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In the present work, a thermal treatment technique is applied for the synthesis of CexSn1−xO2 nanoparticles. Using this method has developed understanding of how lower and higher precursor values affect the morphology, structure, and optical properties of CexSn1−xO2 nanoparticles. CexSn1−xO2 nanoparticle synthesis involves a reaction between cerium and tin sources, namely, cerium nitrate hexahydrate and tin (II) chloride dihydrate, respectively, and the capping agent, polyvinylpyrrolidone (PVP). The findings indicate that lower x values yield smaller particle size with a higher energy band gap, while higher x values yield a larger particle size with a smaller energy band gap. Thus, products with lower x values may be suitable for antibacterial activity applications as smaller particles can diffuse through the cell wall faster, while products with higher x values may be suitable for solar cell energy applications as more electrons can be generated at larger particle sizes. The synthesized samples were profiled via a number of methods, such as scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FT-IR). As revealed by the XRD pattern analysis, the CexSn1−xO2 nanoparticles formed after calcination reflect the cubic fluorite structure and cassiterite-type tetragonal structure of CexSn1−xO2 nanoparticles. Meanwhile, using FT-IR analysis, Ce-O and Sn-O were confirmed as the primary bonds of ready CexSn1−xO2 nanoparticle samples, whilst TEM analysis highlighted that the average particle size was in the range 6−21 nm as the precursor concentration (Ce(NO3)3·6H2O) increased from 0.00 to 1.00. Moreover, the diffuse UV-visible reflectance spectra used to determine the optical band gap based on the Kubelka–Munk equation showed that an increase in x value has caused a decrease in the energy band gap and vice versa.
Naif Mohammed Al-Hada; Rafiziana Md. Kasmani; Hairoladenan Kasim; Abbas M. Al-Ghaili; Muneer Aziz Saleh; Essam M. Banoqitah; Abdulsalam M. Alhawsawi; Anwar Ali Baqer; Jian Liu; Shicai Xu; Qiang Li; Azlan Muhammad Noorazlan; Abdullah A. A. Ahmed; Moayad Husein Flaifel; Suriati Paiman; Nazirul Nazrin; Bandar Ali Al-Asbahi; Jihua Wang. The Effect of Precursor Concentration on the Particle Size, Crystal Size, and Optical Energy Gap of CexSn1−xO2 Nanofabrication. Nanomaterials 2021, 11, 2143 .
AMA StyleNaif Mohammed Al-Hada, Rafiziana Md. Kasmani, Hairoladenan Kasim, Abbas M. Al-Ghaili, Muneer Aziz Saleh, Essam M. Banoqitah, Abdulsalam M. Alhawsawi, Anwar Ali Baqer, Jian Liu, Shicai Xu, Qiang Li, Azlan Muhammad Noorazlan, Abdullah A. A. Ahmed, Moayad Husein Flaifel, Suriati Paiman, Nazirul Nazrin, Bandar Ali Al-Asbahi, Jihua Wang. The Effect of Precursor Concentration on the Particle Size, Crystal Size, and Optical Energy Gap of CexSn1−xO2 Nanofabrication. Nanomaterials. 2021; 11 (8):2143.
Chicago/Turabian StyleNaif Mohammed Al-Hada; Rafiziana Md. Kasmani; Hairoladenan Kasim; Abbas M. Al-Ghaili; Muneer Aziz Saleh; Essam M. Banoqitah; Abdulsalam M. Alhawsawi; Anwar Ali Baqer; Jian Liu; Shicai Xu; Qiang Li; Azlan Muhammad Noorazlan; Abdullah A. A. Ahmed; Moayad Husein Flaifel; Suriati Paiman; Nazirul Nazrin; Bandar Ali Al-Asbahi; Jihua Wang. 2021. "The Effect of Precursor Concentration on the Particle Size, Crystal Size, and Optical Energy Gap of CexSn1−xO2 Nanofabrication." Nanomaterials 11, no. 8: 2143.
