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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Ab lnitio Simulations and Materials Chemistry in the Age of Big Data

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Schleder, Gabriel Ravanhani [1, 2] ; Padilha, Antonio Claudio M. [2] ; Rocha, Alexandre Reily [3] ; Dalpian, Gustavo Martini [1] ; Fazzio, Adalberto [1, 2]
Total Authors: 5
[1] Fed Univ ABC UFABC, Santo Andre, SP - Brazil
[2] Brazilian Nanotechnol Natl Lab LNNano CNPEM, Campinas, SP - Brazil
[3] Sao Paulo State Univ, Inst Fis Teor, Sao Paulo - Brazil
Total Affiliations: 3
Document type: Journal article
Source: JOURNAL OF CHEMICAL INFORMATION AND MODELING; v. 60, n. 2, p. 452-459, FEB 2020.
Web of Science Citations: 1

In this perspective, we discuss computational advances in the last decades, both in algorithms as well as in technologies, that enabled the development, widespread use, and maturity of simulation methods for molecular and materials systems. Such advances led to the generation of large amounts of data, which required the creation of several computational databases. Within this scenario, with the democratization of data access, the field now encounters several opportunities for data-driven approaches toward chemical and materials problems. Specifically, machine learning methods for predictions of novel materials or properties are being increasingly used with great success. However, black box usage fails in many instances; several technical details require expert knowledge in order for the predictions to be useful, such as with descriptors and algorithm selection. These approaches represent a direction for further developments, notably allowing advances for both developed and emerging countries with modest computational infrastructures. (AU)

FAPESP's process: 17/18139-6 - Machine learning for Materials Science: 2D materials discovery and design
Grantee:Gabriel Ravanhani Schleder
Support type: Scholarships in Brazil - Doctorate
FAPESP's process: 17/02317-2 - Interfaces in materials: electronic, magnetic, structural and transport properties
Grantee:Adalberto Fazzio
Support type: Research Projects - Thematic Grants
FAPESP's process: 18/05565-0 - Weyl semi-metal surfaces
Grantee:Antonio Cláudio Michejevs Padilha
Support type: Scholarships in Brazil - Post-Doctorate