Roadmap on data-centric materials science

被引：10

作者：

Bauer, Stefan ^{[1
,2
]}

Benner, Peter ^{[3
]}

Bereau, Tristan ^{[4
]}

Blum, Volker ^{[5
]}

Boley, Mario ^{[6
]}

Carbogno, Christian ^{[7
]}

Catlow, C. Richard A. ^{[8
,9
,10
,11
]}

Dehm, Gerhard ^{[12
]}

Eibl, Sebastian ^{[13
]}

Ernstorfer, Ralph ^{[14
]}

Fekete, Adam ^{[15
]}

Foppa, Lucas ^{[7
]}

Fratzl, Peter ^{[16
]}

Freysoldt, Christoph ^{[12
]}

Gault, Baptiste ^{[12
,17
]}

Ghiringhelli, Luca M. ^{[7
,18
]}

Giri, Sajal K. ^{[19
]}

Gladyshev, Anton ^{[15
]}

Goyal, Pawan ^{[3
]}

Hattrick-Simpers, Jason ^{[20
]}

Kabalan, Lara ^{[8
,21
]}

Karpov, Petr ^{[13
]}

Khorrami, Mohammad S. ^{[12
]}

Koch, Christoph T. ^{[15
]}

Kokott, Sebastian ^{[7
,22
]}

Kosch, Thomas ^{[23
]}

Kowalec, Igor ^{[8
,9
]}

Kremer, Kurt ^{[24
]}

Leitherer, Andreas ^{[7
,25
]}

Li, Yue ^{[12
]}

Liebscher, Christian H. ^{[12
]}

Logsdail, Andrew J. ^{[8
,9
]}

Lu, Zhongwei ^{[8
,9
]}

Luong, Felix ^{[6
]}

Marek, Andreas ^{[13
]}

Merz, Florian ^{[26
]}

Mianroodi, Jaber R. ^{[12
]}

Neugebauer, Joerg ^{[12
]}

Pei, Zongrui ^{[27
]}

Purcell, Thomas A. R. ^{[7
,28
]}

Raabe, Dierk ^{[12
]}

Rampp, Markus ^{[13
]}

Rossi, Mariana ^{[29
]}

Rost, Jan-Michael ^{[30
]}

Saal, James ^{[31
]}

Saalmann, Ulf ^{[30
]}

Sasidhar, Kasturi Narasimha ^{[12
]}

Saxena, Alaukik ^{[12
]}

Sbailo, Luigi ^{[15
]}

Scheidgen, Markus ^{[15
]}

机构：

[1] Tech Univ Munich, Sch Computat Informat & Technol, Garching, Germany

[2] Helmholtz AI, Munich, Germany

[3] Max Planck Inst Dynam Complex Tech Syst, Magdeburg, Germany

[4] Heidelberg Univ, Inst Theoret Phys, Heidelberg, Germany

[5] Duke Univ, Thomas Lord Dept Mech Engn & Mat Sci, Morrisville, NC USA

[6] Monash Univ, Dept Data Sci & AI, Monash, Australia

[7] Fritz Haber Inst Max Planck Soc, NOMAD Lab, Berlin, Germany

[8] Cardiff Univ, Max Planck Cardiff Ctr Fundamentals Heterogeneous, FUNCAT, Sch Chem, Cardiff, Wales

[9] Cardiff Univ, Cardiff Catalysis Inst, Sch Chem, Cardiff, Wales

[10] UK Catalysis Hub, Res Complex Harwell, RAL, Oxford, England

[11] UCL, Dept Chem, London, England

[12] Max Planck Inst Sustainable Mat, Dusseldorf, Germany

[13] Max Planck Comp & Data Facil, Rosenheim, Germany

[14] Tech Univ Berlin, Inst Opt & Atom Phys, Berlin, Germany

[15] Humboldt Univ, Dept Phys & CSMB, Berlin, Germany

[16] Max Planck Inst Colloids & Interfaces, Golm, Germany

[17] Imperial Coll, Dept Mat, London, England

[18] Friedrich Alexander Univ Erlangen Nurnberg FAU, Dept Mat Sci & Engn, Erlangen, Germany

[19] Northwestern Univ, Dept Chem, Evanston, IL USA

[20] Univ Toronto, Dept Mat Sci & Engn, Toronto, ON, Canada

[21] STFC Hartree Ctr, Daresbury Lab, Warrington, England

[22] Mol Simulat First Principles eV, D-14195 Berlin, Germany

[23] Humboldt Univ, Dept Comp Sci, Berlin, Germany

[24] Max Planck Inst Polymer Res, Mainz, Germany

[25] Barcelona Inst Sci & Technol, Inst Ciencies Foton, ICFO, Barcelona, Spain

[26] Lenovo HPC Innovat Ctr, Stuttgart, Germany

[27] NYU, New York, NY 10012 USA

[28] Univ Arizona, Dept Chem & Biochem, Tucson, AZ USA

[29] Max Planck Inst Struct & Dynam Matter, Hamburg, Germany

[30] Max Planck Inst Phys Komplexer Syst, Dresden, Germany

[31] Citrine Informat Inc, Redwood City, CA USA

[32] Fritz Haber Inst, Max Planck Soc, Dept Inorgan Chem, Berlin, Germany

[33] Ecole Polytech Fed Lausanne, Sch Engn, Lausanne, Switzerland

[34] Max Planck Inst Informat, Saarbrucken, Germany

[35] Univ Toronto, Dept Stat Sci, Toronto, ON, Canada

[36] Oak Ridge Natl Lab, Oak Ridge, TN USA

来源：

MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING | 2024年 / 32卷 / 06期

关键词：

data; centric; materials; science; molecular simulations; roadmap; X-RAY-SCATTERING; ELECTRON; RECONSTRUCTION; NANOSTRUCTURE; FRAMEWORK; CATALYSIS;

