The 2019 materials by design roadmap

被引：246

作者：

Alberi, Kirstin ^{[1
]}

Nardelli, Marco Buongiorno ^{[2
]}

Zakutayev, Andriy ^{[1
]}

Mitas, Lubos ^{[3
]}

Curtarolo, Stefano ^{[4
,5
]}

Jain, Anubhav ^{[6
]}

Fornari, Marco ^{[7
]}

Marzari, Nicola ^{[8
]}

Takeuchi, Ichiro ^{[9
]}

Green, Martin L. ^{[10
]}

Kanatzidis, Mercouri ^{[11
]}

Toney, Mike F. ^{[12
]}

Butenko, Sergiy ^{[13
]}

Meredig, Bryce ^{[14
]}

Lany, Stephan ^{[1
]}

Kattner, Ursula ^{[15
]}

Davydov, Albert ^{[15
]}

Toberer, Eric S. ^{[16
]}

Stevanovic, Vladan ^{[16
]}

Walsh, Aron ^{[17
,18
]}

Park, Nam-Gyu ^{[19
]}

Aspuru-Guzik, Alan ^{[20
,21
,22
]}

Tabor, Daniel P. ^{[20
,21
]}

Nelson, Jenny ^{[23
,24
]}

Murphy, James ^{[25
]}

Setlur, Anant ^{[25
]}

Gregoire, John ^{[26
]}

Li, Hong ^{[27
]}

Xiao, Ruijuan ^{[27
]}

Ludwig, Alfred ^{[28
]}

Martin, Lane W. ^{[29
,30
]}

Rappe, Andrew M. ^{[31
]}

Wei, Su-Huai ^{[32
]}

Perkins, John ^{[1
]}

机构：

[1] Natl Renewable Energy Lab, Golden, CO 80401 USA

[2] Univ North Texas, Denton, TX USA

[3] North Carolina State Univ, Raleigh, NC USA

[4] Duke Univ, Durham, NC USA

[5] Max Planck Gesell, Fritz Haber Inst, Berlin, Germany

[6] Lawrence Berkeley Natl Lab, Energy Storage & Distributed Resources Dept, Berkeley, CA USA

[7] Cent Michigan Univ, Dept Phys, Mt Pleasant, MI 48859 USA

[8] Ecole Polytech Fed Lausanne, Theory & Simulat Mat, CH-1015 Lausanne, Switzerland

[9] Univ Maryland, College Pk, MD 20742 USA

[10] NIST, Mat Measurement Sci Div, Gaithersburg, MD 20899 USA

[11] Northwestern Univ, Evanston, IL USA

[12] SLAC, Menlo Pk, CA USA

[13] Texas A&M Univ, Dept Ind & Syst Engn, College Stn, TX USA

[14] Citrine Informat, Redwood City, CA USA

[15] NIST, Mat Sci & Engn Div, Gaithersburg, MD 20899 USA

[16] Colorado Sch Mines, Golden, CO 80401 USA

[17] Imperial Coll London, Dept Mat, Exhibit Rd, London SW7 2AZ, England

[18] Yonsei Univ, Dept Mat Sci & Engn, Seoul 03722, South Korea

[19] Sungkyunkwan Univ SKKU, Sch Chem Engn, Suwon 440746, South Korea

[20] Univ Toronto, Dept Chem, Toronto, ON, Canada

[21] Univ Toronto, Dept Comp Sci, Toronto, ON, Canada

[22] Vector Inst Artificial Intelligence, Toronto, ON, Canada

[23] Imperial Coll London, Dept Phys, London, England

[24] Imperial Coll London, Ctr Plast Elect, London, England

[25] GE Global Res, Funct Mat Lab, Niskayuna, NY USA

[26] CALTECH, Pasadena, CA 91125 USA

[27] Chinese Acad Sci, Inst Phys, Beijing, Peoples R China

[28] Ruhr Univ Bochum, Inst Mat, MEMS Mat, Bochum, Germany

[29] Univ Calif Berkeley, Dept Mat Sci & Engn, Berkeley, CA 94720 USA

[30] Lawrence Berkeley Natl Lab, Div Mat Sci, Berkeley, CA USA

[31] Univ Penn, Dept Chem, Philadelphia, PA 19104 USA

[32] Beijing Computat Sci Res Ctr, Beijing 100193, Peoples R China

来源：

JOURNAL OF PHYSICS D-APPLIED PHYSICS | 2019年 / 52卷 / 01期

基金：

英国工程与自然科学研究理事会;

关键词：

density functional theory; materials genome initative; materials design; high-throughput methods; energy applications; LIGHT-EMITTING-DIODES; DENSITY-FUNCTIONAL THEORY; MONTE-CARLO SIMULATIONS; MATERIALS DISCOVERY; AB-INITIO; MATERIALS SCIENCE; THIN-FILM; COMPUTATIONAL DESIGN; ROOM-TEMPERATURE; ION CONDUCTORS;

D O I：

10.1088/1361-6463/aad926

中图分类号：

O59 [应用物理学];

学科分类号：

摘要：

Advances in renewable and sustainable energy technologies critically depend on our ability to design and realize materials with optimal properties. Materials discovery and design efforts ideally involve close coupling between materials prediction, synthesis and characterization. The increased use of computational tools, the generation of materials databases, and advances in experimental methods have substantially accelerated these activities. It is therefore an opportune time to consider future prospects for materials by design approaches. The purpose of this Roadmap is to present an overview of the current state of computational materials prediction, synthesis and characterization approaches, materials design needs for various technologies, and future challenges and opportunities that must be addressed. The various perspectives cover topics on computational techniques, validation, materials databases, materials informatics, high-throughput combinatorial methods, advanced characterization approaches, and materials design issues in thermoelectrics, photovoltaics, solid state lighting, catalysts, batteries, metal alloys, complex oxides and transparent conducting materials. It is our hope that this Roadmap will guide researchers and funding agencies in identifying new prospects for materials design.

引用

页数：48

共 172 条

[1] Reformulation of DFT plus U as a Pseudohybrid Hubbard Density Functional for Accelerated Materials Discovery [J].