Perfume Composition Synergistic Odor Intensity
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Solution Overview
Problem
Current perfume compositions lack the ability to create synergistic effects, where the sensory impact of odor mixtures is greater than expected from their individual components, due to the complexity and non-linearity of olfactory interactions, making it difficult to predict and replicate desired odor perceptions.
Innovation Solution
The use of specific combinations of resilient odor components from Groups 1A, 1B, and 1C, which include acetyl cedrene, linalol, and other materials, to create synergistic effects by enhancing the intensity and character of perfume compositions, allowing for the creation of stronger, more complex, or unique odors without adding more ingredients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If complex odor mixtures are created to achieve desired odor perceptions, then the sensory impact and odor character are enhanced, but the complexity and non-linearity of olfactory interactions make prediction and replication difficult
Solution Approach 1:
The patent segments the complex olfactory system into distinct functional components: olfactory receptors (ORs) that detect odor molecules, projection neurons (PNs) that transmit signals, and glomeruli that organize odor information. This segmentation allows the model to handle complex odor mixtures by processing them through discrete, manageable neural pathways rather than treating the entire system as an undifferentiated complex network.
Solution Approach 2:
The patent transforms the complex qualitative problem of odor perception into quantitative parameters that can be modeled and predicted. It uses parameters such as receptor activation levels, neuronal firing rates, and glomerular response patterns to represent odor perceptions. By changing the representation from subjective sensory descriptions to measurable physiological parameters, the model can predict odor outcomes of complex mixtures systematically.
2Adaptability or versatility
If multiple odor components are combined to create unique odor characters, then the odor perception is enhanced and more complex, but the non-linear interactions between components make the outcome unpredictable
Solution Approach 1:
The patent implements feedback mechanisms in the olfactory model where neuronal responses are adjusted based on patterns of activation across the receptor-neuron-glomerulus network. The model incorporates feedback loops that allow the system to adapt to different odor combinations, learning to predict outcomes of complex mixtures by analyzing patterns of interaction between components and their combined effects on the neural network.
Solution Approach 2:
The patent creates a composite computational model that integrates multiple biological components (receptors, neurons, glomeruli) into a unified predictive framework. Rather than treating each odor component in isolation, the model synthesizes their interactions through the composite structure of the olfactory network, allowing prediction of emergent properties that arise from component combinations.
Data Source
AI summary
A perfume composition includes groups of perfume components that produce enhanced sensory performance. The composition includes components that have synergistic odor properties.