Back to Search
Start Over
Machine Learning Guided Discovery of Gigantic Magnetocaloric Effect in HoB$_{2}$ Near Hydrogen Liquefaction Temperature
Machine Learning Guided Discovery of Gigantic Magnetocaloric Effect in HoB$_{2}$ Near Hydrogen Liquefaction Temperature
- Publication Year :
- 2020
-
Abstract
- Magnetic refrigeration exploits the magnetocaloric effect which is the entropy change upon application and removal of magnetic fields in materials, providing an alternate path for refrigeration other than the conventional gas cycles. While intensive research has uncovered a vast number of magnetic materials which exhibits large magnetocaloric effect, these properties for a large number of compounds still remain unknown. To explore new functional materials in this unknown space, machine learning is used as a guide for selecting materials which could exhibit large magnetocaloric effect. By this approach, HoB$_{2}$ is singled out, synthesized and its magnetocaloric properties are evaluated, leading to the experimental discovery of gigantic magnetic entropy change 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 our knowledge, near the hydrogen liquefaction temperature thus it is a highly suitable material for hydrogen liquefaction and low temperature magnetic cooling applications.<br />12 pages including 3 figures and 1 table + 11 pages of supplementary information. Published version available at: https://rdcu.be/b36ep
- Subjects :
- FOS: Computer and information sciences
Phase transition
Computer Science - Machine Learning
Materials science
FOS: Physical sciences
02 engineering and technology
Machine learning
computer.software_genre
01 natural sciences
Machine Learning (cs.LG)
0103 physical sciences
Magnetic refrigeration
General Materials Science
Absolute zero
010302 applied physics
Condensed Matter - Materials Science
business.industry
Liquefaction
Refrigeration
Materials Science (cond-mat.mtrl-sci)
Computational Physics (physics.comp-ph)
021001 nanoscience & nanotechnology
Condensed Matter Physics
Magnetic field
Ferromagnetism
Modeling and Simulation
Curie temperature
Artificial intelligence
0210 nano-technology
business
computer
Physics - Computational Physics
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....1780ef640174d51317db681d112a534b