We pursue advanced manufacturing technologies that demand the highest levels of precision and reliability, particularly in semiconductor manufacturing. By understanding and precisely controlling friction, wear, and deformation at surfaces and interfaces, we develop core technologies for next-generation semiconductor packaging, precision machining, and advanced assembly.
We further extend these manufacturing principles and process platforms to diverse applications, including automotive, robotics, energy, and soft devices, enabling the next generation of high-performance, high-reliability, and intelligent manufacturing.
Developing advanced process and interface technologies for next-generation semiconductor packaging, including HBM, chiplet integration, and quantum devices. We integrate wafer thinning, planarization, cleaning, bonding, and metrology to enable reliable, high-density integration.
Developing precision material-removal processes, including chemical mechanical polishing (CMP) and wafer back-grinding, for smooth, low-damage, and integration-ready surfaces. We design pads, slurries, and process conditions based on contact mechanics and surface engineering.
Developing post-cleaning technologies to remove particles and residues generated during polishing and grinding. We investigate brush-based cleaning through contact mechanics, friction, and particle-detachment mechanisms.
Developing hybrid bonding technologies for 3D chip stacking and fine-pitch interconnects. Our research focuses on thermocompression bonding and Cu-Cu direct bonding, with emphasis on Cu diffusion, creep deformation, surface activation, and bonding reliability for advanced semiconductor packaging.
Investigating friction and torque-transfer mechanisms in bolted joints for automated fastening. Our research links surface conditions, coatings, and lubrication to torque transfer, preload consistency, and fastening reliability for robust assembly.
Investigating the friction mechanisms of electroactive PVC-gel materials under varying electrical and contact conditions. We leverage electrically tunable friction to develop lightweight haptic interfaces for wearable robots and haptic gloves.
Integrating AI and physics-informed neural networks (PINNs) frameworks for manufacturing process design. We develop predictive and inverse-design frameworks for manufacturing processes, complex structures, and material interfaces.
Evaluating surface quality and process reliability for polishing, cleaning, bonding, and assembly processes. We correlate process conditions with surface quality, interfacial integrity, and device performance to ensure reliable manufacturing.
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