Machine Learning for Better Computer Cooling Design

  • Project Year: 2025-26
  • Departments Represented: MEng
  • Industry/Track: Artificial Intellegence, Machine Learning, and Data Science

Our project addresses the growing thermal management crisis in data centers by investigating Triply Periodic Minimal Surface (TPMS) lattice structures. TPMS structures offer high surface area compared to traditional strut lattices, or straight fins used in today’s data centers. Our novel methodology for creating TPMS structures at low cost (compared to previous methods) includes (1) generation of geometry, (2) polymer scaffold construction, and (3) nickel electroplating. Our foundation of simulations and construction pipeline will enable future researchers to create TPMS lattices at low cost for deployment in high-performance servers within Berkeley and beyond.

  • Advisor(s): Grace Gu
  • Team: Ryan Carpio-Brown [MSE], Ikechukwu Sunny-Odio [ME], Edward Holthaus [ME], David Zhang [ME].