Find viable OLED emitters from SMILES alone
Screen 400 emitter candidates from SMILES. Get emission wavelength, TADF suitability, and device role classification in minutes. S1 accuracy within 0.05 eV of experiment. Identify top candidates for synthesis or device testing straight from a screen, full quantum workflows optional.
“Find me a blue OLED emitter from this library of 400 candidates, ranked by singlet-triplet gap for TADF suitability.”
How it works
Provide SMILES
Geometry optimizes via ANI-2x or MACE in milliseconds. No conformer setup, no input file preparation.
Frontier orbitals and device classification
predict_frontier_orbitals returns HOMO, LUMO, gap, S1/T1 energies, oscillator strength, and device role - emitter, charge transport, host, or not emissive. 14 OLED-relevant functional-group motifs detected automatically (carbazole, triphenylamine, anthracene, pyrene, oxadiazole, triazine, Ir/Pt complexes).
Excited-state ladder for top candidates
run_excited_states returns the full singlet/triplet ladder via sTDA-xTB with oscillator strengths. Screen for TADF suitability (small singlet-triplet gap) or phosphorescent emitters.
Proof
Anthracene S1: 3.249 eV computed vs 3.3 eV experimental (0.05 eV error). T1: 1.805 eV vs 1.8 eV (0.005 eV error).
Carbazole: correctly classified as UV emission / charge transport. Ethanol: correctly returns not_emissive (no OLED motifs).
14 detected motifs: carbazole, triphenylamine, anthracene, pyrene, oxadiazole, triazine, Ir/Pt complexes, and others.
Tool chain: optimize_geometry_nnp → predict_frontier_orbitals → run_excited_states.
Use this when you need to
Screen emitter libraries for emission wavelength and TADF suitability
Rank candidates by singlet-triplet gap before expensive validation
Classify device roles (emitter, host, charge transport) automatically
Guide early-stage selection with accuracy sufficient to prioritize synthesis
Screen 400 candidates in minutes
S1 within 0.05 eV. Accurate enough to guide selection before expensive validation.