Work

Computational analysis and design of high-entropy nanoparticles: Integrating atomistic simulations with scientific pedagogy in materials research

Year: 2025

Type: article

Abstract: This study leverages reactive molecular dynamics simulations to enhance undergraduate education and research in materials science. Focusing on the oxidation processes of a variety of energetic metal nanoparticles, including Al, Cu, Mg, and Ti, two undergraduate students led the scientific inquiry. They conducted literature reviews, ran simulations, validated assumptions, and analyzed results, deepening their understanding of material behaviors and strengthening their STEM identity. Through these hands-on experiences, the students successfully investigated the energetic properties of these nanoparticles, demonstrating the effectiveness of this approach in promoting inquiry-based learning. This work underscores the transformative potential of computational simulations in advancing computational materials research, fostering diversity, and preparing undergraduates for future contributions to computational modeling-driven science. Graphical abstract

Source: MRS Advances

DOI: 10.1557/s43580-025-01261-4

Authors: Priyanshu Luhar, Ricardo Ramirez, Jiwon Lexi Hwang, Sungwook Leo Hong

Institutions: California State University, Bakersfield, California State University Los Angeles, Loyola Marymount University

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: hybrid

Estimated APC paid: $3,390