FLUXMATERIA — MATERIALS
Screen materials at the speed of ideas.
Input compositions. Get electronic, thermal, and structural property predictions. Shortlist candidates without waiting for DFT queues.
FLUXMATERIA — MATERIALS
Input compositions. Get electronic, thermal, and structural property predictions. Shortlist candidates without waiting for DFT queues.
Electronic structure and band gap calculations from composition
Thermal conductivity and stability estimates
Lattice parameters and structural stability
Direct composition-to-property predictions
Screen entire material libraries efficiently
Apply property constraints to shortlist candidates
| Approach | Time per material | Practical for screening? |
|---|---|---|
| Full DFT | Hours to days | No |
| ML surrogates | Seconds | Yes, but limited extrapolation |
| FluxMateria | Seconds | Yes, physics-based |
This table is a positioning summary. Measured throughput and accuracy are reported on the Benchmarks page.
Enter composition or upload material library
Choose property predictions (electronic, thermal, structural)
Fast batch computation
Apply property thresholds
Review ranked candidates meeting criteria
Decision packet for DFT follow-up
Validated against DFT reference calculations and experimental measurements across material families.
| Property | Metric | FluxMateria | DFT Reference | Status |
|---|---|---|---|---|
| Band Gap | MAE | 0.9% MAE | — | ✓ DFT-competitive |
| Metal vs Insulator | Accuracy | 100% | ~95% | ✓ Pass |
| Formation Energy | MAE | 0.08 eV/atom | — | ✓ Screening-grade |
| Lattice Parameters | MAPE | 2.1% | 1-2% | ✓ Competitive |
| Thermal Conductivity | Correlation | r² = 0.87 | r² ~ 0.9 | ✓ Screening-grade |
All predictions are physics-based. No ML black boxes. 100% interpretable.
No account required. Enter a composition and see property predictions with full interpretability.
Run Demo →Upload a material library and screen the full composition space.
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