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MIT Industrial Battery Consortium
Developing New CAE Tools for Batteries
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Research highlight - multi-scale modeling of batteries
Research highlight - advanced experimental techniques
Research highlight - data-driven analysis of fire accidents
Research highlight - modeling shear fracture of pouch cells
Research highlight - detailed model of 18650
Research highlight - micro-structural model of PP separator
Research highlight - In-plane loading_Experimental
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Recent News
2021 Interim Meeting will be held on 16 & 18 June for two sessions
Sun, 06/13/2021
Postdoctoral Associate Position in the area of machine learning for solid-state batteries
Mon, 04/26/2021
2020 Annual Review Meeting was held virtually!
Fri, 11/20/2020
2020 Interim Meeting was held virtually!
Thu, 06/18/2020
more
Recent progresses
Large-deformation plasticity and fracture behavior of pure lithium under various stress states
Guiding the Design of Heterogeneous Electrode Microstructures for Li‐Ion Batteries: Microscopic Imaging, Predictive Modeling, and Machine Learning
The Application of Data-Driven Methods and Physics-Based Learning for Improving Battery Safety
A physics-guided neural network framework for elastic plates: comparison of governing equations-based and energy-based approaches
Recurrent Neural Network Modeling of the Large Deformation of Lithium-ion Battery Cells
More...
