Proceedings of MATSUS Spring 2024 Conference (MATSUS24)
DOI: https://doi.org/10.29363/nanoge.matsus.2024.013
Publication date: 18th December 2023
Neuromorphic sensors, designed to emulate natural sensory systems, hold the promise of revolutionizing data extraction by facilitating rapid and energy-efficient analysis of extensive datasets. However, a significant challenge lies in accurately distinguishing specific analytes within mixtures of chemically similar compounds using existing neuromorphic chemical sensors. In this study, we present an artificial olfactory system (AOS), which is developed through the integration of human olfactory receptors (hORs) and artificial synapses, for the first time. This AOS is sophisticatedly engineered by interfacing an hOR-functionalized extended-gate with an organic synaptic device. The AOS generates clearly distinct patterns for odorants and mixtures thereof, at the molecular chain length level, attributed to specific hOR-odorant binding affinities. This approach enables precise pattern recognition via training and inference simulations. These findings establish a solid foundation for the development of high-performance sensor platforms and artificial sensory systems, which are ideal for applications in wearable and implantable devices.
This work was supported by the National Research Foundation of Korea (NRF), grants no. NRF-2023R1A2C3007715 and NRF-2021R1A4A1032515; Nano Material Technology Development Program funded by the Ministry of Science and ICT (MSIT) of the Korean government, grant no. NRF-2017M3A7B8063825; Korea Toray Science Foundation fund. The Institute of Engineering Research at Seoul National University provided research facilities for this work.
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