Year: 2025
Type: article
Abstract: The authors summarize the techniques of machine learning in soft materials assembly design, from neural-network potentials to automated image analysis.They contrast traditional soft materials design methods with AI-enhanced techniques like high-throughput crystal structure characterization and inverse design of building blocks for materials assembly and properties.They survey scientific software compatible with molecular dynamics engines such as LAMMPS and HOOMD-blue.
Source: MRS Bulletin
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,490
OpenAlex ID: W7092691531
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