Date of Award

13-8-2024

Document Type

Thesis

School

School of Electrical & Electroncis Engineering

First Advisor

Dr.B.G.Jeyaprakash

Keywords

ZnO, Ammonia Detection, Chemiresistor, Farm Field, Poultry

Abstract

This work aims on the development of nanostructured sensing elements based on ZnO for detecting ammonia, specifically designed for applications in poultry and farm fields. To achieve this objective, we prepared sensing elements, including ZnO, CuO, WO3, NiO, ZnO/CuO, ZnO/WO3, ZnO/NiO, and rGO/ZnO, using the spray pyrolysis technique. Structural, morphological, and compositional analyses were studied using X-ray Diffraction (XRD), Field Emission Microscope (FESEM), and X-ray Photoelectron Spectroscopy (XPS), respectively. The vapour/gas detection studies of fabricated sensing elements were carried out in a home built sensing chamber.

The single oxides, ZnO, CuO, WO3, demonstrated ammonia detection in the range of 5-100 ppm at 350 °C. Mixed oxides, ZnO/NiO, ZnO/CuO, ZnO/WO3, and rGO functionalized ZnO, exhibited an enhanced sensitivity of 0.5 ppm at 300 °C. This improved sensitivity was attributed due to the formation of p-n junctions and increased oxygen vacancies in the materials. The sensors were further tested in a mixed gas environment with major poultry and farm field gases such as methane (500 ppm), carbon dioxide (5000 ppm) and nitrous oxide (25 ppm). The concentrations of these gases were kept at their Permissible Exposure Limit (PEL) and Recommended Exposure Limit (REL). The ammonia concentration was maintained below the permissible limit at 20 ppm.

To address output voltage drift in the sensors, pattern recognition techniques were employed, classifying the concentration of gases into four levels: low range of ammonia (0.5 ppm to 8 ppm), medium range of ammonia (greater than 8 ppm and less than 25 ppm), high range of ammonia (25 ppm to 100 ppm), and other gases. The features extracted from two group of sensors was tested using Random Forest (RF), Support Vector Machine (SVM), and Naive Bayes algorithms, with RF demonstrating the highest classification accuracy of the dataset. Consequently, a sensor array was fabricated using ZnO, CuO, WO3, ZnO/CuO, and ZnO/WO3, achieving an RF accuracy of 96.8%.

Two prototypes of ammonia detectors were developed. The ZnO-based detector exhibited an ammonia detection range of 5-100 ppm at 350 °C with continuous monitoring. The second prototype, based on a sensor array utilizing the RF classifier, displayed different concentration of ammonia levels through LED indication. The findings of the proposed work focus on ammonia detection below trace levels by enhancing the base material composition and subsequently post processing the signals by pattern recognition technics. In this way a systematic approach to develop an effective and selective real time ammonia detectors for poultry and farm field applications, combining ZnO based sensing elements and pattern recognition algorithms for accurate and reliable detection can be accomplished.

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