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We propose a simple yet effective method which allows one to attain large reversible shape changes in shape memory bimetallic composites without training procedure. It is based on the conservation of strongly anisotropic martensite…

Materials Science · Physics 2008-06-10 V. Khovaylo , V. Koledov , E. Perov , V. Shavrov , G. Lebedev , D. Zakharov , M. Ohtsuka , V. Pushin , H. Miki , T. Takagi

Shape-programmable soft materials that exhibit integrated multifunctional shape manipulations, including reprogrammable, untethered, fast, and reversible shape transformation and locking, are highly desirable for a plethora of applications,…

The paper focuses on numerical simulation of the phase-field (PF) equations for modeling martensitic transformations in shape memory alloys (SMAs), their complex microstructures and thermo-mechanical behavior. The PF model is based on the…

Materials Science · Physics 2014-03-25 R. Dhote , H. Gomez , R. Melnik , J. Zu

The impact of shear deformation in $(1\,0\,1)[1\,0\,\bar{1}]$ system of non-modulated (NM) martensite in Ni$_2$MnGa ferromagnetic shape memory alloy is investigated by means of ab initio atomistic simulations. The shear system is associated…

Materials Science · Physics 2024-11-11 Martin Heczko , Petr Šesták , Hanuš Seiner , Martin Zelený

The deformation mechanisms governing the cyclic stress-strain behaviour of a TiNi shape memory alloy were investigated in this work. To understand the development of these mechanisms during cyclic loading, three low-cycle fatigue tests were…

Materials Science · Physics 2013-01-09 Anne-Lise Gloanec , Giovambattista Billota , Michel Gerland

Recent studies in interpretability have explored the inner workings of transformer models trained on tasks across various domains, often discovering that these networks naturally develop highly structured representations. When such…

A polycrystalline plasticity model, which incorporates the contribution of deformation twinning, is proposed. For this purpose, each material point is treated as a composite material consisting of a parent constituent and multiple twin…

Materials Science · Physics 2023-06-22 Charles Mareau , Hamidreza Abdolvand

By mimicking the geometrical relation of nano-twin crystals, we propose novel architected twin mechanical metamaterials (TMMs), which can impede local shearing band formation under external loading, thus avoiding global catastrophic…

Materials Science · Physics 2021-01-05 Wenwang Wu , Seok Kim , Ali Ramazani , Young Tae Cho , Daining Fang

Amongst the various fascinating types of material behavior featured by magnetic gels and elastomers are magnetostrictive effects. That is, deformations in shape or changes in volume are induced from outside by external magnetic fields.…

Soft Condensed Matter · Physics 2024-01-30 Lukas Fischer , Andreas M. Menzel

Memory effects in amorphous materials have been widely studied because of their possible widespread future applications. We show here that ultrastable glasses can exhibit a transient reversible memory effect when subjected to both a local…

Soft Condensed Matter · Physics 2025-05-15 Rashmi Priya , Smarajit Karmakar

Superelastic NiTi 1 shape memory alloy (SMA) wire was subjected to thermomechanical loading tests in tension to evaluate stress and temperature conditions under which the wire deforms plastically. Although the alloy demonstrated a very high…

Materials Science · Physics 2024-06-24 P. Šittner , E. Iaparova , O. Molnárová , O. Tyc , X. Bian , L. Kadeřávek , L. Heller

Martensites are materials that undergo diffusionless, solid-state transitions. The martensitic transition yields properties that depend on the history of the material and may allow it to recover its previous shape after plastic deformation.…

Designing shape memory alloys (SMAs) that meet performance targets while remaining affordable and sustainable is a complex challenge. In this work, we focus on optimizing SMA compositions to achieve a desired martensitic start temperature…

Machine Learning · Computer Science 2025-08-21 S. Josyula , Y. Noiman , E. J. Payton , T. Giovannelli

Understanding the internal representations of large language models is crucial for ensuring their reliability and safety, with sparse autoencoders (SAEs) emerging as a promising interpretability approach. However, current SAE training…

Machine Learning · Computer Science 2025-10-13 T. Ed Li , Junyu Ren

Memristors based on two-dimensional materials (2DMs) have garnered significant attention due to their fast resistive switching (RS) behavior and atomic-level thickness, which enables low power consumption, making them promising candidates…

The mathematical formulation of constitutive models to describe the path-dependent, i.e., inelastic, behavior of materials is a challenging task and has been a focus in mechanics research for several decades. There have been increased…

Computational Engineering, Finance, and Science · Computer Science 2023-09-06 Max Rosenkranz , Karl A. Kalina , Jörg Brummund , Markus Kästner

The motility of a cell can be triggered or inhibited not only by an applied force but also by a mechanically neutral force couple. This type of loading, represented by an applied stress and commonly interpreted as either squeezing or…

Soft Condensed Matter · Physics 2018-01-24 Thibaut Putelat , Pierre Recho , Lev Truskinovsky

A geometrically nonlinear continuum mechanical theory is formulated for deformation and failure behaviors of amorphous polymers. The model seeks to capture material response over a range of loading rates, temperatures, and stress states…

Materials Science · Physics 2026-02-10 John D. Clayton

For their excellent stiffness-to-weight characteristics, triply periodic minimal surfaces (TPMS) are widely adopted in architected materials. However, their geometric regularity often leads to elastic anisotropy, limiting their…

Computational Physics · Physics 2025-05-21 Minwoo Park , Junheui Jo , Seunghwa Ryu

State-Space Models (SSMs), and particularly Mamba, have recently emerged as a promising alternative to Transformers. Mamba introduces input selectivity to its SSM layer (S6) and incorporates convolution and gating into its block definition.…

Machine Learning · Computer Science 2025-06-16 Ningyuan Huang , Miguel Sarabia , Abhinav Moudgil , Pau Rodriguez , Luca Zappella , Federico Danieli
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