Artificial Intelligence and Generative Models for Materials Discovery: A Review

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This is a Literature Review study.

Albertus D. Handoko; Riko I Made

doi:10.1142/s2810922825400018

August 8, 2025World Scientific Annual Review of Functional Materials

Artificial Intelligence and Generative Models for Materials Discovery: A Review

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Key Points

Generative models can significantly enhance materials discovery processes, improving efficiency and outcomes.
AI applications in functional materials research have been gaining traction, enabling innovative material designs.
The review encompasses various generative approaches and their implications for future materials research.
Insights drawn from this review underline the transformative role of artificial intelligence in material science.

Implication

This review discusses artificial intelligence and generative models for advancing materials discovery, highlighting their potential impacts.

Abstract

World Scientific Annual Review of Functional MaterialsAccepted Papers No AccessArtificial Intelligence and Generative Models for Materials Discovery: A ReviewAlbertus Denny Handoko and Riko I MadeAlbertus Denny Handoko and Riko I Madehttps://orcid.org/0000-0002-6534-4651 Search for more papers by this author https://doi.org/10.1142/S2810922825400018Cited by:0 (Source: Crossref) PreviousNext AboutSectionsPDF/EPUB ToolsAdd to favorites

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Cite This Study

Handoko et al. (2025) studied this question.

synapsesocial.com/papers/68c1c32754b1d3bfb60f0faf https://doi.org/10.1142/s2810922825400018

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Artificial Intelligence and Generative Models for Materials Discovery: A Review

Key Points

Implication

Abstract

Discussion

Cite This Study

Artificial Intelligence and Generative Models for Materials Discovery: A Review

Key Points

Implication

Abstract

Discussion

Cite This Study

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