Detection and identification of toxic environmental gases have assumed paramount importance precisely in the defense, industrial and civilian security sector. Numerous methods have been developed for the sensing of toxic gases in the environment ever since surface acoustic wave (SAW) technology came into existence. Such SAW sensors called electronic nose (E-Nose) sensor use the frequency response of a delay line/resonator. SAW device is focused and given importance. The selective coating between input and output interdigital transducers (IDTs) in the SAW device is responsible for corresponding changes in operating frequency of the device for a specific gas/vapour absorbed from the environment. A suitable combination of well-designed SAW delay lines with selective coatings not only help to improve sensor sensitivity and selectivity but also leads to the minimization of false frequency alarms in the E-Nose sensor. This article presents a comprehensive review of design, development, simulation and modelling of a SAW sensor for potential sensing of toxic environmental gases.
Sensing technology has been developed for detection of gases in some environmental, industrial, medical, and scientific applications. The main tasks of these works is to enhance performance of gas sensors taking into account their different applicability and scenarios of operation. This paper presents the descriptions, comparison and recent progress in some existing gas sensing technologies. Detailed introduction to optical sensing methods is presented. In a general way, other kinds of various sensors, such as catalytic, thermal conductivity, electrochemical, semiconductor and surface acoustic wave ones, are also presented. Furthermore, this paper focuses on performance of the optical method in detecting biomarkers in the exhaled air. There are discussed some examination results of the constructed devices. The devices operated on the basis of enhanced cavity and wavelength modulation spectroscopies. The experimental data used for analyzing applicability of these different sensing technologies in medical screening. Several suggestions related to future development are also discussed.
In recent years organic semiconductors have been given attention in the field of active materials for gas sensor applications. In the paper the investigations of the optoelectronic sensor structure of ammonia were presented. The sensor head consists of polyaniline and Nafion layers deposited on the face of the telecommunication optical fiber. The elaborated sensor structure in the form of Fabry-Perot interferometer is of the extremely small dimension – its thickness is of the order of 1 um. Many sensor structures of diffierent combinations of the polyaniline and Nafion layers were constructed and investigated. The optimal solution seems to be the structures with small number of polianiline layers (up to three).
Breath analysis has attracted human beings for centuries. It was one of the simplest methods to detect various diseases by using human smell sense only. Advances in technology enable to use more reliable and standardized methods, based on different gas sensing systems. Breath analysis requires the detection of volatile organic compounds (VOCs) of the concentrations below individual ppm (parts per million). Therefore, advanced detection methods have been proposed. Some of these methods use expensive and bulky equipment (e.g. optical sensors, mass spectrometry –MS), and require time-consuming analysis. Less accurate, but much cheaper, are resistive gas sensors. These sensors use porous materials and adsorptiondesorption processes, determining their physical parameters.We consider the problems of applying resistive gas sensors to breath analysis. Recent advances were underlined, showing that these economical gas sensors can be efficiently employed to analyse breath samples. General problems of applying resistive gas sensors are considered and illustrated with examples, predominantly related to commercial sensors and their long-term performance. A setup for collection of breath samples is considered and presented to point out the crucial parts and problematic issues.
We present the results of a numerical analysis of a two-dimensional photonic crystal with line defect for a laser gas sensor working in a slow light regime. The geometrical parameters of photonic crystals with three different line defects were numerically analyzed: a missing row of holes, a row of holes with changed diameter and air channel. Antireflection sections were also analyzed. The simulations were carried out by MEEP and MPB programs, with the aim to get the values of a group refractive index, transmission and a light-gas overlap as high as possible. The effective refractive index method was used to reduce the simulation time and required computing power. We also described numerical simulation details such as required conditions to work in the slow light regime and the analyzed parameters values’ dependency of the simulation resolution that may influence the accuracy of the results.
Alternating current a.c. measurements enable to understand the physical and chemical processes occurring in semiconductor materials. Impedance spectroscopy has been successfully applied to study the responses of gas sensors based on metal oxides, such as TiO2, SnO2 and TiO2/SnO2 nanocomposites. This work is devoted to dynamic measurements of hydrogen sensor behaviour over the temperature range of 300–450◦C. Frequency dependence of the impedance signal gives evidence that 50 mol% TiO2/50 mol% SnO2 nanocomposites should be treated as resistive-type sensors. Temporal evolution of the response to 500 ppm H2 at 320◦C indicates a very short response time and much longer recovery.
In recent years, smog and poor air quality have become a growing environmental problem. There is a need to continuously monitor the quality of the air. The lack of selectivity is one of the most important problems limiting the use of gas sensors for this purpose. In this study, the selectivity of six amperometric gas sensors is investigated. First, the sensors were calibrated in order to find a correlation between the concentration level and sensor output. Afterwards, the responses of each sensor to single or multicomponent gas mixtures with concentrations from 50 ppb to 1 ppm were measured. The sensors were studied under controlled conditions, a constant gas flow rate of 100 mL/min and 50 % relative humidity. Single Gas Sensor Response Interpretation, Multiple Linear Regression, and Artificial Neural Network algorithms were used to predict the concentrations of SO2 and NO2. The main goal was to study different interactions between sensors and gases in multicomponent gas mixtures and show that it is insufficient to calibrate sensors in only a single gas.