I will discuss the emerging need to massively use and deploy Artificial Intelligence (AI) techniques in materials and devices design and engineering [1]. I will first present our research concerning innovative advanced materials (amorphous boron-nitride based compounds and carbon-based membranes) for boosting the field of interconnects technologies [2]. Using AI techniques [3,4], we achieved unprecedented simulation of electronic/dielectric properties of amorphous models with multimillion atoms while keeping ab-initio accuracy. This is bringing a revolutionary paradigm shift in the way researchers and engineers can access hidden and deeper layers of information for interlinking structural features down to the atomic scale with ultimate material properties as well as device and technology performances across all industrial fields.
I will point towards the emerging revolution of fully describing as-grown materials with AI-driven reconstruction of digital models/twins with atomistic modelling (from polycrystalline graphene to semiconducting materials for qubits industry). This opens a tremendous capability to correlate in-depth atomistic-scale features of as-grown materials with resulting local and global chemical, physical and devices properties, offering reverse engineering and AI-driven co-piloting for industrial innovation strategies. Some illustration will be given on developing end-to-end workflows [5] serving as pathfinder for advanced nanoelectronics, thermal management in high-power devices, neuromorphic computing hardware and advanced spintronic technologies using 2D materials and beyond.
All research and technology fields are to be radically affected and transformed by this AI revolution in materials science and technology, which I will illustrate in particular among the variety of research fields pursued during a decade by the Graphene Flagship initiative and now continued within the Innovative Advanced Innovative Materials initiative/partnership, which will shape the future of European and worldwide landscape for the ten years to come. New initiative like our ICN2-ICREA spinoff “Apeiron Intelligence” [6] will contribute to boost the design of novel materials and devices and reinforce industrial competitiveness.
References
[1]Malica C, Novoselov K, Barnard AS, Kalinin SV, Spurgeon SR, Reuter K, Roche S, et al., J. Phys. Mater. 8 (2025) 021001.
[2]S Hong, CS Lee, MH Lee, Y Lee, KY Ma, G Kim, SI Yoon, K Ihm, KJ Kim, S. Roche et al, Nature 582 (7813), 511-514 (2020); C.T. Toh et al. Nature Electronics (2026)
[3]Fan Z, Garcia JH, Cummings AW, Roche S, et al., Phys. Rep. 903, 1-69 (2021)
[4]Th. Galvani et al. Journal of Physics: Materials 7 (3), 035003 (2024)
[5]Botifoll M, Pinto-Huguet I, Rotunno E, Galvani T, et al., Advanced Materials (2025).
[6]Apeiron Intelligence