The Materials Genome Initiative(MGI)advanced a new paradigm for materials discovery and design,namely that the pace of new materials deployment could be accelerated through complementary efforts in theory,computation,...The Materials Genome Initiative(MGI)advanced a new paradigm for materials discovery and design,namely that the pace of new materials deployment could be accelerated through complementary efforts in theory,computation,and experiment.Along with numerous successes,new challenges are inviting researchers to refocus the efforts and approaches that were originally inspired by the MGI.In May 2017,the National Science Foundation sponsored the workshop“Advancing and Accelerating Materials Innovation Through the Synergistic Interaction among Computation,Experiment,and Theory:Opening New Frontiers”to review accomplishments that emerged from investments in science and infrastructure under the MGI,identify scientific opportunities in this new environment,examine how to effectively utilize new materials innovation infrastructure,and discuss challenges in achieving accelerated materials research through the seamless integration of experiment,computation,and theory.This article summarizes key findings from the workshop and provides perspectives that aim to guide the direction of future materials research and its translation into societal impacts.展开更多
Concrete,as the most widely used construction material,is inextricably connected with human development.Despite conceptual and methodological progress in concrete science,concrete formulation for target properties rem...Concrete,as the most widely used construction material,is inextricably connected with human development.Despite conceptual and methodological progress in concrete science,concrete formulation for target properties remains a challenging task due to the ever-increasing complexity of cementitious systems.With the ability to tackle complex tasks autonomously,machine learning(ML)has demonstrated its transformative potential in concrete research.Given the rapid adoption of ML for concrete mixture design,there is a need to understand methodological limitations and formulate best practices in this emerging computational field.Here,we review the areas in which ML has positively impacted concrete science,followed by a comprehensive discussion of the implementation,application,and interpretation of ML algorithms.We conclude by outlining future directions for the concrete community to fully exploit the capabilities of ML models.展开更多
The underpotential deposition of transition metal ions is a critical step in many electrosynthetic approaches.While underpotential deposition has been intensively studied at the atomic level,first-principles calculati...The underpotential deposition of transition metal ions is a critical step in many electrosynthetic approaches.While underpotential deposition has been intensively studied at the atomic level,first-principles calculations in vacuum can strongly underestimate the stability of underpotentially deposited metals.It has been shown recently that the consideration of co-adsorbed anions can deliver more reliable descriptions of underpotential deposition reactions;however,the influence of additional key environmental factors such as the electrification of the interface under applied voltage and the activities of the ions in solution have yet to be investigated.In this work,copper underpotential deposition on gold is studied under realistic electrochemical conditions using a quantum-continuum model of the electrochemical interface.We report here on the influence of surface electrification,concentration effects,and anion co-adsorption on the stability of the copper underpotential deposition layer on the gold(100)surface.展开更多
The nudged elastic band(NEB)method is a commonly used approach for the calculation of minimum energy pathways of kinetic processes.However,the final paths obtained rely heavily on the nature of the initially chosen pa...The nudged elastic band(NEB)method is a commonly used approach for the calculation of minimum energy pathways of kinetic processes.However,the final paths obtained rely heavily on the nature of the initially chosen path.This often necessitates running multiple calculations with differing starting points in order to obtain accurate results.Recently,it has been shown that the NEB algorithm can only conserve or raise the distortion symmetry exhibited by an initial pathway.Using this knowledge,symmetryadapted perturbations can be generated and used as a tool to systematically lower the initial path symmetry,enabling the exploration of other low-energy pathways that may exist.Here,the group and representation theory details behind this process are presented and implemented in a standalone piece of software(DiSPy).The method is then demonstrated by applying it to the calculation of ferroelectric switching pathways in LiNbO_(3).Previously reported pathways are more easily obtained,with new paths also being found which involve a higher degree of atomic coordination.展开更多
Efficient thermal management is critical to device performance and reliability for energy conversion,nanoelectronics, and the development of quantum technologies. The commonly-used diffusive modelof heat transport bre...Efficient thermal management is critical to device performance and reliability for energy conversion,nanoelectronics, and the development of quantum technologies. The commonly-used diffusive modelof heat transport breaks down for confined nanoscale geometries, and advanced theories beyonddiffusion are based on disparate assumptions that lead to conflicting predictions. Here, we outline andcontrast the two predominant formulations of the Boltzmann equation for heat transport insemiconductors, namely, the ballistic and hydrodynamic models. We examine these methods in lightof experiments and atomistic calculations of heat fluxes and temperature profiles in phononic systemswith nanometer-sized features. Weargue that reconciling the hydrodynamic and ballistic formulationsis an outstanding necessity to develop a unifying theory of confinement effects on phonon flow, whichwill ultimately lead to optimal strategies for thermal management in nanodevices.展开更多
文摘The Materials Genome Initiative(MGI)advanced a new paradigm for materials discovery and design,namely that the pace of new materials deployment could be accelerated through complementary efforts in theory,computation,and experiment.Along with numerous successes,new challenges are inviting researchers to refocus the efforts and approaches that were originally inspired by the MGI.In May 2017,the National Science Foundation sponsored the workshop“Advancing and Accelerating Materials Innovation Through the Synergistic Interaction among Computation,Experiment,and Theory:Opening New Frontiers”to review accomplishments that emerged from investments in science and infrastructure under the MGI,identify scientific opportunities in this new environment,examine how to effectively utilize new materials innovation infrastructure,and discuss challenges in achieving accelerated materials research through the seamless integration of experiment,computation,and theory.This article summarizes key findings from the workshop and provides perspectives that aim to guide the direction of future materials research and its translation into societal impacts.
