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| 1 | New frontiers for the materials genome initiative显示文摘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. | Juan J.de Pablo Nicholas E.Jackson Michael A.Webb Long-Qing Chen Joel E.Moore Dane Morgan Ryan Jacobs Tresa Pollock Darrell G.Schlom Eric S.Toberer James Analytis Ismaila Dabo Dean M.DeLongchamp Gregory A.Fiete Gregory M.Grason Geoffroy Hautier Yifei Mo Krishna Rajan Evan J.Reed Efrain Rodriguez Vladan Stevanovic Jin Suntivich Katsuyo Thornton Ji-Cheng Zhao | 2019 | npj Computational Materials2019，，1： | 7 |
| 2 | Quantum-continuum simulation of underpotential deposition at electrified metal–solution interfaces显示文摘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. | Stephen E.Weitzner Ismaila Dabo | 2017 | npj Computational Materials2017，，1： | 2 |
| 3 | QUANTUM ESPRESSO: a modular and open-source software project for quantumsimulations of materials显示文摘 | Paolo Giannozzi Stefano Baroni Nicola Bonini Matteo Calandra Roberto Car Carlo Cavazzoni Davide Ceresoli Guido L Chiarotti Matteo Cococcioni Ismaila Dabo Andrea Dal Corso Stefano de Gironcoli Stefano Fabris Guido Fratesi Ralph Gebauer Uwe Gerstmann Christ | 2009 | Journal of Physics: Condensed Matter2009，，39： | 1 |
| 4 | Implementation of distortion symmetry for the nudged elastic band method with DiSPy显示文摘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. | Jason M.Munro Vincent S.Liu Venkatraman Gopalan Ismaila Dabo | 2019 | npj Computational Materials2019，，1： | 1 |
| 5 | QUANTUM ESPRESSO: a modular and open-source software project for quantumsimulations of materials显示文摘 | Paolo Giannozzi Stefano Baroni Nicola Bonini Matteo Calandra Roberto Car Carlo Cavazzoni Davide Ceresoli Guido L Chiarotti Matteo Cococcioni Ismaila Dabo Andrea Dal Corso Stefano de Gironcoli Stefano Fabris Guido Fratesi Ralph Gebauer Uwe Gerstmann Christ | 2009 | Journal of Physics: Condensed Matter2009，，： | 1 |
| 6 | Machine learning in concrete science:applications,challenges,and best practices显示文摘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. | Zhanzhao Li Jinyoung Yoon Rui Zhang Farshad Rajabipour Wil V.Srubar III Ismaila Dabo Aleksandra Radlińska | 2022 | npj Computational Materials2022，，1： | 0 |
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