Bulletin of the American Physical Society
APS March Meeting 2020
Volume 65, Number 1
Monday–Friday, March 2–6, 2020; Denver, Colorado
Session U43: Computational design and discovery of novel materials V: Electronic structure
2:30 PM–5:30 PM,
Thursday, March 5, 2020
Room: 702
Sponsoring
Units:
DCOMP DMP
Chair: Vincent Crespi, Pennsylvania State University
Abstract: U43.00009 : Predicting 2D Materials with Machine Learning*
Presenter:
Gabriel Schleder
(Universidade Federal do ABC)
Authors:
Gabriel Schleder
(Universidade Federal do ABC)
Carlos Mera
(Universidade Federal do ABC)
Adalberto Fazzio
(Brazilian Nanotechnology National Laboratory)
According to the formation energy and energy above the convex-hull, we classify materials as having low, medium, or high stability. The proposed approach enables the stability evaluation of novel 2D compounds for further investigation of promising candidates, using only composition properties and structural symmetry, without the need for information about atomic positions.
We demonstrate the usefulness of the model generating more than a thousand novel compounds, corroborating with DFT calculations the classification for five of these materials. To illustrate the applicability we perform a screening of materials suitable for photoelectrocatalytic water splitting, identifying the potential candidate Sn2SeTe generated by our model and PbTe, both not yet reported for this application.
*The authors acknowledge support from FAPESP (17/18139-6, 18/11856-7, 17/02317-2).
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