logo
ResearchBunny Logo
Machine-learning-guided discovery of the gigantic magnetocaloric effect in HoB₂ near the hydrogen liquefaction temperature

Physics

Machine-learning-guided discovery of the gigantic magnetocaloric effect in HoB₂ near the hydrogen liquefaction temperature

P. B. D. Castro, K. Terashima, et al.

This paper reveals groundbreaking use of machine learning to uncover materials with an enormous magnetocaloric effect, showcasing the remarkable HoB₂ which exhibits a magnetic entropy change of 40.1 J kg⁻¹ K⁻¹. This discovery has significant implications for hydrogen liquefaction and low-temperature magnetic cooling applications, conducted by a team including Pedro Baptista de Castro, Kensei Terashima, Takafumi D Yamamoto, and others.

00:00
00:00
~3 min • Beginner • English
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 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 candidate for hydrogen liquefaction and low-temperature magnetic cooling applications.
Publisher
NPG Asia Materials
Published On
Mar 17, 2020
Authors
Pedro Baptista de Castro, Kensei Terashima, Takafumi D Yamamoto, Zhufeng Hou, Suguru Iwasaki, Ryo Matsumoto, Shintaro Adachi, Yoshito Saito, Peng Song, Hiroyuki Takeya, Yoshihiko Takano
Tags
machine learning
magnetocaloric effect
HoB₂
hydrogen liquefaction
magnetic entropy
low-temperature cooling
Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny