Development and Optimization of Mechanical Thermal Metadevices for Advanced Energy Applications
Project Description
The rapid development of sustainable energy systems and high-performance electronics is driving demand for advanced, precise thermal management solutions. Conventional materials conduct heat passively and symmetrically, providing little control over heat flow. By contrast, engineered thermal switches and diodes can actively modulate or direct heat, enabling on-demand transfer, thermal rectification, and programmable thermal circuits—functions analogous to electrical switches and diodes.
Thermal switches and diodes have broad potential in applications such as waste heat harvesting, solid-state cooling, and thermal protection of sensitive devices. However, most existing solid-state switches—based on electrochemical control, field-induced phase change, or similar effects—suffer from limited ON/OFF conductance ratios (typically <10), slow switching, and challenges in miniaturization and integration. There is still significant opportunity to develop compact thermal devices with high ON/OFF ratios that can be seamlessly integrated into practical systems like thermoelectric energy harvesters and solid-state coolers.
Mechanical thermal switches, which control heat by physically making or breaking contact, offer distinct advantages over solid-state approaches: they can achieve much higher ON/OFF ratios (up to 100 in air), fast and reliable switching, and excellent scalability for large-area or modular deployment. The integration of heat pipes—which use vapor-phase transport for efficient heat transfer—can further enhance switching performance, outperforming even the best bulk materials such as diamond.
This project will design, fabricate, and optimize mechanical thermal switches and diodes using actuation mechanisms including shape memory alloys (SMA), electroadhesion, or thermally actuated bilayer expansion based on our previous works. Machine learning will be incorporated to optimize device geometry and actuation parameters for maximum thermal and mechanical efficiency. The ultimate goal is to realize compact, high-performance thermal switches that are well-suited for integration into next-generation energy harvesting and cooling platforms.
Thermal switches and diodes have broad potential in applications such as waste heat harvesting, solid-state cooling, and thermal protection of sensitive devices. However, most existing solid-state switches—based on electrochemical control, field-induced phase change, or similar effects—suffer from limited ON/OFF conductance ratios (typically <10), slow switching, and challenges in miniaturization and integration. There is still significant opportunity to develop compact thermal devices with high ON/OFF ratios that can be seamlessly integrated into practical systems like thermoelectric energy harvesters and solid-state coolers.
Mechanical thermal switches, which control heat by physically making or breaking contact, offer distinct advantages over solid-state approaches: they can achieve much higher ON/OFF ratios (up to 100 in air), fast and reliable switching, and excellent scalability for large-area or modular deployment. The integration of heat pipes—which use vapor-phase transport for efficient heat transfer—can further enhance switching performance, outperforming even the best bulk materials such as diamond.
This project will design, fabricate, and optimize mechanical thermal switches and diodes using actuation mechanisms including shape memory alloys (SMA), electroadhesion, or thermally actuated bilayer expansion based on our previous works. Machine learning will be incorporated to optimize device geometry and actuation parameters for maximum thermal and mechanical efficiency. The ultimate goal is to realize compact, high-performance thermal switches that are well-suited for integration into next-generation energy harvesting and cooling platforms.
Supervisor
ZHENG, Qiye
Quota
1
Course type
UROP1000
UROP1100
Applicant's Roles
Help to develop and optimize the control system and the device; perform characterization and optimization of the metadevice.
Applicant's Learning Objectives
This project will give undergraduates practical experience designing, building, and testing mechanical thermal switches and diodes, using tools like 3D printing, Arduino coding, and COMSOL simulation. Students will also get hands-on exposure to machine learning for device optimization and learn to integrate heat pipes for improved thermal control. These multidisciplinary skills are highly valued in both academia and industry, especially in fields like energy, electronics, and advanced manufacturing.
Complexity of the project
Moderate