The exploitation of competent electrocatalysts is a key issue of the broad application of many promising electrochemical processes,including the hydrogen evolution reaction(HER),the oxygen evolution reaction(OER),the ...The exploitation of competent electrocatalysts is a key issue of the broad application of many promising electrochemical processes,including the hydrogen evolution reaction(HER),the oxygen evolution reaction(OER),the oxygen reduction reaction(ORR),the CO_(2) reduction reaction(CO_(2)RR)and the nitrogen reduction reaction(NRR).The traditional searches for good electrocatalysts rely on the trial-and-error approaches,which are typically tedious and inefficient.In the past decades,some fundamental principles,activity descriptors and catalytic mechanisms have been established to accelerate the discovery of advanced electrocatalysts.Hence,it is time to summarize these theory-related research advances that unravel the structure-performance relationships and enables predictive ability in electrocatalysis studies.In this review,we summarize some basic aspects of catalytic theories that are commonly used in the design of electrocatalysts(e.g.,Sabatier principle,d-band theory,adsorption-energy scaling relation,activity descriptors)and their relevance.Then,we briefly introduced the fundamental mechanisms and central challenges of HER,OER,ORR,CO_(2)RR and NRR electrocatalysts,and highlight the theory-based efforts used to address the challenges facing these electrocatalysis processes.Finally,we propose the key challenges and opportunities of theory-driven electrocatalysis on their future.展开更多
The quantitative structure-property relationship(QSPR) of anabolic androgenic steroids was studied on the half-wave reduction potential(E1/2) using quantum and physico-chemical molecular descriptors. The descriptors w...The quantitative structure-property relationship(QSPR) of anabolic androgenic steroids was studied on the half-wave reduction potential(E1/2) using quantum and physico-chemical molecular descriptors. The descriptors were calculated by semi-empirical calculations. Models were established using partial least square(PLS) regression and back-propagation artificial neural network(BP-ANN). The QSPR results indicate that the descriptors of these derivatives have significant relationship with half-wave reduction potential. The stability and prediction ability of these models were validated using leave-one-out cross-validation and external test set.展开更多
文摘The exploitation of competent electrocatalysts is a key issue of the broad application of many promising electrochemical processes,including the hydrogen evolution reaction(HER),the oxygen evolution reaction(OER),the oxygen reduction reaction(ORR),the CO_(2) reduction reaction(CO_(2)RR)and the nitrogen reduction reaction(NRR).The traditional searches for good electrocatalysts rely on the trial-and-error approaches,which are typically tedious and inefficient.In the past decades,some fundamental principles,activity descriptors and catalytic mechanisms have been established to accelerate the discovery of advanced electrocatalysts.Hence,it is time to summarize these theory-related research advances that unravel the structure-performance relationships and enables predictive ability in electrocatalysis studies.In this review,we summarize some basic aspects of catalytic theories that are commonly used in the design of electrocatalysts(e.g.,Sabatier principle,d-band theory,adsorption-energy scaling relation,activity descriptors)and their relevance.Then,we briefly introduced the fundamental mechanisms and central challenges of HER,OER,ORR,CO_(2)RR and NRR electrocatalysts,and highlight the theory-based efforts used to address the challenges facing these electrocatalysis processes.Finally,we propose the key challenges and opportunities of theory-driven electrocatalysis on their future.
基金Project supported by the Postdoctoral Science Foundation of Central South University,ChinaProject(2015SK20823)supported by Science and Technology Project of Hunan Province,China+2 种基金Project(15A001)supported by Scientific Research Fund of Hunan Provincial Education Department,ChinaProject(CX2015B372)supported by Hunan Provincial Innovation Foundation for Postgraduate,ChinaProject supported by Innovation Experiment Program for University Students of Changsha University of Science and Technology,China
文摘The quantitative structure-property relationship(QSPR) of anabolic androgenic steroids was studied on the half-wave reduction potential(E1/2) using quantum and physico-chemical molecular descriptors. The descriptors were calculated by semi-empirical calculations. Models were established using partial least square(PLS) regression and back-propagation artificial neural network(BP-ANN). The QSPR results indicate that the descriptors of these derivatives have significant relationship with half-wave reduction potential. The stability and prediction ability of these models were validated using leave-one-out cross-validation and external test set.
