Two-dimensional ferroelectrics from high throughput computational screening
Mads Kruse, Urko Petralanda, Morten N. Gjerding, Karsten W. Jacobsen,, Kristian S. Thygesen, Thomas Olsen

TL;DR
This study uses high throughput computational screening to identify new two-dimensional ferroelectric materials, including known and novel compounds, with potential for experimental realization and interesting magnetic properties.
Contribution
The paper introduces a systematic computational approach to discover 2D ferroelectrics from existing databases, identifying 64 candidates with various polarization characteristics.
Findings
Identified 64 2D ferroelectric materials from 252 pyroelectric candidates.
Most predicted ferroelectrics are known bulk van der Waals compounds, suggesting experimental feasibility.
Discovered a magnetic pyroelectric material with switchable polarization coupled to magnetic excitations.
Abstract
We report a high throughput computational search for two-dimensional ferroelectric materials. The starting point is 252 pyroelectric materials from the computational 2D materials database (C2DB) and from these we identify 64 ferroelectric materials by explicitly constructing adiabatic paths connecting states of reversed polarization. In particular we find 49 materials with in-plane polarization, 8 materials with out-of-plane polarization and 6 materials with coupled in-plane and out-of-plane polarization. Most of the known 2D ferroelectrics are recovered by the screening and the far majority of the new predicted ferroelectrics are known as bulk van der Waals bonded compounds, which implies that these could be experimentally accessible by direct exfoliation. For roughly 25{\%} of the materials we find a metastable state in the non-polar structure, which could have important consequences…
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Taxonomy
TopicsMachine Learning in Materials Science · 2D Materials and Applications
