Multiscale modeling approaches have become indispensable for understanding the complex behaviors of conversion-type battery materials, particularly metal fluorides and sulfur cathodes. These materials undergo drastic structural and chemical changes during cycling, presenting challenges that span multiple length and time scales. The inherent complexity arises from coupled phenomena including reaction front propagation, phase transformations, and mechanical degradation, all of which influence battery performance and longevity.

At the atomic scale, quantum chemistry calculations, particularly density functional theory (DFT), provide critical insights into the electronic structure and thermodynamic stability of conversion materials. For iron fluoride (FeF3), DFT reveals the thermodynamic driving forces behind the conversion reaction to form iron metal and lithium fluoride (LiF). The calculations predict voltage profiles and identify intermediate phases that form during lithiation. However, DFT alone cannot capture the mesoscale phase separation and mechanical stresses that develop during cycling.

Phase-field models bridge this gap by simulating the evolution of reaction fronts and phase boundaries. These models treat interfaces as diffuse regions where phases coexist, governed by thermodynamic free energy landscapes and kinetic parameters. For metal fluorides, phase-field simulations show how lithium insertion initiates a conversion reaction that propagates as a front through the particle. The reaction front velocity depends on lithium diffusivity and the energy barrier for phase transformation. In sulfur cathodes, phase-field models capture the precipitation and dissolution of lithium polysulfides, accounting for the complex interplay between electrochemical reactions and transport limitations.

The coupling between quantum chemistry and phase-field models is achieved through parameter passing. DFT-derived free energies, activation barriers, and elastic constants serve as inputs for phase-field simulations. For example, DFT calculations of the FeF3/LiF interface energy directly inform the phase-field model's gradient energy coefficient. This multiscale approach accurately predicts the mosaic-like phase separation observed in metal fluoride cathodes, where nanoscale domains of Fe and LiF form during discharge.

Mechanical effects are critical in conversion materials due to large volume changes. Phase-field models incorporate elasticity theory to simulate stress evolution and fracture. In copper fluoride (CuF2), simulations reveal that the conversion reaction generates compressive stresses exceeding 2 GPa, leading to particle cracking. The models show that smaller particle sizes mitigate cracking by reducing diffusion-induced stress gradients. Experimental observations using in-situ transmission electron microscopy confirm these predictions, showing that particles below 50 nm exhibit improved mechanical stability.

Reaction heterogeneity is another key challenge addressed by multiscale modeling. In sulfur cathodes, the precipitation of solid Li2S occurs non-uniformly due to localized electron and ion transport limitations. Phase-field models coupled with electrochemical kinetics reproduce the observed dendritic Li2S growth patterns. The simulations identify critical parameters such as the electrolyte diffusivity and nucleation barrier that control precipitation morphology. Experimental validation comes from operando X-ray tomography, which visualizes the spatial distribution of Li2S during discharge.

At the macroscale, continuum models integrate the insights from smaller scales to predict cell-level performance. These models account for electrode porosity, tortuosity, and composite electrode architecture. For metal fluoride cathodes, the continuum models incorporate the phase-field-derived reaction rates and stress-dependent degradation mechanisms. The results show how electrode fabrication parameters, such as binder content and conductive additive distribution, influence capacity fade over cycling.

Experimental techniques provide essential validation across scales. In-situ X-ray diffraction tracks phase evolution in metal fluorides, confirming the sequence of intermediate phases predicted by DFT. Atomic force microscopy measures the mechanical properties of individual particles, validating the stress predictions of phase-field models. Electrochemical impedance spectroscopy provides data for refining the transport parameters in continuum models.

Recent advances in machine learning accelerate multiscale modeling by replacing expensive quantum calculations with surrogate models. Neural networks trained on DFT datasets predict material properties with near-DFT accuracy but at much lower computational cost. This enables high-throughput screening of conversion materials and optimization of phase-field parameters.

The multiscale approach has led to specific design guidelines for conversion materials. For metal fluorides, models suggest that nanocomposites with conductive matrices improve electronic conductivity while mitigating mechanical degradation. In sulfur cathodes, the simulations highlight the importance of pore structure and catalyst distribution for controlling polysulfide precipitation. These insights guide experimental synthesis efforts, resulting in materials with higher capacity retention and improved rate capability.

Challenges remain in fully integrating the scales, particularly in capturing the dynamic evolution of interfaces under operating conditions. Future developments will likely focus on tighter coupling between models, incorporating real-time experimental feedback for adaptive simulation parameters. The ultimate goal is a predictive framework that accelerates the development of high-performance conversion materials through targeted design rather than empirical optimization.

The success of multiscale modeling for conversion materials demonstrates its potential for other complex battery systems. By linking fundamental atomic-scale properties to macroscopic performance, these approaches provide a powerful tool for understanding and engineering next-generation battery materials. The continued refinement of these models, supported by advanced characterization techniques, will be crucial for overcoming the limitations of current conversion-type electrodes.