Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

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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Publication Details

Journal
Advanced Intelligent Systems
Published
2026-08-25
DOI
https://doi.org/10.1002/aisy.70496
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
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article

Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

Rachid Laref, Nicola Marzari, Simon M.‐M. Dubois, Juan Rojo et al.
Advanced Intelligent Systems
Machine Learning in Materials Science
article

Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

Rachid Laref, Nicola Marzari, Simon M.‐M. Dubois, Juan Rojo, Wide Hogenhout, Aakash Ashok Naik, Giovanni Pizzi, Peter Klein, Mariví Fernández-Serra, Michele Ceriotti, Sanggyu Chong, Chiara Zanardi, Stephan Roche, Cristiano Malica, Camilla Coletti, Sonia Conesa‐Boj, Jean‐Christophe Charlier, Miguel A. L. Marques, Antonio Rossi, Junfeng Qiao, Minh Tuan Dau, Vincenzo Palermo, Natalia Konchakova, Kostya S. Novoselov, Silvana Botti, Tigany Zarrouk, Tejs Vegge, Janine George, Gian‐Marco Rignanese, Yousung Jung, Victor Trinquet, Seong-Min Kim, A. Ustyuzhanin, Miguel A. Caro, Romain Gautier, José H. García, Sara Navarro Rodriguez, Ömer Hasan Omar, Jean‐Lucas Uslu
article en

Abstract

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.

Advanced Intelligent Systems
Centre National de la Recherche Scientifique (FR), Federal Institute For Materials Research and Testing (DE), Seoul National University (KR), University of Liverpool (GB), Ca' Foscari University of Venice (IT), National University of Singapore (SG), University of Bremen (DE), Constructor University (DE), University of Cambridge (GB), European Commission (BE), SLAC National Accelerator Laboratory (US), Paul Scherrer Institute (CH), Fraunhofer Institute for Industrial Mathematics (DE), Centre National pour la Recherche Scientifique et Technique (CNRST) (MA), Institut des Matériaux Jean Rouxel (FR), National University (SD), Institut Català de Nanociència i Nanotecnologia (ES), National Institute for Subatomic Physics (NL), Groupe de Recherche en Droit, Économie, Gestion (FR), Chorley and South Ribble Hospital (GB), Centre de Recerca Matemàtica (ES), Institute of Organic Synthesis and Photoreactivity (IT), Institut de Ciència de Materials de Barcelona (ES), Helmholtz-Zentrum Hereon (DE), Unité de catalyse et de chimie du solide de Lille (FR), Center for Nanotechnology Innovation (IT), Université d'Artois (FR), École Polytechnique Fédérale de Lausanne (CH), Stony Brook University (US), Chalmers University of Technology (SE), Friedrich Schiller University Jena (DE), Vrije Universiteit Amsterdam (NL), Ruhr University Bochum (DE), UCLouvain (BE), Technical University of Denmark (DK), Stanford University (US), Delft University of Technology (NL), Aalto University (FI)
Openalex Percentile: Top 22%
Machine Learning in Materials Science
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