D O I：

10.1088/1361-651X/ad4d0d

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Science is and always has been based on data, but the terms 'data-centric' and the '4th paradigm' of materials research indicate a radical change in how information is retrieved, handled and research is performed. It signifies a transformative shift towards managing vast data collections, digital repositories, and innovative data analytics methods. The integration of artificial intelligence and its subset machine learning, has become pivotal in addressing all these challenges. This Roadmap on Data-Centric Materials Science explores fundamental concepts and methodologies, illustrating diverse applications in electronic-structure theory, soft matter theory, microstructure research, and experimental techniques like photoemission, atom probe tomography, and electron microscopy. While the roadmap delves into specific areas within the broad interdisciplinary field of materials science, the provided examples elucidate key concepts applicable to a wider range of topics. The discussed instances offer insights into addressing the multifaceted challenges encountered in contemporary materials research.

引用

页数：90

共 212 条

[1] The rise of self-driving labs in chemical and materials sciences [J].

Abolhasani, Milad ;

Kumacheva, Eugenia .

NATURE SYNTHESIS, 2023, 2 (06) :483-492

[2] Perspective: Materials informatics and big data: Realization of the "fourth paradigm" of science in materials science [J].

Agrawal, Ankit ;

Choudhary, Alok .

APL MATERIALS, 2016, 4 (05)

[3]

Alder B J., 1958, INT S TRANSP PROC ST, V97, P131

[4] PHASE TRANSITION IN ELASTIC DISKS [J].

ALDER, BJ ;

WAINWRIGHT, TE .

PHYSICAL REVIEW, 1962, 127 (02) :359-&

[5] DECAY OF VELOCITY AUTOCORRELATION FUNCTION [J].

ALDER, BJ ;

WAINWRIGHT, TE .

PHYSICAL REVIEW A-GENERAL PHYSICS, 1970, 1 (01) :18-+

[6] A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications [J].

Alzubaidi, Laith ;

Bai, Jinshuai ;

Al-Sabaawi, Aiman ;

Santamaria, Jose ;

Albahri, A. S. ;

Al-dabbagh, Bashar Sami Nayyef ;

Fadhel, Mohammed. A. A. ;

Manoufali, Mohamed ;

Zhang, Jinglan ;

Al-Timemy, Ali. H. H. ;

Duan, Ye ;

Abdullah, Amjed ;

Farhan, Laith ;

Lu, Yi ;

Gupta, Ashish ;

Albu, Felix ;

Abbosh, Amin ;

Gu, Yuantong .

JOURNAL OF BIG DATA, 2023, 10 (01)

[7]

An Yuan, 2022, 2022 IEEE International Conference on Big Data (Big Data), P3651, DOI 10.1109/BigData55660.2022.10020568

[8] OPTIMADE, an API for exchanging materials data [J].

Andersen, Casper W. ;

Armiento, Rickard ;

Blokhin, Evgeny ;

Conduit, Gareth J. ;

Dwaraknath, Shyam ;

Evans, Matthew L. ;

Fekete, Adam ;

Gopakumar, Abhijith ;

Grazulis, Saulius ;

Merkys, Andrius ;

Mohamed, Fawzi ;

Oses, Corey ;

Pizzi, Giovanni ;

Rignanese, Gian-Marco ;

Scheidgen, Markus ;

Talirz, Leopold ;

Toher, Cormac ;

Winston, Donald ;

Aversa, Rossella ;

Choudhary, Kamal ;

Colinet, Pauline ;

Curtarolo, Stefano ;

Di Stefano, Davide ;

Draxl, Claudia ;

Er, Suleyman ;

Esters, Marco ;

Fornari, Marco ;

Giantomassi, Matteo ;

Govoni, Marco ;

Hautier, Geoffroy ;

Hegde, Vinay ;

Horton, Matthew K. ;

Huck, Patrick ;

Huhs, Georg ;

Hummelshoj, Jens ;

Kariryaa, Ankit ;

Kozinsky, Boris ;

Kumbhar, Snehal ;

Liu, Mohan ;

Marzari, Nicola ;

Morris, Andrew J. ;

Mostofi, Arash A. ;

Persson, Kristin A. ;

Petretto, Guido ;

Purcell, Thomas ;

Ricci, Francesco ;

Rose, Frisco ;

Scheffler, Matthias ;

Speckhard, Daniel ;

Uhrin, Martin .

SCIENTIFIC DATA, 2021, 8 (01)

[9] Machine learning for analysis of experimental scattering and spectroscopy data in materials chemistry [J].

Anker, Andy S. ;

Butler, Keith T. ;

Selvan, Raghavendra ;

Jensen, Kirsten M. O. .

CHEMICAL SCIENCE, 2023, 14 (48) :14003-14019

[10]

[Anonymous], The OpenACC Application Programming Interface

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