molecular_properties_predictor

To predict molecular properties from a SMILES string, input the string into the predictor to compute up to 11 properties like boiling point, density, and pKa. The tool returns a structured JSON with values, units, and provenance for downstream analysis.

Yes, you can run batch predictions for molecular properties by providing a batch JSON input. This enables high-throughput screening, returning all 11 physicochemical properties for multiple small molecules in a single structured JSON output.

Using RDKit integration, you can calculate 11 small molecule physicochemical properties including melting point, boiling point, refractive index, density, viscosity, surface tension, pKa values, dielectric constant, and vapor pressure from SMILES inputs.

Yes, the molecular property predictor supports high-throughput chemical screening by accepting batch JSON inputs. It processes multiple small molecules simultaneously via the Bamboo-Mixer backend to accelerate chemical screening and decision-making.

Predicted molecular properties are formatted as a structured JSON containing property values, units, and provenance. This structured output is suitable for direct integration into downstream analysis workflows and chemical reporting systems.