Chemistry
Edet Patience Ime; Ede Joseph Ajor; Francis-Dominic Makong Ekpan; Humphrey Sam Samuel; Odii Peter Egwuatu
Abstract
The search for eco-friendly and sustainable materials for electrical applications has stepped up recently, spurred on by the demand for effective, greener solutions. To meet these expectations, a promising class of materials known as clay-reinforced recycled plastic composites has evolved. Increased ...
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The search for eco-friendly and sustainable materials for electrical applications has stepped up recently, spurred on by the demand for effective, greener solutions. To meet these expectations, a promising class of materials known as clay-reinforced recycled plastic composites has evolved. Increased mechanical strength, less thermal expansion, and higher flame resistance are all benefits of incorporating clay nanoparticles into recycled plastics, which are essential for maintaining the dependability and safety of electrical systems. Clay-reinforced recycled plastic composites have been investigated for usage in various applications, including electrical ones. The waste plastic components, such as polystyrene or high-density polyethylene, are combined with clay, such as montmorillonite, to create the composites using a cold pressing technique. In comparison to the original plastic materials, the resultant composites have better mechanical, thermal, and water absorption characteristics. In addition, it has been shown that adding clay to composites improves their electrical qualities, making them appropriate for use in electrical applications. Dielectric strength, dielectric constant, and electrical conductivity tests have all been used to assess the electrical properties of the composites. According to the findings, clay-reinforced recycled plastic composites could be used in electrical applications, such as the production of electrical insulators. Utilizing these composites can help develop sustainable materials for various applications and reduce plastic waste.
Chemistry
Chinedu Innocent Okoye; Obiamaka Doris Oboli
Abstract
Separation of asphaltenes into multiple sub-fractions is performed using different fractionation techniques which are investigated in this study. The method chosen depends on the parameter of interest such as solubility, molecular weight difference, polarity, etc. For this write-up, the methods reviewed ...
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Separation of asphaltenes into multiple sub-fractions is performed using different fractionation techniques which are investigated in this study. The method chosen depends on the parameter of interest such as solubility, molecular weight difference, polarity, etc. For this write-up, the methods reviewed include sequential elution fractionation, solvent extraction, sequential extraction, column chromatography, sequential precipitation, supercritical fluid extraction, etc.The yield and the quality of the fraction are the two important subjects for choosing the separation procedure. For example, the yield is influenced using different hydrocarbon liquids as a significant factor. In addition, the method of choice will determine the presence of co-precipitated resins or not. The advantages of some of the methods were highlighted as well as the future prospects and application of asphaltene.
Chemistry
Samuel N. Ndung’u; Ruth N. Wanjau; Esther W. Nthiga
Abstract
The current study utilizes Silicon Nitride (Si3N4) as a novel adsorbent in evaluating its adsorptive ability for Congo red dyes from an aqueous solution. The adsorbent was prepared using extracted silica from sand and coffee husk biochar in an ammonia environment. The Si3N4 adsorbent was characterized ...
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The current study utilizes Silicon Nitride (Si3N4) as a novel adsorbent in evaluating its adsorptive ability for Congo red dyes from an aqueous solution. The adsorbent was prepared using extracted silica from sand and coffee husk biochar in an ammonia environment. The Si3N4 adsorbent was characterized using a Field Emission Scanning Electron Microscope (FEI ESEM) which showed rod-like and fiber-like structures for α-Si3N4 and β- Si3N4, respectively. The SEM results also showed pores on the adsorbent surface before adsorption and a more rigid and restrained surface after adsorption. The adsorbent surface is hydroxylated in water to give important adsorption sites of silanolate ions (Si-O-) and silazane groups (Si2=NH2+) responsible for congo red (CR) dye removal. The adsorption process was investigated by batch mode. The maximum adsorption capacity (28.87 mg/g) was obtained at an optimal pH=1.00, agitation time (50 minutes), adsorbent dosage (25 mg), and initial concentration (50 mg/L). The Langmuir isotherm model was best fitted with equilibrium data with R2 > 0.9, showing that the adsorption was chemisorption in nature. The results revealed Si3N4 adsorbent as a potential adsorbent in textile dye wastewater treatment.
