ALBERT

Description: The problem associated with mixtures of fillers and polymers is that they result in mechanical degradation of the material (polymer) as the filler content increases. This problem will increase the weight of the material and manufacturing cost. For this reason, experimentation on the electrical conductivities of the polymer-composites (PCs) is not enough to research their electrical properties; models have to be adopted to solve the encountered challenges. Hitherto, several models by previous researchers have been developed and proposed, with each utilizing different design parameters. It is imperative to carry out analysis on these models so that the suitable one is identified. This paper indeed carried out a comprehensive parametric analysis on the existing electrical conductivity models for polymer composites. The analysis involves identification of the parameters that best predict the electrical conductivity of polymer composites for energy storage, viz: (batteries and capacitor), sensors, electronic device components, fuel cell electrodes, automotive, medical instrumentation, cathode scanners, solar cell, and military surveillance gadgets applications. The analysis showed that the existing models lack sufficient parametric ability to determine accurately the electrical conductivity of polymer-composites.

Description: We investigated total electron content (TEC) at Ilorin (8.50∘ N 4.65∘ E, dip lat. 2.95) for the year 2010, a year of low solar activity in 2010 with Rz=15.8. The investigation involved the use of TEC derived from GPS, estimated TEC from digisonde portable sounder data (DPS), and the International Reference Ionosphere (IRI) and NeQuick 2 (NeQ) models. During the sunrise period, we found that the rate of increase in DPS TEC, IRI TEC, and NeQ TEC was higher compared with GPS TEC. One reason for this can be attributed to an overestimation of plasmaspheric electron content (PEC) contribution in modeled TEC and DPS TEC. A correction factor around the sunrise, where our finding showed a significant percentage deviation between the modeled TEC and GPS TEC, will correct the differences. Our finding revealed that during the daytime when PEC contribution is known to be absent or insignificant, GPS TEC and DPS TEC in April, September, and December predict TEC very well. The lowest discrepancies were observed in May, June, and July (June solstice) between the observed values and all the model values at all hours. There is an overestimation in DPS TEC that could be due to extrapolation error while integrating from the peak electron density of F2 (NmF2) to around ∼1000 km in the Ne profile. The underestimation observed in NeQ TEC must have come from the inadequate representation of contribution from PEC on the topside of the NeQ model profile, whereas the exaggeration of PEC contribution in IRI TEC amounts to overestimation in GPS TEC. The excess bite-out observed in DPS TEC and modeled TEC indicates over-prediction of the fountain effect in these models. Therefore, the daytime bite-out observed in these models requires a modifier that could moderate the perceived fountain effect morphology in the models accordingly. The daytime DPS TEC performs better than the daytime IRI TEC and NeQ TEC in all the months. However, the dusk period requires attention due to the highest percentage deviation recorded, especially for the models, in March, November, and December. Seasonally, we found that all the TECs maximize and minimize during the March equinox and June solstice, respectively. Therefore, GPS TEC and modeled TEC reveal the semiannual variations in TEC.

Description: Rate of change of TEC (ROT) and its index (ROTI) are considered a good proxy to characterize the occurrence of ionospheric plasma irregularities like those observed after sunset at low latitudes. SBASs (satellite-based augmentation systems) are civil aviation systems that provide wide-area or regional improvement to single-frequency satellite navigation using GNSS (Global Navigation Satellite System) constellations. Plasma irregularities in the path of the GNSS signal after sunset cause severe phase fluctuations and loss of locks of the signals in GNSS receiver at low-latitude regions. ROTI is used in this paper to characterize plasma density ionospheric irregularities in central–western Africa under nominal and disturbed conditions and identified some days of irregularity inhibition. A specific low-latitude algorithm is used to emulate potential possible SBAS message using real GNSS data in the western African low-latitude region. The performance of a possible SBAS operation in the region under different ionospheric conditions is analysed. These conditions include effects of geomagnetic disturbed periods when SBAS performance appears to be enhanced due to ionospheric irregularity inhibition. The results of this paper could contribute to a feasibility assessment of a European Geostationary Navigation Overlay System-based SBAS in the sub-Saharan African region.

Description: We investigated total electron content (TEC) at Ilorin (8.50°N 4.65°E, dip lat. 2.95) during a low solar activity 2010. The investigation involved the use of GPS derived TEC, TEC estimated from digisonde portable sounder data (DPS-TEC), the International Reference Ionosphere model (IRI-TEC) and NeQuick 2 model (NeQ-TEC). The five most quietest days of the months obtained from the international quiet days (IQD) from the website http://www.ga.gov.au/oracle/geomag/iqd_form.jsp were used for the investigation. During the sunrise period, we found that the rate of increases in DPS-TEC, IRI-TEC and NeQ-TEC were higher with respect to GPS-TEC. One reason for this can be alluded to an overestimation of plasmaspheric electron content (PEC) contribution in modeled TEC and DPS-TEC. A correction factor around the sunrise where a significant percentage difference of overestimations between the modeled TEC and GPS-TEC was obtained will correct the differences. Our finding revealed that during the daytime when PEC contribution is known to be absent or insignificant, GPS-TEC and DPS-TEC in April, September and December predicts TEC very well. The lowest discrepancies were observed in May, June and July (June solstice) between the observed and all the model values in all hours. There is an overestimation in DPS-TEC that could be due to extrapolation error while integrating from the peak electron density of F2 (NmF2) to around ~1000km in the Ne profile. The underestimation observed in NeQ-TEC must have come from the inadequate representation of contribution from PEC on the topside of NeQ model profile whereas the exaggeration of PEC contribution in IRI-TEC amount to overestimations of GPS-TEC. The excess bite-out observed in DPS-TEC and NeQ-TEC show the indication of overprediction of fountain effect in these models. Therefore, the daytime bite-out observed in these two models require a modifier that could moderate the perceived fountain effect morphology in the models accordingly. Seasonally, we found that all the TECs maximize and minimize during the March equinox and June solstice, respectively. Therefore, GPS-, DPS-, IRI- and NeQ-TEC reveal the semi-annual variations in TEC as reported in all regions. The daytime DPS-TEC performs better than the daytime IRI-TEC and NeQ-TEC in all the months, however, the dusk period requires attention due to highest percentage difference recorded especially for DPS-TEC and the models in March, and November and December for DPS-TEC.

