Dynamic Temperature Modulation Sensing Technique of Electronic Nose: A Review

Electronic nose (E-nose) is a simulation of human nose, which consists of a gas sensor array and an artificial intelligent algorithm. The gas sensing properties of semiconductor sensors are affected by the heating temperature. For most gases, there exists the optimum oxidation temperature. If sensor response is recorded, we can obtain the data with abundant information at different working temperatures. The selectivity and sensitivity of a gas sensor array are the bottleneck of its development. Dynamic temperature modulation sensing technique is a use of semiconductor sensor temperature modulation characteristics by modulating its heating voltage to realize the heating temperature in a range of changes, people can record the corresponding response. The temperature modulation sensing technique can effectively improve the sensitivity of E-nose and realize the detection of low concentration gas, so it is of great practical significance to development technique of E-nose, which is based on temperature modulated sensing system for promoting the detection speed. But so far, the technique is only used for the detection of several common gases (such as methanol, ethanol, carbon monoxide, et al). The aim of this review is to supply a summary of the development and significant achievements of dynamic temperature modulation sensing technique used in E-nose in recent years. We are also looking forward to seeing dynamic temperature modulation sensing technique to accomplish more breakthroughs and get more achievements

Modification of n-type and p-type metal oxide semiconductor systems for gas sensing applications

This thesis investigates the modification of three metal oxide semiconductor gas sensors with zeolite materials for the purposes of detecting trace concentrations of gases that have an effect on health, security, safety and the environment. SnO2, Cr2O3 and Fe2O3 were chosen as the base materials of interest. Zeolites HZSM- 5, Na-A and H-Y were incorporated into the sensing system either as admixtures with the base material or as coatings on top of it. The aim of introducing zeolites into the sensing system was to improve the performance of the otherwise unmodified sensors. Twenty-two novel zeolite-modified sensor systems are presented for the detection of a range of hydrocarbons and inorganic gases. Whilst sensors based on SnO2 systems were more responsive to gases, some sensors were also found to provide a greater degree of variability among repeat tests, particularly at lower operating temperatures i.e. 300 °C. Cr2O3 sensors modified by admixture with zeolite H-ZSM- 5 were seen to be poorly sensitive to most analytes. Cr2O3 sensors modified by admixture with zeolite Na-A and by overlayer of zeolite H-Y provided very promising sensitive and selective results towards toluene gas. Sensors based on the zeolite modification of Fe2O3 were not found to be promising candidates as gas sensors at this stage. Sensors were purposely exposed to gases that had similar molecular structures or kinetic diameters to assess the true capability of the sensors to discriminate among analytes. An array of four sensors based on n-type and p-type systems was subsequently chosen to see whether machine learning classifiers could be used to accurately discriminate among nine analytes. Using an SVM SMO classifier with a polykernel function, the model was 94.1% accurate in correctly classifying nine analytes of interest just after five seconds into the gas injection. Using an RBF kernel function, the model was 90.2% accurate in correctly classifying the data into gas type. These are very encouraging results, which highlight the importance of furthering research in this field; a sensing array based on zeolite-modified metal oxide semiconductor sensors may benefit a number of research domains by providing accurate results in a very fast and inexpensive manner

The 1st International Electronic Conference on Chemical Sensors and Analytical Chemistry

The 1st International Electronic Conference on Chemical Sensors and Analytical Chemistry was held on 1–15 July 2021. The scope of this online conference was to gather experts that are well-known worldwide who are currently working in chemical sensor technologies and to provide an online forum for the presention and discussion of new results. Throughout this event, topics of interest included, but were not limited to, the following: electrochemical devices and sensors; optical chemical sensors; mass-sensitive sensors; materials for chemical sensing; nano- and micro-technologies for sensing; chemical assays and validation; chemical sensor applications; analytical methods; gas sensors and apparatuses; electronic noses; electronic tongues; microfluidic devices; lab-on-a-chip; single-molecule sensing; nanosensors; and medico-diagnostic testing

Investigation of Volatile Organic Compounds (VOCs) released as a result of spoilage in whole broccoli, carrots, onions and potatoes with HS-SPME and GC-MS

Vegetable spoilage renders a product undesirable due to changes in sensory characteristics. The aim of this study was to investigate the change in the fingerprint of VOC composition that occur as a result of spoilage in broccoli, carrots, onions and potatoes. SPME and GC-MS techniques were used to identify and determine the relative abundance of VOC associated with both fresh and spoilt vegetables. Although a number of similar compounds were detected in varying quantities in the headspace of fresh and spoilt samples, certain compounds which were detected in the headspace of spoilt vegetables were however absent in fresh samples. Analysis of the headspace of fresh vegetables indicated the presence of a variety of alkanes, alkenes and terpenes. Among VOCs identified in the spoilt samples were dimethyl disulphide and dimethyl sulphide in broccoli; Ethyl propanoate and Butyl acetate in carrots; 1-Propanethioland 2-Hexyl-5-methyl-3(2H)-furanone in onions; and 2, 3-Butanediol in potatoes. The overall results of this study indicate the presence of VOCs that can serve as potential biomarkers for early detection of quality deterioration and in turn enhance operational and quality control decisions in the vegetable industry