Historically, research into olfaction and its related technologies has developed at a slower pace than work into other human senses. Recently, the impact of COVID-19 has resulted in temporary smell loss for many people and has brought the importance of olfaction to the public's attention. This has prompted ideas on how we might utilise olfaction and its related technologies better in our daily lives. However, the limited research in this area means the public has been restricted to devices as simple as air fresheners and scented candles.

In this paper, we present the analog circuit design and implementation of an adaptive neuromorphic olfaction chip. An analog VLSI device with on-chip chemosensor array, on-chip sensor interface circuitry and on-chip learning neuromorphic olfactory model has been fabricated in a single chip using Austria Microsystems 0.6 mum CMOS technology. Drawing inspiration from biological olfactory systems, the neuromorphic analog circuits used to process signals from the on-chip odour sensors make use of temporal "spiking" signals to act as carriers of odour information. An on-chip spike time dependent learning circuit is integrated to dynamically adapt weights for odour detection and classification. All the component subsystems implemented on chip have been successfully tested in silicon