Abstract

Magnetic refrigeration exploits the magnetocaloric effect, which is the entropy change upon the application and removal of magnetic fields in materials, providing an alternate path for refrigeration other than conventional gas cycles. While intensive research has uncovered a vast number of magnetic materials that exhibit a large magnetocaloric effect, these properties remain unknown for a substantial number of compounds. To explore new functional materials in this unknown space, machine learning is used as a guide for selecting materials that could exhibit a large magnetocaloric effect. By this approach, HoB2 is singled out and synthesized, and its magnetocaloric properties are evaluated, leading to the experimental discovery of a gigantic magnetic entropy change of 40.1 J kg−1 K−1 (0.35 J cm−3 K−1) for a field change of 5 T in the vicinity of a ferromagnetic second-order phase transition with a Curie temperature of 15 K. This is the highest value reported so far, to the best of our knowledge, near the hydrogen liquefaction temperature; thus, HoB2 is a highly suitable material for hydrogen liquefaction and low-temperature magnetic cooling applications.

Machine learning: The search for cooler materials

A material for magnetically cooling hydrogen to its liquid form has been identified by a data-driven approach. Some materials get colder when they are exposed to an alternating magnetic field. This so-called magnetocaloric effect enables refrigeration to within one thousandth of a degree of absolute zero. Trial and error have uncovered many magnetocaloric materials, but Pedro Baptista de Castro, from the National Institute for Materials Science in Tsukuba, Japan, and co-workers have instead approached material discovery in a more systematic way using machine learning. They trained their algorithm to screen prospective compounds using data from the scientific literature. In this way they identified, and then experimentally confirmed, that holmium boride, HoB2, has a giant magnetocaloric effect at temperatures around 15 Kelvin (–258 °C), near the liquefaction point of hydrogen.

Details

Title
Machine-learning-guided discovery of the gigantic magnetocaloric effect in HoB2 near the hydrogen liquefaction temperature
Author
Castro Pedro Baptista de 1   VIAFID ORCID Logo  ; Terashima Kensei 2   VIAFID ORCID Logo  ; Yamamoto, Takafumi D 2   VIAFID ORCID Logo  ; Hou Zhufeng 3   VIAFID ORCID Logo  ; Iwasaki Suguru 2 ; Matsumoto Ryo 1   VIAFID ORCID Logo  ; Adachi Shintaro 2   VIAFID ORCID Logo  ; Saito Yoshito 1   VIAFID ORCID Logo  ; Song, Peng 1   VIAFID ORCID Logo  ; Takeya Hiroyuki 2   VIAFID ORCID Logo  ; Takano Yoshihiko 1   VIAFID ORCID Logo 

 National Institute for Materials Science, Tsukuba, Japan (GRID:grid.21941.3f) (ISNI:0000 0001 0789 6880); University of Tsukuba, Tsukuba, Japan (GRID:grid.20515.33) (ISNI:0000 0001 2369 4728) 
 National Institute for Materials Science, Tsukuba, Japan (GRID:grid.21941.3f) (ISNI:0000 0001 0789 6880) 
 Chinese Academy of Sciences, State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Fuzhou, China (GRID:grid.9227.e) (ISNI:0000000119573309) 
Publication year
2020
Publication date
2020
Publisher
Nature Publishing Group
ISSN
18844049
e-ISSN
18844057
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2493706941
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.