Efficient electrocatalysts are crucial for hydrogen generation from electrolyzing water.Nevertheless,the conventional"trial and error"method for producing advanced electrocatalysts is not only cost-ineffecti...Efficient electrocatalysts are crucial for hydrogen generation from electrolyzing water.Nevertheless,the conventional"trial and error"method for producing advanced electrocatalysts is not only cost-ineffective but also time-consuming and labor-intensive.Fortunately,the advancement of machine learning brings new opportunities for electrocatalysts discovery and design.By analyzing experimental and theoretical data,machine learning can effectively predict their hydrogen evolution reaction(HER)performance.This review summarizes recent developments in machine learning for low-dimensional electrocatalysts,including zero-dimension nanoparticles and nanoclusters,one-dimensional nanotubes and nanowires,two-dimensional nanosheets,as well as other electrocatalysts.In particular,the effects of descriptors and algorithms on screening low-dimensional electrocatalysts and investigating their HER performance are highlighted.Finally,the future directions and perspectives for machine learning in electrocatalysis are discussed,emphasizing the potential for machine learning to accelerate electrocatalyst discovery,optimize their performance,and provide new insights into electrocatalytic mechanisms.Overall,this work offers an in-depth understanding of the current state of machine learning in electrocatalysis and its potential for future research.展开更多
Hetero-element doping is a promising strategy to improve the cycling stability of nickel-rich cobalt-free cathodes for the next-generation high energy-density Li ion batteries.To make doping effective,it is important ...Hetero-element doping is a promising strategy to improve the cycling stability of nickel-rich cobalt-free cathodes for the next-generation high energy-density Li ion batteries.To make doping effective,it is important to understand the mechanism of how the dopants regulate the electronic band,lattice parameter adjusting,or hetero-phase formation to achieve high stability.In this study,we investigate LiNi_(0.9)Mn_(0.1)O_(2)cathodes doped with IVB grouping elements via multiple characterization techniques.By utilizing in situ XRD and TEM methods,we found that the stronger Ti-O bond effectively improves the cathode stability via a dual protection mechanism.Specifically,the bulk lattice of cathode is wellpreserved during cycling as a result of the suppressed H_(2)-H_(3)phase transition,while a in situ formed Ti-rich surface layer can prevent continuous surface degradation.As a result,the 5%Ti doped LiNi_(0.9)Mn_(0.1)O_(2)cathode exhibits a high capacity retention of 96%after 100 cycles.Whereas,despite IVB group elements Zr and Hf have stronger bonding energy with oxygen,their larger ionic radii actually impede their diffusion into the cathode,thereby they can not improve the cycling stability.Our findings uncover the functional origin of doped elements with their dynamic modification on cathode structure,providing mechanistic insights into the design of nickel-rich cobalt-free cathodes.展开更多
Wadsley-Roth (W-R) structured oxides featured with wide channels represent one of the most promising material families showing compelling rate performance for lithium-ion batteries.Herein,we report an indepth study on...Wadsley-Roth (W-R) structured oxides featured with wide channels represent one of the most promising material families showing compelling rate performance for lithium-ion batteries.Herein,we report an indepth study on the fast and extensive intercalation chemistry of phosphorus stabilized W-R phase PNb_(9)O_(25) and its application in high energy and fast-charging devices.We explore the intercalation geometry of PNb_(9)O_(25) and identify two geometrical types of stable insertion sites with the total amount much higher than conventional intercalation-type electrodes.We reveal the ion transportation kinetics that the Li ions initially diffuse along the open type Ⅲ channels and then penetrate to edge sites with low kinetic barriers.During the lithiation,no remarkable phase transition is detected with nearly intact host phosphorous niobium oxide backbone.Therefore,the oxide framework of PNb_(9)O_(25) keeps almost unchanged with all the fast diffusion channels and insertion cavities well-maintained upon cycling,which accomplishes the unconventional electrochemical performance of W-R structured electrodes.展开更多
