Inverse Design of Metasurface based Absorbers using Physics Guided Conditional Diffusion Models

2026-05-19

AI Summary

This work addresses the limitations of conventional metasurface inverse design, which relies on time-consuming full-wave simulations and struggles to balance spectral accuracy with manufacturability, while existing generative approaches often lack precise conditional control and yield impractical structures. To overcome these challenges, the study introduces a physics-guided conditional diffusion model that integrates target reflection spectra via Feature-wise Linear Modulation (FiLM) and embeds a pre-trained electromagnetic surrogate model to impose spectrum-level physical regularization. The proposed method enables efficient, high-fidelity generation of manufacturable metasurfaces tailored to specific absorption performance, supports one-to-many design for a single target, achieves an average spectral mean squared error of 0.0006 and a band-alignment accuracy of 0.958 across the 2–18 GHz range, requires only ~30 seconds per generation—dramatically accelerating the design cycle from months—and has been experimentally validated.

Abstract

Inverse design of metasurfaces for specific electromagnetic responses requires generating geometries that satisfy stringent spectral constraints while maintaining manufacturability. Conventional design methodologies rely on iterative optimization routines using full wave simulations, which become extremely time consuming and computationally intensive for large design spaces. In addition, commonly employed generative approaches often exhibit limited conditional fidelity and the generated designs often contain fine or irregular features that are impractical to fabricate. In this regard, we propose a physics guided condition quality enhanced diffusion framework for the inverse design of metasurface based absorbers. Here, the conditioning information consisting of target reflection characteristics is integrated into the model using feature wise linear modulation (FiLM). Furthermore, to enforce adherence to target spectra, a pre trained surrogate EM simulator is embedded into the framework introducing physics aware regularization through spectrum level loss functions. The efficiency of the proposed model is demonstrated by generating practically realizable metasurfaces for different types of reflection characteristics in the frequency range of 2 to 18 GHz. The proposed framework achieves an average spectral mean squared error of 0.0006 and band alignment accuracy of 0.958 between the target spectra and the spectra produced by the generated designs, demonstrating high conditional accuracy. In addition, the model generates multiple geometries for the same condition, thereby providing diverse design alternatives to the engineer. The proposed model produces the suitable design in approximately 30 seconds, whereas the conventional approach can take several months under comparable computational resources. The efficiency of the model is also established via experimental measurements.

Problem

• inverse design
• metasurface absorbers
• electromagnetic response
• manufacturability
• conditional fidelity

Innovation

• conditional diffusion model
• physics-guided design
• metasurface absorber
• inverse design
• surrogate EM simulator