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Related papers: Designing shape-memory-like microstructures in int…

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Hierarchically designed mechanical metamaterials involve nested levels of structural organization, mimicking natural structures (such as bones, wood, and bird feathers) to create advanced functional materials. Compositional hierarchy, a…

Soft Condensed Matter · Physics 2026-05-21 Shammo Dutta , Girish Krishnan , Sree Kalyan Patiballa

We present a practical algorithm for partially relaxing multiwell energy densities such as pertain to materials undergoing martensitic phase transitions. The algorithm is based on sequential lamination, but the evolution of the…

Materials Science · Physics 2015-06-24 S. Aubry , M. Fago , M. Ortiz

Sublattice melting is the loss of order of one lattice component in binary or ternary ionic crystals upon increase in temperature. A related transition has been predicted in colloidal crystals. To understand the nature of this transition,…

Soft Condensed Matter · Physics 2023-10-12 Hector Lopez-Rios , Ali Ehlen , Monica Olvera de la Cruz

Layered "mosaic" metal-halide perovskite materials display a wide-variety of microstructures that span the order-disorder spectrum and can be tuned via the composition of their constituent B-site octahedral species. Such materials are…

Materials Science · Physics 2025-11-25 Murray Skolnick , Salvatore Torquato

The computational prediction of the structure and stability of hybrid organic-inorganic interfaces provides important insights into the measurable properties of electronic thin film devices, coatings, and catalyst surfaces and plays an…

Needle-like twins are observed experimentally within the transition layer at the martensite-twinned martensite interface. We utilize a phase-field approach to investigate this microstructure. Our goal is to simulate the morphology of the…

Materials Science · Physics 2023-09-06 Seyedshoja Amini , Mohsen Rezaee-Hajidehi , Stanislaw Stupkiewicz

Intrinsically low lattice thermal conductivity ($\kappa_l$) is a desired requirement in many crystalline solids such as thermal barrier coatings and thermoelectrics. Here, we design an advanced machine-learning (ML) model based on crystal…

Materials Science · Physics 2021-09-09 Koushik Pal , Cheol Woo Park , Yi Xia , Jiahong Shen , Chris Wolverton

To extend rational materials design and discovery into the space of metastable polymorphs, rapid and reliable assessment of their lifetimes is essential. Motivated by the early work of Buerger (1951), here we investigate the routes to…

Materials Science · Physics 2018-04-04 Vladan Stevanovic , Ryan Trottier , Felix Therrien , Charles Musgrave , Aaron Holder , Peter Graf

Developing inverse design methods for functional materials with specific properties is critical to advancing fields like renewable energy, catalysis, energy storage, and carbon capture. Generative models based on diffusion principles can…

Materials Science · Physics 2026-05-19 Xiao-Qi Han , Peng-Jie Guo , Ze-Feng Gao , Hao Sun , Zhong-Yi Lu

A natural embodiment for multifunctional materials combining energy-storing capabilities and structural mechanical properties are layered structures, similar to both laminate structural composites and electrochemical energy storage devices.…

Materials Science · Physics 2020-08-13 Moumita Rana , Yunfu Ou , Chenchen Meng , Federico Sket , Carlos González , Juan J. Vilatela

Materials which can undergo extremely fast displacive transformations as well as very slow diffusive transformations are studied using a Ginzburg-Landau framework to understand the physics behind microstructure formation and…

Materials Science · Physics 2007-05-23 Mathieu Bouville , Rajeev Ahluwalia

Amorphous solids form an enormous and underutilized class of materials. In order to drive the discovery of new useful amorphous materials further we need to achieve a closer convergence between computational and experimental methods. In…

Disordered Systems and Neural Networks · Physics 2024-11-19 Ata Madanchi , Emna Azek , Karim Zongo , Laurent K. Béland , Normand Mousseau , Lena Simine

A flat sheet programmed with a planar pattern of spontaneous shape change will morph into a curved surface. Such metric mechanics is seen in growing biological sheets, and may be engineered in actuating soft matter sheets such as…

Soft Condensed Matter · Physics 2022-07-01 Fan Feng , Daniel Duffy , Mark Warner , John S. Biggins

In this work, we conducted molecular dynamics simulations to study the fracture mechanism of ice crystals in a bulk phase and at ice-ice interfaces at the atomistic scale. We show that there exists a narrow disordered interfacial layer…

Chemical Physics · Physics 2019-07-23 A. Afshar , J. Zhong , D. S. Thompson , D. Meng

Deformation heterogeneities within microstructures of polycrystalline shape memory alloys (SMAs) during superelastic stressing are studied using both experiments and simulations. In situ X-ray diffraction, specifically the far-field high…

The behavior of identical particles interacting through the harmonic-repulsive pair potential has been studied in 3D using molecular dynamics simulations at a number of different densities. We found that at many densities, as the…

Soft Condensed Matter · Physics 2017-10-11 V. A. Levashov

As the length-scales of materials decrease, heterogeneities associated with interfaces approach the importance of the surrounding materials. Emergent electronic and magnetic interface properties in superlattices have been studied…

In this paper we introduce a 3D phenomenological model for shape memory behavior, accounting for: martensite reorientation, asymmetric response of the material to tension/compression, different kinetics between forward and reverse phase…

Analysis of PDEs · Mathematics 2012-10-05 Ferdinando Auricchio , Elena Bonetti

Shape memory alloys are remarkable 'smart' materials used in a broad spectrum of applications, ranging from aerospace to robotics, thanks to their unique thermomechanical coupling capabilities. Given the complex properties of shape memory…

Computational Engineering, Finance, and Science · Computer Science 2024-02-19 C. Erdogan , T. Bode , P. Junker

Machine-learning interatomic potentials (MLIPs) offer a powerful avenue for simulations beyond length and timescales of ab initio methods. Their development for investigation of mechanical properties and fracture, however, is far from…