London Dispersion-Corrected Density Functionals Applied to van der Waals Stacked Layered Materials: Validation of Structure, Energy, and Electronic Properties

Birkan Emrem, Roman Kempt, Kati Finzel, Thomas Heine

Research output: Contribution to journalArticlepeer-review

Abstract

Most density functionals lack to correctly account for long-range London dispersion interactions, and numerous a posteriori correction schemes have been proposed in recent years. In van der Waals structures, the interlayer distance controls the proximity effect on the electronic structure, and the interlayer interaction energy indicates the possibility to mechanically exfoliate a layered material. For upcoming twisted van der Waals heterostructures, a reliable but efficient and scalable theoretical scheme to correctly predict the interlayer distance is required. Therefore, the performance of a series of popular London dispersion corrections combined with computationally affordable density functionals is validated. As reference data, the experimental interlayer distance of layered bulk materials is used, and corresponding interlayer interaction energies are calculated using the random phase approximation. We demonstrate that the SCAN-rVV10 and PBE-rVV10L functionals predict interlayer interaction energies and interlayer distances of the studied layered systems within the range of the defined error limits of 10 meV per atom and 0.12 Å, respectively. Semi-empirical and empirical dispersion-corrected functionals show significantly larger error bars, with PBE+dDsC performing best with comparable quality of geometries, but with higher interlayer interaction energy error limits of ≈20 meV per atom.

Original languageEnglish
Article number2200055
JournalAdvanced Theory and Simulations
Volume5
Issue number7
DOIs
Publication statusPublished - 2022 Jul

Bibliographical note

Funding Information:
This work was financially supported by DFG HE 3543/35-1 and the German Ministry of Education and Research (BMBF) under the project ForMikro-NobleNEMS (16ES1121). The authors thank the Center for Information Services and High-Performance Computing (ZIH) at TU Dresden for generous allocations of computer time. The authors gratefully acknowledge the Gauss Centre for Supercomputing e.V. (www.gauss-centre.eu) for funding this project by providing computing time through the John von Neumann Institute for Computing (NIC) on the GCS Supercomputer JUWELS at Jülich Supercomputing Centre (JSC). The authors also thank CRC 1415 for support. Open Access funding enabled and organized by Projekt DEAL.

Funding Information:
This work was financially supported by DFG HE 3543/35‐1 and the German Ministry of Education and Research (BMBF) under the project ForMikro‐NobleNEMS (16ES1121). The authors thank the Center for Information Services and High‐Performance Computing (ZIH) at TU Dresden for generous allocations of computer time. The authors gratefully acknowledge the Gauss Centre for Supercomputing e.V. ( www.gauss‐centre.eu ) for funding this project by providing computing time through the John von Neumann Institute for Computing (NIC) on the GCS Supercomputer JUWELS at Jülich Supercomputing Centre (JSC). The authors also thank CRC 1415 for support.

Publisher Copyright:
© 2022 The Authors. Advanced Theory and Simulations published by Wiley-VCH GmbH.

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Numerical Analysis
  • Modelling and Simulation
  • General

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