High atomic number nanoparticles are of increasing interest in radiotherapy due to their significant positive impact on the local dose applied to the treatment site. In this work, three types of metal nanoparticles were utilized to investigate their dose enhancement based on the GATE Monte Carlo simulation tool. Gold, gadolinium, and silver were implanted at three different concentrations to a 1 cm radius sphere to mimic a cancerous tumor inside a 10 × 10 × 30 cm3 water phantom. The innermost layer of the tumor represents a necrotic region, where the metal nanoparticles uptake is assumed to be zero, arising from hypoxic conditions. The nanoparticles were defined using the mixture technique, where nanoparticles are added to the chemical composition of the tumor. A directional 2 × 2 cm2 monoenergetic photon beam was used with several energies ranging from 50 keV to 4000 keV. The dose enhancement factor (DEF) was measured for all three metal nanoparticles under all beam energies. The maximum DEF was ~7 for silver nanoparticles with the 50 keV beam energy at the highest nanoparticle concentration of 30 mg/g of water. Gold followed the same trend as it registered the highest DEF at the 50 keV beam energy with the highest concentration of nanoparticles at 30 mg/g, while gadolinium registered the highest at 100 keV.
Fouad Abolaban; Eslam Taha; Abdulsalam Alhawsawi; Fathi Djouider; Essam Banoqitah; Andrew Nisbet. Estimation of Dose Enhancement for Inhomogeneous Distribution of Nanoparticles: A Monte Carlo Study. Applied Sciences 2021, 11, 4900 .
AMA StyleFouad Abolaban, Eslam Taha, Abdulsalam Alhawsawi, Fathi Djouider, Essam Banoqitah, Andrew Nisbet. Estimation of Dose Enhancement for Inhomogeneous Distribution of Nanoparticles: A Monte Carlo Study. Applied Sciences. 2021; 11 (11):4900.
Chicago/Turabian StyleFouad Abolaban; Eslam Taha; Abdulsalam Alhawsawi; Fathi Djouider; Essam Banoqitah; Andrew Nisbet. 2021. "Estimation of Dose Enhancement for Inhomogeneous Distribution of Nanoparticles: A Monte Carlo Study." Applied Sciences 11, no. 11: 4900.
It is a known fact that phosphate rocks have high levels of natural radioactivity due to the presence of large concentrations of radionuclides. This work aims to estimate radiation exposure and dose levels at Al-Jalamid site in northern Saudi Arabia. Al-Jalamid area is one of the largest reserves of phosphate worldwide. Ma’aden, a Saudi Government public company, owns the mine and is responsible for all mining activities. Phosphate and soil samples collected from Al-Jalamid phosphate mining area have been analysed for their uranium and thorium content by an α-spectrometer using radiochemical techniques. The quantity of radon gas was measured both in groundwater and in the atmosphere (indoor and outdoor) at the site using a portable radiation survey instrument. Groundwater samples collected from wells surrounding the mining area were analysed using a liquid scintillation counter in addition to an α-spectrometer. Finally, it is found that phosphate rock concentrate products cannot be utilized economically based on the standards set by the International Atomic Energy Agency (IAEA), since the average activity concentration does not reach the limit set by IAEA and hence are not commercially feasible.
Abdulsalam M. Alhawsawi; E. I. Shababa; Maher M. T. Qutub; Essam M. Banoqitah; A. A. Kinsara. Radiological characterization of the phosphate deposit in Al-Jalamid phosphate mining area, Saudi Arabia. Nukleonika 2021, 66, 35 -44.
AMA StyleAbdulsalam M. Alhawsawi, E. I. Shababa, Maher M. T. Qutub, Essam M. Banoqitah, A. A. Kinsara. Radiological characterization of the phosphate deposit in Al-Jalamid phosphate mining area, Saudi Arabia. Nukleonika. 2021; 66 (1):35-44.
Chicago/Turabian StyleAbdulsalam M. Alhawsawi; E. I. Shababa; Maher M. T. Qutub; Essam M. Banoqitah; A. A. Kinsara. 2021. "Radiological characterization of the phosphate deposit in Al-Jalamid phosphate mining area, Saudi Arabia." Nukleonika 66, no. 1: 35-44.
Radioactive sealed sources and radiotracer techniques are used to diagnose industrial process units. This work introduces a workspace to simulate four sealed sources and radiotracer applications, namely, gamma scanning of distillation columns, gamma scanning of pipes, gamma transmission tomography, and radiotracer flow rate measurements. The workspace was created in Geant4 Application for Tomographic Emission (GATE) simulation toolkit and was called Industrial Radioisotope Applications Virtual Laboratory. The flexibility of GATE and the fact that it is an open-source software render it advantageous to radioisotope technology practitioners, educators, and students. The comparison of the simulation results with experimental results that are available in the literature showed the effectiveness of the virtual laboratory.
