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The selection of novel planar electromagnetic sensors for the application of nitrate contamination detection

Md. Yunus, M. A. M. and Mukhopadhyay, S. C. and Rahman, M. S. A. and Zahidin, N. S. and Ibrahim, S. (2013) The selection of novel planar electromagnetic sensors for the application of nitrate contamination detection. In: Smart Sensors, Measurement and Instrumentation. Springer International Publishing, pp. 171-195.

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Abstract

Twenty four novel planar electromagnetic sensors based on the combination of meander and interdigital sensors have been designed and fabricated using the simple PCB technology for the application of nitrate contamination detection. Experiments were conducted to obtain the impedance characterization for each sensor, and the results were used to estimate the important parameters that influence the performance of the sensors based on the equivalent electrical circuits. Furthermore, the best sensors have been tested to detect nitrates contamination in distilled water from two sets of experiments. Firstly, two nitrate forms, namely sodium nitrates (NaNO3) and ammonium nitrates (NH4NO3), each of different concentration between 5 mg and 20 mg dissolved in 1 litre of distilled water were used to observe the sensor response. Secondly, NaNO3 and NH4NO3 were mixed in several different ratios dissolved in 1 litre of distilled water and the responses of the sensors were observed. The outcomes concluded that a sensor with the combination of interdigital sensor enclosed with a meander sensor can very well detect the presence of nitrate added into distilled water and is capable of distinguishing the concentration level. This paper will discuss the process that was involved to select the best sensor for the application of nitrate contamination detection.

Item Type:Book Section
Uncontrolled Keywords:equivalent electrical circuits
Subjects:T Technology > TJ Mechanical engineering and machinery
Divisions:Mechanical Engineering
ID Code:74669
Deposited By: Haliza Zainal
Deposited On:23 Nov 2017 04:34
Last Modified:23 Nov 2017 04:34

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