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Kirigami, the Japanese art of paper cutting, has recently enabled the design of stretchable mechanical metamaterials that can be easily realized by embedding arrays of periodic cuts into an elastic sheet. Here, we exploit kirigami…

Soft Condensed Matter · Physics 2020-07-16 Lishuai Jin , Antonio Elia Forte , Bolei Deng , Ahmad Rafsanjani , Katia Bertoldi

Soft deployable structures - unlike conventional piecewise rigid deployables based on hinges and springs - can assume intricate 3-D shapes, thereby enabling transformative technologies in soft robotics, shape-morphing architecture, and…

Soft Condensed Matter · Physics 2023-03-21 Leixin Ma , Mrunmayi Mungekar , Vwani Roychowdhury , M. Khalid Jawed

By integrating the principles of kirigami cutting and data-driven modeling, this study aims to develop a personalized, rapid, and low-cost design and fabrication pipeline for creating body-conformable surfaces around the knee joint. The…

Biological Physics · Physics 2025-11-19 Jyotshna Bali , Jinyang Li , Jie Chen , Suyi Li

For centuries, cutting and folding the papers with special patterns have been used to build beautiful, flexible and complex three-dimensional structures. Inspired by the old idea of kirigami (paper cutting), and the outstanding properties…

Mesoscale and Nanoscale Physics · Physics 2017-11-03 Bohayra Mortazavi , Aurélien Lherbier , Zheyong Fan , Ari Harju , Timon Rabczuk , Jean-Christophe Charlier

Two-dimensional (2D) materials have been a central focus of recent research because they host a variety of properties, making them attractive both for fundamental science and for applications. It is thus crucial to be able to identify…

Materials Science · Physics 2022-11-18 Mohammad Tohidi Vahdat , Kumar Agrawal Varoon , Giovanni Pizzi

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

This paper investigates the optimization of 2D and 3D composite structures using machine learning (ML) techniques, focusing on fracture toughness and crack propagation in the Double Cantilever Beam (DCB) test. By exploring the intricate…

Materials Science · Physics 2024-06-25 Mohammad Naqizadeh Jahromi , Mohammad Ravandi

Fibrillar adhesion, observed in animals like beetles, spiders, and geckos, relies on nanoscopic or microscopic fibrils to enhance surface adhesion via 'contact splitting.' This concept has inspired engineering applications across robotics,…

Machine Learning · Computer Science 2024-10-08 Mohammad Shojaeifard , Matteo Ferraresso , Alessandro Lucantonio , Mattia Bacca

Kirigami tessellations, regular planar patterns formed by cutting flat, thin sheets, have attracted recent scientific interest for their rich geometries, surprising material properties and promise for technologies. Here we pose and solve…

Soft Condensed Matter · Physics 2020-02-10 Gary P. T. Choi , Levi H. Dudte , L. Mahadevan

Microstructure--property relationships are key to effective design of structural materials for advanced applications. Advances in computational methods enabled modeling microstructure-sensitive properties using 3D models (e.g., finite…

Materials Science · Physics 2023-03-20 Guangyu Hu , Marat I. Latypov

We present an additive approach for the inverse design of kirigami-based mechanical metamaterials by focusing on the empty (negative) spaces instead of the solid tiles. By considering each negative space as a four-bar linkage, we identify a…

Soft Condensed Matter · Physics 2023-05-29 Levi H. Dudte , Gary P. T. Choi , Kaitlyn P. Becker , L. Mahadevan

Kirigami, art of paper cutting, enables two-dimensional sheets transforming into unique shapes which are also hard to reshape once with prescribed cutting patterns. Rare kirigami designs manipulate cuts on three-dimensional objects to…

Materials Science · Physics 2021-03-30 Yanbin Li , Jie Yin

We introduce a new class of thin flexible structures that morph from a flat shape into prescribed 3D shapes without an external stimulus such as mechanical loads or heat. To achieve control over the target shape, two different concepts are…

Applied Physics · Physics 2023-01-20 Jan Zavodnik , Yunbo Wang , Wenzhong Yan , Miha Brojan , M. Khalid Jawed

Designing functional materials requires a deep search through multidimensional spaces for system parameters that yield desirable material properties. For cases where conventional parameter sweeps or trial-and-error sampling are impractical,…

Materials Science · Physics 2022-03-22 Sanket Kadulkar , Zachary M. Sherman , Venkat Ganesan , Thomas M. Truskett

The presence of cuts in a thin planar sheet can dramatically alter its mechanical and geometrical response to loading, as the cuts allow the sheet to deform strongly in the third dimension. We use numerical experiments to characterize the…

Soft Condensed Matter · Physics 2021-12-28 Gaurav Chaudhary , Lauren Niu , Marta Lewicka , Qing Han , L Mahadevan

Kirigami, the art of paper cutting, has become a paradigm for mechanical metamaterials in recent years. The basic building blocks of any kirigami structures are repetitive deployable patterns that derive inspiration from geometric art forms…

Soft Condensed Matter · Physics 2021-08-17 Lucy Liu , Gary P. T. Choi , L. Mahadevan

We use machine learning (ML) to infer stress and plastic flow rules using data from repre- sentative polycrystalline simulations. In particular, we use so-called deep (multilayer) neural networks (NN) to represent the two response…

Computational Physics · Physics 2018-09-05 Reese E. Jones , Jeremy A. Templeton , Clay M. Sanders , Jakob T. Ostien

Flexible surfaces can modulate fluid forces through deformation, enabling passive adaptation to flow conditions. Here we show that kirigami sheets, planar surfaces patterned with arrays of parallel slits, provide a simple route to tunable…

Fluid Dynamics · Physics 2026-04-23 Agathe Schmider , Tom Marzin , Sophie Ramananarivo

Machine learning (ML) based materials discovery has emerged as one of the most promising approaches for breakthroughs in materials science. While heuristic knowledge based descriptors have been combined with ML algorithms to achieve good…

Materials Science · Physics 2021-09-28 Sadman Sadeed Omee , Steph-Yves Louis , Nihang Fu , Lai Wei , Sourin Dey , Rongzhi Dong , Qinyang Li , Jianjun Hu

Magnetic moments near zigzag edges in graphene allow complex nanostructures with customised spin properties to be realised. However, computational costs restrict theoretical investigations to small or perfectly periodic structures. Here we…

Mesoscale and Nanoscale Physics · Physics 2022-09-14 Meriç E. Kucukbas , Seán McCann , Stephen R. Power
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