Boron-dipyrromethene(BODIPY)is one promising class of sensitizers for dye-sensitized solar cells(DSSCs)due to unique merits of high absorption coefficient and versatile structural modification capability.However,such ...Boron-dipyrromethene(BODIPY)is one promising class of sensitizers for dye-sensitized solar cells(DSSCs)due to unique merits of high absorption coefficient and versatile structural modification capability.However,such derivatives usually suffer from limited power conversion efficiencies(PCEs)because of narrow light absorption band and low electron injection.To aid the discovery of BODIPY sensitizers,we employ an inverse design method to design efficient sensitizers by integrating data mining and firstprinciple techniques.We establish robust data-mining models using genetic algorithm and multiple linear regression,where the features are filtered from 5515 descriptors and their meanings are explicitly explored for next inverse designs.Based on the features’understanding,we design candidates NH1-6 and predict their PCEs,demonstrating remarkable enhancements(58%maximum)compared to previous works.Furthermore,their optoelectronic properties including maximum absorption wavelengths,oscillator strengths,bandgaps,transferred charges,charge transferred distances,TiO_(2) conduction band shifts,short-circuit currents and electron injection efficiencies simulated via first-principle calculations indicate significant increasements(93 nm,122.41%,23.70%,36.36%,471.17%,63.64%,28.55%,107.86%maximum),which testifies the corresponding highly predicted PCEs and may overcome BODIPY dyes’shortcomings.The as-designed BODIPY sensitizers can be promising candidates for DSSCs,and such method could help accelerate the discovery of other energy materials.展开更多
基金This work was supported by the National Natural Science Foundation of China(Grant No.22008098,52122408)the Program for Science&Technology Innovation Talents in Universities of Henan Province(No.22HASTIT008)+3 种基金the Programs for Science and Technology Development of Henan Province,China(No.222102320065)the Key Specialized Research and Development Breakthrough(Science and Technology)in Henan Province(No.212102210214)the Natural Science Foundations of Henan Province(No.222300420502)the Key Scientific Research Projects of University in Henan Province(No.23B430002).
文摘Efficient electrocatalysts are crucial for hydrogen generation from electrolyzing water.Nevertheless,the conventional"trial and error"method for producing advanced electrocatalysts is not only cost-ineffective but also time-consuming and labor-intensive.Fortunately,the advancement of machine learning brings new opportunities for electrocatalysts discovery and design.By analyzing experimental and theoretical data,machine learning can effectively predict their hydrogen evolution reaction(HER)performance.This review summarizes recent developments in machine learning for low-dimensional electrocatalysts,including zero-dimension nanoparticles and nanoclusters,one-dimensional nanotubes and nanowires,two-dimensional nanosheets,as well as other electrocatalysts.In particular,the effects of descriptors and algorithms on screening low-dimensional electrocatalysts and investigating their HER performance are highlighted.Finally,the future directions and perspectives for machine learning in electrocatalysis are discussed,emphasizing the potential for machine learning to accelerate electrocatalyst discovery,optimize their performance,and provide new insights into electrocatalytic mechanisms.Overall,this work offers an in-depth understanding of the current state of machine learning in electrocatalysis and its potential for future research.
基金the funding support from the National Key Research and Development Program of China(2020YFB2007400)the National Natural Science Foundation of China(22209202,22075317)the Strategic Priority Research Program(B)(XDB33030200)of Chinese Academy of Sciences。
文摘Hetero-element doping is a promising strategy to improve the cycling stability of nickel-rich cobalt-free cathodes for the next-generation high energy-density Li ion batteries.To make doping effective,it is important to understand the mechanism of how the dopants regulate the electronic band,lattice parameter adjusting,or hetero-phase formation to achieve high stability.In this study,we investigate LiNi_(0.9)Mn_(0.1)O_(2)cathodes doped with IVB grouping elements via multiple characterization techniques.By utilizing in situ XRD and TEM methods,we found that the stronger Ti-O bond effectively improves the cathode stability via a dual protection mechanism.Specifically,the bulk lattice of cathode is wellpreserved during cycling as a result of the suppressed H_(2)-H_(3)phase transition,while a in situ formed Ti-rich surface layer can prevent continuous surface degradation.As a result,the 5%Ti doped LiNi_(0.9)Mn_(0.1)O_(2)cathode exhibits a high capacity retention of 96%after 100 cycles.Whereas,despite IVB group elements Zr and Hf have stronger bonding energy with oxygen,their larger ionic radii actually impede their diffusion into the cathode,thereby they can not improve the cycling stability.Our findings uncover the functional origin of doped elements with their dynamic modification on cathode structure,providing mechanistic insights into the design of nickel-rich cobalt-free cathodes.
