2.2k citations · 5.9k across the 62 of their papers we have counts for
50 papers · 1 filter
When do machine-learning potentials need a configuration-dependent kernel? Learning long-range interactions with Fourier neural operators
Wei Chen, Gian-Marco Rignanese
Long-range interactions in machine-learning interatomic potentials are commonly treated by coupling learned sources through either a prescribed electrostatic kernel or a learned bu…
Magnetic-configuration design for reliable Heisenberg exchange parameters
Ben Li, Stephan von Malottki, Gian-Marco Rignanese
The determination of magnetic exchange interactions is essential for the quantitative description and predictive modeling of magnetic materials. In this work, we present a neighbor…
First-Principles Spin-Lattice Coupling from Downfolded Electron-Phonon Interaction
Xu He, Álvaro Adrián Carrasco Álvarez, Gian-Marco Rignanese +3
We present a method to calculate spin-phonon coupling parameters from first-principles perturbation theory by downfolding the electron-phonon coupling (EPC). We exploit the localiz…
Optical decoherence in Er-doped CeO spin qubit platforms
Vrindaa Somjit, Ignas Masiulionis, Gregory D. Grant +7
Erbium ions (Er) in cerium dioxide (CeO) represent a promising spin-photon interface for quantum communication, but the mechanisms limiting their optical coherence remai…
Short-range order in the CoCrFeMnNi high-entropy alloy from cluster expansion
Wei Chen, Gian-Marco Rignanese, Geoffroy Hautier
We investigate the short-range order (SRO) and phase stability of the equiatomic CoCrFeMnNi high-entropy alloy using cluster expansion supplemented by an eigen-decomposition analys…
Towards MatCore: A Unified Metadata Standard for Materials Science
Jane Greenberg, Pamela Boveda-Aguirre, John Allison +18
The materials science community seeks to support the FAIR principles for computational simulation research. The MatCore Project was recently launched to address this need, with the…
Assessing carrier mobility, dopability, and defect tolerance in the chalcogenide perovskite BaZrS
Zhenkun Yuan, Diana Dahliah, Romain Claes +4
The chalcogenide perovskite BaZrS has attracted much attention as a promising solar absorber for thin-film photovoltaics. Here, we use first-principles calculations to evaluate…
Systematic assessment of various universal machine-learning interatomic potentials
Haochen Yu, Matteo Giantomassi, Giuliana Materzanini +2
Machine-learning interatomic potentials have revolutionized materials modeling at the atomic scale. Thanks to these, it is now indeed possible to perform simulations of \abinitio q…
Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
Matthew L. Evans, Johan Bergsma, Andrius Merkys +56
The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enh…
Native point defects in HgCdTe infrared detector material: Identifying deep centers from first principles
Wei Chen, Gian-Marco Rignanese, Jifeng Liu +1
We investigate the native point defects in the long-wavelength infrared (LWIR) detector material HgCdTe using a dielectric-dependent hybrid density functional com…
Discovery of the Zintl-phosphide BaCdP as a long carrier lifetime and stable solar absorber
Zhenkun Yuan, Diana Dahliah, Muhammad Rubaiat Hasan +17
Thin-film photovoltaics offers a path to significantly decarbonize our energy production. Unfortunately, current materials commercialized or under development as thin-film solar ce…
A substitutional quantum defect in WS discovered by high-throughput computational screening and fabricated by site-selective STM manipulation
John C. Thomas, Wei Chen, Yihuang Xiong +21
Point defects in two-dimensional materials are of key interest for quantum information science. However, the space of possible defects is immense, making the identification of high…
How to verify the precision of density-functional-theory implementations via reproducible and universal workflows
Emanuele Bosoni, Louis Beal, Marnik Bercx +42
In the past decades many density-functional theory methods and codes adopting periodic boundary conditions have been developed and are now extensively used in condensed matter phys…
Nonunique fraction of Fock exchange for defects in two-dimensional materials
Wei Chen, Sinéad M. Griffin, Gian-Marco Rignanese +1
By investigating the vacancy and substitutional defects in monolayer WS with hybrid functionals, we find that there is no unique amount of Fock exchange that concurrently satis…
Shared Metadata for Data-Centric Materials Science
Luca M. Ghiringhelli, Carsten Baldauf, Tristan Bereau +32
The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps r…
A simple denoising approach to exploit multi-fidelity data for machine learning materials properties
Xiaotong Liu, Pierre-Paul De Breuck, Linghui Wang +1
Machine-learning models have recently encountered enormous success for predicting the properties of materials. These are often trained based on data that present various levels of…
Assessing the quality of relaxation-time approximations with fully-automated computations of phonon-limited mobilities
Romain Claes, Guillaume Brunin, Matteo Giantomassi +2
The mobility of carriers, as limited by their scattering with phonons, can now routinely be obtained from first-principles electron-phonon coupling calculations. However, so far, m…
Giant thermoelectric figure of merit in multivalley high-complexity-factor LaSO
Roberta Farris, Francesco Ricci, Giulio Casu +4
We report a giant thermoelectric figure of merit (up to 6 at 1100 K) in -doped lanthanum oxysulphate LaSO. Thermoelectric coefficients are computed from ab initio bands wit…
Common workflows for computing material properties using different quantum engines
Sebastiaan P. Huber, Emanuele Bosoni, Marnik Bercx +23
The prediction of material properties through electronic-structure simulations based on density-functional theory has become routinely common, thanks, in part, to the steady increa…
OPTIMADE, an API for exchanging materials data
Casper W. Andersen, Rickard Armiento, Evgeny Blokhin +53
The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible an…
Robust model benchmarking and bias-imbalance in data-driven materials science: a case study on MODNet
Pierre-Paul De Breuck, Matthew L. Evans, Gian-Marco Rignanese
As the number of novel data-driven approaches to material science continues to grow, it is crucial to perform consistent quality, reliability and applicability assessments of model…
CZTS Raman spectra beyond kesterite: a first-principles study
S. P. Ramkumar, H. P. C. Miranda, X. Gonze +1
CuZnSnS is an earth-abundant photovoltaic absorber material predicted to provide a sustainable solution for commercial solar applications. One of the main limitations restr…
Ferroelectricity and multiferroicity in anti-Ruddlesden-Popper structures
Maxime Markov, Louis Alaerts, Henrique P. C. Miranda +7
Combining ferroelectricity with other properties such as visible light absorption or long-range magnetic order requires the discovery of new families of ferroelectric materials. He…
Boron phosphide as a \emph{p}-type transparent conductor: optical absorption and transport through electron-phonon coupling
Viet-Anh Ha, Bora Karasulu, Ryo Maezono +5
Boron phosphide has recently been identified as a potential high hole mobility transparent conducting material. This promise arises from its low hole effective masses. However, BP…