Roadmap on metamaterial theory, modelling and design

Review (2025)
Author(s)

Bryn Davies (University of Warwick, Imperial College London)

Stefan Szyniszewski (Durham University)

Marcelo A. Dias (The University of Edinburgh)

Anastasia Kisil (The University of Manchester)

Shane Cooper (University College London)

Marie Touboul (Imperial College London, ENSTA Paris Institut Polytechnique de Paris)

Simon A.R. Horsley (University of Exeter)

Gareth J. Conduit (Cavendish Laboratory, The Studio)

Oliver Duncan (Manchester Metropolitan University)

Łukasz Kaczmarczyk (University of Glasgow)

Fabrizio Scarpa (University of Bristol)

Daniel Torrent (Universitat Jaume I)

Elena Cherkaev (University of Utah)

Niklas Wellander (Luleå University of Technology)

Andrea Alù (City University of New York)

Katie H. Madine (University of Liverpool)

Ping Sheng (The Hong Kong University of Science and Technology)

Luke G. Bennetts (University of Melbourne)

Anastasiia O. Krushynska (Rijksuniversiteit Groningen)

Mohammad J. Mirzaali (TU Delft - Biomaterials & Tissue Biomechanics)

Amir Zadpoor (TU Delft - Biomaterials & Tissue Biomechanics)

undefined More Authors (External organisation)

DOI related publication
https://doi.org/10.1088/1361-6463/adc271 Final published version
More Info
expand_more
Publication Year
2025
Language
English
Journal title
Journal of Physics D: Applied Physics
Issue number
20
Volume number
58
Article number
203002
Downloads counter
422
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

This Roadmap surveys the diversity of different approaches for characterising, modelling and designing metamaterials. It contains articles covering the wide range of physical settings in which metamaterials have been realised, from acoustics and electromagnetics to water waves and mechanical systems. In doing so, we highlight synergies between the many different physical domains and identify commonality between the main challenges. The articles also survey a variety of different strategies and philosophies, from analytic methods such as classical homogenisation to numerical optimisation and data-driven approaches. We highlight how the challenging and many-degree-of-freedom nature of metamaterial design problems call for techniques to be used in partnership, such that physical modelling and intuition can be combined with the computational might of modern optimisation and machine learning to facilitate future breakthroughs in the field.