Rheology, dispersion and stability, calibrated on industrial data.
The slurry module covers coarse-grained molecular dynamics, DEM, CFD-DEM and machine-learning surrogates. It predicts viscosity evolution, particle distribution, binder stability and ink quality across formulations, mixing protocols and batch sizes.
Particle-resolved physics, calibrated on your formulation.
The slurry step is primarily addressed through Coarse-Grained Molecular Dynamics (CGMD), run in LAMMPS, which resolves particle–particle and particle–solvent interactions via calibrated force fields. The output is a true 3D microstructure of the wet film and physically meaningful rheological curves, not regressions on viscosity data.
High-solid-content formulations and dry mixing processes call for the Discrete Element Method (DEM) instead. DEM captures frictional contacts and realistic particle geometries derived from nano-CT imaging. CFD-DEM coupling resolves the fluid phase explicitly for dispersion studies.
One slurry, three levels of resolution.
CGMD in LAMMPS
Coarse-grained molecular dynamics with calibrated force fields. Predicts 3D microstructure organization and rheological behavior such as viscosity curves. The workhorse for industrial formulations.
DEM & CFD-DEM
Discrete Element Method for high-solid and dry mixing, with realistic particle shapes from nano-CT imaging. CFD-DEM coupling resolves the fluid phase explicitly for slurry flow and dispersion.
AI surrogates
Deep-learning autoencoders (VAE), Gaussian Naive Bayes classifiers for homogeneity, PCA/SVM pipelines for film quality, and functional data-driven frameworks that accelerate ongoing MD simulations by an order of magnitude.
From formulation space to electrode KPIs.
Bayesian optimization layered on top of regression models trained on physics-based synthetic data enables multi-objective optimization of ink composition against downstream electrode performance targets (viscosity, dispersion quality, eventual porosity and tortuosity after coating and calendering).
The result is a screening loop where formulation candidates get pre-filtered in silico before any mixer is started. Engineers see the trade-offs between rheology, stability and downstream electrochemistry on the same chart.
What formulation teams ask.
Move formulation screening upstream of the mixer.
Share a target chemistry and a few calibration data points. We'll return a slurry simulation plan and a Bayesian optimization scope within a week.