Physikalische Chemie - Direktor: Prof. Dr. Martin Wolf
Online Seminar
Chair: Ralph Ernstorfer

Wednesday, August 12, 2020, 3:30 pm
Patrick Xian
Northwestern University, USA
Towards materials data science – where high-throughput computation will meet high-throughput experimentation
Constructing a materials discovery platform requires concerted efforts between multiple domains, including theory, experiments and the computational methods for synergetic exchanges in between [1]. Firstly, these exchanges require domain-informed, compact data representations and metrics to facilitate the high-throughput methodology and unite disparate fields associated with materials science. I discuss corresponding examples from electronic structure [2] and crystal structure [3] data. Secondly, existing materials characterization methods are not designed to scale up to macroscopic samples and batches, and the correspondence between multimodal measurements are often not exact [4], I discuss these existing limitations and propose solutions by co-designing experimental and computational workflows [5].
[1] M. Aykol et al. Matter 1, 1 (2019).
[2] R. P. Xian, V. Stimper et al. arXiv:2005.10210.
[3] C. J. Bartel et al. J. Am. Chem. Soc. 142, 5135 (2020).
[4] T. L. Burnett and P. J. Withers, Nat. Mater. 18, 1041 (2019).
[5] M. Du et al. under review.

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