Statistical Mechanical Model of the Giant Electrocaloric Effect in Ferroelectric Polymers

Thedevelopment of highly efficient cooling technologies has beenidentified as a key strategy to address the mitigation of global warming.Especially, electrocaloric materials have emerged as promising candidatesfor cooling applications, owing to their potential to provide highcooling capacity with low energy consumption. To advance the developmentof electrocaloric materials with a significant electrocaloric effect(ECE), a thorough understanding of the underlying mechanisms is required.Previous studies have estimated the maximum ECE temperature changeby calculating the entropy change between two assumed states of adipole model, assuming polarization saturation with a sufficientlylarge electric field. However, it is more relevant to assess the ECEunder continuously changing electric fields as this is more reflectiveof real-world conditions. To this end, we establish a continuous transitionbetween the complete disorder state and the polarization saturationstate using the partition function to derive the entropy change. Ourresults demonstrate excellent agreement with experimental data, andour analysis of energy items within the partition function attributesthe increase in the ECE entropy change with decreasing crystal sizeto interfacial effects. This statistical mechanical model revealsthe in-depth ferroelectric polymers producing the ECE and offers significantpotential for predicting the ECE in ferroelectric polymers and thusguides the design of high-performance ECE materials.

Automated summary

The development of efficient cooling technologies, especially electrocaloric materials, is crucial for addressing global warming. Understanding the underlying mechanisms of electrocaloric effects is necessary for advancing their development. Previous studies estimated the maximum temperature change using a polarization model, but it is more relevant to assess the electrocaloric effect under continuously changing electric fields to simulate real-world conditions.