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This guide will walk you through the essential steps to get up and running with Ionworks Studio. We’ll create a new project, a cell, a parameterized model, a study, and run a basic simulation.

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Step-by-Step Guide

Every organization starts with a Project named “Default”, so you have somewhere to work straight away.
  1. Navigate to the Projects page from the main menu.
  2. Click the auto-created “Default” project to open it. (You can create your own later with New Project, top-right.)
Now, let’s define the cell you want to work with. A Cell Specification is the blueprint for your cell.
  1. Navigate to the Cells page.
  2. Click “New Cell”.
  3. Fill in the properties, e.g.:
    • Name: A descriptive name, e.g., “My First NMC Cell”.
    • Chemistry: e.g., “NMC/Graphite”.
    • Nominal Capacity: e.g., 5 Ah.
    • Voltage Limits: e.g., 2.5 V (lower) and 4.2 V (upper).
  4. Click “Create” to save it.
Next, we need a Parameterized Model to describe the cell’s electrochemical behavior. A parameterized model combines a Model (the mathematical framework) with a specific set of parameters.
  1. Navigate to the Parameterized Models page.
  2. Click “New Parameterized Model”.
  3. In the creation wizard, select the Cell Specification you just created.
  4. Select a Model to use — for this quickstart, a built-in system model is the quickest start.
  5. Choose a starting set of parameters (a built-in parameter set is a good starting point).
  6. Review the parameter validation results for any warnings or errors.
  7. Give your parameterized model a name and click “Create” to finalize it.
A Study lives inside a project and is used for a focused investigation.
  1. Open your project. The Studies panel lists its studies.
  2. Click the + button (labelled Create Study) at the top of the Studies panel.
  3. Give your study a name, e.g., “Cycling Test”.
  4. Click “Create study”.
Now we’re ready to run a Simulation within your study.
  1. Open your study and, on the Simulations tab, click “New Simulation”.
  2. In step “Select Cell & Parameterized Model”, choose the Cell Specification and Parameterized Model you created.
  3. Provide the protocol to run: upload a battery cycler protocol file (Arbin, Maccor, Neware, Novonix, or BioLogic). Studio parses it into a Universal Cycler Protocol.
  4. Review the parsed protocol and run it. Ionworks Studio starts the simulation.
Once the run completes, it appears on the study’s Simulations tab.
  1. Open the simulation from the list to see its result plots (voltage, capacity, and more).
  2. Use the tab’s Table / Visualization toggle to switch between the run list and comparison plots across runs.
Congratulations! You’ve just run your first simulation in Ionworks Studio.

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Prefer Python?

You can drive the same platform from Python with the ionworks-api client, configuring your pipeline with ionworks-schema. Here’s a minimal end-to-end pipeline — install, submit, and read the result. This one derives the positive electrode’s maximum lithium concentration from a known capacity and electrode geometry, so it runs without any data file:
ElectrodeCapacity solves for the one unknown among capacity, concentration, and geometry — here it returns the maximum concentration. Swap in a DataFit element to fit model parameters against your own data. See the Python API client page for authentication and the Pipelines API page for the full pipeline surface.

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Next Steps

Now that you’ve run a basic simulation, you can explore more advanced features:

Manage Experimental Data

Upload and manage your battery cycling data for visualization and analysis.

Explore Protocols

Create protocols or use built-in experiment templates.

Organize with Studies

Create focused investigations and compare simulation results.

Run Parameter Sweeps

Explore the effect of changing multiple parameters at once.

Refine Your Models

Clone and edit parameterized models to improve their accuracy.

Optimize Parameters

Automatically find optimal parameters for your battery design.

Parameterize with Python

Use the Python API client to parameterize models from experimental data.