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  Published Paper Details:

  Paper Title

Scent Synthesis: An AI-Driven Framework for Creating Novel Fragrance Profiles

  Authors

  Palash Halder

  Keywords

Artificial Intelligence, Perfumery, Machine Learning, Fragrance Formulation, Scent Prediction, Molecular Descriptors

  Abstract


The world of perfumery a classically handmade industry is discreetly slinking into the 21st century with artificial intelligence (AI). We introduce in this paper "ScentSynth", a new AI-based framework targeting the generation of fragrances. By employing olfactory databases, molecular descriptors and consumer taste patterns, the model combines supervised and generative machine learning methods. The goal is to drastically save on time and cost to formulate scent as well as to improve creativity and customization. We advance a naturally evolving technical map of AI in perfumery, build a detailed breakdown of the system architecture, as well as validate the feasibility of the system by deployment and evaluation.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2507004

  Paper ID - 290535

  Page Number(s) - a38-a42

  Pubished in - Volume 13 | Issue 7 | July 2025

  DOI (Digital Object Identifier) -    https://doi.org/10.56975/ijcrt.v13i7.290535

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Palash Halder,   "Scent Synthesis: An AI-Driven Framework for Creating Novel Fragrance Profiles", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 7, pp.a38-a42, July 2025, Available at :http://www.ijcrt.org/papers/IJCRT2507004.pdf

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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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