Molecular dynamics simulations have become an indispensable tool for understanding dendrite formation in alkali metal anodes at atomic resolution. These simulations capture the nucleation, growth kinetics, and morphological evolution of dendrites by solving Newton's equations of motion for ensembles of atoms interacting through empirically derived potentials. The temporal resolution spans picoseconds to nanoseconds, while spatial resolution reaches sub-nanometer scales, providing insights inaccessible to experimental techniques alone.

The nucleation phase in metal plating begins with stochastic clustering of lithium or sodium ions at surface defect sites. Simulations show nucleation barriers between 0.2-0.5 eV for lithium on pristine surfaces, decreasing to 0.1-0.3 eV at grain boundaries or vacancies. The critical nucleus size typically ranges from 20-50 atoms at room temperature, with smaller critical sizes observed under higher overpotentials. Nucleation rates follow Arrhenius behavior with pre-exponential factors on the order of 10^12-10^14 s^-1 cm^-2 for lithium systems.

Dendrite growth kinetics exhibit three distinct regimes in MD simulations. Initial surface diffusion-limited growth follows a t^1/2 time dependence, transitioning to interface reaction-limited growth with linear time dependence, and finally to diffusion-limited aggregation at larger scales showing fractal dimensionality between 1.7-2.3. Growth velocities range from 0.5-5 m/s along preferred crystallographic directions under typical battery operating conditions. The anisotropy arises from differences in surface energies, with lithium favoring (110) and (200) growth planes while sodium prefers (110) and (211) orientations.

The solid electrolyte interphase plays a crucial role in dendrite morphology evolution. Heterogeneous SEI composition creates localized variations in ionic conductivity spanning 10^-8 to 10^-5 S/cm, leading to preferential plating at low-resistance regions. MD simulations reveal that inorganic components like Li2O and LiF provide better dendrite suppression than organic components due to higher mechanical modulus and more homogeneous Li+ transport. SEI thickness fluctuations exceeding 20% of the mean value consistently correlate with dendrite initiation sites in simulations.

Mechanical stress development during plating shows complex spatial distributions. Compressive stresses up to 100 MPa develop at dendrite tips due to volumetric expansion, while tensile stresses up to 50 MPa form in adjacent regions. Stress gradients exceeding 10 MPa/μm induce plastic deformation in lithium metal at room temperature, with dislocations nucleating at stress concentrations near grain boundaries. Sodium systems show similar behavior but with approximately 30% lower stress magnitudes due to softer mechanical properties.

Electric field distributions exhibit strong localization effects during plating. Field enhancement factors of 5-20x occur at dendrite tips, creating positive feedback loops for ion deposition. The field heterogeneity depends on SEI dielectric properties, with relative permittivity variations between 2-50 causing local field distortions. Simulations demonstrate that field homogeneity improves when the SEI's dielectric constant exceeds 10, reducing dendrite formation probability by 40-60%.

Force field selection critically impacts simulation accuracy. For lithium systems, the embedded atom method potential reproduces experimental elastic constants within 5% and surface energies within 10%. ReaxFF potentials better capture SEI formation chemistry but require 3-5x greater computational resources. Sodium simulations often employ modified Johnson potentials that accurately reproduce the bcc-to-hcp phase transition at 36 K. Comparison of force fields shows variations up to 15% in predicted growth velocities and 20% in nucleation barriers.

Crystallographic growth direction predictions vary significantly between potentials. EAM potentials predict lithium growth along <110> directions with 70% probability, while ReaxFF shows more isotropic growth. Sodium simulations consistently show <211> preference across multiple potentials, matching experimental observations. The discrepancies highlight the importance of potential parameterization against quantum mechanical calculations of surface energies and diffusion barriers.

Simulation results show strong correlation with experimental SEM/TEM observations. MD-predicted dendrite tip radii of 10-50 nm match TEM measurements within 20%. The fractal dimension of simulated dendrites (1.72 ± 0.15) agrees with SEM image analysis (1.68 ± 0.12). Cross-sectional comparisons reveal that simulations capture the transition from mossy to needle-like morphology at current densities above 1 mA/cm^2, consistent with experimental findings.

The temporal evolution of dendrite aspect ratios in simulations follows the same three-stage pattern observed experimentally: initial slow increase (1-10 ns), rapid linear growth (10-100 ns), and saturation (>100 ns). The critical aspect ratio for short-circuit conditions ranges from 50-100 in both simulations and experimental cells, depending on separator mechanical properties.

Comparative analysis of lithium versus sodium systems reveals key differences. Sodium exhibits lower surface diffusion coefficients (10^-9 vs 10^-8 cm^2/s for Li) but higher bulk diffusivity (10^-7 vs 10^-8 cm^2/s). This leads to more compact dendrite morphologies in sodium, with 30-40% lower porosity than lithium dendrites at equivalent deposition conditions. The mechanical modulus difference (7.5 GPa for Na vs 4.5 GPa for Li) contributes to sodium's reduced stress concentrations during plating.

Recent advances in reactive force fields enable simulation of SEI formation concurrent with metal deposition. These simulations show that carbonate electrolytes decompose within 0.5-1 ns at dendrite tips, forming nanometer-scale SEI layers. The decomposition products distribution matches XPS depth profiles within 15% accuracy, validating the simulation approach.

The integration of MD simulations with continuum models has produced multiscale frameworks that extend the spatial and temporal ranges accessible to pure MD. These hybrid approaches maintain atomic resolution at critical interfaces while efficiently modeling larger system scales. Validation against operando X-ray tomography shows the hybrid models capture dendrite penetration through separators with 85% accuracy in predicted failure times.

Future developments in MD methodology will focus on improving potential accuracy for mixed interfaces, incorporating explicit electron transfer reactions, and extending timescales through advanced sampling techniques. The continued refinement of simulation approaches promises to provide fundamental insights that will guide the design of dendrite-suppressing strategies for next-generation metal anode batteries.