Lithium Recovery Predictor
Predicts overall lithium recovery from brine or hard-rock feed through the process circuit.
This model is a reference implementation. Industrial use requires validation on plant-specific data. Customer-specific fine-tuning remains private unless explicitly approved for publication.
Input schema
| Field | Type | Description |
|---|---|---|
| feed_grade | float · mg/L | Lithium feed grade |
| process_conditions | float[] | Reagent + temperature profile |
Output schema
| Field | Type | Description |
|---|---|---|
| recovery | float · % | Predicted recovery |
Training data & evaluation
Training data type
Synthetic lithium circuit dataset
Evaluation metrics
Limitations
- Brine and hard-rock routes behave differently; select the matching config.
Discussion
- s.Validation note
s.iyer
ML researcher · 3d
Reproduced the reported metric on the public split with a fixed seed. Numbers line up within noise, so it's a good baseline to build on.
18 - l.Improvement
l.zhang
Process engineer · 1w
Adding an uncertainty head would make this far more useful for prioritization. Happy to open a PR against the reference repo.
11
Validate on your data, keep the result private
Reference models are a starting point. We can fine-tune privately on plant-specific data, with customer-owned IP and no public disclosure.