Data integrity in materials science in the era of AI: balancing accelerated discovery with responsible science and innovation

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.

Authors

Nik Reeves‐McLaren (ORCID: https://orcid.org/0000-0002-1061-1230)
Søren Christensen

Institutions

University of Sheffield (GB)

Publication Details

Journal: Journal of Materials Chemistry A
Published: 2025-11-04
DOI: https://doi.org/10.1039/d5ta05512a
Citations: 1
Primary Topic: Machine Learning in Materials Science
Type: article
Field-Weighted Citation Impact: 0.52

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article

Data integrity in materials science in the era of AI: balancing accelerated discovery with responsible science and innovation

Nik Reeves‐McLaren, Søren Christensen

Nov 4, 2025

1 citations

Journal of Materials Chemistry A

Machine Learning in Materials Science

0.52

article

Data integrity in materials science in the era of AI: balancing accelerated discovery with responsible science and innovation

Nik Reeves‐McLaren, Søren Christensen

November 4, 2025article en

1 citations

Abstract

Journal of Materials Chemistry AVol. 14(1)

University of Sheffield (GB)

Openalex Percentile: Top 31%

Machine Learning in Materials Science

0.52

DOI Open Access PDF OpenAlex

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Data integrity in materials science in the era of AI: balancing accelerated discovery with responsible science and innovation — Nik Reeves‐McLaren, Søren Christensen · Journal of Materials Chemistry A (2025) | TGRS Research Map | TGRS