Chemiresistor gas sensors based on conductive copolymer and ZnO blend – prototype fabrication, experimental testing, and response prediction by artificial neural networks

Abstract

Nitric oxide(NO), nitrogen dioxide (NO2), nitrous oxide (N2O), and their derivatives generally known as nitrogen oxides (NOx) are primary pollutants in the atmosphere originated from natural and anthropogenic sources. The paper presents investigation of electric performance of novel chemiresistor NOx gas sensors. A novel material was utilized for active sensing layer-conductive copolymer and zinc oxide blend. The main advantage of the presented solution is low-cost and environment-friendly production. A series of this type of sensors was manufactured and tested experimentally. During the tests, the gas flow was controlled and signals of sensor responses, temperature, and humidity were computer-acquired using LabVIEW program. Sensor behavior for different thicknesses of the active layer has been investigated and interpreted. The research revealed that the electrical resistance of the sensors has changed in predictable manner depending on the gas concentrations. A recurrent artificial neural network architecture is proposed as a mathematical model to classify sensor responses to gas concentrations variation in a time-dependent regime. In this research, an enhanced method for gas concentration prediction is proposed using non-linear autoregression model with exogenous input (NARX). The performed simulations show good agreement between simulated and experimental data useful for predictions of sensor gas response.

Multiscale Analysis of Composite Structures with Artificial Neural Network Support for Micromodel Stress Determination

“…The output information of the neurons is passed through the layers until the output is obtained. The network can be trained and learn complex patterns and relationships from provided reference data, by adjusting the weight and bias values of all its neurons [ 58 , 59 , 60 ].…”

Graphene-based chemiresistive gas sensors

“…Here an artificial neural network was fed time dependent signal responses of four sensor substrates of the same material, but with different layer thicknesses. 163 It is expected that such data analysis protocols will be beneficial for all kinds of chemiresistive gas sensors.…”

Light and bias-induced room temperature negative differential conductance in Ni-doped ZnO/p-Si Schottky photodiodes for quantum optical applications

“…In the last decade, ZnO-based HJSCs have been demonstrated with photovoltaic power conversion efficiencies (PCE) >15% [7]. ZnO has also found widespread application in photoconductive, gas and other sensors [8,9,10] In this article, we present evidence of room temperature (300K) NDC in suitably Ni-doped ZnO metalśsemiconductorśmetal (MSM) Schottky photo-diodes with the structure Al/(Ni:ZnO)/p-Si/Al. The electronegativity and ionic radius (r) of Ni (r=0.69Å) imply an affinity and good substitutional compatibility with Zn (r=0.74Å) with minimal distortion of the host structure [11].…”