Competitive driving effect on calorics by dual-fields in ferroic materials with strong magnetostructural coupling
Source abstract
Abstract
Solid state refrigeration based on caloric effect of a solid has received extensive attention. From theoretical viewpoint, the caloric effect driven by multiple fields yields larger caloric response due to cross-interaction for ferroic materials with multiple order parameters. However, experimental evidence involving cross-responses is very limited. Here, we report the first experimental study on the modulation of the barocaloric effect (BCE) by magnetic field in Ni50Mn35In15 materials with strong magnetostructural coupling. The results demonstrate that the modulating behavior of BCE by magnetic field, which is dominated by cross-response, depends crucially on the magnitude of pressure. At low pressures, an abnormal minimum appears in the magnetic field dependent barocaloric entropy change |ΔSTBCE|, while it turns into a monotonic enhancement as the pressure reaches 4 kbar or larger. The enhanced ratio of |ΔSTBCE| is as much as ∼ 40 % when a magnetic field of 5 T is applied, accordingly the barocaloric refrigeration performance enhances. For the underlying mechanism, Ab initio calculations were performed, which provide a theoretical explanation about the driving effect by single pressure, single magnetic field, and dual-fields on the magnetostructural transition from the perspective of total energy and Mn-d/Ni-d electronic hybridization. The present work reveals that the modulation of BCE by magnetic field is not independent or additive but a synergistic effect of dual-fields, which lays a solid basis in guiding dual-fields driven solid-state refrigeration applications.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Magnetic and transport properties of perovskites and related materials · Shape Memory Alloy Transformations · Thermal Expansion and Ionic Conductivity
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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