Developing fast-charging batteries is critical for the electrification of transportation to mitigate carbon emissions and climate change. The U.S. Department of Energy has set an ambitious goal of enabling electric vehicles to recharge under 10 minutes, covering a distance of 200 miles. This objective presents significant challenges and opportunities for scientists and engineers to overcome conventional obstacles in different aspects and scales. The main hurdle is balancing the battery's capacity and charging rate. Most batteries struggle to maintain high capacity when charged quickly due to the mass transport limitation and the ineffective utilization of deep electrode materials. Addressing this issue requires rational designs of the electrode microstructures and materials. However, with increasing resolutions of electrode design and characterization, more complex datasets are generated, leading to a need for advanced analysis techniques to extract detailed insights about samples. As a result, DL models become viable tools to assist in the analysis and deduction of complex datasets and parameters space and bridge the gap between experimental data and multiphysics modeling.