基金supported by the National Natural Science Foundation of China (51774251)the Hebei Natural Science Foundation for Distinguished Young Scholars (B2017203313)+7 种基金the Hundred Excellent Innovative Talents Support Program in Hebei Province (SLRC2017057)the Scientific Research Foundation for the Returned Overseas Chinese Scholars (CG2014003002)the Canada Foundation for Innovationthe Government of OntarioOntario Research Fund - Research Excellencethe University of Torontosupported by the National Natural Science Foundation of China (51702207 and 11972219)the Program for Professor of Special Appointment (Young Eastern Scholar Program) at Shanghai Institutions of Higher Learning。
文摘Wadsley-Roth (W-R) structured oxides featured with wide channels represent one of the most promising material families showing compelling rate performance for lithium-ion batteries.Herein,we report an indepth study on the fast and extensive intercalation chemistry of phosphorus stabilized W-R phase PNb_(9)O_(25) and its application in high energy and fast-charging devices.We explore the intercalation geometry of PNb_(9)O_(25) and identify two geometrical types of stable insertion sites with the total amount much higher than conventional intercalation-type electrodes.We reveal the ion transportation kinetics that the Li ions initially diffuse along the open type Ⅲ channels and then penetrate to edge sites with low kinetic barriers.During the lithiation,no remarkable phase transition is detected with nearly intact host phosphorous niobium oxide backbone.Therefore,the oxide framework of PNb_(9)O_(25) keeps almost unchanged with all the fast diffusion channels and insertion cavities well-maintained upon cycling,which accomplishes the unconventional electrochemical performance of W-R structured electrodes.
基金supported by the National Key Research and Development Program of China(2016YFB0700504)Natural Science Foundation of Shanghai,China(16ZR1411500)+1 种基金Science and Technology Commission of Shanghai Municipality(18520723500)the Niagara supercomputer at the SciNet HPC Consortium in Canada and the High-Performance Computing Center of Shanghai University。
文摘Boron-dipyrromethene(BODIPY)is one promising class of sensitizers for dye-sensitized solar cells(DSSCs)due to unique merits of high absorption coefficient and versatile structural modification capability.However,such derivatives usually suffer from limited power conversion efficiencies(PCEs)because of narrow light absorption band and low electron injection.To aid the discovery of BODIPY sensitizers,we employ an inverse design method to design efficient sensitizers by integrating data mining and firstprinciple techniques.We establish robust data-mining models using genetic algorithm and multiple linear regression,where the features are filtered from 5515 descriptors and their meanings are explicitly explored for next inverse designs.Based on the features’understanding,we design candidates NH1-6 and predict their PCEs,demonstrating remarkable enhancements(58%maximum)compared to previous works.Furthermore,their optoelectronic properties including maximum absorption wavelengths,oscillator strengths,bandgaps,transferred charges,charge transferred distances,TiO_(2) conduction band shifts,short-circuit currents and electron injection efficiencies simulated via first-principle calculations indicate significant increasements(93 nm,122.41%,23.70%,36.36%,471.17%,63.64%,28.55%,107.86%maximum),which testifies the corresponding highly predicted PCEs and may overcome BODIPY dyes’shortcomings.The as-designed BODIPY sensitizers can be promising candidates for DSSCs,and such method could help accelerate the discovery of other energy materials.
