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Embedding magnetic colloidal particles in an elastic polymer matrix leads to smart soft materials that can reversibly be addressed from outside by external magnetic fields. We discover a pronounced nonlinear superelastic stress-strain…

Soft Condensed Matter · Physics 2015-10-28 Peet Cremer , Hartmut Löwen , Andreas M. Menzel

Metamaterials hold significant promise for enhancing the imaging capabilities of MRI machines as an additive technology, due to their unique ability to enhance local magnetic fields. However, despite their potential, the metamaterials…

Medical Physics · Physics 2023-11-27 Ke Wu , Xia Zhu , Thomas G. Bifano , Stephan W. Anderson , Xin Zhang

An elastomer swelling actuator deforms by absorbing a fluid, thus generating mechanical movement. We show that depositing small droplets of low molecular weight liquid crystal on liquid crystal elastomer (LCE) films leads to shape changes…

Soft Condensed Matter · Physics 2025-02-18 Mahesha Kodithuwakku Arachchige , Rohan Dharmarathna , Paul Fleischer , Antal Jakli

Mechanical metamaterials are periodic lattice structures with complex unit cell architectures that can achieve extraordinary mechanical properties beyond the capability of bulk materials. A new class of metamaterials is proposed, whose…

Applied Physics · Physics 2022-07-22 Marius Wagner , Fabian Schwarz , Nick Huber , Lena Geistlich , Henning Galinski , Ralph Spolenak

Biological cells in living tissues form dynamic patterns with local orientational order and topological defects. Here we demonstrate an approach to produce cell monolayer with the predesigned orientational patterns using human dermal…

Recent studies of azo-dye doped liquid crystal elastomers show a strong photomechanical response. We report on models that predict experimental results that suggest photothermal heating is the dominant mechanism in a planar constrained…

We create mechanical metamaterials whose response to uniaxial compression can be programmed by lateral confinement, allowing monotonic, non-monotonic and hysteretic behavior. These functionalities arise from a broken rotational symmetry…

Soft Condensed Matter · Physics 2015-06-22 Bastiaan Florijn , Corentin Coulais , Martin van Hecke

In the pursuit of reducing the number of trainable parameters in deep transformer networks, we employ Reinforcement Learning to dynamically select layers during training and tie them together. Every few iterations, the RL agent is asked…

Machine Learning · Computer Science 2024-01-24 Tamir David Hay , Lior Wolf

Mechanism - collections of rigid elements coupled by perfect hinges which exhibit a zero-energy motion -- motivate the design of a variety of mechanical metamaterials. We significantly enlarge this design space by considering…

Soft Condensed Matter · Physics 2021-06-23 Nitin Singh , Martin van Hecke

Elastomers are used in a wide range of applications because of their large strain to failure, low density, and tailorable stiffness and toughness. The mechanical behavior of elastomers derives mainly from the entropic elasticity of the…

Soft Condensed Matter · Physics 2022-08-24 Michael R. Buche , Meredith N. Silberstein

Density functional theory is routinely applied to predict crystal structures. The most common exchange-correlation functionals used to this end are the Perdew-Burke-Ernzerhof (PBE) approximation and its variant PBEsol. We investigate the…

Materials Science · Physics 2022-05-18 Robert Hussein , Jonathan Schmidt , Tomás Barros , Miguel A. L. Marques , Silvana Botti

From self-assembly and protein folding to combinatorial metamaterials, a key challenge in material design is finding the right combination of interacting building blocks that yield targeted properties. Such structures are fiendishly…

Soft Condensed Matter · Physics 2025-06-26 Ryan van Mastrigt , Marjolein Dijkstra , Martin van Hecke , Corentin Coulais

Loss of plasticity, trainability loss, and primacy bias have been identified as issues arising when training deep neural networks on sequences of tasks -- all referring to the increased difficulty in training on new tasks. We propose to use…

Machine Learning · Computer Science 2024-12-11 Wesley Chung , Lynn Cherif , David Meger , Doina Precup

Here, we report the rate-dependent energy absorption behavior of a liquid crystal elastomer (LCE)-based architected material consisting of repeating unit cells of bistable tilted LCE beams sandwiched between stiff supports. Viscoelastic…

Particle based methods such as the Discrete Element Method and the Lattice Spring Method may be used for describing the behaviour of isotropic linear elastic materials. However, the common bond models employed to describe the interaction…

Computational Engineering, Finance, and Science · Computer Science 2021-07-06 Rahav Gowtham Venkateswaran , Ursula Kowalsky , Dieter Dinkler

In this paper, the two-dimensional pure bending of a hyperelastic substrate coated by a nematic liquid crystal elastomer (abbreviated as NLCE) is studied within the framework of nonlinear elasticity. The governing system, arising from the…

Soft Condensed Matter · Physics 2021-06-16 Yang Liu , Wendi Ma , Hui-Hui Dai

Plasticity is inherent to many engineering materials such as metals. While it can degrade the load-carrying capacity of structures via material yielding, it can also protect structures through plastic energy dissipation. To fully harness…

Computational Engineering, Finance, and Science · Computer Science 2025-02-05 Yingqi Jia , Xiaojia Shelly Zhang

Superhydrophobic materials are often inspired by nature, whereas metamaterials are engineered to have properties not usually found in naturally occurring materials. In both cases, the key that unlocks their unique properties is structure.…

For two-dimensional polycrystals the effective elasticity tensor $C_*$ as a function $C_*(C_0)$ of the elasticity tensor $C_0$ of the constituent crystal is considered. It is shown that this function can be approximated by one with a…

Materials Science · Physics 2025-10-14 Graeme W. Milton

Passive elastic elements can contribute to stability, energetic efficiency, and impact absorption in both biological and robotic systems. They also add dynamical complexity which makes them more challenging to model and control. The impact…

Robotics · Computer Science 2019-09-30 Ali Marjaninejad , Jie Tan , Francisco J. Valero-Cuevas
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