Chemistry
Blessing Ifeyinwa Tabugbo; Rilwan Usman; Mikaila Abdullahi; Jackso Karniliyus
Abstract
In Nasarawa State, groundwater is the most often used source of fresh water for daily consumption, but its quality still remains a serious concern due to rising concentrations of radon resulting from activities of mining. This study evaluated the potential pose resulting from radon exposure via groundwater ...
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In Nasarawa State, groundwater is the most often used source of fresh water for daily consumption, but its quality still remains a serious concern due to rising concentrations of radon resulting from activities of mining. This study evaluated the potential pose resulting from radon exposure via groundwater ingestion and inhalation in Keffi, Nigeria using the liquid scintillation detector. Ten borehole samples of groundwater were collected. The mean content of radon from water samples of Keffi was 19.368 Bq/l. the average ingested and inhaled dose effectiveness annually was 0.099 mSv/y and 4.9 x10-5 mSv/y, respectively. In Keffi, the average ingested extra lifetime cancer risk was 3.5 x10-4 and for inhalation was 1.71 x10-7. Research area's average radon concentration was higher than the standard of 11.1 Bq/l set by the SON and USEPA. Based on the findings of the present work, the radon concentration is unacceptable, hence, inhabitants should be restricted from using the water until measures are put into place. However further analysis could be carried out in the area to prevent people from cancer risk. To cover the entire zone, additional research should be conducted covering additional sources in the study area. As concentrations of radon in water sources varies with time as a result of dilution by rainfall, more examination may be conducted in dry and raining periods.
Chemistry
Abdullahi Muhammad Ayuba; Thomas Aondofa Nyijime; Safiyya Abubakar Minjibir; Fater Iorhuna
Abstract
Quantum functions were used to assess a theoretical investigation on mild steel's resistance to corrosion. To determine the stable geometry of the investigated compounds, TPE and PME, local density function B3LYP was optimized and simulated using DFT under restricted spin polarization DNP basis. The ...
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Quantum functions were used to assess a theoretical investigation on mild steel's resistance to corrosion. To determine the stable geometry of the investigated compounds, TPE and PME, local density function B3LYP was optimized and simulated using DFT under restricted spin polarization DNP basis. The molecules' local and global reactivity, including their electronegativity (χ), dipole moment (μ), energy gap (ΔE), global hardness (η), global electrophilicity index (ω), energy of back donation (∆Eb-d), fraction of electron transfer (ΔN), and the (ω+) and (ω-) electron accepting and donating powers between the molecule and the iron, were all studied. The inhibition process was assumed to be a chemisorption interaction between the surface and the molecule based on the number of adsorption sites and the binding energy obtained from the process. This is because the molecules contain hetero-atoms, such as oxygen and methylene (-CH2-) functional groups. For PME and flourine for TPE, which serve as the focal point for the selectivity of electron donation and acceptance between the metal and the TPE and PME moieties.
Chemistry
Merit Oluchi Ori; Edet Patience Ime; Francis-dominic Makong Ekpan; Humphrey Sam Samuel; Odii Peter Egwuatu; Ede Joseph Ajor
Abstract
Industrial filters are important components in the manufacturing and processing of polymer products. They are used to remove impurities, contaminants, and foreign particles from polymer materials, ensuring high-quality and consistent products. The polymer industry, which is at the centre of contemporary ...
