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Explore how materials and microstructures impact battery performance, safety, and durability through advanced modeling techniques for more efficient energy storage systems.
Explore density functional theory applications in electrochemical systems through advanced computational modeling techniques and stochastic interaction approaches.
Explore stochastic phenomena in electrochemical systems from an experimental perspective, bridging atomistic to continuum scales in this UCLA research presentation.
Explore the SPIDER framework for inferring interpretable continuum models through physically-informed machine learning, with applications to fluid turbulence and molecular gas systems.
Explore advanced techniques for bridging scales in materials modeling using atomistic simulations, information theory, and generative models in electrochemical systems.
Discover the Distributional Koopman Operator for analyzing random dynamical systems using probability distributions instead of particle tracking in electrochemical modeling.
Explore advanced electrochemical reaction rate modeling beyond Butler-Volmer, featuring MHC variants and Julia-based software for multidimensional phase mapping at extreme conditions.
Discover algorithmic differentiation techniques for plane-wave density-functional theory, combining AD and DFPT for material inverse design and uncertainty propagation.
Explore a groundbreaking quantum theory unifying electrochemical kinetics through coupled ion-electron transfer, bridging quantum chemistry with battery and electrocatalysis applications.
Discover energy-stable ML models for non-Newtonian fluid dynamics that preserve physical constraints while bridging molecular and continuum scales through variational structures.
Discover finite volume methods for continuum-scale electrolyte simulations in electrochemical systems, bridging atomistic and continuum modeling approaches.
Explore hybrid density-potential functional theory for bridging atomistic to continuum scales in electrochemical systems, addressing electronic orbital challenges.
Explore continuum thermodynamic models for electrochemical interfaces, covering space charge layers, surface adsorption, charge transfer reactions, and scale bridging approaches.
Discover weak form Scientific Machine Learning techniques for creating interpretable mathematical models across different scales from data without forward-solve discretizations.
Explore advanced phase field modeling for lithium battery dendrite formation, dead lithium mechanisms, and thermal gradient effects on electrochemical microstructure evolution.
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