- Determine the relationship between available parameters and target (faradaic efficiency, FE)?.
- Develop accurate predictive model for the FE response.
- Explain the impact of the features on the FE response.
- Design novel conditions with the proposed ML-based models.
- Clean and perform preliminary analysis on the data.
- Train ML model using methods such as ANN, RF, XGB, etc.
- Use best model to perform feature analysis.
- Deploy the model to app.
- Verify model predictions with new experiments.
- Propose novel optimized experimental conditions for assessment.
- Prepare manuscript
Name | Affilation | Duty | |
---|---|---|---|
Dauda Monsuru | Louisiana State University | mdauda1@lsu.edu | Experiment |
Teslim Olayiwola | Louisiana State University | tolayi1@lsu.edu | Simulation |
This project is a work-in-progress and kindly desist from using the information contained here without notifying the authors.