AI-Driven Monte Carlo Uncertainty Analysis of Curie Temperature Effects on Active Magnetic Regenerator Performance

In the paper AI-Driven Monte Carlo Uncertainty Analysis of Curie Temperature Effects on Active Magnetic Regenerator Performance , published in the International Journal of Refrigeration (IF = 3.8), researchers from the Laboratory for Refrigeration and District Energy revisited the methodology for analyzing the impact of statistical variations in Curie temperature on the performance of multilayer magnetocaloric regenerators.

The launch of Heat4energy project

TU Delft leads HEAT4ENERGY, a European consortium, dedicated to develop thermomagnetic devices and novel materials to harvest heat from data centres, food, pulp and paper industries and convert this waste heat to electricity. This project ticks all the boxes: energy transition, decarbonising, low and high power devices for conversion of Read more…

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