Curie temperature modeling of magnetocaloric lanthanum manganites using Gaussian process regression

Abstract

Efficient solid-state refrigeration techniques have drawn increasing attention due to their potential for improving energy efficiency of refrigeration, air-conditioning, and temperature-control systems without using harmful gas as in conventional gas compression techniques. Research on magnetocaloric lanthanum manganites with near-room-temperature Curie temperature, TC, shows promising results for further developments of magnetic refrigeration devices. By incorporating chemical substitutions, oxygen content modifications, and various synthesis methods, these manganites experience lattice distortions from perovskite cubic structures to pseudocubic, orthorhombic, and rhombohedral structures. Further changes in lattice parameters can also be achieved by the introduction of strain due to lattice mismatches, where TC can be tuned more effectively. Empirical results and previous models through thermodynamics and first-principles have shown that changes in lattice parameters correlate with those in TC, but correlations are merely general tendencies and obviously not universal. In this work, the Gaussian process regression model is developed to find statistical correlations between TC and lattice parameters among lanthanum manganites. Nearly 100 lattices, cubic, pseudocubic, orthorhombic, and rhombohedral, with TC ranging from 40 K to 375 K are explored for this purpose. The modeling approach demonstrates a high degree of accuracy and stability, contributing to efficient and low-cost estimations of TC, providing guidance on thin film structure design and helping understandings of magnetic phase transformations and magnetocaloric effects in lanthanum manganites.