Gabriel M. Nascimento^1*, Elton Ogoshi^1*, Adalberto Fazzio^2*, Carlos Mera Acosta^1*, Gustavo M. Dalpian^1*

1 Center for Natural and Human Sciences, Federal University of ABC, Santo Andre, SP, Brazil

2 Brazilian Nanotechnology National Laboratory (LNNano), CNPEM, 13083‐970, Campinas, São Paulo, Brazil

* Corresponding authors emails: demiranda.gabrielnascimento@gmail.com, elton.ogoshi@gmail.com, adalberto.fazzio@gmail.com, cmeraacosta@gmail.com, dalpian@gmail.com

DOI10.24435/materialscloud:kr-7s [version v1]

Publication date: Dec 17, 2021

How to cite this record

Gabriel M. Nascimento, Elton Ogoshi, Adalberto Fazzio, Carlos Mera Acosta, Gustavo M. Dalpian, High throughput inverse design and Bayesian optimization of functionalities: spin splitting in two-dimensional compounds, Materials Cloud Archive 2021.224 (2021), doi: 10.24435/materialscloud:kr-7s.

Description

The development of spintronic devices demands the existence of materials with some kind of spin splitting (SS). In this work, we have built a database of ab initio calculated SS in 2D materials. More than that, we propose a workflow for materials design integrating an inverse design approach and a Bayesian inference optimization. We use the prediction of SS prototypes for spintronic applications as an illustrative example of the proposed workflow. The prediction process starts with the establishment of the design principles (the physical mechanism behind the target properties), that are used as filters for materials screening, and followed by density functional theory (DFT) calculations. Applying this process to the C2DB database, we identify and classify 315 2D materials according to SS type at the valence and/or conduction bands. The Bayesian optimization captures trends that are used for the rationalized design of 2D materials with the ideal conditions of band gap and SS for potential spintronics applications. This repository then contains the main source of data generated in this work, which encompasses full information regarding the materials structure and band structure calculations results, and a database of all the identified spin splittings for these compounds, available in multiple formats.

Materials Cloud sections using this data

Files

File name	Size	Description
databases.tar.gz MD5md5:a75abd76260f8571dbdc63a390c88ef6	46.4 MiB	Database with the extensive results of this work (material-specific data, band structure description, and spin-splitting description data).
materials.tar.gz MD5md5:e9482dbf68946e24b3a960096cb30fc2	1.1 GiB	Materials data, including structure information, band structure calculations results and images.
ss_tables.tar.gz MD5md5:9d97f9aeb6785bd23f11b43c4f13f956	18.2 KiB	Datasets (.csv files) containing general information about the identified spin splittings.
README.md MD5md5:d459cd22f00a3437fc1e957590117394	14.1 KiB	Detailed description of the data and instructions to access them.

License

Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.

External references

Keywords

2D materials high-throughput spintronics spin splitting Bayesian optimization