Work

Machine learning-assisted analysis of ignition and combustion properties in as-milled and annealed Al-Zr composite powders

Year: 2025

Type: article

Source: Combustion and Flame

DOI: 10.1016/j.combustflame.2025.114660

Authors: Michael R. Flickinger, Sreenivas Raguraman, Amee L. Polk, Colin Goodman, Megan Bokhoor, Rami Knio, Michael Kruppa, Mark A. Foster, Timothy P. Weihs

Institutions: Johns Hopkins University, Hopkins Extreme Materials Institute, United States Army, U.S. Army Combat Capabilities Development Command Chemical Biological Center

Language: English

Topic: Energetic Materials and Combustion

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, U.S. Department of Defense, Defense Threat Reduction Agency, U.S. Army, Division of Materials Research, U.S. Army Combat Capabilities Development Command Chemical Biological Center

Awards: G746383624, Excess Vacancy Enabled Transformations in Light Metal Alloys

OpenAlex ID: W4416772759

FWCI: 1.077

Cites: 63

Cited by: 6

Related to: 10