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The martensitic transformation in NiTi-based Shape Memory Alloys (SMAs) provides a basis for shape memory effect and superelasticity, thereby enabling applications requiring solid-state actuation and large recoverable shape changes upon…

The main purpose of this study is to determine, via a three dimensions Finite Element analysis (FE), the stress and strain fields at the inner surface of a tubular specimen submitted to thermo-mechanical fatigue. To investigate the surface…

The outstanding mechanical properties of high-manganese steels (HMnS) are a result of their high strain-hardenability. That is facilitated by strong suppression of dynamic recovery, predominant planar glide, and the activation of additional…

Materials Science · Physics 2019-09-20 Christian Haase , Franz Roters , Angela Quadfasel

For nanostructured materials, strain is of fundamental importance in stabilizing a specific crystallographic phase, modifying electronic properties, and in consequence their magnetism when it applies. Here we describe a magnetic shape…

Mesoscale and Nanoscale Physics · Physics 2010-10-07 C. Echeverría-Arrondo , J. Pérez-Conde , A. Ayuela

The objective of this work is to assess computationally efficient coarse-grained plasticity models against high-fidelity crystal plasticity simulations for magnesium polycrystals over a wide range of textures and grain sizes. A basic…

Materials Science · Physics 2026-01-13 R. Vigneshwaran , Showren Datta , A. A. Benzerga , Shailendra P. Joshi

Purpose: The purpose of this work is to apply a recently proposed constitutive model for mechanically induced martensitic transformations to the prediction of transformation loci. Additionally, this study aims to elucidate if a…

Thermally-driven semi-crystalline polymer networks are capable to achieve both the one-way shape-memory effect and two-way shape-memory effect under stress and stress-free conditions, therefore representing an appealing class of polymers…

Shape memory materials have the ability to recover their original shape after a significant amount of deformation when they are subjected to certain stimuli, for instance, heat or magnetic fields. However, their performance is often limited…

A Ginzburg-Landau model for the macroscopic behaviour of a shape memory alloy is proposed. The model is one-dimensional in essence, in that we consider the effect of the martensitic phase transition in terms of a uniaxial deformation along…

Materials Science · Physics 2011-08-01 D. Grandi , M. Maraldi , L. Molari

Martensitic and magnetic properties of ferromagnetic shape memory alloys are known to depend up on structural modulations and associated changes in the Fermi surface. These modulations although periodic and spanning over multiple unit…

Materials Science · Physics 2008-04-24 K. R. Priolkar , P. A. Bhobe , P. R. Sarode

Molecular dynamics simulations are performed to provide a detailed understanding of the functional degradation of shape memory alloys at small scale. The origin of the experimentally reported accumulation of plastic deformation and the…

Materials Science · Physics 2021-04-02 Won-Seok Ko , Won Seok Choi , Guanglong Xu , Pyuck-Pa Cho , Yuji Ikeda , Blazej Grabowski

Machine learning approaches informed by physics have offered new insights into the discovery of constitutive models from data, helping overcome some limitations of traditional constitutive modelling while reducing the cost of otherwise…

Materials Science · Physics 2026-05-19 Filippo Masi

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

This work presents a novel Shape Memory Alloy spring actuated continuum robotic neck that derives inspiration from pennate muscle architecture. The proposed design has 2DOF, and experimental studies reveal that the designed joint can…

Robotics · Computer Science 2023-09-08 Ratnangshu Das , Yashaswi Sinha , Anirudha Bhattacharjee , Bishakh Bhattacharya

Materials that behave like machines, e.g. functional materials that are able to change shape in response to external stimuli (Bhattacharya and James, 2005), often do so by exploiting phase transitions. Shape memory materials and the tail…

Materials Science · Physics 2019-03-13 Matthew P. O'Donnell , Jonathan P. Stacey , Isaac V. Chenchiah , Alberto Pirrera

Mechanical and shape memory properties of a polycrystalline Ni2.18Mn0.82Ga alloy prepared by a PDS (Pulse Discharge Sintering) method were investigated. It was found that the material demonstrates the two-way shape memory effect after a…

Materials Science · Physics 2007-05-23 T. Takagi , V. Khovailo , T. Nagatomo , M. Matsumoto , M. Ohtsuka , T. Abe , H. Miki

Shape memory alloys that can deform and then spring back to their original shape, have found a wide range of applications in the medical field, from heart valves to stents. As we push the boundaries of technology creating smaller, more…

Materials Science · Physics 2024-08-01 Mostafa Karami , Xian Chen

The present contribution proposes a general constitutive model to simulate the orthotropic stiffness, pre-peak nonlinearity, failure envelopes, and the post-peak softening and fracture of textile composites. Following the microplane model…

Materials Science · Physics 2015-09-09 Marco Salviato , Shiva Esna Ashari Esfahani , Gianluca Cusatis

Predicting the stress-strain behaviors of additively manufactured materials is crucial for part qualification in additive manufacturing (AM). Conventional physics-based constitutive models often oversimplify material properties, while…

Machine Learning · Computer Science 2026-03-17 Chenglong Duan , Dazhong Wu

Amorphous elastomers exhibit significant rate-stiffening and unique viscous flow characteristics across a wide range of strain rates, often undergoing glass transition above a strain rate threshold. We have developed a…

Soft Condensed Matter · Physics 2026-05-26 Bibekananda Datta , Sushan Nakarmi , Nitin P. Daphalapurkar