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Prioritize stable compounds before you spend simulation budget.

Formation Energy Predictor

Score candidate chemistries for formation energy, relative stability, and shortlist priority without manually stitching together multiple databases or running DFT on every option first.

Key outcomes

R² 0.933
held-out model fit
204K
training structures
Minutes
to rank a candidate set

What goes in

Inputs this feature expects

  • Formula or structure candidates from search, literature, or lab notebooks
  • Optional composition constraints for a screening batch
  • Lists exported from materials discovery workflows

What comes out

Outputs your team can act on

  • Predicted formation-energy ranking for every candidate
  • A shortlist to send into DFT, synthesis, or deeper review
  • Warehouse-backed context for why a candidate ranked where it did

Workflow

How teams use Formation Energy Predictor

01

Assemble the candidate pool

Start with formulas, structures, or upstream search results already inside Lattice Graph.

02

Score for stability

Run the predictor to estimate energetic favorability and triage obvious dead ends.

03

Promote the best options

Push the top-ranked materials into simulation, synthesis planning, or review queues.

Best fit

Where this feature adds the most leverage

  • Front-loading materials screening before DFT
  • Discovery teams ranking a large formula list
  • Reducing manual spreadsheet triage for stability decisions

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