Engineers at North Carolina State University have unveiled a new classical physics model designed to significantly advance research into energy storage technologies. The Chen-Huang Nonequilibrium Phasex Transformation (NExT) Model, developed by former Ph.D. student Hongjiang Chen and Associate Professor Hsiao-Ying Shadow Huang, addresses the complex dynamic nonequilibrium processes that occur within energy storage materials during charging and discharging. This breakthrough, detailed in The Journal of Physical Chemistry C, is crucial for optimizing battery performance and extending lifespan, particularly in high-demand applications like electric vehicles and grid integration.

Nonequilibrium processes are fundamental to how lithium-ion batteries operate, even during slow charging. Unlike a battery at rest, which approaches equilibrium with uniform ion distribution and stable temperatures, a battery under charge or discharge experiences significant deviations. Rapid operation intensifies these deviations, causing uneven ion concentrations, substantial heat generation with localized hot spots, and electrochemical imbalances that demand high overpotentials. Furthermore, the swift movement of lithium ions induces physical expansion and contraction, creating internal stress and micro-cracks that accelerate material degradation. Understanding and managing these processes are paramount for developing faster, safer charging protocols, effective thermal management systems, and new electrode materials capable of withstanding dynamic conditions.

Existing classical physical models for lithium-ion batteries often fall short in predictive accuracy due to simplified assumptions, the omission of complex phenomena like mass transport, and an incomplete understanding of underlying processes. Many commercial simulation tools, for instance, are limited to modeling equilibrium conditions. The NExT Model fills this void by providing the essential mathematical foundations and conceptual frameworks necessary for advanced computational modeling and machine learning applications in materials science.

The NExT Model proposes a novel mechanism to explain how battery materials such as lithium iron phosphate (LFP) and lithium nickel manganese cobalt oxides (NMC) undergo phase transitions under nonequilibrium conditions. It introduces “path factors” that influence energy changes within the material, interacting with properties like lithium content, mechanical strain, structural defects (dislocations), and material order. Simulations demonstrate that dislocation density, which increases with faster electrochemical reactions, plays a critical role in driving these internal structural shifts. The model’s validation against experimental data for both LFP and NMC materials across various charge/discharge rates confirms its accuracy and utility.

While the NExT Model is broadly applicable to various nonequilibrium processes, its initial focus on electrodes and lithium-ion batteries was driven by the extensive availability of experimental data for these widely studied systems. This abundance of empirical evidence allowed the researchers to rigorously validate their theoretical constructs, ensuring the model’s formulations accurately reflect real physical processes. The ability to incorporate this model into computational tools promises to significantly enhance the engineering of more efficient and durable batteries, marking a critical step forward for the energy storage industry.