Detection of LPG Gas by Using Multi Sensors Array and Fabricated ZnO Gas Sensor

The demand for LPG (Liquefied Petroleum Gas) detection constitutes a major and critical problem in the field of gas detection. LPG is used for domestic appliances used in the heating of buildings, producing petrochemicals and as a motor fuel. The current paper used the fabricated ZnO, in addition to TGS 813, TGS 2600, TGS 4160, TGS 3870, TGS 822 as semiconductor gas sensors, in varying temperature and load resistance in a prototype setup so as to explore each model’s accuracy for performance prediction for gas detection. The fabricated ZnO gas sensor is used also to detect the LPG. The comparison is done between gas sensors array and the fabricated one from ZnO. The actual results are put in comparison with the empirical algorithms’ predictions. The optimal model is found to be the full quadratic empirical model based on the lowest error with different sensors.

A Graphical Pressure Sensor Array With Multilayered Structure: Written Through Graphene Ink on Cellulose Paper Substrate

Paper based flexible pressure sensors have received extensive attention due to their recoverability and accessibility. In this paper, we proposed graphical pressure sensors array with multilayered structure. A simple writing method was adopted to achieve the adsorption of sensitive materials on the fiber structure of cellulose paper. Pressure sensors with 1, 3, 5 and 7 stacked layers were fabricated and compared, respectively. The results show that the 7layers sensor combined high sensitivity (44 kPa-1) and fast time response (150 ms). The highly sensitive stacked paper-based sensor array realizes the pressure detection of objects and special-shaped surfaces. A pressure sensor base on commercial corrugated box was also fabricated to compare. The corrugated carton array was made to switch reminder devices for its convenience and accessibility. Since there are many scenarios that require a safe distance, especially under the influence of the COVID-19, the writable paper-based sensor array was used to realize graphical distance perception and warning.

IoT Based Air Quality Monitoring System

A remote online carbon dioxide (CO2) concentration monitoring system is developed, based on the technologies of wireless sensor networks, in allusion to the gas leakage monitoring requirement for CO2 capture and storage. The remote online CO2 monitoring system consists of monitoring equipment, a data center server, and the clients. The monitoring equipment is composed of a central processing unit (CPU), air environment sensors array, global positioning system (GPS) receiver module, secure digital memory card (SD) storage module, liquid crystal display (LCD) module, and general packet radio service (GPRS) wireless transmission module. The sensors array of CO2, temperature, humidity, and light intensity are used to collect data and the GPS receiver module is adopted to collect location and time information. The CPU automatically stores the collected data in the server and displays them on the LCD display module in real-time. Afterwards, the GPRS module continuously wirelessly transmits the collected information to the data center server. The online monitoring Web GIS clients are developed using a PHP programming language, which runs on the Apache web server. MySQL is utilized as the database because of its speed and reliability, and the stunning cross browser web maps are created, optimized, and deployed with the Open Layers JavaScript web-mapping library.

A Hairpin DNA-Based Piezoelectric E-Nose: Exploring the Performances of Heptamer Loops for the Detection of Volatile Organic Compounds

A hairpin DNA (hpDNA) piezoelectric gas sensors array with heptamer loops as sensing elements was designed, realized, and challenged with pure volatile organic compounds VOCs and real samples (beer). The virtual binding versus five chemical classes (alcohols, aldehydes, esters, hydrocarbons, and ketones) of the entire combinatorial library of heptamer loops (16,384 elements) was studied by molecular modelling. Six heptamer loops, having the largest variance in binding the chemical classes, were selected to build the array. The six gas sensors were realized by immobilizing onto gold nanoparticles (AuNPs) via a thiol spacer the hpDNA constituted by the heptamer loops and the same double helix stem of four base pairs (GAAG at 5′ and CTTC at 3′ end). The HpDNA-AuNP was used to modify the surface of 20 MHz quartz crystal microbalances (QCMs). The realized E-nose was able to clearly discriminate among 15 pure VOCs of different chemical classes, as demonstrated by hierarchical cluster analysis. The analysis of real beer samples during fermentation was also carried out. In such a challenging matrix consisting of 23 different VOCs, the hpDNA E-nose with heptamer loops was able to discriminate among different fermentation times with high success rate. Class assignment using the Bayes theorem gave an excellent 98% correct beer samples classification in cross-validation.