Battery materials simulation: from material properties to cell performance | Ionworks

Electrolyte, anode, and cathode developers are asked the same question by every cell maker: what does this do in our cell? Ionworks Studio turns your material data into physics-based cell models, so you can answer it with a simulation before anyone builds a prototype.
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Coin cells are designed to screen materials, and they do that well. But the conditions that make them good screens also hide the constraints a commercial cell runs into: limited lithium inventory, lean electrolyte, thick electrodes, and long transport paths.
A material that looks strong at the electrode level can deliver less at the cell level than the incumbent it was meant to replace. Cell makers know this, which is why half-cell capacity alone rarely moves a qualification forward.
Read more on material properties vs cell metrics
Take the loading row from the table. In a 21700 at fixed can volume, the sweep re-derives electrode width from the winding geometry at each loading, so a thicker coating trades separator and foil for active material. At 0.5C and 1C that trade keeps paying: capacity rises across the whole range.
At higher rates it stops. The 2C capacity peaks near 4.9 mAh/cm², and the 3C capacity near 3.9 mAh/cm². Past that, lithium ions can’t cross the thick electrode fast enough, the electrolyte depletes deep in the coating, and capacity falls away.
For an electrolyte developer, that peak is the number to move. Rerun the sweep with your own conductivity and transference number and see how far it shifts, before a single pouch cell is built.
Measured properties or the output of your own property models: ionic conductivity, diffusivity, transference number, open-circuit potential, particle size. Coin-cell and half-cell tests fill in what property data alone cannot.
Fit a DFN or SPMe model against your test data, with every parameter traced back to the measurement it came from. When a new batch or formulation is tested, the model is refit against it.
Place the parameterized material in a target design, from a 21700 jellyroll to a large-format pouch, at realistic loading and N/P ratio. Run the protocols a cell maker cares about: fast charge, rate capability, drive cycles.
Hand a partner’s engineering team the parameterized cell model in an open-source format that runs in PyBaMM. They can run it in their own tools and test your material in their own design space before they build anything.
At Anthro Energy, we develop novel polymer electrolyte materials and the models that predict their properties, from ion transport to mechanical and electrochemical behavior. Translating those material-level insights into confident predictions of how a full cell will perform is a different challenge, and that’s where Ionworks has been an exceptional partner.
Their team helped us build modeling and simulation workflows that take our material property predictions and show how they play out at the cell level. That has meaningfully sped up how quickly we can evaluate and integrate our new electrolytes into existing lithium-ion cell designs.
Ionworks brings deep expertise, responsiveness, and a genuinely collaborative approach, and they’ve become an important part of how we move from materials innovation to real-world cell performance.
We are working with Sila Nanotechnologies on the same workflow for silicon-carbon anodes: screening blend ratios, projecting swelling, and transferring fast-charge protocols across chemistries.
Bring property data or a set of coin-cell tests. We will walk through building a cell-level model from them and running it in the format your partners use.
The battery data and simulation layer.
Built by the creators of PyBaMM
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