Models of electrochemical sensors play a critical role for electronic engineers in designing electrochemical nanosensor-based integrated systems and are also widely used in analyzing chemical reactions to model the current, electrical potential, and impedance occurring at the surface of an electrode. However, the use of jargon and the different perspectives of scientists and electronic engineers often result in different viewpoints on principles of electrochemical models, which can impede the effective development of sensor technology. This paper is aimed to fill the knowledge gap between electronic engineers and scientists by providing a review and an analysis of electrochemical models. First, a brief review of the electrochemical sensor mechanism from a scientist’s perspective is presented. Then a general model, which reflects a more realistic situation of nanosensors is proposed from an electronic engineer point of view and a comparison between the Randles Model is given with its application in electrochemical impedance spectroscopy and general sensor design. Finally, with the help of the proposed equivalent model, a cohesive explanation of the scan rate of cyclic voltammetry is discussed. The information of this paper can contribute to enriching the knowledge of electrochemical sensor models for scientists and is also able to guide the electronic engineer on designing next-generation sensor layouts.
This work describes a flexible and portable data acquisition system that has been developed to interface to nano and ultra-micro scale electrochemical sensors at the point of use. It can perform a range of voltammetric tests, including Cyclic Voltammetry, Square Wave Voltammetry and Generator Collector Voltammetery. The data acquisition system interfaces to a smartphone, operates from a rechargeable battery and is of suitable form factor to ensure that it's fully portable. By utilising commercially available components, this system has been developed to lower the barrier for entry for the development of emerging portable electrochemical sensing technologies at micro and nano scale. To show the full range of functionality of the system, a use case involving river water quality monitoring is presented through generation of a calibration curve, using a recently developed Tyndall National Institute ultra-microband electrochemical sensor, for the detection of dissolved oxygen in river water.
Global food production needs to increase in order to meet the demands of an ever growing global population. As resources are finite, the most feasible way to meet this demand is to minimize losses and improve efficiency. Regular monitoring of factors like animal health, soil and water quality for example, can ensure that the resources are being used to their maximum efficiency. Existing monitoring techniques however have limitations, such as portability, turnaround time and requirement for additional reagents. In this work, we explore the use of micro- and nano-scale electrode devices, for the development of an electrochemical sensing platform to digitalize a wide range of applications within the agri-food sector. With this platform, we demonstrate the direct electrochemical detection of pesticides, specifically clothianidin and imidacloprid, with detection limits of 0.22 ng/mL and 2.14 ng/mL respectively, and nitrates with a detection limit of 0.2 µM. In addition, interdigitated electrode structures also enable an in-situ pH control technique to mitigate pH as an interference and modify analyte response. This technique is applied to the analysis of monochloramine, a common water disinfectant. Concerning biosensing, the sensors are modified with bio-molecular probes for the detection of both bovine viral diarrhea virus species and antibodies, over a range of 1 ng/mL to 10 µg/mL. Finally, a portable analogue front end electronic reader is developed to allow portable sensing, with control and readout undertaken using a smart phone application. Finally, the sensor chip platform is integrated with these electronics to provide a fully functional end-to-end smart sensor system compatible with emerging Agri-Food digital decision support tools.
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