Electrochemical-Based Biosensors on Different Zinc Oxide Nanostructures: A Review.

Electrochemical biosensors have shown great potential in the medical diagnosis field. The performance of electrochemical biosensors depends on the sensing materials used. ZnO nanostructures play important roles as the active sites where biological events occur, subsequently defining the sensitivity and stability of the device. ZnO nanostructures have been synthesized into four different dimensional formations, which are zero dimensional (nanoparticles and quantum dots), one dimensional (nanorods, nanotubes, nanofibers, and nanowires), two dimensional (nanosheets, nanoflakes, nanodiscs, and nanowalls) and three dimensional (hollow spheres and nanoflowers). The zero-dimensional nanostructures could be utilized for creating more active sites with a larger surface area. Meanwhile, one-dimensional nanostructures provide a direct and stable pathway for rapid electron transport. Two-dimensional nanostructures possess a unique polar surface for enhancing the immobilization process. Finally, three-dimensional nanostructures create extra surface area because of their geometric volume. The sensing performance of each of these morphologies toward the bio-analyte level makes ZnO nanostructures a suitable candidate to be applied as active sites in electrochemical biosensors for medical diagnostic purposes. This review highlights recent advances in various dimensions of ZnO nanostructures towards electrochemical biosensor applications.

Effect of solution pH and adsorbent concentration on the sensing parameters of TGN-based electrochemical sensor.

The response of trilayer graphene nanoribbon (TGN)-based ion-sensitive field-effect transistor (ISFET) to different pH solutions and adsorption effect on the sensing parameters are analytically studied in this research. The authors propose a TGN-based sensor to electrochemically detect pH. To this end, absorption effect on the sensing area in the form of carrier concentration, carrier velocity, and conductance variations are investigated. Also, the caused electrical response on TGN as a detection element is analytically proposed, in which significant current decrease of the sensor is observed after exposure to high pH values. In order to verify the accuracy of the model, it is compared with recent reports on pH sensors. The TGN-based pH sensor exposes higher current compared to that of carbon nanotube (CNT) counterpart for analogous ambient conditions. While, the comparative results demonstrate that the conductance of proposed model is lower than that of monolayer graphene-counterpart for equivalent pH values. The results confirm that the conductance of the sensor is decreased and Vg-min is obviously right-shifted by increasing value of pH. The authors demonstrate that although there is not the experimental evidence reported in the part of literature for TGN sensor, but the model can assist in comprehending experiments involving nanoscale pH sensors.

A carrier velocity model for electrical detection of gas molecules.

Nanomaterial-based sensors with high sensitivity, fast response and recovery time, large detection range, and high chemical stability are in immense demand for the detection of hazardous gas molecules. Graphene nanoribbons (GNRs) which have exceptional electrical, physical, and chemical properties can fulfil all of these requirements. The detection of gas molecules using gas sensors, particularly in medical diagnostics and safety applications, is receiving particularly high demand. GNRs exhibit remarkable changes in their electrical characteristics when exposed to different gases through molecular adsorption. In this paper, the adsorption effects of the target gas molecules (CO and NO) on the electrical properties of the armchair graphene nanoribbon (AGNR)-based sensor are analytically modelled. Thus, the energy dispersion relation of AGNR is developed considering the molecular adsorption effect using a tight binding (TB) method. The carrier velocity is calculated based on the density of states (DOS) and carrier concentration (n) to obtain I-V characteristics and to monitor its variation in the presence of the gas molecules. Furthermore, the I-V characteristics and energy band structure of the AGNR sensor are simulated using first principle calculations to investigate the gas adsorption effects on these properties. To ensure the accuracy of the proposed model, the I-V characteristics of the AGNR sensor that are simulated based both on the proposed model and first principles calculations are compared, and an acceptable agreement is achieved.

Toxic metals in Perna viridis mussel and surface seawater in Pasir Gudang coastal area, Malaysia, and its health implications.

