Abstract Magnetic refrigeration is a promising alternative to traditional vapor compression systems, with potential efficiency and environmental sustainability advantages. However, the narrow operational temperature range of magnetocaloric materials (MCMs) and their reliance on rare‐earth elements remain key challenges. Multilayer active magnetic regenerators (AMRs) address the temperature range limitations by combining multiple magnetocaloric layers, each with different Curie temperatures. This study investigates the impact of statistical deviations in Curie temperatures on the performance of multilayer AMRs, specifically using second‐order La‐Fe‐Co‐Si materials. A 1D multilayer AMR numerical model is developed to simulate the effects of Curie temperature variability, with radial basis function neural networks employed to efficiently predict performance. The results indicate that although increasing the number of MCM layers enhances cooling power and coefficient of performance (COP) , Curie temperature uncertainties significantly degrade the AMR performance. The likelihood of achieving cooling targets diminishes as the number of MCM layers increases, particularly for standard deviations exceeding 1 K. These findings emphasize the importance of accounting for Curie temperature uncertainties in AMR design. Moreover, enhancing the manufacturing precision of the Curie temperatures of MCMs is essential for improving the performance and commercialization of magnetocaloric technology.
Tomc et al. (Wed,) studied this question.