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Data-driven studies of magnetic two-dimensional materials

Trevor David Rhone1*, Wei Chen1, Shaan Desai1, Amir Yacoby1, Efthimios Kaxiras1*

1 Department of Physics, Harvard University, 17 Oxford street, Cambridge MA 02138

* Corresponding authors emails: trr715@g.harvard.edu, kaxiras@g.harvard.edu
DOI10.24435/materialscloud:2019.0020/v1 [version v1]

Publication date: May 20, 2019

How to cite this record

Trevor David Rhone, Wei Chen, Shaan Desai, Amir Yacoby, Efthimios Kaxiras, Data-driven studies of magnetic two-dimensional materials, Materials Cloud Archive 2019.0020/v1 (2019), https://doi.org/10.24435/materialscloud:2019.0020/v1

Description

We use a data-driven approach to study the magnetic and thermodynamic properties of van der Waals (vdW) layered materials. We investigate monolayers of the form A2B2X6, based on the known material Cr2Ge2Te6, using density functional theory (DFT) calculations and determine their magnetic properties, such as magnetic order and magnetic moment. We also examine formation energies and use them as a proxy for chemical stability.

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Files

File name Size Description
magneticmoment_Ef_data.csv
MD5md5:d3caada8e9652220c4416e03281e02de
223.8 KiB csv file of materials descriptors and the target properties: magnetic moment and formation energy.
README.rtf
MD5md5:5ba0a7f5336fd58399a48170ae6f7fc4
6.4 KiB Description of materials descriptors

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.

Keywords

machine learning two-dimensional materials magnetic materials

Version history:

2019.0020/v1 (version v1) [This version] May 20, 2019 DOI10.24435/materialscloud:2019.0020/v1