output
20102026
most citedRecent Advances and Applications of Deep Learning Methods in Materials Science

1.2k citations

Showing 2021Show all

18 papers · 1 filter

cond-mat.mtrl-sci2021★ 87 cited

Graph Neural Network Predictions of Metal Organic Framework CO2 Adsorption Properties

Kamal Choudhary, Taner Yildirim, Daniel Siderius +3

The increasing CO2 level is a critical concern and suitable materials are needed to capture such gases from the environment. While experimental and conventional computational metho…

eess.IV2021★ 1 cited

Advantage of Machine Learning over Maximum Likelihood in Limited-Angle Low-Photon X-Ray Tomography

Zhen Guo, Jung Ki Song, George Barbastathis +5

Limited-angle X-ray tomography reconstruction is an ill-conditioned inverse problem in general. Especially when the projection angles are limited and the measurements are taken in…

cond-mat.mtrl-sci2021★ 21 cited

Fast and Accurate Prediction of Material Properties with Three-Body Tight-Binding Model for the Periodic Table

Kevin F. Garrity, Kamal Choudhary

Parameterized tight-binding models fit to first principles calculations can provide an efficient and accurate quantum mechanical method for predicting properties of molecules and s…

cond-mat.supr-con2021★ 22 cited

Elucidating the local atomic and electronic structure of amorphous oxidized superconducting niobium films

Thomas F. Harrelson, Evan Sheridan, Ellis Kennedy +8

Qubits made from superconducting materials are a mature platform for quantum information science application such as quantum computing. However, materials-based losses are now a li…

cond-mat.mtrl-sci2021★ 10 cited

Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping

A. Gilad Kusne, Austin McDannald, Brian DeCost +5

Application of artificial intelligence (AI), and more specifically machine learning, to the physical sciences has expanded significantly over the past decades. In particular, scien…

cond-mat.mtrl-sci2021

The Initiation of Shear Band Formation in Deformed Metallic Glasses from Soft Localized Domains

Xinyi Wang, Hao Zhang, Jack F. Douglas

It has long been thought that shear band (SB) formation in amorphous solids initiates from relatively 'soft' regions in the material in which large-scale non-affine deformations be…

cond-mat.mtrl-sci2021★ 1.2k cited

Recent Advances and Applications of Deep Learning Methods in Materials Science

Kamal Choudhary, Brian DeCost, Chi Chen +10

Deep learning (DL) is one of the fastest growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data mo…

physics.optics2021★ 14 cited

Hybrid-mode-family Kerr optical parametric oscillation for robust coherent light generation on chip

Feng Zhou, Xiyuan Lu, Ashutosh Rao +5

Optical parametric oscillation (OPO) using the third-order nonlinearity () in integrated photonics platforms is an emerging approach for coherent light generation, and has…

physics.optics2021★ 32 cited

Exceptional points in lossy media enable decay-free wave propagation

Alexander Yulaev, Sangsik Kim, Qing Li +4

Waves entering a spatially uniform lossy medium typically undergo exponential decay, arising from either the energy loss of the Beer-Lambert-Bouguer transmission law or the evanesc…

quant-ph2021★ 15 cited

Definitive Detection of Orbital Angular Momentum States in Neutrons by Spin-polarized He

Terrence Jach, John Vinson

A standard method to detect thermal neutrons is the nuclear interaction He(n,p)H. The spin-dependence of this interaction is also the basis of a neutron spin-polarization f…

cond-mat.str-el2021★ 5 cited

Magnetic and structural properties of the intermetallic Ce(1-x)LaxCrGe3 series of compounds

B. Bosch-Santos, G. A. Cabrera-Pasca, E. L. Correa +8

The Ce(1-x)LaxCrGe3 (x = 0, 0.19, 0.43, 0.58 and 1) intermetallic compound system has been investigated by magnetization measurements and neutron scattering techniques to determine…

cond-mat.mtrl-sci2021★ 56 cited

On-the-fly Autonomous Control of Neutron Diffraction via Physics-Informed Bayesian Active Learning

Austin McDannald, Matthias Frontzek, Andrei T. Savici +8

Neutron scattering is a unique and versatile characterization technique for probing the magnetic structure and dynamics of materials. However, instruments at neutron scattering fac…

physics.optics2021★ 41 cited

Dual-comb cavity ring-down spectroscopy

D. Lisak, D. Charczun, A. Nishiyama +10

Cavity ring-down spectroscopy is a ubiquitous optical method used to study light-matter interactions with high resolution, sensitivity and accuracy. However, it has never been perf…

cond-mat.mtrl-sci2021★ 775 cited

Atomistic Line Graph Neural Network for Improved Materials Property Predictions

Kamal Choudhary, Brian DeCost

Graph neural networks (GNN) have been shown to provide substantial performance improvements for atomistic material representation and modeling compared with descriptor-based machin…

cond-mat.mtrl-sci2021★ 61 cited

Giant spin Hall angle in the Heusler alloy Weyl ferromagnet CoMnGa

L. Leiva, S. Granville, Y. Zhang +6

Weyl semimetals are playing a major role in condensed matter physics due to exotic topological properties, and their coexistence with ferromagnetism may lead to enhanced spin-relat…

cond-mat.mtrl-sci2021★ 107 cited

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…

physics.app-ph2021★ 10 cited

Demonstration of a laser powder bed fusion combinatorial sample for high-throughput microstructure and indentation characterization

Jordan S. Weaver, Adam L. Pintar, Carlos Beauchamp +3

High-throughput experiments that use combinatorial samples with rapid measurements can be used to provide process-structure-property information at reduced time, cost, and effort.…

cond-mat.mtrl-sci2021★ 59 cited

Fast Dynamics in a Model Metallic Glass-forming Material

Hao Zhang, Xinyi Wang, Hai-Bin Yu +1

We investigate the fast - and Johari-Goldstein (JG) -relaxation processes, along with the elastic scattering response of glass-forming (GF) liquids and the Boson peak, in a s…