Designing materials with targeted lattice thermal conductivity(LTC)demands electronic-level insight into chemical bonding.We introduce two bonding descriptors,namely normalized negative integrated COHP(-ICOHP)and norm...Designing materials with targeted lattice thermal conductivity(LTC)demands electronic-level insight into chemical bonding.We introduce two bonding descriptors,namely normalized negative integrated COHP(-ICOHP)and normalized integrated COBI,that correlate strongly with LTC and rattling(meansquared displacement),surpassing empirical rules and the unnormalized−ICOHP across>4500 inorganic crystals by first-principles.We train a crystal attention graph neural network(CATGNN)to predict these descriptors and screen~200,000 database structures for extreme LTCs.From 367(533)candidates with low(high)normalized-ICOHP and normalized ICOBI,first-principles validation identifies 106 dynamically stable compounds with LTC<5Wm^(−1)K^(−1)(68%<2Wm^(−1)K^(−1))and 13 stable compounds with LTC>100Wm^(−1)K^(−1).The descriptors’low cost and clear physical meaning provide a rapid,reliable route to high-throughput discovery and inverse design of crystalline materials with ultralow or ultrahigh LTC for applications in thermal insulation,thermoelectrics,and electronics cooling.展开更多
Lead-based organic–inorganic metal halides(OIMHs)have recently attracted special attention due to their efficient broadband photoluminescence.However,the toxicity of lead poses a challenge for their further developme...Lead-based organic–inorganic metal halides(OIMHs)have recently attracted special attention due to their efficient broadband photoluminescence.However,the toxicity of lead poses a challenge for their further development.Here,we selected Sn(IV)as the metal center to synthesize the environmentally friendly and stable luminescent OIMHs(C_(9)H_(15)N_(3))_(2)SnCl_(8)and(C_(9)H_(15)N_(3))_(2)SnBr_(8)(C_(9)H_(13)N_(3)is 1-(_(2)-pyridyl)piperazine).展开更多
A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data.While prior examples have demonstrated successful models ...A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data.While prior examples have demonstrated successful models for some applications,many more applications exist where machine learning can make a strong impact.To enable faster development of machine-learning-based models for such applications,we have created a framework capable of being applied to a broad range of materials data.Our method works by using a chemically diverse list of attributes,which we demonstrate are suitable for describing a wide variety of properties,and a novel method for partitioning the data set into groups of similar materials to boost the predictive accuracy.In this manuscript,we demonstrate how this new method can be used to predict diverse properties of crystalline and amorphous materials,such as band gap energy and glass-forming ability.展开更多
The contribution of theoretical calculations and predictions in the development of advanced high-performance thermoelectrics has been increasingly significant and has successfully guided experiments to understand as w...The contribution of theoretical calculations and predictions in the development of advanced high-performance thermoelectrics has been increasingly significant and has successfully guided experiments to understand as well as achieve record-breaking results.In this review,recent developments in high-performance nanostructured bulk thermoelectric materials are discussed from the viewpoint of theoretical calculations.An effective emerging strategy for boosting thermoelectric performance involves minimizing electron scattering while maximizing heat-carrying phonon scattering on many length scales.We present several important strategies and key examples that highlight the contributions of first-principles-based calculations in revealing the intricate but tractable relationships for this synergistic optimization of thermoelectric performance.The integrated optimization approach results in a fourfold design strategy for improved materials:(1)a significant reduction of the lattice thermal conductivity through multiscale hierarchical architecturing,(2)a large enhancement of the Seebeck coefficient through intramatrix electronic band convergence engineering,(3)control of the carrier mobility through band alignment between the host and second phases,and(4)design of intrinsically low-thermal-conductivity materials by maximizing vibrational anharmonicity and acoustic-mode Gruneisen parameters.These combined effects serve to enhance the power factor while reducing the lattice thermal conductivity.This review provides an improved understanding of how theory is impacting the current state of this field and helps to guide the future search for high-performance thermoelectric materials.展开更多