Description: This study was undertaken to forecast the waste generation rates of the accommodation sector in North Cyprus. Three predictor models, multiple linear regression (MLR), artificial neural networks (ANNs) and central composite design (CCD), were applied to predict the waste generation rate during the lean and peak seasons. ANN showed highest prediction performance, specifically, lowest values of the standard error of prediction (SEP = 2.153), mean absolute error (MAE = 1.378) and highest R2 value (0.998) confirmed the accuracy of the model. The analysed waste was categorised into recyclable, general waste and food residue. The authors estimated the total waste generated during the lean season at 2010.5 kg/day, in which large hotels accounted for the largest fraction (66.7%), followed by medium-sized hotels (19.4%) and guesthouses (2.6%). During the peak season, about 49.6% increases in waste generation rates were obtained. Interestingly, 45% of the waste was generated by British tourists, while the least waste was generated by African tourists (7.5%). The ANN predicted that small and large hotels would produce 5.45 and 22.24 tons of waste by the year 2020, respectively. The findings herein are promising and useful in establishing a sustainable waste management system.

Description: This study evaluated pawpaw (Carica papaya) peel ash as a green solid base catalyst for Moringa oleifera oil methyl esters (MOOME) production. Taguchi orthogonal array approach was used to examine the impact of vital process input variables (calcined pawpaw peel (CPP) loading, reaction temperature, methanol-to-M. oleifera oil (MeOH:MOO) molar ratio and reaction time) on the MOOME yield. Catalytic potency potential of the CPP was evaluated by Fourier transform infrared (FTIR), Barrett-Joyner-Halenda (BJH), Brunauer-Emmett-Teller (BET), scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDX) and X-ray diffraction (XRD) methods. The results obtained indicate that the CPP consists of nanoparticles and alkaline elements K (23.89 wt.%), Ca (2.86 wt.%) and Mg (1.00 wt.%). The high values of coefficient of determination, R2 (0.9992) and adjusted R2 (0.9968) as well as the low value of the coefficient of variation (0.31%) for the model developed indicate it can be used to sufficiently describe the transesterification process. MOOME yield of 96.43 ± 0.10 wt.% was achieved at the optimum values of 3.5 wt.% CPP loading, 9:1 MeOH:MOO molar ratio, 35 °C reaction temperature and 40 min reaction time. The kinetic modeling of the transesterification process determined the reaction rate constant and overall reaction order as 0.20465 L·mol−1·s−1 and 2, respectively. The results of this study demonstrate both CPP and MOO are feasible renewable resources for MOOME production. The kinetic data generated may be useful in reactor design for the transesterification process.

Description: In this study, the electrical properties of graphene–polypyrrole (graphene-PPy) nanocomposites were thoroughly investigated. A numerical model, based on the Simmons and McCullough equations, in conjunction with the Monte Carlo simulation approach, was developed and used to analyze the effects of the thickness of the PPy, aspect ratio diameter of graphene nanorods, and graphene intrinsic conductivity on the transport of electrons in graphene–PPy–graphene regions. The tunneling resistance is a critical factor determining the transport of electrons in composite devices. The junction capacitance of the composite was predicted. A composite with a large insulation thickness led to a poor electrochemical electrode. The dependence of the electrical conductivity of the composite on the volume fraction of the filler was studied. The results of the developed model are consistent with the percolation theory and measurement results reported in literature. The formulations presented in this study can be used for optimization, prediction, and design of polymer composite electrical properties.

Description: In this study, a hybrid of graphene nanoplatelets with a polypyrrole having 20 wt.% loading of carbon-black (HGPPy.CB20%), has been fabricated. The thermal stability, structural changes, morphology, and the electrical conductivity of the hybrids were investigated using thermogravimetric analyzer, differential scanning calorimeter, X-ray diffraction analyzer, scanning electron microscope, and laboratory electrical conductivity device. The morphology of the hybrid shows well dispersion of graphene nanoplatelets on the surface of the PPy.CB20% and the transformation of the gravel-like PPy.CB20% shape to compact spherical shape. Moreover, the hybrid’s electrical conductivity measurements showed percolation threshold at 0.15 wt.% of the graphene nanoplatelets content and the curve is non-linear. The electrical conductivity data were analyzed by comparing different existing models (Weber, Clingerman and Taherian). The results show that Taherian and Clingerman models, which consider the aspect ratio, roundness, wettability, filler electrical conductivity, surface interaction, and volume fractions, closely described the experimental data. From these results, it is evident that Taherian and Clingerman models can be modified for better prediction of the hybrids electrical conductivity measurements. In addition, this study shows that graphene nanoplatelets are essential and have a significant influence on the modification of PPy.CB20% for energy storage applications.