Work

FRaPPE: Fragrance Raw Materials Performance Prediction Explained

Year: 2026

Type: article

Source: Industrial & Engineering Chemistry Research

DOI: 10.1021/acs.iecr.6c02447

Authors: Flora Esposito, Ulderico Di Caprio, Mattia Collu, Raffaele Graziano, Vincenzo Guida, Idelfonso B. R. Nogueira, Florence Vermeire, M. Enis Leblebici

Institutions: KU Leuven, Delft University of Technology, Norwegian University of Science and Technology

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funders: Agentschap Innoveren en Ondernemen, KU Leuven

Awards: G3648245437, G8197707571

OpenAlex ID: W7203619992

FWCI:

Cites: 25

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