Artificial intelligence for advanced functional materials: exploring current and future directions

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Cristiano Malica - , Universität Bremen (Autor:in)
  • Kostya S. Novoselov - , National University of Singapore (Autor:in)
  • Amanda S. Barnard - , Australian National University (Autor:in)
  • Sergei V. Kalinin - , University of Tennessee, Knoxville, Pacific Northwest National Laboratory (Autor:in)
  • Steven R. Spurgeon - , National Renewable Energy Laboratory, University of Colorado Boulder (Autor:in)
  • Karsten Reuter - , Fritz Haber Institute of the Max Planck Society (Autor:in)
  • Maite Alducin - , Centro de Fisica de Materiales CFM/MPC (CSIC-UPV/EHU), Donostia International Physics Center (Autor:in)
  • Volker L. Deringer - , University of Oxford (Autor:in)
  • Gábor Csányi - , University of Cambridge (Autor:in)
  • Nicola Marzari - , Universität Bremen, École Polytechnique Fédérale de Lausanne (Autor:in)
  • Shirong Huang - , Professur für Materialwissenschaft und Nanotechnik, Max Bergmann Zentrum für Biomaterialien Dresden (MBZ) (Autor:in)
  • Gianaurelio Cuniberti - , Professur für Materialwissenschaft und Nanotechnik, Max Bergmann Zentrum für Biomaterialien Dresden (MBZ) (Autor:in)
  • Qiushi Deng - , Royal Melbourne Institute of Technology University (Autor:in)
  • Pablo Ordejón - , Catalan Institute of Nanoscience and Nanotechnology (Autor:in)
  • Ivan Cole - , Australian National University (Autor:in)
  • Kamal Choudhary - , National Institute of Standards and Technology (NIST) (Autor:in)
  • Kedar Hippalgaonkar - , Nanyang Technological University, Agency for Science, Technology and Research, Singapore (Autor:in)
  • Ruiming Zhu - , Nanyang Technological University, Agency for Science, Technology and Research, Singapore (Autor:in)
  • O. Anatole von Lilienfeld - , University of Toronto, Vector Institute, Technische Universität Berlin (Autor:in)
  • Mohamed Hibat-Allah - , Vector Institute, University of Waterloo (Autor:in)
  • Juan Carrasquilla - , ETH Zürich (Autor:in)
  • Giulia Cisotto - , Università degli Studi di Trieste (Autor:in)
  • Alberto Zancanaro - , Università degli studi di Padova (Autor:in)
  • Wolfgang Wenzel - , Karlsruher Institut für Technologie (Autor:in)
  • Andrea C. Ferrari - , University of Cambridge (Autor:in)
  • Andrey Ustyuzhanin - , National University of Singapore, Constructor University (Autor:in)
  • Stephan Roche - , Catalan Institute of Nanoscience and Nanotechnology, ICREA - Institució Catalana de Recerca i Estudis Avançats (Autor:in)

Abstract

This perspective addresses the topic of harnessing the tools of artificial intelligence (AI) for boosting innovation in functional materials design and engineering as well as discovering new materials for targeted applications in energy storage, biomedicine, composites, nanoelectronics or quantum technologies. It gives a current view of experts in the field, insisting on challenges and opportunities provided by the development of large materials databases, novel schemes for implementing AI into materials production and characterization as well as progress in the quest of simulating physical and chemical properties of realistic atomic models reaching the trillion atoms scale and with near ab initio accuracy.

Details

OriginalspracheEnglisch
Aufsatznummer021001
Seitenumfang19
FachzeitschriftJPhys materials
Jahrgang8 (2025)
Ausgabenummer2
PublikationsstatusVeröffentlicht - 23 Apr. 2025
Peer-Review-StatusJa

Externe IDs

ORCID /0000-0002-4349-793X/work/189708224

Schlagworte

Schlagwörter

  • artificial intelligence (AI), machine learning (ML), materials science