Search

Understanding the role of symmetry in the physical sciences is critical for choosing an appropriate machine-learning method. While invariant models are the most prevalent symmetry-aware models, equivariant models such as Euclidean neural networks more faithfully represent physical interactions and are ready to take on challenges across the physical sciences.

Ferroelectric materials have technological applications in information storage and electronic devices. The ferroelectric polar phase can be controlled with external fields, chemical substitution and size-effects in bulk and ultrathin film form, providing a platform for future technologies and for exploratory research. In this work, we integrate spin-polarized density functional theory (DFT) calculations, crystal structure databases, symmetry tools, workflow software, and a custom analysis toolkit to build a library of known, previously-proposed, and newly-proposed ferroelectric materials. With our automated workflow, we screen over 67,000 candidate materials from the Materials Project database to generate a dataset of 255 ferroelectric candidates, and propose 126 new ferroelectric materials. We benchmark our results against experimental data and previous first-principles results. The data provided includes atomic structures, output files, and DFT values of band gaps, energies, and the spontaneous polarization for each ferroelectric candidate. We contribute our workflow and analysis code to the open-source python packages atomate and pymatgen so others can conduct analogous symmetry driven searches for ferroelectrics and related phenomena.

This work presents Neural Equivariant Interatomic Potentials (NequIP), an E(3)-equivariant neural network approach for learning interatomic potentials from ab-initio calculations for molecular dynamics simulations. While most contemporary symmetry-aware models use invariant convolutions and only act on scalars, NequIP employs E(3)-equivariant convolutions for interactions of geometric tensors, resulting in a more information-rich and faithful representation of atomic environments. The method achieves state-of-the-art accuracy on a challenging and diverse set of molecules and materials while exhibiting remarkable data efficiency. NequIP outperforms existing models with up to three orders of magnitude fewer training data, challenging the widely held belief that deep neural networks require massive training sets. The high data efficiency of the method allows for the construction of accurate potentials using high-order quantum chemical level of theory as reference and enables high-fidelity molecular dynamics simulations over long time scales., (© 2022. The Author(s).)

Two-dimensional (2D) excitons arise from electron-hole confinement along one spatial dimension. Such excitations are often described in terms of Frenkel or Wannier limits according to the degree of exciton spatial localization and the surrounding dielectric environment. In hybrid material systems, such as the 2D perovskites, the complex underlying interactions lead to excitons of an intermediate nature, whose description lies somewhere between the two limits, and a better physical description is needed. Here, we explore the photophysics of a tuneable materials platform where covalently bonded metal-chalcogenide layers are spaced by organic ligands that provide confinement barriers for charge carriers in the inorganic layer. We consider self-assembled, layered bulk silver benzeneselenolate, [AgSePh] ∞ , and use a combination of transient absorption spectroscopy and ab initio GW plus Bethe-Salpeter equation calculations. We demonstrate that in this non-polar dielectric environment, strongly anisotropic excitons dominate the optical transitions of [AgSePh] ∞ . We find that the transient absorption measurements at room temperature can be understood in terms of low-lying excitons confined to the AgSe planes with in-plane anisotropy, featuring anisotropic absorption and emission. Finally, we present a pathway to control the exciton behaviour by changing the chalcogen in the material lattice. Our studies unveil unexpected excitonic anisotropies in an unexplored class of tuneable, yet air-stable, hybrid quantum wells, offering design principles for the engineering of an ordered, yet complex dielectric environment and its effect on the excitonic phenomena in such emerging materials.

Spin and orbital quantum numbers play a key role in the physics of Mott insulators, but in most systems they are connected only indirectly--via the Pauli exclusion principle and the Coulomb interaction. Iridium-based oxides (iridates) introduce strong spin-orbit coupling directly, such that these numbers become entwined together and the Mott physics attains a strong orbital character. In the layered honeycomb iridates this is thought to generate highly spin-anisotropic magnetic interactions, coupling the spin to a given spatial direction of exchange and leading to strongly frustrated magnetism. Here we report a new iridate structure that has the same local connectivity as the layered honeycomb and exhibits striking evidence for highly spin-anisotropic exchange. The basic structural units of this material suggest that a new family of three-dimensional structures could exist, the 'harmonic honeycomb' iridates, of which the present compound is the first example.