The group led by Prof. Mohini Sain at the University of Toronto is committed to advancing battery technologies that are crucial for electric vehicles (EVs) and sustainable energy storage. The team focuses on a wide array of battery chemistries, including lithium-sulfur (Li-S), nickel manganese cobalt (NMC), lithium manganese iron phosphate (LMFP), lithium iron phosphate (LFP), and lithium nickel manganese oxide (LNMO). These systems are explored for their potential to meet the energy density, efficiency, and longevity requirements of modern EVs and renewable energy solutions.
Our research spans materials development, where the group is working on cutting-edge anode and cathode materials, functional separators, and quasi-gel electrolytes. These materials are designed to improve ionic conductivity, enhance electrochemical performance, and reduce capacity loss over extended cycles. The team also focuses on optimizing separators and electrolytes to ensure better interfacial compatibility and minimize polysulfide shuttling in lithium-sulfur systems. Alongside materials development, extensive cell testing is carried out using advanced techniques such as cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), galvanostatic charge-discharge (GCD), and state-of-charge (SOC) and state-of-health (SOH) evaluations. We perform a range of cell configurations, including half cells, symmetric cells, and full cells, to assess the performance, degradation, and life cycle of the battery systems.
Postmortem analysis is a critical part of our research, helping us understand structural and chemical changes after cycling. Using X-ray diffraction (XRD), we examine lattice and structural changes in electrodes, while X-ray photoelectron spectroscopy (XPS) reveals chemical transformations at the electrode/electrolyte interface. Scanning electron microscopy (SEM) is employed to assess film cracking and surface degradation, and EIS allows us to study the resistance at the electrode/electrolyte interface. To monitor real-time behavior, we conduct operando analysis, including in-situ XRF spectroscopy to track undesired reactions in working cells.
Our computational modeling efforts integrate machine learning, density functional theory (DFT), and simulations using tools like ANSYS and COMSOL Multiphysics to predict and optimize material properties and cell performance. In addition to electrochemical and structural analysis, the team addresses safety concerns, including thermal runaway, by employing IR imaging, nail penetration tests, and stress failure analysis to understand battery stability under extreme conditions.
Finally, we are actively engaged in the sustainability aspect of battery technologies, focusing on recycling critical materials and repurposing used batteries to reduce environmental impact. This holistic approach ensures that our battery systems are not only high-performance but also environmentally friendly and ready for the demands of the green energy transition.