Most crystalline materials follow the guidelines of T^(-1) temperature-dependent lattice thermal conductivity(κ_(L))at elevated temperatures.Here,we observe a weak temperature dependence ofκL in Mg_(3)Sb_(2),T^(-0:4...Most crystalline materials follow the guidelines of T^(-1) temperature-dependent lattice thermal conductivity(κ_(L))at elevated temperatures.Here,we observe a weak temperature dependence ofκL in Mg_(3)Sb_(2),T^(-0:48) from theory and T-0:57 from measurements,based on a comprehensive study combining ab initio molecular dynamics calculations and experimental measurements on single crystal Mg_(3)Sb_(2).These results can be understood in terms of the so-called“phonon renormalization”effects due to the strong temperature dependence of the interatomic force constants(IFCs).The increasing temperature leads to the frequency upshifting for those low-frequency phonons dominating heat transport,and more importantly,the phononphonon interactions are weakened.In-depth analysis reveals that the phenomenon is closely related to the temperature-induced asymmetric movements of Mg atoms within MgSb_(4) tetrahedron.With increasing temperature,these Mg atoms tend to locate at the areas with relatively low force in the force profile,leading to reduced effective 3^(rd)-order IFCs.The locally asymmetrical atomic movements at elevated temperatures can be further treated as an indicator of temperature-induced variations of IFCs and thus relatively strong phonon renormalization.The present work sheds light on the fundamental origins of anomalous temperature dependence of κ_(L) in thermoelectrics.展开更多
基金supported in part by the NSF(award numbers 2110033,2311202,2320292)SC EPSCoR/IDeA Program under NSF OIA-1655740(23-GC01)+2 种基金R.R.acknowledges financial support by the Severo Ochoa Centers of Excellence Program under grant CEX2023-001263-Sby the Generalitat de Catalunya under grant 2021 SGR 01519Calculations were performed at the Centro de Supercomputación de Galicia(CESGA)within actions FI-2023-1-0003,FI-2023-2-0005,and FI-2024-1-0012 of the Red Española de Supercomputación(RES).
文摘Designing materials with targeted lattice thermal conductivity(LTC)demands electronic-level insight into chemical bonding.We introduce two bonding descriptors,namely normalized negative integrated COHP(-ICOHP)and normalized integrated COBI,that correlate strongly with LTC and rattling(meansquared displacement),surpassing empirical rules and the unnormalized−ICOHP across>4500 inorganic crystals by first-principles.We train a crystal attention graph neural network(CATGNN)to predict these descriptors and screen~200,000 database structures for extreme LTCs.From 367(533)candidates with low(high)normalized-ICOHP and normalized ICOBI,first-principles validation identifies 106 dynamically stable compounds with LTC<5Wm^(−1)K^(−1)(68%<2Wm^(−1)K^(−1))and 13 stable compounds with LTC>100Wm^(−1)K^(−1).The descriptors’low cost and clear physical meaning provide a rapid,reliable route to high-throughput discovery and inverse design of crystalline materials with ultralow or ultrahigh LTC for applications in thermal insulation,thermoelectrics,and electronics cooling.
基金supported by The National Key Research and Development Program of China(2021YFA0718900)the National Natural Science Foundation of China(51972021)the Fundamental Research Funds for the Central Universities FRF-IDRY-19-005SHand cW are supported by the US Department of Energy,Office of Science and Office of Basic Energy Sciences|under award number DE-SC0014520.
文摘Lead-based organic–inorganic metal halides(OIMHs)have recently attracted special attention due to their efficient broadband photoluminescence.However,the toxicity of lead poses a challenge for their further development.Here,we selected Sn(IV)as the metal center to synthesize the environmentally friendly and stable luminescent OIMHs(C_(9)H_(15)N_(3))_(2)SnCl_(8)and(C_(9)H_(15)N_(3))_(2)SnBr_(8)(C_(9)H_(13)N_(3)is 1-(_(2)-pyridyl)piperazine).
基金supported in part by the following grants:DARPA SIMPLEX award N66001-15-C-4036NSF awards IIS-1343639+3 种基金CCF-1409601DOE award DESC0007456AFOSR award FA9550-12-1-0458supported by the Department of Defense(DoD)through the National Defense Science&Engineering Graduate Fellowship(NDSEG)Program.