Contamination of toxic metals in P. viridis mussels has been prevalently reported; hence, health risk assessment for consuming this aquaculture product as well as the surrounding surface seawater at its harvesting sites appears relevant. Since Kampung Pasir Puteh, Pasir Gudang is the major harvesting site in Malaysia, and because the last heavy metal assessment was done in 2009, its current status remains unclear. Herein, flame atomic absorption spectrometry and flow injection mercury/hydride system were used to determine the concentrations of Pb, Cd, Cu and total Hg in P. viridis mussels and surface seawater (January-March 2015), respectively. Significantly higher concentrations of these metals were found in P. viridis mussels (p < 0.05) than that of surface seawater samples. The concentrations for Pb (4.27-6.55 µg/g) and Cd (1.55-2.21 µg/g) in P. viridis mussels exceeded the maximum permitted proportion prescribed by the Malaysian law. The concentrations of all metals in surface seawater also violated the Malaysia Marine Water Quality Criteria and Standards. Significant (p < 0.05) and high strength of association (r = 0.787) observed between Pb concentration in P. viridis mussel with the surface seawater indicates its possible application for inferring Pb concentrations in the mussel. Since both the calculated target hazard quotient and hazard index for Pb and Cd exceeded 1, the possible detrimental health impacts on human for consuming P. viridis mussels from this rearing site cannot be ignored. Hence, promoting continuous monitoring programmes and developing efficient toxic metal removal techniques prior to entering the market are required.

Experimental and theoretical investigation of sensing parameters in carbon nanotube-based DNA sensor.

Nowadays, sensitive biosensors with high selectivity, lower costs and short response time are required for detection of DNA. The most preferred materials in DNA sensor designing are nanomaterials such as carbon and Au nanoparticles, because of their very high surface area and biocompatibility which lead to performance and sensitivity improvements in DNA sensors. Carbon nanomaterials such as carbon nanotubes (CNTs) can be considered as a suitable DNA sensor platform due to their high surface-to-volume ratio, favourable electronic properties and fast electron transfer rate. Therefore, in this study, the CNTs which are synthesised by pulsed AC arc discharge method on a high-density polyethylene substrate are used as conducting channels in a chemiresistor for the electrochemical detection of double stranded DNA. Moreover, the response of the proposed sensor is investigated experimentally and analytically in different temperatures, which confirm good agreement between the presented model and experimental data.

Graphene Based Biosensor Model for Escherichia Coli Bacteria Detection.

As a new nanomaterial, graphene demonstrates great potential as an electrode for biomedical applications in sensing molecules and cells. Thus, development of biosensors based on graphene is gaining much interest due to its exceptional properties such as, large surface-to-volume ratio, high conductivity and high flexibility. In this work a liquid gated graphene field effect transistor based biosensor model is analytically developed for electrical detection of Escherichia Coli O157:H7 bacteria. The effect of graphene functionalization on the graphene conductance in the presence of E. coli is investigated. E. coli absorption effects on the graphene surface in the form of conductance variation are considered. Therefore the graphene conductance as a function of E. coli concentration which controls the current­voltage characteristics of biosensors is presented. According to the simulated results, the proposed sensor model can be applied as a powerful tool to predict the biosensor performance.

Analytical performance of 3 m and 3 m +1 armchair graphene nanoribbons under uniaxial strain.

The electronic band structure and carrier density of strained armchair graphene nanoribbons (AGNRs) with widths of n =3 m and n =3 m +1 were examined using tight-binding approximation. The current-voltage (I-V) model of uniaxial strained n =3 m AGNRs incorporating quantum confinement effects is also presented in this paper. The derivation originates from energy dispersion throughout the entire Brillouin zone of uniaxial strained AGNRs based on a tight-binding approximation. Our results reveal the modification of the energy bandgap, carrier density, and drain current upon strain. Unlike the two-dimensional graphene, whose bandgap remains near to zero even when a large strain is applied, the bandgap and carrier density of AGNRs are shown to be sensitive to the magnitude of uniaxial strain. Discrepancies between the classical calculation and quantum calculation were also measured. It has been found that as much as 19% of the drive current loss is due to the quantum confinement. These analytical models which agree well with the experimental and numerical results provide physical insights into the characterizations of uniaxial strained AGNRs.

Graphene nanoribbon field-effect transistor at high bias.

