Roadmap on Data-Centric Materials Science
Sebastian Bauer
1, 2, 3
,
Peter Benner
4, 5
,
Tristan Bereau
6, 7
,
V. Blum
8, 9
,
Mario Boley
10, 11
,
Christian Carbogno
12, 13
,
C. Richard Catlow
14, 15, 16, 17
,
G. Dehm
18, 19
,
Sebastian Eibl
20, 21
,
R. Ernstorfer
22, 23
,
Ádám Fekete
24, 25
,
Lucas Foppa
12, 26
,
Paulo Rui Fernandes
27
,
Peter Fratzl
28
,
C. Freysoldt
18, 29
,
Baptiste Gault
18, 30, 31
,
Luca M. Ghiringhelli
12, 32, 33
,
Sajal Kumar Giri
34, 35
,
Anton Gladyshev
24, 36
,
Pawan Goyal
4, 37
,
Jason Hattrick-Simpers
38, 39
,
Lara Kabalan
14, 17, 40
,
P.I. Karpov
21, 41
,
Mohammad S. Khorrami
18, 29
,
Christoph Koch
24, 42
,
Sebastian Kokott
12, 43, 44
,
Thomas Kosch
24, 45
,
Igor Kowalec
14, 17, 46
,
Kurt Kremer
47, 48
,
Andreas Leitherer
12, 44, 49
,
Yue Li
18, 29
,
Christian H. Liebscher
18, 29
,
Andrew Logsdail
14, 50, 51
,
Zhongwei Lu
14, 17, 50
,
Phuc Luong
10, 52
,
Andreas Marek
21, 41
,
Florian Merz
53
,
Jaber Rezaei Mianroodi
18, 54
,
Jörg Neugebauer
18, 55
,
Zongrui Pei
56, 57
,
Thomas A. R. Purcell
12, 58, 59
,
Dierk Raabe
18, 60
,
Markus Rampp
41, 61
,
MARIANA FONSECA ROSSI
62, 63
,
Jan M. Rost
64, 65
,
James Saal
66, 67
,
Ulf Saalmann
64, 68
,
Kasturi Narasimha Sasidhar
69
,
K N Sasidhar
18
,
Alaukik Saxena
18, 29
,
Luigi Sbailò
24, 25
,
Markus Scheidgen
24, 70
,
Marcel Schloz
24, 71
,
Daniel Francis Schmidt
10, 72
,
Simon Teshuva
10, 73
,
A Trunschke
12, 74
,
Ye Wei
75, 76
,
Gerhard Weikum
77, 78
,
R. Patrick Xian
38, 79
,
Yi Yao
12
,
Yiyu Yao
80
,
Junqi Yin
81, 82
,
Meng Zhao
24, 83
,
Matthias Scheffler
12, 81, 84
1
Helmholtz AI (Germany)
|
11
22
Technical Univ. of Berlin (Germany)
|
36
Department of Physics, Universität zu Berlin, Department of Physics, Berlin, 17716, GERMANY
|
42
Department of Physics, Universität zu Berlin, Department of Physics, Humboldt, 11776, GERMANY
|
43
Molecular Simulations from First Principles e.V., Berlin (Germany)
|
45
Department of Computer Science, Universität zu Berlin, Department of Computer Science, Berlin, 14154, GERMANY
|
46
Max Planck Centre on the Fundamentals of Heterogeneous Catalysis (FUNCAT) (Germany)
|
48
Polymer Theory Group, Max-Planck-Institut fuer Polymerforschung, Ackermannweg 10, Mainz, 55128, GERMANY
|
50
Max Planck Centre on the Fundamentals of Heterogeneous Catalysis (FUNCAT)
52
Department of Data Science, AI, Department of Data Science, London, WC1X 0DW, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
53
Lenovo HPC Innovation Center, Stuttgart (Germany)
|
55
Max-Planck-Institut fuer Eisenforschung GmbH, Postfach 140 444, D-40074 Duesseldorf, Dusseldorf, 67523, GERMANY
|
60
Department of Microstructure Physics and Metal Forming, Max-Planck-Institut fuer Eisenforschung GmbH, Max-Planck-Str. 1, D-40237 Duesseldorf, DÜSSELDORF, 40237, GERMANY
|
65
Max-Planck-Institut fuer Physik komplexer Systeme, Noethnitzer Str.38, D-01187 Dresden, Dresden, 40182, GERMANY
|
66
Citrine Informatics, Inc., Redwood City, CA (United States)
|
67
Citrine Informatics Inc, Citrine Informatics, Inc, Redwood City, California, 94063-2483, UNITED STATES
