Computational design of barocaloric materials for solid-state refrigeration

EXTENDED ABSTRACT: Solid-state refrigeration based on barocaloric effect (BCE) holds out promise for environmentally friendly cooling with high energy-efficiency and downsize scalability, however, their comprehensive refrigeration performance is notably inferior in comparison to commercial refrigerant due to the lack of scientific guidance for material discovery and performance improvement. In this talk, we report recent progress on understanding and improving refrigeration performance in plastic crystals (PC), such as neopentylglycol (NPG), pentaerythritol (PE), neopentane (PA), etc., which represent a class of disordered molecular solids. We show that the intermolecular hydrogen bond plays a key role in the orientational order of PC molecules, while its broken due to thermal perturbation prominently weakens the activation barrier of orientational disorder. It is found that low concentration of defects and substitution is able to regulate the isothermal entropy, adiabatic temperature, and thermal hysteresis of PC. Furthermore, phase transition temperature of molecular order to disorder can be tuned by alloying PA or NPG into PE imbedded in carbon frame, meanwhile demonstrating both giant isothermal entropy changes . The large BCE mainly comes from the order– disorder transition of PC molecules imbedded in carbon frame through analysis of the dynamic process of the composites. Importantly, the thermal conductivity of these compsites is as high as 10, enabling efficient thermal exchange that is vital for improving cooling performance during the cyclic refrigeration process. These advances establish relatively complete microscopic mechanism of BCE in PCs and provides important guidance for the design and improvement of their refrigeration performance for next generation solid-state refrigeration technologies. 


Keywords: solid-state refrigeration, barocaloric effect, isothermal entropy change, adiabatic temperature change, thermal hysteresis and transport, multi-scale simulation, machine learning
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Brief Introduction of Speaker
Hui Wang

Prof. Wang has completed his PhD from Institute of Metal Research, Chinese Academy of Sciences and Postdoctoral Studies from University of California, Irvine, U.S.A. He is the Dean of department of physics of Central South University, vice Dean of Provincial key Lab. He has published more than 100 papers in reputed journals, including Nature, Nature Materials, Nature Communications and PRL, etc, and has been serving as an editorial board member/editor in MGE Advances, Info. Funct. Mater., Materials and Font. Phys, etc.