Literature DB >> 33410218

Digital Transformation in Materials Science: A Paradigm Change in Material's Development.

Julian Kimmig1,2, Stefan Zechel1,2, Ulrich S Schubert1,2.   

Abstract

The ongoing digitalization is rapidly changing and will further revolutionize all parts of life. This statement is currently omnipresent in the media as well as in the scientific community; however, the exact consequences of the proceeding digitalization for the field of materials science in general and the way research will be performed in the future are still unclear. There are first promising examples featuring the potential to change discovery and development approaches toward new materials. Nevertheless, a wide range of open questions have to be solved in order to enable the so-called digital-supported material research. The current state-of-the-art, the present and future challenges, as well as the resulting perspectives for materials science are described.
© 2021 The Authors. Advanced Materials published by Wiley-VCH GmbH.

Keywords:  artificial intelligence; automation; combinatorial science; digital transformation; machine learning

Year:  2021        PMID: 33410218     DOI: 10.1002/adma.202004940

Source DB:  PubMed          Journal:  Adv Mater        ISSN: 0935-9648            Impact factor:   30.849


  4 in total

1.  Data-Centric Architecture for Self-Driving Laboratories with Autonomous Discovery of New Nanomaterials.

Authors:  Maria A Butakova; Andrey V Chernov; Oleg O Kartashov; Alexander V Soldatov
Journal:  Nanomaterials (Basel)       Date:  2021-12-21       Impact factor: 5.076

2.  Automation and Standardization-A Coupled Approach towards Reproducible Sample Preparation Protocols for Nanomaterial Analysis.

Authors:  Jörg Radnik; Vasile-Dan Hodoroaba; Harald Jungnickel; Jutta Tentschert; Andreas Luch; Vanessa Sogne; Florian Meier; Loïc Burr; David Schmid; Christoph Schlager; Tae Hyun Yoon; Ruud Peters; Sophie M Briffa; Eugenia Valsami-Jones
Journal:  Molecules       Date:  2022-02-01       Impact factor: 4.411

3.  Machine-Learning Rationalization and Prediction of Solid-State Synthesis Conditions.

Authors:  Haoyan Huo; Christopher J Bartel; Tanjin He; Amalie Trewartha; Alexander Dunn; Bin Ouyang; Anubhav Jain; Gerbrand Ceder
Journal:  Chem Mater       Date:  2022-08-05       Impact factor: 10.508

Review 4.  Self-Driving Laboratories for Development of New Functional Materials and Optimizing Known Reactions.

Authors:  Mikhail A Soldatov; Vera V Butova; Danil Pashkov; Maria A Butakova; Pavel V Medvedev; Andrey V Chernov; Alexander V Soldatov
Journal:  Nanomaterials (Basel)       Date:  2021-03-02       Impact factor: 5.076

  4 in total

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