Data integrity in materials science in the era of AI: balancing accelerated discovery with responsible science and innovation
Year: 2025
Type: article
Abstract: Artificial intelligence promises to revolutionise materials discovery through accelerated prediction and optimisation, yet this transformation brings critical data integrity challenges that threaten the scientific record.
Source: Journal of Materials Chemistry A
DOI: 10.1039/d5ta05512a
Authors: Nik Reeves-McLaren, Sarah Moth-Lund Christensen
Institution: University of Sheffield
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4415869417