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Chemically Controllable Magnetic Transition Temperature and Magneto-Elastic Coupling in MnZnSb Compounds
Authors:Philip A. E. Murgatroyd  Kieran Routledge  Samantha Durdy  Michael W. Gaultois  T. Wesley Surta  Matthew S. Dyer  John B. Claridge  Stanislav N. Savvin  Denis Pelloquin  Sylvie Hébert  Jonathan Alaria
Affiliation:1. Department of Physics, University of Liverpool, Oxford Street, Liverpool, L69 7ZE UK;2. Leverhulme Research Centre for Functional Materials Design The Materials Innovation Factory, University of Liverpool, 51 Oxford Street, Liverpool, L7 3NY UK

Department of Computer Science, University of Liverpool, Ashton Street, Liverpool, L69 3BX UK;3. Leverhulme Research Centre for Functional Materials Design The Materials Innovation Factory, University of Liverpool, 51 Oxford Street, Liverpool, L7 3NY UK;4. Department of Chemistry, University of Liverpool, Crown Street, Liverpool, L69 7ZD UK;5. Institut Laue–Langevin, 71 Avenue des Martyrs, Grenoble, 38000 France;6. CRISMAT UMR 6508, 6 Boulevard du Maréchal Juin – F-14050, Caen, cedex 4 France

Abstract: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.
Keywords:chemical control  computational proxy  machine learning  magnetic materials  magnetocalorics
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