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Reverse engineering can be used to derive a 3D model of an existing physical part when such a model is not readily available. For parts that will be fabricated with subtractive and formative manufacturing processes, existing reverse…

Computational Engineering, Finance, and Science · Computer Science 2026-03-24 Jannatul Bushra , Md Habibor Rahman , Mohammed Shafae , Hannah D. Budinoff

Inverse electromagnetic design has emerged as a way of efficiently designing active and passive electromagnetic devices. This maturing strategy involves optimizing the shape or topology of a device in order to improve a figure of merit--a…

Optics · Physics 2018-12-05 Andrew Michaels , Eli Yablonovitch

Inverse design enables automating the discovery and optimization of devices achieving performance significantly exceeding that of traditional human-engineered designs. However, existing methodologies to inverse-design electromagnetic…

Computational Physics · Physics 2026-01-30 Jui-Hung Sun , Mohamed Elsawaf , Yifei Zheng , Ho-Chun Lin , Chia Wei Hsu , Constantine Sideris

This article reviews recent inverse statistical-mechanical methodologies that we have devised to optimize interaction potentials in soft matter systems that correspond to stable "target" structures. We are interested in finding the…

Soft Condensed Matter · Physics 2008-11-05 Salvatore Torquato

On-demand vibration mitigation in a mechanical system needs the suitable design of multiscale metastructures, involving complex unit cells. In this study, immersing in the world of patterns and examining the structural details of some…

Time-varying nanostructures allow us to control the spatial and temporal properties of light. The temporal modulation of the nanostructures constitutes an additional degree of freedom to control their scattering properties on demand and in…

Functionally graded porous plates have been validated as remarkable lightweight structures with excellent mechanical characteristics and numerous applications. With inspiration from the high strength-to-volume ratio of triply periodic…

Materials Science · Physics 2023-04-11 H. Nguyen-Xuan , Kim Q. Tran , Chien H. Thai , Jaehong Lee

Understanding how nano- or micro-scale structures and material properties can be optimally configured to attain specific functionalities remains a fundamental challenge. Photonic metasurfaces, for instance, can be spectrally tuned through…

Kirigami is an increasingly useful fabrication method to produce shape-programmable metamaterial structures. However, inverse design remains difficult because deployment is nonlinear, and feasible cut layouts must satisfy discrete…

Machine Learning · Computer Science 2026-05-12 Milad Yazdani , Shahriar Shalileh , Dena Shahriari

For many materials, macroscopic mechanical behavior is determined by an intricate microstructure. Understanding the relation between these two scales helps scientists and engineers design better materials. The relation which maps…

Computational Physics · Physics 2026-05-13 Arnaud Vadeboncoeur , Mark Girolami , Kaushik Bhattacharya , Andrew M. Stuart

The inverse design of metasurfaces faces inherent challenges due to the nonlinear and highly complex relationship between geometric configurations and their electromagnetic behavior. Traditional optimization approaches often suffer from…

Recent advances in meta-optics have enabled diverse functionalities in compact optical devices; however, conventional forward design approaches become inadequate as device complexity and scale grow. Inverse design offers a powerful…

To create heterogeneous, multiscale structures with unprecedented functionalities, recent topology optimization approaches design either fully aperiodic systems or functionally graded structures, which compete in terms of design freedom and…

Computational Engineering, Finance, and Science · Computer Science 2022-04-05 Yu-Chin Chan , Daicong Da , Liwei Wang , Wei Chen

Optical metasurfaces have been heralded as the platform to integrate multiple functionalities in a compact form-factor, potentially replacing bulky components. A central stepping stone towards realizing this promise is the demonstration of…

The advent of computational statistical disciplines, such as machine learning, is leading to a paradigm shift in the way we conceive the design of new compounds. Today computational science does not only provide a sound understanding of…

Materials Science · Physics 2019-11-07 Alessandro Lunghi , Stefano Sanvito

Numerical simulations have become an essential design tool in the field of photonics, especially for nanophotonics. In particular, 3D finite-difference-time-domain (FDTD) simulations are popular for their powerful design capabilities.…

Optics · Physics 2023-03-31 Michael Efseaff , Kyle Wynne , Krishna Narayan , Mark C. Harrison

In machine learning and molecular design, there exist two approaches: discriminative and generative. In the discriminative approach dubbed forward design, the goal is to map a set of features/molecules to their respective electronics…

Chemical Physics · Physics 2019-04-24 Alain Tchagang , Julio Valdés

Discovering new physical products and processes often demands enormous experimentation and expensive simulation. To design a new product with certain target characteristics, an extensive search is performed in the design space by trying out…

Machine Learning · Statistics 2018-11-16 Phuoc Nguyen , Truyen Tran , Sunil Gupta , Santu Rana , Svetha Venkatesh

Programmable shape-shifting materials can take different physical forms to achieve multifunctionality in a dynamic and controllable manner. Although morphing a shape from 2D to 3D via programmed inhomogeneous local deformations has been…

Soft Condensed Matter · Physics 2018-09-05 Hillel Aharoni , Yu Xia , Xinyue Zhang , Randall D. Kamien , Shu Yang

Composites with high strength and high fracture resistance are desirable for structural and protective applications. Most composites, however, suffer from poor damage tolerance and are prone to unpredictable fractures. Understanding the…

Materials Science · Physics 2024-04-23 Tommaso Magrini , Chelsea Fox , Adeline Wihardja , Athena Kolli , Chiara Daraio