Combination of high-mean free path and scaling ability makes graphene nanoribbon (GNR) attractive for application of field-effect transistors and subject of intense research. Here, we study its behaviour at high bias near and after electrical breakdown. Theoretical modelling, Monte Carlo simulation, and experimental approaches are used to calculate net generation rate, ionization coefficient, current, and finally breakdown voltage (BV). It is seen that a typical GNR field-effect transistor's (GNRFET) breakdown voltage is in the range of 0.5 to 3 V for different channel lengths, and compared with silicon similar counterparts, it is less. Furthermore, the likely mechanism of breakdown is studied.

Analytical development and optimization of a graphene-solution interface capacitance model.

Graphene, which as a new carbon material shows great potential for a range of applications because of its exceptional electronic and mechanical properties, becomes a matter of attention in these years. The use of graphene in nanoscale devices plays an important role in achieving more accurate and faster devices. Although there are lots of experimental studies in this area, there is a lack of analytical models. Quantum capacitance as one of the important properties of field effect transistors (FETs) is in our focus. The quantum capacitance of electrolyte-gated transistors (EGFETs) along with a relevant equivalent circuit is suggested in terms of Fermi velocity, carrier density, and fundamental physical quantities. The analytical model is compared with the experimental data and the mean absolute percentage error (MAPE) is calculated to be 11.82. In order to decrease the error, a new function of E composed of α and ß parameters is suggested. In another attempt, the ant colony optimization (ACO) algorithm is implemented for optimization and development of an analytical model to obtain a more accurate capacitance model. To further confirm this viewpoint, based on the given results, the accuracy of the optimized model is more than 97% which is in an acceptable range of accuracy.

Use of pilot plant scale continuous fryer to simulate industrial production of potato chips: thermal properties of palm olein blends under continuous frying conditions.

Binary blends of palm olein (PO) with sunflower oil (SFO), canola oil (CNO), and cottonseed oil (CSO) were formulated to assess their stability under continuous frying conditions. The results were then compared with those obtained in PO. The oil blends studied were: (1) 60:40 for PO + SFO; (2) 70:30 for PO + CNO; and (3) 50:50 for PO + CSO. The PO and its blends were used to fry potato chips at 180°C for a total of 56 h of operation. The evolution of analytical parameters such as tocols, induction period, color, p-anisidine value, free fatty acid, smoke point, polar compounds, and polymer compounds were evaluated over the frying time. Blending PO with unsaturated oils was generally proved to keep most qualitative parameters comparable to those demonstrated in PO. Indeed, none of the oils surpassed the legislative limits for used frying. Overall, it was noted that oil containing PO and SFO showed higher resistance toward oxidative and hydrolytic behaviors as compared to the other oil blends.

Analytical modeling of glucose biosensors based on carbon nanotubes.

In recent years, carbon nanotubes have received widespread attention as promising carbon-based nanoelectronic devices. Due to their exceptional physical, chemical, and electrical properties, namely a high surface-to-volume ratio, their enhanced electron transfer properties, and their high thermal conductivity, carbon nanotubes can be used effectively as electrochemical sensors. The integration of carbon nanotubes with a functional group provides a good and solid support for the immobilization of enzymes. The determination of glucose levels using biosensors, particularly in the medical diagnostics and food industries, is gaining mass appeal. Glucose biosensors detect the glucose molecule by catalyzing glucose to gluconic acid and hydrogen peroxide in the presence of oxygen. This action provides high accuracy and a quick detection rate. In this paper, a single-wall carbon nanotube field-effect transistor biosensor for glucose detection is analytically modeled. In the proposed model, the glucose concentration is presented as a function of gate voltage. Subsequently, the proposed model is compared with existing experimental data. A good consensus between the model and the experimental data is reported. The simulated data demonstrate that the analytical model can be employed with an electrochemical glucose sensor to predict the behavior of the sensing mechanism in biosensors.

The effect of uniaxial strain on graphene nanoribbon carrier statistic.

: Armchair graphene nanoribbon (AGNR) for n=3m and n=3m+1 family carrier statistic under uniaxial strain is studied by means of an analytical model based on tight binding approximation. The uniaxial strain of AGNR carrier statistic models includes the density of state, carrier concentration, and carrier velocity. From the simulation, it is found that AGNR carrier concentration has not been influenced by the uniaxial strain at low normalized Fermi energy for n=3m and n=3m+1. In addition, the carrier velocity of AGNR is mostly affected by strain at high concentration of n≈3.0×107 and 1.0 × 107 m-1 for n=3m and n=3m+1, respectively. The result obtained gives physical insight into the understanding of uniaxial strain in AGNR.

