5 papers
Physics-Informed Machine Learning for Pouch Cell Temperature Estimation
Zheng Liu
Accurate temperature estimation of pouch cells with indirect liquid cooling is essential for optimizing battery thermal management systems for transportation electrification. Howev…
Generative Design for Direct-to-Chip Liquid Cooling for Data Centers
Zheng Liu
Rapid growth in artificial intelligence (AI) workloads is driving up data center power densities, increasing the need for advanced thermal management. Direct-to-chip liquid cooling…
Discovering physical mechanisms from experiment-simulation mismatches
Yue Li, Penghui Yang, Yushan Xiao +7
Scientific discovery often begins where observation and prediction disagree. As computation and machine learning survey chemical space, experiment-simulation mismatches are exposed…
MATAI: A Generalist Machine Learning Framework for Property Prediction and Inverse Design of Advanced Alloys
Yanchen Deng, Chendong Zhao, Yixuan Li +10
The discovery of advanced metallic alloys is hindered by vast composition spaces, competing property objectives, and real-world constraints on manufacturability. Here we introduce…
Autonomous Multi-objective Alloy Design through Simulation-guided Optimization
Penghui Yang, Chendong Zhao, Bijun Tang +11
Alloy discovery is constrained by vast compositional spaces, competing objectives, and prohibitive experimental costs. Although simulations and machine learning have each accelerat…