AI for Science
IOP Publishing · United Kingdom
Aims & Scope✦ Inferred from recent articles
AI for Science focuses on the application of machine learning and artificial intelligence to scientific research, particularly in materials science, chemistry, and physics. The journal features work on developing and applying machine learning models for molecular design, predicting material properties, understanding chemical reactions, and accelerating scientific discovery through data-driven approaches. Topics include machine learning force fields, representation learning for atomic structures, and AI-driven optimization for material synthesis and property prediction.
AI-summarised from recent articles · verify on publisher page →
General Information
Submission Info
Ethics & Quality
Think.Check.Submit Compliance
A twelfth criterion — whether APC fees are clearly disclosed — is not scored here; it is left out of the total rather than counted as a failure. Publication charges appear in the metrics card above.
Based on the Think.Check.Submit framework by DOAJ, COPE & OASPA. All data from verified open sources.
Subject Classification
Research Topics (OpenAlex)
Frequently asked questions about AI for Science
Is AI for Science a predatory journal?
PubScope has no integrity flags on record for AI for Science: it is indexed in DOAJ, and is not on DOAJ's withdrawn list. Indexing is a transparency signal, not a guarantee — always confirm fit and policies before submitting.
What is the impact factor of AI for Science?
AI for Science is not in the Web of Science Core Collection, so it has no official Clarivate Journal Impact Factor.
Is AI for Science indexed in Scopus and Web of Science?
AI for Science is indexed in DOAJ.
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See all →Data updated: 2026-05-26 · Sources: SJR, DOAJ, OpenAlex, WoS, Crossref