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Industrial filters are important components in the manufacturing and processing of polymer products. They are used to remove impurities, contaminants, and foreign particles from polymer materials, ensuring high-quality and consistent products. The polymer industry, which is at the centre of contemporary manufacturing, is under increasing pressure to strike a balance between environmental sustainability and the demand for outstanding product quality. In this perspective, industrial filters stand out as unsung heroes who have a significant impact on the polymers manufacture. This in-depth analysis explores the most recent advancements in industrial filtering technology and their strategic uses in the production of polymers. It emphasizes how these filters successfully remove pollutants, impurities, and undesired particles from the polymer feedstock, producing products that stand out for having better mechanical, thermal, and optical qualities. Furthering the cause of sustainability and ecologically responsible production, the elimination of unwanted by-products, and the maintenance of constant polymer compositions greatly reduce waste formation. Analyses of case studies and practical instances provide verifiable proof of the revolutionary advantages offered by industrial filters. These benefits include improved energy efficiency, lower maintenance costs, and the establishment of an unwavering standard for product quality. The research also explores the use of green filtering systems, which not only boost output, but also comply with the growing demand for environmentally responsible manufacturing methods.
Chemistry
Humphrey Sam Samuel; Ugo Nweke-Maraizu; Emmanuel Edet Etim Etim
Abstract
Chalcogen bonding, a non-covalent interaction involving chalcogen atoms (e.g., sulfur, selenium, and tellurium), plays a crucial role in various chemical and biological processes. Understanding and characterizing chalcogen bonding interactions are essential for designing novel materials, medications, ...
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Chalcogen bonding, a non-covalent interaction involving chalcogen atoms (e.g., sulfur, selenium, and tellurium), plays a crucial role in various chemical and biological processes. Understanding and characterizing chalcogen bonding interactions are essential for designing novel materials, medications, and catalysts. In recent years, machine learning has emerged as a powerful tool for studying molecular interactions, including chalcogen bonding. This study provides an overview of the application of machine learning in characterizing chalcogen bonding. Experimental techniques, such as infrared (IR), nuclear magnetic resonance (NMR) spectroscopy, and X-ray crystallography, have been used to study chalcogen bonding. However, these methods often suffer from inherent experimental challenges. On the other hand, computational approaches, including quantum mechanics (QM) and molecular dynamics (MD) simulations, offer valuable insights into the electronic structure and energetics of chalcogen bonding. Nonetheless, they can be computationally demanding and may not fully encompass the diversity of chalcogen bonding interactions. Machine learning, with its ability to identify patterns and relationships in vast datasets, presents a promising alternative for characterizing chalcogen bonding. The study explains how machine learning algorithms, such as supervised and unsupervised learning, can be employed to classify and predict chalcogen-bonded complexes using neural network potentials to assess the persistence of chalcogen bonds in solution and ML models to predict two key solid-state synthesis conditions that must be specified for chalcogenide glasses. By integrating experimental data and computational results, machine learning models offer a holistic approach to understanding chalcogen bonding in various molecular systems. It emphasizes the integration of experimental and computational data as a means to maximize the accuracy and applicability of machine learning models and envisions a promising future for machine learning in characterizing chalcogen bonding interactions.
Chemistry
Fater Iorhuna; Muhammad Abdullahi Ayuba; Aondofa Thomas Nyijime; Musa Sani; Hamisu Abdulmumini; John Oluwafemi Oyeyode
Abstract
Metals, such as Iron, zinc, zluminium, and copper are vital in various industries and construction. However, these metals are susceptible to corrosion upon exposure to corrosive elements. Metals used at homes and part of our car bodies under goes corrosion at a little contact of the corrosion factors. ...