|
68
Max-Planck-Institut fuer Physik komplexer Systeme, Nöthnitzer Str. 38, Dresden, 01187, GERMANY
|
70
Universität zu Berlin, Universität zu Berlin, Humboldt, 16004, GERMANY
|
71
Department of Physics, Universität zu Berlin, Department of Physics, Berlin, 39821, GERMANY
|
73
Department of Data Science, Monash University, Department of Data Science, Clayton, Victoria, 3800, AUSTRALIA
|
83
Department of Physics, Universität zu Berlin, Department of Physics, Berlin, 98241, GERMANY
|
Publication type: Journal Article
Publication date: 2024-07-03
scimago Q2
wos Q3
SJR: 0.519
CiteScore: 3.3
Impact factor: 2.4
ISSN: 09650393, 1361651X
Abstract
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 (AI) and its subset Machine Learning (ML), 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, 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.
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17
Total citations:
17
Citations from 2024:
16
(94.12%)
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Bauer S. et al. Roadmap on Data-Centric Materials Science // Modelling and Simulation in Materials Science and Engineering. 2024. Vol. 32. No. 6. p. 63301.
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Bauer S. et al. Roadmap on Data-Centric Materials Science // Modelling and Simulation in Materials Science and Engineering. 2024. Vol. 32. No. 6. p. 63301.
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@article{2024_Bauer,
author = {Sebastian Bauer and Peter Benner and Tristan Bereau and V. Blum and Mario Boley and Christian Carbogno and C. Richard Catlow and G. Dehm and Sebastian Eibl and R. Ernstorfer and Ádám Fekete and Lucas Foppa and Paulo Rui Fernandes and Peter Fratzl and C. Freysoldt and Baptiste Gault and Luca M. Ghiringhelli and Sajal Kumar Giri and Anton Gladyshev and Pawan Goyal and Jason Hattrick-Simpers and Lara Kabalan and P.I. Karpov and Mohammad S. Khorrami and Christoph Koch and Sebastian Kokott and Thomas Kosch and Igor Kowalec and Kurt Kremer and Andreas Leitherer and Yue Li and Christian H. Liebscher and Andrew Logsdail and Zhongwei Lu and Phuc Luong and Andreas Marek and Florian Merz and Jaber Rezaei Mianroodi and Jörg Neugebauer and Zongrui Pei and Thomas A. R. Purcell and Dierk Raabe and Markus Rampp and MARIANA FONSECA ROSSI and Jan M. Rost and James Saal and Ulf Saalmann and Kasturi Narasimha Sasidhar and K N Sasidhar and Alaukik Saxena and others},
title = {Roadmap on Data-Centric Materials Science},
journal = {Modelling and Simulation in Materials Science and Engineering},
year = {2024},
volume = {32},
publisher = {IOP Publishing},
month = {jul},
url = {https://iopscience.iop.org/article/10.1088/1361-651X/ad4d0d},
number = {6},
pages = {63301},
doi = {10.1088/1361-651x/ad4d0d}
}
Cite this
MLA
Copy
Bauer, Stefan, et al. “Roadmap on Data-Centric Materials Science.” Modelling and Simulation in Materials Science and Engineering, vol. 32, no. 6, Jul. 2024, p. 63301. https://iopscience.iop.org/article/10.1088/1361-651X/ad4d0d.