Modeling Lithium Dendrites in Batteries

ISEF Category: Materials Science

Subcategory: Computation and Theory  ·  Difficulty: Advanced  ·  Setup: University Lab  ·  Time: Full Year

The Hook

Lithium-metal batteries can store a lot of energy, but they can also grow sharp metal branches called dendrites. Those tiny spikes can short-circuit a cell. If you can model when and why they form, you can compare charging strategies before anyone builds the battery. That makes this a strong project for simulation, design, and prediction.

What Is It?

Phase-field modeling is a way to simulate how structures grow and change without drawing every tiny edge by hand. Think of it like a weather map for a material. Instead of tracking one perfect line between solid lithium and electrolyte, the model uses a smooth field that changes across space. That makes it easier to study messy shapes like dendrites, which are the branching metal structures that can grow during battery charging.

MOOSE is a software framework that helps researchers build these kinds of simulations. In this project, you would compare two charging styles, pulsed current and direct current, or DC. Pulsed current turns the flow on and off in a pattern. DC keeps it steady. You can test whether one style encourages smoother lithium plating and whether the other lets dendrites spread faster. Your main job is not to build a battery. Your job is to build a model that predicts shape changes under different conditions.

Why This Is a Good Topic

This is a strong science fair topic because you can change one input, run the simulation again, and measure how the morphology changes. You do not need a wet lab to ask a real research question. The project connects to battery safety, electric vehicle design, and energy storage. You can also learn how computational models, boundary conditions, and comparison plots work in real materials research.

Research Questions

• How does pulsed current change dendrite length compared with DC plating?
• What is the effect of pulse duty cycle on dendrite branching density?
• Does higher current density increase the predicted dendrite tip growth rate?
• To what extent does surface roughness change the first site where dendrites form?
• Which plating regime produces the most uniform lithium deposit in the model?
• How does electrolyte diffusivity affect dendrite shape under pulsed-current conditions?
• To what extent do model assumptions change the predicted safety risk between charging regimes?

Basic Materials

• Computer with enough memory to run simulation software.
• MOOSE framework installed and configured.
• Linux operating system or a virtual machine that can run Linux.
• Text editor or code editor such as VS Code.
• Python for plotting and data handling.
• Spreadsheet software for organizing simulation outputs.
• Git for version control and file tracking.
• A notebook for recording model settings, parameter choices, and run outcomes.

Advanced Materials

• Workstation or university cluster access for longer simulations.
• MOOSE source code and example applications for phase-field modeling.
• Mesh generation tool such as Gmsh.
• Python scientific stack for analysis and plotting.
• ImageJ for measuring morphology in saved simulation images.
• Paraview for visualizing field evolution in space and time.
• Git and a shared repository for reproducible model development.
• Access to battery materials literature for parameter selection and validation.

Software & Tools

• MOOSE: Runs phase-field simulations and lets you compare dendrite growth under different plating regimes.
• Python: Processes output data, makes plots, and supports statistical comparisons.
• ParaView: Visualizes how lithium morphology evolves across the simulation domain.
• Gmsh: Builds and edits computational meshes for the model geometry.
• ImageJ: Measures branch length, area, and shape descriptors from saved simulation images.

Experiment Steps

1. Define one morphology metric you will compare, such as branch length, branching density, or surface roughness.
2. Choose the smallest model geometry that still captures dendrite growth and plating instability.
3. Set up a baseline DC case, then keep every other parameter fixed while you build the pulsed-current case.
4. Plan the output data you need so you can convert simulation frames into numbers, not just pictures.
5. Design controls that separate charging regime effects from mesh, timestep, and parameter choices.
6. Organize a comparison plan that includes plots, summary statistics, and a clear rule for saying one regime is more stable.

Common Pitfalls

• Changing the mesh between runs, which makes morphology differences hard to trust.
• Comparing pulsed current and DC without keeping the total charge input consistent.
• Reading too much into one simulation frame instead of tracking growth over the full run.
• Using parameter values with no literature support, which weakens the model’s connection to real batteries.
• Forgetting to test mesh or timestep sensitivity, which can make dendrite tips look like numerical artifacts.

What Makes This Competitive

A competitive version of this project goes beyond a visual comparison of two line plots. You would test whether the trend survives sensitivity checks, mesh refinement, and multiple parameter sets. Strong work also connects the simulation outputs to a meaningful morphology metric, such as tip curvature, branching frequency, or deposit uniformity. If you compare regime performance across a small parameter map instead of one case, your analysis starts to look like real research.

Project Variations

• Compare dendrite growth under different pulse frequencies while keeping the average current fixed.
• Test how electrolyte diffusivity changes the morphology difference between pulsed-current and DC plating.
• Add surface roughness to the initial electrode boundary and measure how it shifts the first dendrite hotspot.

Learn More

• MOOSE Documentation: Search the official MOOSE site for phase-field examples, solver setup, and model documentation.
• MOOSE Examples Repository: Look for battery and phase-field tutorial problems in the public examples that ship with MOOSE.
• Computational Materials Science: Search this journal for review articles on phase-field modeling of battery degradation.
• Journal of The Electrochemical Society: Search for papers on lithium plating, dendrite formation, and pulse charging effects.
• NIST Battery Materials Data: Search NIST resources for materials property data and measurement references that can support parameter choices.
• MIT OpenCourseWare: Search for courses on computational materials science, numerical methods, and battery engineering.