Engineers are increasingly leveraging computational tools to advance energy storage technologies, which are crucial for integrating sustainable energy sources and powering electric vehicles. A significant development in this area is the creation of a new classical physics model designed to understand dynamic nonequilibrium processes. These processes critically influence the chemical, mechanical, and physical balance of materials during a battery's charge and discharge cycles.
The Chen-Huang Nonequilibrium Phasex Transformation (NExT) Model, developed by Hongjiang Chen and his advisor Hsiao-Ying Shadow Huang at NC State, was detailed in The Journal of Physical Chemistry C on July 10, 2025. This model aims to deepen our comprehension of battery behavior, particularly under rapid charging and discharging conditions. While batteries in a resting state tend towards equilibrium with no current flow and uniform ion concentration, even slow charging and discharging occur under nonequilibrium conditions. Rapid cycling, however, causes substantial deviations from equilibrium, leading to physical and chemical changes that can impact performance and longevity.
During rapid charging, uneven ion distribution and significant heat generation create internal temperature gradients. These gradients result in varied reaction rates, further destabilizing the battery system. The battery also operates at voltages far from ideal, necessitating large overpotentials that push it further from equilibrium. The swift movement of ions can cause materials to expand and contract at rates exceeding their mechanical adjustment capabilities, leading to internal stress. This mechanical strain can manifest as cracks in electrode materials, accelerating wear. For instance, in materials like LiFePO4, these conditions can force structural changes to occur rapidly rather than through stable thermodynamic processes.
Understanding these nonequilibrium processes is vital for developing faster charging protocols that balance speed with safety and longevity. It is also essential for creating effective thermal management systems and designing electrode materials that can better withstand these dynamic conditions. Existing models often struggle with predictive accuracy due to simplified assumptions and the omission of complex phenomena like mass transport. The NExT Model addresses this by explaining how materials such as LiFePO4 and NMC undergo phase transitions under nonequilibrium conditions, introducing 'path factors' that influence energy changes during ion insertion and removal. Simulations indicate that dislocation density plays a critical role in driving structural changes during faster electrochemical reactions.
The model's validity was confirmed by comparing its simulation results with experimental data for LFP and NMC materials across various charge/discharge rates. The strong agreement supports the model's pathway-altering mechanism as a valuable tool for understanding and potentially improving battery performance. This model can be integrated into computational tools to engineer more efficient batteries. While currently focused on lithium-ion batteries, the fundamental principles of the NExT Model are broadly applicable to other energy storage systems, including multivalent batteries, where nonequilibrium effects are often more pronounced. This advancement contributes to computational materials science by providing a predictive tool for rate-dependent processes, supporting the rational design of next-generation energy storage materials and devices and accelerating discovery through physics-informed modeling grounded in experimental validation.