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Artificial Intelligence for advanced functional materials: progress and emerging frontiers

C. Malica, K. Novoselov, S. Kim, Y. Jung, S. Botti, M. Marques, T. Zarrouk, M. Caro, S. Chong, M. Ceriotti, M. Fernandez‐Serra, S. Navarro‐Rodriguez, A. Naik, J. George, Ö. Hasan Omar, V. Trinquet, G. Rignanese, A. Ustyuzhanin, S. Conesa‐Boj, J. Rojo, M. Dau, S. Dubois, J. Charlier, J. Garcia, R. Gautier, R. Laref, J. Qiao, G. Pizzi, N. Marzari, C. Coletti, A. Rossi, J. Uslu, C. Zanardi, V. Palermo, W. Hogenhout, N. Konchakova, P. Klein, T. Vegge, S. Roche

Advanced Intelligent Systems, xx, e70496, (2026)

DOI: 10.1002/aisy.70496

Download: BibTEX

Artificial intelligence (AI) is transforming the way materials are designed, understood, and manufactured. This Perspective examines how recent advances in data-driven modeling, high-performance simulation, and autonomous experimentation are converging to accelerate the discovery of functional materials for next-generation technologies—from energy storage and biomedicine to nanoelectronics and quantum devices. We outline ongoing strategies to embed AI across the materials design workflow—from synthesis and characterization to large-scale simulations enabled by machine learning techniques and approaching ab initio accuracy—and discuss key challenges that remain on the path toward intelligent (bio)materials discovery.

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