Mohammed Siddig H. Mohammed; Essam M. Banoqitah; Ezzat Elmoujarkach; Abdulsalam M. Alhawsawi; Fathi Djouider. A virtual laboratory for radiotracer and sealed-source applications in industry. Nukleonika 2021, 66, 21 -27.
AMA StyleMohammed Siddig H. Mohammed, Essam M. Banoqitah, Ezzat Elmoujarkach, Abdulsalam M. Alhawsawi, Fathi Djouider. A virtual laboratory for radiotracer and sealed-source applications in industry. Nukleonika. 2021; 66 (1):21-27.
Chicago/Turabian StyleMohammed Siddig H. Mohammed; Essam M. Banoqitah; Ezzat Elmoujarkach; Abdulsalam M. Alhawsawi; Fathi Djouider. 2021. "A virtual laboratory for radiotracer and sealed-source applications in industry." Nukleonika 66, no. 1: 21-27.
As system thinking is a recognized approach to the comprehension and realization of energy sustainability, this paper applies a holistic representation to the World Energy Trilemma Index (WETI) key indicators using Bayesian Belief Networks (BBN) to illuminate the probabilistic information of their influences in Saudi Arabia’s context. The reached realization is suggested to inform the policies to improve energy sustainability, and thus the country’s rank in the WETI. The analysis used two groups of learning cases, one used the energy statistics of the period from 1995 to 2019 to show the outlook of the Business as Usual path, and the other addressed the projected data for the period from 2018 to 2037 to investigate the expected impact of the new policies. For both BAU and new policies, the BBN calculated the improvement, stability, and declining beliefs. The most influential factors on energy sustainability performance were the electricity generation mix, CO2 emissions, energy intensity, and energy storage. Moreover, the interlinkage between the influential indicators and their causes was estimated in the new policies model. A back-casting analysis was carried out to show the changes required to drive the improvement belief to 100%. The compiled BBN can be used to support structuring policymaking and analyzing the projections’ outcomes by investigating different scenarios for improvement probabilities of energy sustainability.
Mohammed Mohammed; Abdulsalam Alhawsawi; Abdelfattah Soliman. An Integrated Approach to the Realization of Saudi Arabia’s Energy Sustainability. Sustainability 2020, 13, 205 .
AMA StyleMohammed Mohammed, Abdulsalam Alhawsawi, Abdelfattah Soliman. An Integrated Approach to the Realization of Saudi Arabia’s Energy Sustainability. Sustainability. 2020; 13 (1):205.
Chicago/Turabian StyleMohammed Mohammed; Abdulsalam Alhawsawi; Abdelfattah Soliman. 2020. "An Integrated Approach to the Realization of Saudi Arabia’s Energy Sustainability." Sustainability 13, no. 1: 205.
The exceptional performance of machine learning methods has led to their adaptation in many different domains. In the nuclear industry, it has been proposed that machine learning methods have the potential to revolutionize nuclear safety and radiation detection by leveraging that they can be used to augment human and device capabilities. While many applications focus on the accuracy of the learning algorithm’s prediction, it has been shown in practice that these algorithms are prone to learn characteristics that are not descriptive or relevant. Hence, this paper focuses on understanding the reasoning behind the classification using saliency methods. Visual representations of the network’s learned regions of interest are used to demonstrate whether domain-specific characteristics are being identified, which allows for the end-user to evaluate the performance based on domain knowledge. The results obtained show that focusing on a human-centered approach will ultimately enhance the transparency and trust of the deep learning algorithm’s decision.
Mario Gomez-Fernandez; Weng-Keen Wong; Akira Tokuhiro; Kent Welter; Abdulsalam M. Alhawsawi; Haori Yang; Kathryn Higley. Isotope identification using deep learning: An explanation. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 2020, 988, 164925 .
AMA StyleMario Gomez-Fernandez, Weng-Keen Wong, Akira Tokuhiro, Kent Welter, Abdulsalam M. Alhawsawi, Haori Yang, Kathryn Higley. Isotope identification using deep learning: An explanation. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2020; 988 ():164925.
Chicago/Turabian StyleMario Gomez-Fernandez; Weng-Keen Wong; Akira Tokuhiro; Kent Welter; Abdulsalam M. Alhawsawi; Haori Yang; Kathryn Higley. 2020. "Isotope identification using deep learning: An explanation." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 988, no. : 164925.