Data-driven studies of magnetic two-dimensional materials

Authors: 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:,

DOI10.24435/materialscloud:2019.0020/v1 (version v1, submitted on 20 May 2019)

How to cite this entry

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


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.

Materials Cloud sections using this data

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File name Size Description
MD5MD5: d3caada8e9652220c4416e03281e02de
223.8 KiB csv file of materials descriptors and the target properties: magnetic moment and formation energy.
MD5MD5: 5ba0a7f5336fd58399a48170ae6f7fc4
6.4 KiB Description of materials descriptors


Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.

External references

Journal reference (Preprint where the data is discussed)


machine learning two-dimensional materials magnetic materials

Version history

20 May 2019 [This version]