Giant room-temperature magnetocaloric effect MM′X alloys explored by machine learning
Magnetic refrigeration is emerging as a promising alternative to conventional gas compression refrigeration. The key to advancing this technology lies in identifying materials with high magnetocaloric effect (MCE). However, traditional experimental methods require time-consuming and labor-intensive...
| Autores: | , , , , , , , , , , , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/398192 |
| Acceso en línea: | http://hdl.handle.net/10261/398192 https://api.elsevier.com/content/abstract/scopus_id/105010679746 |
| Access Level: | acceso abierto |
| Palabra clave: | Room temperature Machine learning Magnetic refrigeration MM′X alloy temperature machine learning refrigeration Magnetic |
| Sumario: | Magnetic refrigeration is emerging as a promising alternative to conventional gas compression refrigeration. The key to advancing this technology lies in identifying materials with high magnetocaloric effect (MCE). However, traditional experimental methods require time-consuming and labor-intensive experimentation to screen compositions. Herein, we developed a machine learning (ML) model utilizing the Random Forest algorithm to efficiently identify MM'X alloy compositions with giant MCE near room temperature based on a small dataset (<200). The ML-predicted results were perfectly confirmed by the validation experiments. Notably, while most typical magnetic refrigeration materials near room temperature show a maximum ∆S around or <20 kg<sup>-1</sup> K<sup>-1</sup>(0–5 T), our predicted alloys show a remarkable ∆S of up to 51 kg<sup>-1</sup> K<sup>-1</sup>, which is more than four times higher than that of the benchmark material, Gd. The origin of this giant MCE is linked to atomic disorder and lattice ∆S predominantly from Ni atoms, as confirmed through spherical aberration corrected transmission electron microscopy, neutron powder diffraction and element-resolved vibrational density of states analysis. This work accelerates the discovery of magnetic refrigerants and significantly promotes the development of magnetic refrigeration. |
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