In this study the authors report on the development of a new type of electronic nose (e-nose) instrument, which the authors refer to as the Portable electronic Mucosa (PeM) as a continuation of previous research. It is designed to mimic the human nose by taking significant biological features and replicating them electronically. The term electronic mucosa or simply e-mucosa was used because our e-nose emulates the nasal chromatographic effect discovered in the olfactory epithelium, located within the upper turbinate. The e-mucosa generates spatio-temporal information that the authors believe could lead to improved odour discrimination. The PeM comprises three large sensor arrays each containing a total of 576 sensors, with 24 different coatings, to increase the odour selectivity. The nasal chromatographic effect provides temporal information in the human olfactory system, and is mimicked here using two-coated retentive channels. These channels are coated with polar and non-polar compounds to enhance the selectivity of the instrument. Thus, for an unknown sample, the authors have both the spatial information (as with a traditional e-nose) and the temporal information. The authors believe that this PeM may offer a way forward in developing a new range of low-cost e-noses with superior odour specificity.
Graphene has attracted great interest because of unique properties such as high sensitivity, high mobility, and biocompatibility. It is also known as a superior candidate for pH sensing. Graphene-based ion-sensitive field-effect transistor (ISFET) is currently getting much attention as a novel material with organic nature and ionic liquid gate that is intrinsically sensitive to pH changes. pH is an important factor in enzyme stabilities which can affect the enzymatic reaction and broaden the number of enzyme applications. More accurate and consistent results of enzymes must be optimized to realize their full potential as catalysts accordingly. In this paper, a monolayer graphene-based ISFET pH sensor is studied by simulating its electrical measurement of buffer solutions for different pH values. Electrical detection model of each pH value is suggested by conductance modelling of monolayer graphene. Hydrogen ion (H+) concentration as a function of carrier concentration is proposed, and the control parameter (Ƥ) is defined based on the electro-active ions absorbed by the surface of the graphene with different pH values. Finally, the proposed new analytical model is compared with experimental data and shows good overall agreement.
Neuroimaging is a new technique used to create images of the structure and function of the nervous system in the human brain. Currently, it is crucial in scientific fields. Neuroimaging data are becoming of more interest among the circle of neuroimaging experts. Therefore, it is necessary to develop a large amount of neuroimaging tools. This paper gives an overview of the tools that have been used to image the structure and function of the nervous system. This information can help developers, experts, and users gain insight and a better understanding of the neuroimaging tools available, enabling better decision making in choosing tools of particular research interest. Sources, links, and descriptions of the application of each tool are provided in this paper as well. Lastly, this paper presents the language implemented, system requirements, strengths, and weaknesses of the tools that have been widely used to image the structure and function of the nervous system.