Current-diffusion model for metasurface structure discoveries with spatial-frequency dynamics

Nature Machine Intelligence (2025)Cite this article In AI-driven metamaterials discovery, designing metasurfaces requires extrapolation to unexplored performance regimes to discover new structures. Here we introduce MetaAI, a physics-aware current-diffusion framework that synergizes spatial topologies and frequency-domain responses to discover non-intuitive metasurface architectures. Unlike conventional inverse design constrained by predefined specifications, MetaAI operates as a performance synthesizer by generating electrical current distributions that bridge electromagnetic performance and metasurface structures. This enables both in-distribution and out-of-distribution targets with diverse topologies. The core innovation of the proposed framework lies in its dual-domain diffusion module, which directly correlates meta-atom current mechanisms with electromagnetic behaviours to enable the discovery of structures with 17.2% wider operational bandwidths. We validate MetaAI across single-layer, multilayer and dynamically tunable metasurfaces, demonstrating out-of-distribution generalization across full-wave simulations and experimental prototypes. Access to this article via ICE Institution of Civil Engineers is not available. This is a preview of subscription content, access via your institution Access to this article via ICE Institution of Civil Engineers is not available. Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription Receive 12 digital issues and online access to articles Prices may be subject to local taxes which are calculated during checkout