Formation of amorphous carbon multi-walled nanotubes from random initial configurations

Amorphous carbon nanotubes (a-CNT) with up to four walls and sizes ranging from 200 to 3200 atoms have been simulated, starting from initial random configurations and using the Gaussian Approximation Potential [Phys. Rev. B 95, 094203 (2017)]. The important variables (like density, height, and diameter) required to successfully simulate a-CNTs, were predicted with a machine learning random forest technique. The models were validated $\textit{ex post facto}$ using density functional codes. The a-CNT models ranged from 0.55 nm - 2 nm wide with an average inter-wall spacing of 0.31 nm. The topological defects in a-CNTs were discussed and new defect configurations were observed. The electronic density of states and localization in these phases were discussed and delocalized electrons in the $\pi$ subspace were identified as an important factor for inter-layer cohesion. Spatial projection of the electronic conductivity favors axial transport along connecting hexagons, while non-hexagonal parts of the network either hinder or bifurcate the electronic transport. A vibrational density of states was calculated and is potentially an experimentally testable fingerprint of the material and the appearance of a low-frequency radial breathing mode was discussed. The thermal conductivity at 300 K was calculated using the Green-Kubo formula

Simulation of multi-shell fullerenes using Machine-Learning Gaussian Approximation Potential

Multi-shell fullerenes ”buckyonions” were simulated, starting from initially random configurations, using a density-functional-theory (DFT)-trained machine-learning carbon potential within the Gaussian Approximation Potential (GAP) Framework [Volker L. Deringer and Gábor Csányi, Phys. Rev. B 95, 094203 (2017)]. Fullerenes formed from seven different system sizes, ranging from 60 ∼ 3774 atoms, were considered. The buckyonions are formed by clustering and layering starting from the outermost shell and proceeding inward. Inter-shell cohesion is partly due to interaction between delocalized π electrons protruding into the gallery. The energies of the models were validated ex post facto using density functional codes, VASP and SIESTA, revealing an energy difference within the range of 0.02 - 0.08 eV/atom after conjugate gradient energy convergence of the models was achieved with both methods

Bioelectrical Impedance Analysis (BIA) of Body Segment Composition as an Obesty Assessment Tool Among Jordanians

Bioelectrical impedance analysis (BIA) is a body composition assessing technique for estimating body components; fat, and muscle mass, and body water (BW) by measuring the electrical resistance in ohm (Ω) of those components with response to the flow of a small electrical current through the body. Bioelectrical impedance analysis was used to investigate the relationships between segmental body composition, obesity and body mass index (BMI). The analysis in this study involved the use of InBody 370S equipment to conduct the body composition study of 48 adult participants (30 females and 18 males) at the Applied Science Private University (ASU) School of Pharmacy, Department of Clinical Nutrition and Dietetics, between October, 2019 and January, 2020, Jordan. Anthropometric parameters such as weight, height, body mass index (BMI), and waist-to-hip (W/H) ratio for each individual were measured. The values indicated that BMI of 26.5 for males and 25.42 for females and body composition such as body fat mass (BFM), protein, and visceral fat level (VFL) of females of BMI > 30 was 39.82 compared to 32.60 for males of the same category. The VFL for female individuals was higher than males (13.0 and 17.5) of the same BMI category. The results of BIA analysis, lean body mass, and body muscle mass were found to be significantly (p 30 was 39.82±4.35 compared to 32.6±3.67 for males of the same group. Additionally, the BFM (−3.86**), segmental muscle mass (SMM) was 0.784**, and total body water (TBW) of −0.658** were all indirectly correlated at (p <0.01) with the BIA impedance evaluated as Z(Ω) at 250 kHz. However, the lean mass of the left arm ( −0.662**) and left leg muscle (− 0.514**) were found to be significantly correlated (p < 0.01) and lower in identified obese females compared to non-obese individuals. The findings demonstrate the strong correlation between lean and fat segmental analysis values, and the level of obesity and segmental analysis for male and female individuals can be taken into consideration in obesity and disease prevention

Consumer adoption of Internet banking in Jordan: examining the role of hedonic motivation, habit, self-efficacy and trust

YesDespite the rapid growth of Internet banking (IB), customers in developing countries still hesitate to adopt this technology and its use in the Middle East remains low. This study aims to identify and examine the factors that predict behavioural intention and adoption of IB in Jordan. Four factors – hedonic motivation, habit, self-efficacy and trust – are proposed in a conceptual model. Data was collected by means of a survey with bank customers in Jordan. Structural equation modelling (SEM) was used to analyse the data. The results strongly supported the conceptual model. Further, hedonic motivation, habit, self-efficacy and trust were all confirmed to have a significant influence on behavioural intention. Trust was found to be strongly predicted by both hedonic motivation and self-efficacy. This study provides both academics and practitioners with an insight into the factors that can be used to encourage customer adoption of IB specifically in a Middle East context