文摘A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data.While prior examples have demonstrated successful models for some applications,many more applications exist where machine learning can make a strong impact.To enable faster development of machine-learning-based models for such applications,we have created a framework capable of being applied to a broad range of materials data.Our method works by using a chemically diverse list of attributes,which we demonstrate are suitable for describing a wide variety of properties,and a novel method for partitioning the data set into groups of similar materials to boost the predictive accuracy.In this manuscript,we demonstrate how this new method can be used to predict diverse properties of crystalline and amorphous materials,such as band gap energy and glass-forming ability.
基金The authors acknowledge support by the U.S.Department of Energy,Office of Science,Office of Basic Energy Sciences under Award Number DE-SC0014520.
文摘The contribution of theoretical calculations and predictions in the development of advanced high-performance thermoelectrics has been increasingly significant and has successfully guided experiments to understand as well as achieve record-breaking results.In this review,recent developments in high-performance nanostructured bulk thermoelectric materials are discussed from the viewpoint of theoretical calculations.An effective emerging strategy for boosting thermoelectric performance involves minimizing electron scattering while maximizing heat-carrying phonon scattering on many length scales.We present several important strategies and key examples that highlight the contributions of first-principles-based calculations in revealing the intricate but tractable relationships for this synergistic optimization of thermoelectric performance.The integrated optimization approach results in a fourfold design strategy for improved materials:(1)a significant reduction of the lattice thermal conductivity through multiscale hierarchical architecturing,(2)a large enhancement of the Seebeck coefficient through intramatrix electronic band convergence engineering,(3)control of the carrier mobility through band alignment between the host and second phases,and(4)design of intrinsically low-thermal-conductivity materials by maximizing vibrational anharmonicity and acoustic-mode Gruneisen parameters.These combined effects serve to enhance the power factor while reducing the lattice thermal conductivity.This review provides an improved understanding of how theory is impacting the current state of this field and helps to guide the future search for high-performance thermoelectric materials.
基金This work was supported by the National Key Research and Development Program of China(Nos.2018YFB0703600,2017YFB0701600,and 2019YFA0704901)Natural Science Foundation of China(Grant Nos.11674211,51632005,and 51761135127)+7 种基金the 111 Project D16002W.Z.also acknowledges the support from the Guangdong Innovation Research Team Project(No.2017ZT07C062)Guangdong Provincial Key Lab program(No.2019B030301001)Shenzhen Municipal Key Lab program(ZDSYS20190902092905285)Shenzhen Pengcheng-Scholarship ProgramC.F.acknowledges funding support by the Deutsche Forschungsgemeinschaft(DFG,German Research Foundation)—Projektnummer(392228380)Y.X.and C.W.acknowledge the financial support received from the U.S.Department of Commerce and National Institute of Standards and Technology as part of the Center for Hierarchical Materials Design(CHiMaD)under Grant No.70NANB14H012This research used resources of the National Energy Research Scientific Computing Center,a DOE Office of Science User Facility supported by the Office of Science of the U.S.Department of Energy(U.S.Department of Energy Contract No.DEAC02-05CH11231).
文摘Most crystalline materials follow the guidelines of T^(-1) temperature-dependent lattice thermal conductivity(κ_(L))at elevated temperatures.Here,we observe a weak temperature dependence ofκL in Mg_(3)Sb_(2),T^(-0:48) from theory and T-0:57 from measurements,based on a comprehensive study combining ab initio molecular dynamics calculations and experimental measurements on single crystal Mg_(3)Sb_(2).These results can be understood in terms of the so-called“phonon renormalization”effects due to the strong temperature dependence of the interatomic force constants(IFCs).The increasing temperature leads to the frequency upshifting for those low-frequency phonons dominating heat transport,and more importantly,the phononphonon interactions are weakened.In-depth analysis reveals that the phenomenon is closely related to the temperature-induced asymmetric movements of Mg atoms within MgSb_(4) tetrahedron.With increasing temperature,these Mg atoms tend to locate at the areas with relatively low force in the force profile,leading to reduced effective 3^(rd)-order IFCs.The locally asymmetrical atomic movements at elevated temperatures can be further treated as an indicator of temperature-induced variations of IFCs and thus relatively strong phonon renormalization.The present work sheds light on the fundamental origins of anomalous temperature dependence of κ_(L) in thermoelectrics.
