The effect of microwaves on the functionalization of single-walled carbon nanotubes (SWNTs) by the diazonium method was studied. The usage of a new approach led to the identification of the strength of the interaction (physical or chemical) between the functional groups and the carbon nanotube surface. Moreover, the nature (chemical formula) of the adsorbed/grafted functional groups was determined. According to thermogravimetric analysis coupled with mass spectrometry and Raman spectroscopy, the optimal functionalization level was reached after 5 min of reaction. Prolonged reaction times can lead to undesired reactions such as defunctionalization, solvent addition and polymerization of the grafted functions. The strength (chemi- vs physisorption) of the bonds between the grafted functional groups and the SWNTs is discussed showing the occurrence of physical adsorption as a consequence of defunctionalization after 15 min of reaction under microwaves. Several chemical mechanisms of grafting could be identified, and it was possible to distinguish conditions leading to the desired chemical grafting from those leading to undesired reactions such as physisorption and polymerization.
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 β 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.
Carbon, in its variety of allotropes, especially graphene and carbon nanotubes (CNTs), holds great potential for applications in variety of sensors because of dangling π-bonds that can react with chemical elements. In spite of their excellent features, carbon nanotubes (CNTs) and graphene have not been fully exploited in the development of the nanoelectronic industry mainly because of poor understanding of the band structure of these allotropes. A mathematical model is proposed with a clear purpose to acquire an analytical understanding of the field-effect-transistor (FET) based gas detection mechanism. The conductance change in the CNT/graphene channel resulting from the chemical reaction between the gas and channel surface molecules is emphasized. NH3 has been used as the prototype gas to be detected by the nanosensor and the corresponding current-voltage (I-V) characteristics of the FET-based sensor are studied. A graphene-based gas sensor model is also developed. The results from graphene and CNT models are compared with the experimental data. A satisfactory agreement, within the uncertainties of the experiments, is obtained. Graphene-based gas sensor exhibits higher conductivity compared to that of CNT-based counterpart for similar ambient conditions.
We report a sonochemical method of functionalizing superparamagnetic iron oxide nanoparticles (SPION) with (3-aminopropyl)triethoxysilane (APTES). Mechanical stirring, localized hot spots and other unique conditions generated by an acoustic cavitation (sonochemical) process were found to induce a rapid silanization reaction between SPION and APTES. FTIR, XPS and XRD measurements were used to demonstrate the grafting of APTES on SPION. Compared to what was reported in literature, the results showed that the silanization reaction time was greatly minimized. More importantly, the product displayed superparamagnetic behaviour at room temperature with a more than 20% higher saturation magnetization.
Various types of carbon-based and non-carbon-based catalyst supports for nitric oxide (NO) removal through selective catalytic reduction (SCR) with ammonia are examined in this review. A number of carbon-based materials, such as carbon nanotubes (CNTs), activated carbon (AC), and graphene (GR) and non-carbon-based materials, such as Zeolite Socony Mobil-5 (ZSM-5), TiO2, and Al2O3 supported materials, were identified as the most up-to-date and recently used catalysts for the removal of NO gas. The main focus of this review is the study of catalyst preparation methods, as this is highly correlated to the behaviour of NO removal. The general mechanisms involved in the system, the Langmuir-Hinshelwood or Eley-Riedeal mechanism, are also discussed. Characterisation analysis affecting the surface and chemical structure of the catalyst is also detailed in this work. Finally, a few major conclusions are drawn and future directions for work on the advancement of the SCR-NH3 catalyst are suggested.
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.