Fabrication and optimization of a conducting polymer sensor array using stored grain model volatiles

Artificial Olfactory Signal Modulation for Detection in Changing Environments

Animals have evolved to sense in complex environments through both modulation behavior including sniffing as well as sophisticated neural processing including memory and neuromodulation. Here, we explore thermal modulation of chemically diverse sensor arrays, where response patterns are based on partitioning of odorants across the array. The differential response patterns contain information about the chemical nature of the odorant for identification. By transitioning away from well-defined concentration modulation, traditionally used in the field, to thermal modulation, it is possible to capture both diagnostic patterns as well as intensity information in complex environments. This performance is demonstrated with carbon-black based, chemically diverse sensor arrays, that are thermally modulated with light at 25 mHz exposed to different analytes of varying concentrations.

Molecularly Imprinted Sol-Gel-Based QCM Sensor Arrays for the Detection and Recognition of Volatile Aldehydes

The detection and recognition of metabolically derived aldehydes, which have been identified as important products of oxidative stress and biomarkers of cancers; are considered as an effective approach for early cancer detection as well as health status monitoring. Quartz crystal microbalance (QCM) sensor arrays based on molecularly imprinted sol-gel (MISG) materials were developed in this work for highly sensitive detection and highly selective recognition of typical aldehyde vapors including hexanal (HAL); nonanal (NAL) and bezaldehyde (BAL). The MISGs were prepared by a sol-gel procedure using two matrix precursors: tetraethyl orthosilicate (TEOS) and tetrabutoxytitanium (TBOT). Aminopropyltriethoxysilane (APT); diethylaminopropyltrimethoxysilane (EAP) and trimethoxy-phenylsilane (TMP) were added as functional monomers to adjust the imprinting effect of the matrix. Hexanoic acid (HA); nonanoic acid (NA) and benzoic acid (BA) were used as psuedotemplates in view of their analogous structure to the target molecules as well as the strong hydrogen-bonding interaction with the matrix. Totally 13 types of MISGs with different components were prepared and coated on QCM electrodes by spin coating. Their sensing characters towards the three aldehyde vapors with different concentrations were investigated qualitatively. The results demonstrated that the response of individual sensors to each target strongly depended on the matrix precursors; functional monomers and template molecules. An optimization of the 13 MISG materials was carried out based on statistical analysis such as principle component analysis (PCA); multivariate analysis of covariance (MANCOVA) and hierarchical cluster analysis (HCA). The optimized sensor array consisting of five channels showed a high discrimination ability on the aldehyde vapors; which was confirmed by quantitative comparison with a randomly selected array. It was suggested that both the molecularly imprinting (MIP) effect and the matrix effect contributed to the sensitivity and selectivity of the optimized sensor array. The developed MISGs were expected to be promising materials for the detection and recognition of volatile aldehydes contained in exhaled breath or human body odor.

Electronic detection of Drechslera sp. fungi in charentais melon ( Cucumis melo Naudin) using carbon-nanostructure-based sensors

The development of chemical sensor technology in recent years has stimulated an interest regarding the use of characteristic volatiles and odors as a rapid and early indication of deterioration in fruit quality. The fungal infestation by Drechslera sp. in melons is a severe problem, and we demonstrate that electronic sensors based on carbon nanostructures are able to detect the presence of these fungi in melon. The responses of sensor conductance G and capacitance C at 27 kHz were measured and used to calculate their ΔG and ΔC variation over the full melon ripening process under shelf conditions with proliferation of Drechslera sp. fungi. The sensor response showed that these fungi can be electronically identified in charentais melon, constituting an effective and cheap test procedure to differentiate between infected and uninfected melon.

Battery-free radio frequency identification (RFID) sensors for food quality and safety

Market demands for new sensors for food quality and safety stimulate the development of new sensing technologies that can provide an unobtrusive sensor form, battery-free operation, and minimal sensor cost. Intelligent labeling of food products to indicate and report their freshness and other conditions is one important possible application of such new sensors. This study applied passive (battery-free) radio frequency identification (RFID) sensors for the highly sensitive and selective detection of food freshness and bacterial growth. In these sensors, the electric field generated in the RFID sensor antenna extends from the plane of the RFID sensor and is affected by the ambient environment, providing the opportunity for sensing. This environment may be in the form of a food sample within the electric field of the sensing region or a sensing film deposited onto the sensor antenna. Examples of applications include monitoring of milk freshness, fish freshness, and bacterial growth in a solution. Unlike other food freshness monitoring approaches that require a thin film battery for operation of an RFID sensor and fabrication of custom-made sensors, the passive RFID sensing approach developed here combines the advantages of both battery-free and cost-effective sensor design and offers response selectivity that is impossible to achieve with other individual sensors.