Work

Materials Fingerprinting Classification

Year: 2021

Type: article

Source: Computer Physics Communications

DOI: 10.1016/j.cpc.2021.108019

Authors: Adam Spannaus, Kody J.H. Law, Piotr Luszczek, Farzana Nasrin, Cassie Putman Micucci, Peter K. Liaw, Louis J. Santodonato, David J. Keffer, Vasileios Maroulas

Institutions: Oak Ridge National Laboratory, University of Manchester, University of Tennessee at Knoxville, University of Hawaiʻi at Mānoa, Eastman Chemical Company (United States), Advanced Research Systems

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: bronze

Funders: National Science Foundation, U.S. Department of Energy, Battelle, University of Tennessee, University of Tennessee, Knoxville, UT-Battelle, Directorate for Engineering, Office of Science, Army Research Office, Oak Ridge National Laboratory

Awards: G1026679911, G121915436, G1645119126, G166562317, G203625172, G2411683797, G2988778103, G313676650, G3846575513, G4423657506, G5589556504, G5726405315, G675320460, G7452299184, G8269158468, Online Spatiotemporal Filtering and Bayesian Topology for Tracking in Dynamically Designed Sensor Networks, G8906985441, G8943143067

OpenAlex ID: W3158460769

FWCI: 0.57

Cites: 51

Cited by: 14

Related to: 10