Neural-network-based depth-resolved multiscale structural optimization using density functional theory and electron diffraction data

Robert S. Pennington, Catalina Coll, Sònia Estradé, Francesca Peiró, and Christoph T. Koch
Phys. Rev. B 97, 024112 – Published 24 January 2018

Abstract

Iterative neural-network-based three-dimensional structural optimization of atomic positions over tens of nanometers is performed using transmission electron microscope (TEM) diffraction data simulated from density functional theory (DFT) all-electron densities, thus retrieving parameter variations along the beam direction. We first use experimental data to show that the GPAW DFT code's all-electron densities are considerably more accurate for electron diffraction calculations compared to conventional isolated-atom scattering factors, and they also compare well to Wien2K DFT simulations. This DFT-TEM combination is then integrated into an iterative neural-network-optimization-based algorithm (PRIMES, parameter retrieval and inversion from multiple electron scattering) to retrieve nanometer-scale ferroelectric polarization domains and strain in theoretical bulklike specimens from TEM data. DFT and isolated-atom methods produce substantially different diffraction patterns and retrieved polarization domain parameters, and DFT is sufficient to retrieve strain properties from a silicon specimen simulated using experimentally derived structure factors. Thus, we show that the improved accuracy, fast computation, and intuitive integration make the GPAW DFT code well suited for three-dimensional materials characterization and demonstrate this using an iterative neural-network algorithm that is verifiable on the mesoscale and, with DFT integration, self-consistent on the nanoscale.

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  • Received 2 December 2016

DOI:https://doi.org/10.1103/PhysRevB.97.024112

©2018 American Physical Society

Physics Subject Headings (PhySH)

Condensed Matter, Materials & Applied Physics

Authors & Affiliations

Robert S. Pennington1,*, Catalina Coll2,3, Sònia Estradé2,3, Francesca Peiró2,3, and Christoph T. Koch1

  • 1AG Structure Research and Electron Microscopy, Institut für Physik, Humboldt-Universität zu Berlin, 12489 Berlin, Germany
  • 2Laboratory of Electron Nanoscopies (LENS-MIND), Departament d'Enginyeries: Electrònica, Universitat de Barcelona, Barcelona, Spain
  • 3Institute of Nanoscience and Nanotechnology (IN2UB), Universitat de Barcelona, Spain

  • *Corresponding author: robert.pennington@physik.hu-berlin.de

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Issue

Vol. 97, Iss. 2 — 1 January 2018

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