Artificial olfaction is an emerging field aiming to mimic natural olfactory systems. Olfactory systems rely on a first step of molecular recognition where volatile organic compounds (VOCs) bind to an array of specialized olfactory proteins. As a result, electrical signals are transduced to the brain where pattern recognition is performed. An efficient approach in artificial olfaction uses electronic noses, devices that combine gas-sensitive material arrays with machine learning signal processing and classification tools.

Supramolecular self-assembly provides the possibility to generate modular and tunable materials with self-powered stimuli-responsive properties. This field is attracting enormous interest as an approach to functional materials design, and has tremendous, mostly untapped opportunities in creating new types of sensors. We have recently developed the concept of hybrid gels in artificial olfaction (Fig 1A) [1]. These materials result from the co-assembly of functional components – liquid crystals for reporting, ionic liquid as solvent, biopolymer as matrix - which give rise to VOC-molecular recognition properties not seen in the individual components. Each component has its own role, yet in combination, they provide a molecular environment and compartmentalization that provides the selectivity required for VOC-sensing. When casting the hybrid gels as thin films, they exhibited dual optical and electrical stimuli-responsive properties in the presence of VOCs. In this work, films of hybrid gels are studied as gas sensing materials in a custom-built electronic nose. Several features were extracted from the signals obtained upon VOC exposure, and then used to implement a dedicated automatic classifier based on support vector machines for data processing [2] (Fig. 1B). Alternatively, it is also possible to employ deep convolutional neural networks (CNN) as pattern recognition systems to analyse optical textures dynamics in liquid crystal-droplets exposed to a set of different VOCs [4]. Furthermore, we show that the developed device can be used in dry and humid conditions, for the quantification of ethanol in automotive fuel or in fish spoilage monitoring [3,5]. The versatility shown by the developed opto-electronic gas sensing materials opens a wide range of applications in different areas such as medical diagnostics, food or agriculture.