Solid-state batteries represent a significant advancement in energy storage technology, offering higher energy density and improved safety compared to traditional lithium-ion batteries. However, their degradation mechanisms are distinct and require specialized physics-based models to accurately predict performance over time. Key failure modes in solid-state batteries include interfacial delamination, dendrite growth, and chemo-mechanical stress, each influenced by material properties and operational conditions. Understanding these phenomena through modeling is critical for optimizing battery design and longevity.

Interfacial delamination occurs when mechanical stresses cause separation between the solid electrolyte and electrode layers. This failure mode is exacerbated by repeated cycling, as volumetric changes in electrodes induce strain at the interfaces. Physics-based models for delamination incorporate parameters such as interfacial adhesion energy, elastic moduli of materials, and cycling-induced strain. These models often use cohesive zone formulations to simulate crack initiation and propagation. Compared to liquid electrolyte systems, where interfacial stability is less critical due to self-healing mechanisms, solid-state batteries rely on perfect interfacial contact for ion transport. Experimental validation of these models involves techniques like in-situ scanning electron microscopy to observe delamination in real-time or acoustic emission testing to detect microcracks.

Dendrite growth in solid-state batteries differs fundamentally from liquid systems. In traditional lithium-ion batteries, dendrites form due to uneven lithium plating and electrolyte decomposition. In solid-state systems, dendrites propagate through grain boundaries or defects in the electrolyte, often driven by localized mechanical failure. Physics-based models for dendrite growth incorporate stress-coupled electrochemical equations, accounting for the interplay between lithium ion flux and mechanical deformation. The stiffness of the solid electrolyte plays a crucial role; harder electrolytes may resist dendrite penetration but are prone to brittle fracture, while softer materials may allow dendrite propagation under lower stresses. In-situ X-ray tomography and impedance spectroscopy are used to validate these models, providing insights into dendrite morphology and growth kinetics.

Chemo-mechanical stress arises from the mismatch in volumetric expansion between electrodes and the solid electrolyte during lithiation and delithiation. This stress can lead to fracture, contact loss, or accelerated degradation. Models for chemo-mechanical stress often employ coupled diffusion-mechanics frameworks, solving for lithium concentration and stress fields simultaneously. Key parameters include the electrode's expansion coefficients, electrolyte stiffness, and electrode porosity. Porous electrodes, for instance, can mitigate stress by accommodating volume changes, but excessive porosity may reduce energy density. Nanoindentation and strain mapping via digital image correlation are experimental methods used to validate these models, providing direct measurements of stress evolution.

Material properties are central to parameterizing degradation models for solid-state batteries. The elastic modulus of the solid electrolyte influences both dendrite growth and interfacial stability. For example, sulfide-based electrolytes, which are relatively soft, may exhibit different degradation behaviors compared to oxide-based electrolytes with higher stiffness. Electrode porosity also plays a dual role: while it alleviates stress, it may increase interfacial resistance if not optimized. Models must account for these trade-offs by integrating material-specific data from characterization techniques like nanoindentation, X-ray diffraction for strain analysis, or electrochemical impedance spectroscopy for interfacial resistance measurements.

Traditional lithium-ion battery degradation models focus on mechanisms like solid electrolyte interphase growth, lithium plating, and particle cracking. These models often neglect mechanical stress or treat it as a secondary effect due to the liquid electrolyte's ability to accommodate volume changes. In contrast, solid-state battery models must explicitly couple electrochemical and mechanical phenomena, as stress directly impacts ion transport and interfacial stability. For instance, while lithium-ion models may use empirical aging equations, solid-state models require finite element approaches to resolve stress distributions accurately.

Experimental validation of solid-state battery degradation models is challenging but essential. In-situ microscopy techniques, such as transmission electron microscopy, enable direct observation of interfacial degradation and dendrite formation. Impedance spectroscopy provides insights into interfacial resistance changes, correlating with model predictions of contact loss. Accelerated aging tests under controlled mechanical and thermal conditions help validate chemo-mechanical models, though care must be taken to avoid introducing unrealistic failure modes.

The development of physics-based degradation models for solid-state batteries is still evolving, with ongoing research addressing gaps in understanding material behavior at interfaces and under dynamic loads. Future models may incorporate machine learning to refine parameter estimation or multi-scale approaches to bridge atomistic defects with macroscopic performance. By advancing these models, researchers can accelerate the commercialization of solid-state batteries, ensuring reliability and performance across diverse applications.

In summary, physics-based degradation models for solid-state batteries must address unique failure modes like interfacial delamination, dendrite growth, and chemo-mechanical stress, which are less critical in liquid electrolyte systems. These models rely heavily on material properties such as electrolyte stiffness and electrode porosity, requiring sophisticated experimental techniques for validation. As the field progresses, integrating multi-physics simulations with high-fidelity experimental data will be key to unlocking the full potential of solid-state battery technology.