Work

Accelerated screening of functional atomic impurities in halide perovskites using high-throughput computations and machine learning

Year: 2022

Type: article

Source: Journal of Materials Science

DOI: 10.1007/s10853-022-06998-z

Authors: Arun Mannodi-Kanakkithodi, Maria K. Y. Chan

Institutions: Argonne National Laboratory, Purdue University West Lafayette, Center for Nanoscale Materials

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: green

Funders: U.S. Department of Energy, Purdue University, Kyungpook National University, Office of Science, University of California, San Diego, Argonne National Laboratory

Awards: G102163711, G107546177, G1286236842, G1313983767, G1664757510, G2287611682, G262962599, G2638771445, G3075337988, G3083819904, G419881185, G42916606, G4501827968, G498139845, G6848031779, G6918803902, G8384327199, G969889393, G993149817

OpenAlex ID: W4214936575

FWCI: 1.784

Cites: 81

Cited by: 34

Related to: 10