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Related papers: Fermi Surface as a Driver for the Shape-Memory Eff…

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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

The large variety of complex electronic structure materials and their alloys, offer highly promising directions for improvements in thermoelectric (TE) power factors (PF). Their electronic structure contains rich features, referred to as…

Materials Science · Physics 2023-11-08 Patrizio Graziosi , Neophytos Neophytou

In this paper we consider a simplified two-dimensional scalar model for the formation of mesoscopic domain patterns in martensitic shape-memory alloys at the interface between a region occupied by the parent (austenite) phase and a region…

Mathematical Physics · Physics 2012-09-19 Alessandro Giuliani , Stefan Mueller

MnSi has been extensively studied for five decades, nonetheless detailed information on the Fermi surface (FS) symmetry is still lacking. This missed information prevented from a comprehensive understanding the nature of the magnetic…

We demonstrate the existence of metallic spin density waves (SDWs) in the Kondo lattice model on a square lattice for a wide range of parameters by means of real space dynamical mean field theory. In these SDWs, the spin polarization as…

Strongly Correlated Electrons · Physics 2015-08-17 Robert Peters , Norio Kawakami

The Magnetoelectric (ME) effect in solids is a prominent cross correlation phenomenon, in which the electric field (${\bm E}$) controls the magnetization (${\bm M}$) and the magnetic field (${\bm H}$) controls the electric polarization…

Strongly Correlated Electrons · Physics 2015-09-30 Makoto Naka , Sumio Ishihara

Magnetoelectric effect is a fundamental physics phenomenon that synergizes electric and magnetic degrees of freedom to generate distinct material responses like electrically tuned magnetism, which serves as a key foundation of the emerging…

Shape memory alloys (SMAs) have been intensively investigated as actuators for the past several decades. Due to their high actuation energy density compared to other active materials, their current and potential applications in engineering…

Materials Science · Physics 2018-12-31 Lei Xu , Alexandros Solomou , Dimitris Lagoudas

Since electronic and magnetic properties of many transition-metal oxides can be efficiently controlled by external factors such as the temperature, pressure, electric or magnetic field, they are regarded as promising materials for various…

Strongly Correlated Electrons · Physics 2015-05-18 I. V. Solovyev

We propose a ferromagnetic Heusler alloy that can switch between a metal and a half-metal. Thiseffect can provide tunable spintronics properties. Using the density functional theory (DFT) withreliable implementations of the electron…

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…

Modulated phases occur in numerous functional materials like giant ferroelectrics and magnetic shape memory alloys. To understand the origin of these phases, we review and generalize the concept of adaptive martensite. As a starting point,…

Materials Science · Physics 2015-05-13 S. Kaufmann , U. K. Roessler , O. Heczko , M. Wuttig , J. Buschbeck , L. Schultz , S. Fahler

Non-symmorphic materials have recently been predicted to exhibit many different exotic features in their electronic structures. These originate from forced band degeneracies caused by the non-symmorphic symmetry, which not only creates the…

Nanoscale superlattices with uniaxial ferromagnetic layers antiferromagnetically coupled through non-magnetic spacers are recently used as components of magnetoresistive and recording devices. In the last years intensive experimental…

Materials Science · Physics 2015-06-24 U. K. Roessler , A. N. Bogdanov

The magnetic properties of Mn$_{2}$Ni$_{(1+x)}$In$_{(1-x)}$ ($x$ = 0.5, 0.6, 0.7) and Mn$_{(2-y)}$Ni$_{(1.6+y)}$In$_{0.4}$ ($y$ = -0.08, -0.04, 0.04, 0.08) shape memory alloys have been studied. Magnetic interactions in the martensitic…

Materials Science · Physics 2015-06-17 D. N. Lobo , Sandhya Dwivedi , C. A. daSilva , N. O. Moreno , K. R. Priolkar , A. K. Nigam

The shape of the Fermi surface influences many physical phenomena in materials and a growing interest in how the spin-dependent properties are related to the fermiology of crystals has surged. Recently, a novel current-dependent nonlinear…

Mesoscale and Nanoscale Physics · Physics 2024-05-14 Anna C. Marx , Homayoun Jafari , Eelco Tekelenburg , Maria A. Loi , Jagoda Slawinska , Marcos H. D. Guimaraes

Lifshitz transition, a change in Fermi surface topology, is likely to greatly influence exotic correlated phenomena in solids, such as high-temperature superconductivity and complex magnetism. However, since the observation of Fermi…

This work presents a three-dimensional constitutive model for the martensitic transformation in polycrystalline Shape Memory Alloys (SMAs) under large deformation. By utilizing the logarithmic strain and rate, the model is able to account…

Materials Science · Physics 2019-09-04 Lei Xu , Theocharis Baxevanis , Dimitris Lagoudas

Precursor phenomena observed prior to the martensite phase transition plays a critical role towards the understanding of important technological properties of shape memory and magnetic shape memory alloys (MSMAs). The premartensite (PM)…

Materials Science · Physics 2021-11-01 Anupam K. Singh , Sanjay Singh , Dhananjai Pandey

Using density functional plus dynamical mean-field theory method (DFT+DMFT) with full self-consistency over the charge density, we study the effect of electronic correlations on the electronic structure, magnetic properties,…

Strongly Correlated Electrons · Physics 2019-12-25 S. L. Skornyakov , I. Leonov
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