Electrochemical modeling of interfaces in all-solid-state batteries provides critical insights into the complex interactions between solid electrodes and solid electrolytes. These models address fundamental challenges in battery design by simulating the coupled chemical and mechanical phenomena at interfaces, predicting stability under operational conditions, and elucidating the formation of space-charge layers. The accuracy of these models directly influences material selection, enabling the development of high-performance, durable solid-state batteries.

The interface between a solid electrolyte and electrode is a critical determinant of battery performance. Unlike liquid electrolytes, solid electrolytes exhibit rigid mechanical properties that introduce unique challenges. Chemo-mechanical coupling arises due to the interplay between electrochemical reactions and mechanical stresses at the interface. During cycling, lithium insertion and extraction cause volume changes in the electrode, generating stresses that can lead to delamination or crack propagation. Electrochemical models incorporate strain-dependent reaction kinetics to predict how mechanical deformation alters ionic transport and charge transfer. For example, density functional theory calculations coupled with continuum mechanics reveal that certain sulfide-based solid electrolytes exhibit favorable elastic properties to accommodate volume changes in high-capacity electrodes like silicon. Models also identify optimal interfacial coatings that mitigate stress concentrations while maintaining high ionic conductivity.

Interfacial stability is another key consideration addressed by electrochemical modeling. The thermodynamic stability window of a solid electrolyte must align with the electrochemical potentials of the electrodes to prevent parasitic reactions. First-principles calculations based on phase diagrams predict decomposition products that form at the interface. For instance, oxide electrolytes such as LLZO may react with high-voltage cathodes, leading to the formation of resistive interphases. Models quantify the driving forces for these reactions by computing the Gibbs free energy of possible decomposition pathways. This information guides the selection of compatible electrode-electrolyte pairs or the design of artificial interlayers that kinetically suppress undesirable reactions. Additionally, models assess the long-term evolution of interfaces under cycling by simulating the diffusion of elements across the interface and the growth of interphases over time.

Space-charge layer effects dominate interfacial behavior in all-solid-state batteries due to the absence of liquid electrolytes to screen charge imbalances. When a solid electrolyte contacts an electrode, the difference in electrochemical potentials induces charge redistribution, creating a space-charge layer with altered ionic concentrations. Poisson-Nernst-Planck models solve the coupled transport and electrostatic equations to predict the thickness and potential drop across this layer. The results show that space-charge layers can significantly increase interfacial resistance, particularly for electrolytes with low dielectric constants. For example, thiophosphate electrolytes exhibit pronounced space-charge effects due to their limited charge screening capability. Models suggest strategies such as doping or interfacial engineering to mitigate these effects by aligning the chemical potentials of the electrolyte and electrode.

Material selection for solid electrolytes and electrodes relies heavily on insights from electrochemical modeling. Key parameters include ionic conductivity, electronic conductivity, and mechanical properties. Models screen candidate materials by simulating their performance under realistic operating conditions. For electrolytes, the primary criterion is high ionic conductivity with negligible electronic conductivity to prevent self-discharge. Molecular dynamics simulations predict ionic transport mechanisms, revealing that certain crystalline structures like argyrodites facilitate fast lithium diffusion through interconnected pathways. For electrodes, models evaluate capacity, volume expansion, and compatibility with the electrolyte. Phase-field models simulate lithium plating and stripping at the anode, identifying materials that resist dendrite formation. Sulfide electrolytes, for instance, exhibit favorable interfacial properties with lithium metal due to their inherent ductility and ability to form stable interfaces.

The impact of temperature on interfacial behavior is another critical aspect captured by electrochemical models. Temperature variations alter ionic transport, reaction kinetics, and mechanical properties. Arrhenius-type equations incorporated into models quantify how conductivity changes with temperature, highlighting materials that maintain performance across a wide range. For example, certain halide-based solid electrolytes demonstrate superior low-temperature performance compared to oxides due to their lower activation energies for ion hopping. Models also predict thermal runaway scenarios by simulating heat generation at interfaces during high-rate cycling, guiding the selection of thermally stable materials.

Electrochemical modeling extends to the study of heterogeneous interfaces, where multiple phases coexist. Composite electrodes containing active materials, conductive additives, and solid electrolytes present complex interfacial networks. Effective medium theory and percolation models analyze how the spatial distribution of phases influences overall performance. These models reveal that optimizing the volume fraction and connectivity of each phase enhances ionic and electronic transport while minimizing interfacial resistances. For instance, a well-dispersed conductive additive in a cathode composite reduces the tortuosity of ion transport paths, improving rate capability.

Validation of electrochemical models is essential to ensure their predictive accuracy. Experimental techniques such as impedance spectroscopy and X-ray photoelectron spectroscopy provide data to refine model parameters. The iterative process of model validation and refinement enhances the reliability of predictions, enabling more confident material selection. For example, impedance data can be used to calibrate the interfacial resistance terms in a model, ensuring that it accurately reflects real-world behavior.

In summary, electrochemical modeling serves as a powerful tool for understanding and optimizing interfaces in all-solid-state batteries. By addressing chemo-mechanical coupling, interfacial stability, and space-charge layer effects, these models provide actionable insights for material selection and interface design. The integration of multi-scale simulations with experimental validation accelerates the development of robust solid-state battery systems, paving the way for next-generation energy storage solutions.