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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

Direct experimental characterization of indentation-induced martensitic microstructures in pseudoelastic shape memory alloys (SMAs) is not possible, and thus there is a lack of evidence and understanding regarding the microstructure pattern…

Computational Physics · Physics 2023-04-26 Mohsen Rezaee-Hajidehi , Karel Tůma , Stanisław Stupkiewicz

We report on measurements of the adiabatic temperature change in the inverse magnetocaloric Ni$_{50}$Mn$_{34}$In$_{16}$ alloy. It is shown that this alloy heats up with the application of a magnetic field around the Curie point due to the…

Acoustic emission signals are known to exhibit a high degree of reproducibility in time and show correlations with the growth and shrinkage of martensite domains when athermal martensites are subjected to repeated thermal cycling in a…

Materials Science · Physics 2009-11-10 S. Sreekala , G. Ananthakrishna

Superelastic shape-memory alloys (SMAs) are unique smart materials with a considerable energy dissipation potential for dynamic loadings with varying strain-rates. The energy dissipation depends on the latent heat generated by the…

Materials Science · Physics 2021-07-27 A. Kaup , O. Altay , S. Klinkel

We explore the possibilities and limitations of using a coherent second phase to engineer the thermo-mechanical properties of a martensitic alloy by modifying the underlying free energy landscape that controls the transformation. We use…

Materials Science · Physics 2020-05-28 Saaketh Desai , Samuel Temple Reeve , Karthik Guda Vishnu , Alejandro Strachan

The magnetic and structural properties of MnAs are studied with ab initio methods, and by mapping total energies onto a Heisenberg model. The stability of the different phases is found to depend mainly on the volume and on the amount of…

Materials Science · Physics 2009-11-11 Ivan Rungger , Stefano Sanvito

A negative-positive-negative switching behavior of magnetoresistance (MR) with temperature is observed in a ferromagnetic shape memory alloy Ni_1.75Mn_1.25Ga. In the austenitic phase between 300 and 120 K, MR is negative due to s-d…

Shape memory alloys have a wide range of applications, including high stroke actuation, energy-efficient ferroic cooling, and energy harvesting. These applications are based on a reversible martensitic transformation, which results in a…

Functional behavior of NiTi shape memory alloys is restricted to temperatures below 150 {\deg}C. To shed light on the origin of the loss of functional properties of NiTi with increasing temperature, we have investigated stress induced…

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

The martensitic transformation in new-type all-d-metal Heusler alloys Pd2MnTi and Pt2MnTi have been investigated based on first-principles investigations. The calculated results indicate that the martenstic transformation have great…

Materials Science · Physics 2019-10-30 L. Feng

We study through the time evolution of magnetization the low temperature (T) dynamics of the metastable coexisting phases created by traversing different paths in magnetic field (H) and T space in a shape memory alloy system,…

Strongly Correlated Electrons · Physics 2015-05-30 A. Banerjee , P. Chaddah , S. Dash , Kranti Kumar , Archana Lakhani , X. Chen , R. V. Ramanujan

In search for the origins of the extraordinary low twinning stress of Ni-Mn-Ga magnetic shape memory alloys we studied the thermally induced changes of structure in Ni$_{50}$Mn$_{25+x}$Ga$_{25-x}$ ($x$=2.7--3.9) single crystal samples and…

We propose a Ginzburg-Landau theory for the elastic properties of shape memory polycrystals. A single crystal elastic free energy for a system that undergoes a square-to-rectangle transformation is generalized to a polycrystal by…

Materials Science · Physics 2007-05-23 Rajeev Ahluwalia , Turab Lookman , Avadh Saxena , Robert C Albers

The fascinating multiple magnetic states observed in the Ni-Mn-Sn based metamagnetic shape memory alloy are addressed through a combined muon spin relaxation (muSR) and neutron powder diffraction studies. The material used in the present…

Strongly Correlated Electrons · Physics 2019-06-12 J. Sannigrahi , S. Pramanick , S. Chatterjee , J. S. Lord , D. Khalyavin , A. D. Hillier , D. T. Adroja , S. Majumdar

Machine Learning (ML) has impacted numerous areas of materials science, most prominently improving molecular simulations, where force fields were trained on previously relaxed structures. One natural next step is to predict material…

Materials Science · Physics 2023-11-28 Robin Hilgers , Daniel Wortmann , Stefan Blügel

The ramp reversal memory (RRM) is a non-volatile memory effect previously observed in correlated oxides exhibiting temperature-driven metal-insulator transitions (MITs). In essence, when a system displaying RRM is heated to a specific…

Strongly Correlated Electrons · Physics 2025-07-08 Avital Fried , Ouriel Gotesdyner , Irena Feldman , Amit Kanigel , Amos Sharoni

The behavior of shape memory alloy (SMA) nanostructures is influenced by strain rate and temperature evolution during dynamic loading. The coupling between temperature, strain and strain rate effects is essential to capture inherent…

Materials Science · Physics 2014-07-01 R. Dhote , H. Gomez , R. Melnik , J. Zu

The large magnetocaloric effect in Heusler alloys showing martensite phase transformation puts them forward as efficient materials for magnetic refrigeration. However, irreversibility of the magnetocaloric cooling cycle is a major challenge…

Materials Science · Physics 2018-06-14 Luana Caron , Parul Devi , Alexandre M. G. Carvalho , Claudia Felser , Sanjay Singh

We developed a method for fitting machine-learning interatomic potentials with magnetic degrees of freedom, namely, magnetic Moment Tensor Potentials (mMTP). The main feature of our method consists in fitting mMTP to magnetic forces…