University of Oulu

Botella, R., Kistanov, A. A., & Cao, W. (2023). Swarm smart meta-estimator for 2d/2d heterostructure design. Journal of Chemical Information and Modeling, 63(20), 6212–6223. https://doi.org/10.1021/acs.jcim.3c01509

Swarm smart meta-estimator for 2D/2D heterostructure design

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Author: Botella, Romain1; Kistanov, Andrey A.1; Cao, Wei1
Organizations: 1Nano and Molecular Systems Research Unit, Faculty of Science, University of Oulu, FIN 90014, Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 5.4 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe20231026141434
Language: English
Published: American Chemical Society, 2023
Publish Date: 2023-10-26
Description:

Abstract

Two-dimensional (2D) semiconductors are central to many scientific fields. The combination of two semiconductors (heterostructure) is a good way to lift many technological deadlocks. Although ab initio calculations are useful to study physical properties of these composites, their application is limited to few heterostructure samples. Herein, we use machine learning to predict key characteristics of 2D materials to select relevant candidates for heterostructure building. First, a label space is created with engineered labels relating to atomic charge and ion spatial distribution. Then, a meta-estimator is designed to predict label values of heterostructure samples having a defined band alignment (descriptor). To this end, independently trained k-nearest neighbors (KNN) regression models are combined to boost the regression. Then, swarm intelligence principles are used, along with the boosted estimator’s results, to further refine the regression. This new “swarm smart” algorithm is a powerful and versatile tool to select, among experimentally existing, computationally studied, and not yet discovered van der Waals heterostructures, the most likely candidate materials to face the scientific challenges ahead.

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Series: Journal of chemical information and modeling
ISSN: 1549-9596
ISSN-E: 1549-960X
ISSN-L: 1549-9596
Volume: 63
Issue: 20
Pages: 6212 - 6223
DOI: 10.1021/acs.jcim.3c01509
OADOI: https://oadoi.org/10.1021/acs.jcim.3c01509
Type of Publication: A1 Journal article – refereed
Field of Science: 114 Physical sciences
Subjects:
Funding: This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 101002219).
EU Grant Number: (101002219) CATCH - Cross-dimensional Activation of Two-Dimensional Semiconductors for Photocatalytic Heterojunctions
Dataset Reference: The data and code used for this study are available at:
  http://dx.doi.org/10.5281/zenodo.8248512
Copyright information: © 2023 The Authors. Published by American Chemical Society. This article is licensed under CC-BY 4.0
  https://creativecommons.org/licenses/by/4.0/