Tuning Magnetocaloric Effect of a Mn-Cr-Sb-Ga alloy by the Nonvolatile Residual Strain of a Ti-Ni Shape Memory Alloy
Source abstract
Abstract
Abstract The multiferroic composites with a layer of magnetocaloric materials (MCMs) on a piezoelectric substrate have recently been developed to tune the magnetocaloric effect (MCE) through the stress from the piezoelectric substrate, which could help achieve high-efficiency and miniaturized refrigeration. The small strain of piezoelectric substrates is sufficient to tune the MCE of alloys whose transformation temperature (TM) is sensitive to the external stress. However, it might not work effectively for those stress-insensitive MCMs, which are also important MCMs with considerable MCE and small hysteresis. In this paper, we design a new composite with a Mn1.95Cr0.05Sb0.95Ga0.05 ribbon on a Ti50Ni50 shape-memory-alloy substrate. The Ti50Ni50 substrate can provide much larger nonvolatile stress than a piezoelectric substrate, which thus successfully tunes the MCE of the Mn1.95Cr0.05Sb0.95Ga0.05, despite its low stress sensitivity. With a 2% residual strain of the Ti50Ni50 substrate, TM of the Mn1.95Cr0.05Sb0.95Ga0.05 is increased by ~6 K, which ~7.5 times that (0.8 K) achieved via a Mn1.95Cr0.05Sb0.95Ga0.05/PMN-PT composite. With different residual strains of Ti50Ni50 substrate from 0% to 2%, a wide working temperature window of 31 K is obtained at a low magnetic field of 1 T. Moreover, this composite exhibits an almost constant refrigeration capacity and a small hysteresis of 4.9 K under different stress, which promotes homogeneous heat transfer and improves the working efficiency. This work provides an effective method to tune the MCE of both stress-sensitive and stress-insensitive MCMs, which could be used in miniaturized refrigerators.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Shape Memory Alloy Transformations · Magnetic and transport properties of perovskites and related materials · Multiferroics and related materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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