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Aryballe offers a universal electronic nose


This digital sniffer can recognize thousands of smells from the most delicate (flowers, perfumes, fruits and monitoring their ripening) to the less pleasant (putrefaction, ammonia, etc.). 

Published on 9 December 2021
​"Mimicry has enabled us to design our NeOse Advance electronic nose", explains Tristan Rousselle, co-founder of start-up Aryballe with two CEA researchers. "It combines biochemical sensors mimicking the nose's natural sensors and a data analysis module mimicking the olfactory bulb". 

This digital sniffer can recognize thousands of smells from the most delicate (flowers, perfumes, fruits and monitoring their ripening) to the less pleasant (putrefaction, ammonia, etc.). 

The idea was born in 2014, when the entrepreneur, wishing to "launch a breakthrough project at the interface of several technologies", turned to CEA-Grenoble with which he was familiar, having previously founded a start-up with one of the latter's laboratories. The digital olfaction theme then emerged very quickly: Inac  proposed the sensor and CEA-Leti its photonics know-how.

"There was a pressing need, especially on the part of the aroma and fragrance industry, which was seeking odor recognition tools that delivered objective information and are lighter, faster and cheaper than gas chromatography coupled with mass spectroscopy". Other markets have expressed their interest including that of household appliances. "For example, manufacturers are imagining ovens that switch off automatically when the fodd is cooked", says Tristan Rousselle.

Great promises are also expected in the health sector in relation to detecting illnesses, just like the dogs trained in olfactive recognition of breast or prostate cancer.


  • Technology
An association of 64 biochemical nanosensors (peptides capturing volatile odor molecules) grafted onto an optical micronetwork (photonic on silicon). Interferences between a light source and sensor/odor molecule complexes are measured using a photodetector. Each odor thereby generates its own visual imprint, which is identified by comparing it with an olfactive database built by machine learning.

  • Markets
Perfumery: quality control of raw materials, detection of counterfeits, etc.
Food production: quality control, conservation monitoring, etc.
Car industry (rental, sharing): checking interior odor before usage
Household appliances: monitoring food cooking and conservation
Health: detecting certain illnesses

  • Key dates
2014: start-up creation
2016: raising 3.6 million euro capital investment - Industrial investor: Asahi Kasei
2018: launching of NeOse Pro
2019-2020: raising 14 million euro capital investment - Industrial investors: Seb, Samsung, Hyundai, International

  •  Flavors & Fragrances Inc. 
2021: launching of NeOse Advance - pilot, clean-room, industrial production line


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