Lanthanide–organic frameworks(Ln-MOFs)have garnered increasing research interest as photoluminescent materials.However,the characteristic fluorescence of Ln^(3+)ions is constrained by the energy level matching betwee...Lanthanide–organic frameworks(Ln-MOFs)have garnered increasing research interest as photoluminescent materials.However,the characteristic fluorescence of Ln^(3+)ions is constrained by the energy level matching between Ln^(3+)ions and organic ligands,and the impact of the spatial structure of Ln-MOFs on the energy transfer process remains insufficiently explored,thereby limiting their broader optical applications.In this work,we propose a Cd^(2+)-induced heterobimetallic Ln-MOF(HNU-72)as a fluorescence modulation strategy,marking a significant breakthrough in activating the characteristic fluorescence of Ln^(3+)ions,transitioning from absence to emergence.Both experimental measurements and theoretical calculations reveal that the incorporation of Cd^(2+)ions reconfigures the energy transfer pathway,thereby enhancing the energy transfer modulation between H_(4)TCPE(1,1,2,2-tetra(4-carboxyphenyl)ethylene)and Eu^(3+)ions.Furthermore,leveraging the dual fluorescence emission peaks observed in HNU-72,we achieved an ultra-low detection limit of 14 ppb for the proportional fluorescence detection of dimethyl sulfide in marine environments.This study not only deepens our understanding of the energy transfer mechanisms in Ln-MOF materials,but also paves the way for the development of multifunctional fluorescence sensing platforms.展开更多
Li_(2)FeSiO_(4)is a superior cathode material for lithium ion batteries(LIBs)owing to its high capacity,low cost,and superior stability.Exhilaratingly,the material also exhibits the desired electrochemical performance...Li_(2)FeSiO_(4)is a superior cathode material for lithium ion batteries(LIBs)owing to its high capacity,low cost,and superior stability.Exhilaratingly,the material also exhibits the desired electrochemical performance as the anode for LIBs in comparison with traditional carbon materials.However,the Li_(2)FeSiO_(4)anode is subject to a fatal capacity degradation in long cycles,due to its low conductivity and serious particle agglomeration.展开更多
Second-principles method is an efficient way to build atomistic models and is widely used to simulate various properties of perovskite ferroelectric materials.However,the state-of-the-art approach to constructing trai...Second-principles method is an efficient way to build atomistic models and is widely used to simulate various properties of perovskite ferroelectric materials.However,the state-of-the-art approach to constructing training set for second-principles model still highly relies on researcher’s experience and a universal approach remains elusive.In this work,we combine machine learning and second principles method to achieve automatic generation of second-principles model.The original training set is derived from phonons and is then updated based on the uncertainties predicted by machine learning with data generated via molecular dynamics simulations.This approach allows us to obtain a machine learning assisted second-principles model for BaTiO_(3),which has amuch-improved accuracy compared to the model in our previous work[Physical Review B,108134117(2023)].Furthermore,we investigate thermal transport properties of BaTiO_(3)with the new second-principles model,and find a weak wave-like contribution to the thermal conductivity.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.22361017)the Specific Research Fund of the Innovation Platform for Academicians of Hainan Province(Grant No.YSPTZX202321)+1 种基金the Hainan Province Science and Technology Special Fund(ZDYF2024GXJS300)the Innovation Platform for Academicians of Hainan Province.
文摘Lanthanide–organic frameworks(Ln-MOFs)have garnered increasing research interest as photoluminescent materials.However,the characteristic fluorescence of Ln^(3+)ions is constrained by the energy level matching between Ln^(3+)ions and organic ligands,and the impact of the spatial structure of Ln-MOFs on the energy transfer process remains insufficiently explored,thereby limiting their broader optical applications.In this work,we propose a Cd^(2+)-induced heterobimetallic Ln-MOF(HNU-72)as a fluorescence modulation strategy,marking a significant breakthrough in activating the characteristic fluorescence of Ln^(3+)ions,transitioning from absence to emergence.Both experimental measurements and theoretical calculations reveal that the incorporation of Cd^(2+)ions reconfigures the energy transfer pathway,thereby enhancing the energy transfer modulation between H_(4)TCPE(1,1,2,2-tetra(4-carboxyphenyl)ethylene)and Eu^(3+)ions.Furthermore,leveraging the dual fluorescence emission peaks observed in HNU-72,we achieved an ultra-low detection limit of 14 ppb for the proportional fluorescence detection of dimethyl sulfide in marine environments.This study not only deepens our understanding of the energy transfer mechanisms in Ln-MOF materials,but also paves the way for the development of multifunctional fluorescence sensing platforms.
基金supported by the National Natural Science Foundation of China(51672235 and 51902277)the Xinjiang University Doctoral Research Foundation(2018),the Xinjiang Tianchi Doctoral Project(2018),the Natural Science Foundation of Xinjiang Uygur Autonomous Region of China(2019D01C044),and the National Ten Thousand Talents Program(2017).
文摘Li_(2)FeSiO_(4)is a superior cathode material for lithium ion batteries(LIBs)owing to its high capacity,low cost,and superior stability.Exhilaratingly,the material also exhibits the desired electrochemical performance as the anode for LIBs in comparison with traditional carbon materials.However,the Li_(2)FeSiO_(4)anode is subject to a fatal capacity degradation in long cycles,due to its low conductivity and serious particle agglomeration.
基金supported by the National Natural Science Foundation of China(Grant Nos.12302208 and 12432007)the National Program on Key Basic Research Project(Grant No.2022YFB3807601).
文摘Second-principles method is an efficient way to build atomistic models and is widely used to simulate various properties of perovskite ferroelectric materials.However,the state-of-the-art approach to constructing training set for second-principles model still highly relies on researcher’s experience and a universal approach remains elusive.In this work,we combine machine learning and second principles method to achieve automatic generation of second-principles model.The original training set is derived from phonons and is then updated based on the uncertainties predicted by machine learning with data generated via molecular dynamics simulations.This approach allows us to obtain a machine learning assisted second-principles model for BaTiO_(3),which has amuch-improved accuracy compared to the model in our previous work[Physical Review B,108134117(2023)].Furthermore,we investigate thermal transport properties of BaTiO_(3)with the new second-principles model,and find a weak wave-like contribution to the thermal conductivity.