Analytical modeling of trilayer graphene nanoribbon Schottky-barrier FET for high-speed switching applications.

Recent development of trilayer graphene nanoribbon Schottky-barrier field-effect transistors (FETs) will be governed by transistor electrostatics and quantum effects that impose scaling limits like those of Si metal-oxide-semiconductor field-effect transistors. The current-voltage characteristic of a Schottky-barrier FET has been studied as a function of physical parameters such as effective mass, graphene nanoribbon length, gate insulator thickness, and electrical parameters such as Schottky barrier height and applied bias voltage. In this paper, the scaling behaviors of a Schottky-barrier FET using trilayer graphene nanoribbon are studied and analytically modeled. A novel analytical method is also presented for describing a switch in a Schottky-contact double-gate trilayer graphene nanoribbon FET. In the proposed model, different stacking arrangements of trilayer graphene nanoribbon are assumed as metal and semiconductor contacts to form a Schottky transistor. Based on this assumption, an analytical model and numerical solution of the junction current-voltage are presented in which the applied bias voltage and channel length dependence characteristics are highlighted. The model is then compared with other types of transistors. The developed model can assist in comprehending experiments involving graphene nanoribbon Schottky-barrier FETs. It is demonstrated that the proposed structure exhibits negligible short-channel effects, an improved on-current, realistic threshold voltage, and opposite subthreshold slope and meets the International Technology Roadmap for Semiconductors near-term guidelines. Finally, the results showed that there is a fast transient between on-off states. In other words, the suggested model can be used as a high-speed switch where the value of subthreshold slope is small and thus leads to less power consumption.

Antioxidative properties of Pandanus amaryllifolius leaf extracts in accelerated oxidation and deep frying studies.

The potential uses of Pandanus amaryllifolius leaf extract as a natural antioxidant were evaluated in refined, bleached and deodorized (RBD) palm olein, using accelerated oxidation and deep frying studies at 180°C from 0 to 40h. The extracts (optimum concentration 0.2%) significantly retarded oil oxidation and deterioration (P<0.05), comparably to 0.02% BHT in tests such as peroxide value, anisidine value, iodine value, free fatty acid, oxidative stability index (OSI), polar and polymer compound contents. In sensory evaluation studies, different batches of French fries were not significantly different (P<0.05) from one another for oiliness, crispiness, taste and overall acceptability when the same oil was used for up to the 40th hour of frying. P. amaryllifolius leaf extract, which had a polyphenol content of 102mg/g, exhibited an excellent heat-stable antioxidant property and may be a good natural alternative to existing synthetic antioxidants in the food industry.

Palm oil and palm olein frying applications.

Several million tones of palm oil and palm olein are used annually in the world for frying. This paper will discuss their frying performances in three major applications - industrial production of potato chips/crisps, industrial production of pre-fried frozen French fries and in fast food outlets. In the first study, about four tones of potato chips were continuously fried 8 hours a day and five days a week. The palm olein used (with proper management) performed well and was still in excellent condition and usable at the end of the trial. This was reflected in its low free fatty acid (FFA) content of around 0.23%, peroxide value of 4 meq/kg, anisidine value of 16, low polar and polymer contents of 10% and 2%, respectively, induction period (OSI) of 21 hours and high content of tocopehrols and tocotrienols of 530 ppm even after >1900 hours. In the second study in which an average 12 tones pre-fried frozen French fries were continuously fried a day for 5 days a week, palm oil performed excellently as reflected by its low FFA of 0.34%, food oil sensor reading of 1.1, low polar and polymer contents of 17% and 2.8%, respectively, over the 12 days of trial. In the third study in which palm shortening, palm oil and palm olein were simultaneously used to intermittently fry chicken parts in the laboratory simulating the conditions in fast food outlets, the three frying oils also performed very satisfactorily as reflected by their reasonably low FFA of <1%, smoke points of >180 degrees C, and polar and polymer contents of <25% and <6%, respectively, after 5 days of consecutive frying. All the quality indicators did not exceed the maximum discard points for frying oils/fats in the three applications, while the fried food product was well accepted by the in-house train sensory panel using a-nine point hedonic score.