文摘Concrete,as the most widely used construction material,is inextricably connected with human development.Despite conceptual and methodological progress in concrete science,concrete formulation for target properties remains a challenging task due to the ever-increasing complexity of cementitious systems.With the ability to tackle complex tasks autonomously,machine learning(ML)has demonstrated its transformative potential in concrete research.Given the rapid adoption of ML for concrete mixture design,there is a need to understand methodological limitations and formulate best practices in this emerging computational field.Here,we review the areas in which ML has positively impacted concrete science,followed by a comprehensive discussion of the implementation,application,and interpretation of ML algorithms.We conclude by outlining future directions for the concrete community to fully exploit the capabilities of ML models.
文摘The underpotential deposition of transition metal ions is a critical step in many electrosynthetic approaches.While underpotential deposition has been intensively studied at the atomic level,first-principles calculations in vacuum can strongly underestimate the stability of underpotentially deposited metals.It has been shown recently that the consideration of co-adsorbed anions can deliver more reliable descriptions of underpotential deposition reactions;however,the influence of additional key environmental factors such as the electrification of the interface under applied voltage and the activities of the ions in solution have yet to be investigated.In this work,copper underpotential deposition on gold is studied under realistic electrochemical conditions using a quantum-continuum model of the electrochemical interface.We report here on the influence of surface electrification,concentration effects,and anion co-adsorption on the stability of the copper underpotential deposition layer on the gold(100)surface.
基金This material is based upon work supported by the National Science Foundation under Grant No.1807768 and No.1210588We acknowledge the support of the Natural Sciences and Engineering Research Council of Canada(NSERC)+1 种基金the NSFMRSEC Center for Nanoscale Science at the Pennsylvania State University,Grant No.DMR-1420620J.M.M.and I.D.also acknowledge partial support from the Soltis faculty support award and the Ralph E.Powe junior faculty award from Oak Ridge Associated Universities.
文摘The nudged elastic band(NEB)method is a commonly used approach for the calculation of minimum energy pathways of kinetic processes.However,the final paths obtained rely heavily on the nature of the initially chosen path.This often necessitates running multiple calculations with differing starting points in order to obtain accurate results.Recently,it has been shown that the NEB algorithm can only conserve or raise the distortion symmetry exhibited by an initial pathway.Using this knowledge,symmetryadapted perturbations can be generated and used as a tool to systematically lower the initial path symmetry,enabling the exploration of other low-energy pathways that may exist.Here,the group and representation theory details behind this process are presented and implemented in a standalone piece of software(DiSPy).The method is then demonstrated by applying it to the calculation of ferroelectric switching pathways in LiNbO_(3).Previously reported pathways are more easily obtained,with new paths also being found which involve a higher degree of atomic coordination.
基金support from the STROBE National Science Foundation Science & Technology Center, Grant No. DMR-1548924A.B. acknowledges support from the Spanish Ministerio de Ciencia, Innovación y Universidades, Grant No. PID2021-122322NB-I00 and TED2021-129612B-C22 (MCIU/AEI/10.13039/501100011033/FEDER UE)+2 种基金the AGAUR - Generalitat de Catalunya, Grant No. 2021-SGR-00644This work utilized the Alpine high performance computing resource at the University of Colorado Boulder. Alpine is jointly funded by the University of Colorado Boulder, the University of Colorado Anschutz, and Colorado State UniversityT.K.S. and I.D. acknowledge primarily support from the Center for Nanoscale Science under Grants No. DMR-1420620 and No. DMR-2011839 [NSF-funded Materials Research Science and Engineering Centers (MRSEC)].
文摘Efficient thermal management is critical to device performance and reliability for energy conversion,nanoelectronics, and the development of quantum technologies. The commonly-used diffusive modelof heat transport breaks down for confined nanoscale geometries, and advanced theories beyonddiffusion are based on disparate assumptions that lead to conflicting predictions. Here, we outline andcontrast the two predominant formulations of the Boltzmann equation for heat transport insemiconductors, namely, the ballistic and hydrodynamic models. We examine these methods in lightof experiments and atomistic calculations of heat fluxes and temperature profiles in phononic systemswith nanometer-sized features. Weargue that reconciling the hydrodynamic and ballistic formulationsis an outstanding necessity to develop a unifying theory of confinement effects on phonon flow, whichwill ultimately lead to optimal strategies for thermal management in nanodevices.
