4.8 Article

Chemically Controllable Magnetic Transition Temperature and Magneto-Elastic Coupling in MnZnSb Compounds

期刊

ADVANCED FUNCTIONAL MATERIALS
卷 31, 期 17, 页码 -

出版社

WILEY-V C H VERLAG GMBH
DOI: 10.1002/adfm.202100108

关键词

chemical control; computational proxy; machine learning; magnetic materials; magnetocalorics

资金

  1. Engineering and Physical Science Research Council (EPSRC) [EP/N004884]
  2. EPSRC Doctoral Training Partnership [EP/N509693/1]
  3. EPSRC [EP/P001513/1]
  4. Royal Society [IEC\R2\170036]
  5. Leverhulme Trust from the Leverhulme Research Centre for Functional Materials Design
  6. METSA Federation (CNRS) [FR3507]
  7. U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences [DE-AC02-06CH11357, 65125]
  8. CNRS through Thermospin PRC
  9. EPSRC [2112206, EP/P001513/1] Funding Source: UKRI

向作者/读者索取更多资源

Magneto-caloric materials have the potential for environmentally friendly thermal management devices, but developing solid-state technology faces challenges in material selection and performance control. The study of compounds derived from the PbFCl structure reveals that the c/a parameter can be used as an accurate proxy to control magnetic transition, and chemical substitution allows tuning of Curie temperature over a broad temperature span.
Magneto-caloric materials offer the possibility to design environmentally friendlier thermal management devices compared to the widely used gas-based systems. The challenges to develop this solid-state based technology lie in the difficulty of finding materials presenting a large magneto-caloric effect over a broad temperature span together with suitable secondary application parameters such as low heat capacity and high thermal conductivity. A series of compounds derived from the PbFCl structure is investigated using a combination of computational and experimental methods focusing on the change of cell volume in magnetic and non-magnetic ground states. Scaling analysis of the magnetic properties determines that they are second order phase transition ferromagnets and that the magnetic entropy change is driven by the coupling of magneto-elastic strain in the square-net through the magnetic transition determined from neutron and synchrotron X-ray diffraction. The primary and secondary application related properties are measured experimentally, and the c/a parameter is identified as an accurate proxy to control the magnetic transition. Chemical substitution on the square-net affords tuning of the Curie temperature over a broad temperature span between 252 and 322 K. A predictive machine learning model for the c/a parameter is developed to guide future exploratory synthesis.

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