsequently embedded fully connected neural networks to establish the mapping between features and predicted properties.With our well-designed judicious training pattern about feature-guided stratified random sampling,we have obtained a high-precision and robust reorganization energy prediction model,which can be used as one of the important descriptors for rapid screening potential OSCs.The root-meansquare error(RMSE)and the squared Pearson correlation coefficient(R^(2))of this model are 2.6 me V and0.99,respectively.More importantly,we confirm and emphasize that training pattern plays a crucial role in constructing supreme ML models.We are calling for more attention to designing innovative judicious training patterns in addition to high-quality databases,efficient material feature engineering and algorithm framework construction.展开更多
Electrochemical CO_(2) reduction reaction(CO_(2)RR)is an attractive pathway for closing the anthropogenic carbon cycle and storing intermittent renewable energy by converting CO_(2) to valuable chemicals and fuels.The...Electrochemical CO_(2) reduction reaction(CO_(2)RR)is an attractive pathway for closing the anthropogenic carbon cycle and storing intermittent renewable energy by converting CO_(2) to valuable chemicals and fuels.The production of highly reduced carbon compounds beyond CO and formate,such as hydrocarbon and oxygenate products with higher energy density,is particularly desirable for practical applications.However,the productivity towards highly reduced chemicals is typically limited by high overpotential and poor selectivity due to the multiple electron-proton transfer steps.Tandem catalysis,which is extensively utilized by nature for producing biological macromolecules with multiple enzymes via coupled reaction steps,represents a promising strategy for enhancing the CO_(2)RR performance.Improving the efficiency of CO_(2)RR via tandem catalysis has recently emerged as an exciting research frontier and achieved significant advances.Here we describe the general principles and also considerations for designing tandem catalysis for CO_(2)RR.Recent advances in constructing tandem catalysts,mainly including bimetallic alloy nanostructures,bimetallic heterostructures,bimetallic core-shell nanostructures,bimetallic mixture catalysts,metal-metal organic framework(MOF)and metal-metallic complexes,metal-nonmetal hybrid nanomaterials and copper-free hybrid nanomaterials for boosting the CO_(2)RR performance are systematically summarized.The study of tandem catalysis for CO_(2)RR is still at the early stage,and future research challenges and opportunities are also discussed.展开更多
Combined theoretical and experimental studies have explained the mechanism of Pd-catalyzed δ-C(sp^(3))-H arylation of primary amines. Instead of the monomeric Pd mechanism, our research unveils that all steps includi...Combined theoretical and experimental studies have explained the mechanism of Pd-catalyzed δ-C(sp^(3))-H arylation of primary amines. Instead of the monomeric Pd mechanism, our research unveils that all steps including C–H activation, oxidative addition, and reductive elimination take place via the heterodimeric Pd–Ag intermediates and transition states. Experimentally, the active heterodimeric Pd–Ag species were detected by mass spectrometry, which further confirms the proposed heterodimeric mechanism. Insight gained through this study reveals the synergistic manner of palladium catalysis and silver(Ⅰ)additives in native NH;-directed C–H activation and C–C coupling reactions.展开更多
基金financially supported by the Ministry of Science and Technology of China (2017YFA0204503 and 2018YFA0703200)the National Natural Science Foundation of China (52121002,U21A6002 and 22003046)+1 种基金the Tianjin Natural Science Foundation (20JCJQJC00300)“A Multi-Scale and High-Efficiency Computing Platform for Advanced Functional Materials”program,funded by Haihe Laboratory in Tianjin (22HHXCJC00007)。
文摘Reorganization energy(RE)is closely related to the charge transport properties and is one of the important parameters for screening novel organic semiconductors(OSCs).With the rise of data-driven technology,accurate and efficient machine learning(ML)models for high-throughput screening novel organic molecules play an important role in the boom of material science.Comparing different molecular descriptors and algorithms,we construct a reasonable algorithm framework with molecular graphs to describe the compositional structure,convolutional neural networks to extract material features,and subsequently embedded fully connected neural networks to establish the mapping between features and predicted properties.With our well-designed judicious training pattern about feature-guided stratified random sampling,we have obtained a high-precision and robust reorganization energy prediction model,which can be used as one of the important descriptors for rapid screening potential OSCs.The root-meansquare error(RMSE)and the squared Pearson correlation coefficient(R^(2))of this model are 2.6 me V and0.99,respectively.More importantly,we confirm and emphasize that training pattern plays a crucial role in constructing supreme ML models.We are calling for more attention to designing innovative judicious training patterns in addition to high-quality databases,efficient material feature engineering and algorithm framework construction.
基金This work was supported by the National Key R&D Program(No.2017YFA0204503)the National Natural Science Foundation of China(Nos.22071172,91833306,21875158,51633006,and 51733004)+1 种基金Z.F.thanks the funding support from ITC via Hong Kong Branch of National Precious Metals Material Engineering Research Center(NPMM),and the Start-Up Grants(Nos.9610480 and 7200651)Grant from City University of Hong Kong(No.7005512).
文摘Electrochemical CO_(2) reduction reaction(CO_(2)RR)is an attractive pathway for closing the anthropogenic carbon cycle and storing intermittent renewable energy by converting CO_(2) to valuable chemicals and fuels.The production of highly reduced carbon compounds beyond CO and formate,such as hydrocarbon and oxygenate products with higher energy density,is particularly desirable for practical applications.However,the productivity towards highly reduced chemicals is typically limited by high overpotential and poor selectivity due to the multiple electron-proton transfer steps.Tandem catalysis,which is extensively utilized by nature for producing biological macromolecules with multiple enzymes via coupled reaction steps,represents a promising strategy for enhancing the CO_(2)RR performance.Improving the efficiency of CO_(2)RR via tandem catalysis has recently emerged as an exciting research frontier and achieved significant advances.Here we describe the general principles and also considerations for designing tandem catalysis for CO_(2)RR.Recent advances in constructing tandem catalysts,mainly including bimetallic alloy nanostructures,bimetallic heterostructures,bimetallic core-shell nanostructures,bimetallic mixture catalysts,metal-metal organic framework(MOF)and metal-metallic complexes,metal-nonmetal hybrid nanomaterials and copper-free hybrid nanomaterials for boosting the CO_(2)RR performance are systematically summarized.The study of tandem catalysis for CO_(2)RR is still at the early stage,and future research challenges and opportunities are also discussed.
基金supported by the Tianjin University and the National Natural Science Foundation of China (Nos. 22073067 and 21673156)。
文摘Combined theoretical and experimental studies have explained the mechanism of Pd-catalyzed δ-C(sp^(3))-H arylation of primary amines. Instead of the monomeric Pd mechanism, our research unveils that all steps including C–H activation, oxidative addition, and reductive elimination take place via the heterodimeric Pd–Ag intermediates and transition states. Experimentally, the active heterodimeric Pd–Ag species were detected by mass spectrometry, which further confirms the proposed heterodimeric mechanism. Insight gained through this study reveals the synergistic manner of palladium catalysis and silver(Ⅰ)additives in native NH;-directed C–H activation and C–C coupling reactions.