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Metals, such as Iron, zinc, zluminium, and copper are vital in various industries and construction. However, these metals are susceptible to corrosion upon exposure to corrosive elements. Metals used at homes and part of our car bodies under goes corrosion at a little contact of the corrosion factors. In this research, a coumarin derivative was theoretically studied using quantum parameters such as Electronegativity (χ), Global hardness (η), Electron donating power(ω-), Electron accepting power (ω+), Global softness (σ), Global hardness (η), and fraction of electron transfer (ΔN) couple with the simulation process to ascertain and compare the corrosion inhibition of metals such Zn, Al, Cu, and Fe. Based on the results, low magnitude of ELUMO combined with the high magnitude of EHOMO reveals that Coumarin-6-ol, 3,4-dihydro-4,4-dimethyl-7-nitro- (CML) molecule was reactive by serving as a donor, hence confirming the predicted inhibition of the simulated parameters. The electronegativity atoms have a significant effect on the corrosion inhibition efficiency of CML inhibitor molecule, and the atom with a negative charge depicts the potential of a HOMO center. The binding energy of the inhibitor (CML) on the metals were in order of CML-Fe (111)> CML-Cu (110)> CML-Al (110)> CML-Zn (110) for -90.768834kcal/mol, -48.643544 kcal/mol, -45.734485 kcal/mol, and -26.909952 kcal/mol, respectively. According to the results, CML inhibitor molecule shows high significant corrosion protection properties and is shown to be highly effective on CML-Fe (111) compare to the other metals studied. All CML-metal contact in the study depicts a physical adsorption based on the values of binding and obtained adsorption energy.
Chemistry
Roozbeh Behzadi
Abstract
The removal of sulfur compounds in hydrocarbon fuels is important from an environmental point of view, because in the combustion process of fuels in engines, sulfur compounds in the fuel are converted into sulfur oxides (SoX), which will cause the problem of acid rain. In addition, (SoX) resulting from ...
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The removal of sulfur compounds in hydrocarbon fuels is important from an environmental point of view, because in the combustion process of fuels in engines, sulfur compounds in the fuel are converted into sulfur oxides (SoX), which will cause the problem of acid rain. In addition, (SoX) resulting from the combustion of sulfur-containing fuels in internal combustion engines, while causing corrosion in the internal parts of the engine, causes poisoning of the catalytic converters installed in the exhaust of cars, and finally causes the deactivation of these catalytic converters in a short period. An important plan of these catalytic converters is to reduce the emission of nitrogen oxides into the environment. Likewise, sulfur oxides lead to the rapid deactivation of the filters installed in the exhaust to prevent the release of suspended particles into the atmosphere. Therefore, the presence of sulfur compounds in hydrocarbon fractions, in addition to cause problems related to the release of sulfur oxides into the atmosphere, leads to the aggravation of the problem of the release of pollutants such as nitrogen oxides and suspended particles into the environment.
Chemistry
Aliyu Benson; Ayodele Akinterinwa; Charles Milam; Abdulazeez M. Hammed
Abstract
Evaluation of natural resources via chemical profiling is a prerequisite to mining and material sourcing, which are important activities in positioning an economy for the future. This study explores the untapped rocks located within the Bakin Dutse hills in Adamawa State, northeastern Nigeria. The minerals ...
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Evaluation of natural resources via chemical profiling is a prerequisite to mining and material sourcing, which are important activities in positioning an economy for the future. This study explores the untapped rocks located within the Bakin Dutse hills in Adamawa State, northeastern Nigeria. The minerals and elemental compositions of the rock samples were determined using X-ray diffractometer (XRD) and X-ray fluorescence (XRF) instruments respectively. Results of the mineral composition of the rock samples showed (in order of abundance) the presence of quartz, albite, annite, and microcline, as well as orthoclase, phlogopite, oligoclase, chrysotile, and cordierite which were sparsely found in the study area. The abundant presence of silicate and aluminum silicate minerals in the study area was also shown in the major elemental composition of the rock samples, which follow the order SiO2 (55.76 – 63.81%) > Al2O3 (11.06 - 13.15%) > Fe2O3 (8.41 – 11.2%) > K2O (6.12 – 7.75%) > CaO (2.29 – 6.37%) > Na2O (2.4%) > MgO (0.09 -2.2%) > SO3 (0.37 – 1.05%). The minor elements in the rocks include PbO, TiO2, BaO, CuO, ZnO, P2O5, ZrO2, Rb2O, MnO, and Cl. The mineral and elemental compositions of the soil in the study area show similarities that link the origin of the soil to the weathering of the rocks. The geo-chemical data provided in this study will make an important contribution to both the literature and the database for future mining prospects in the study area.
Chemistry
Segun Michael Abegunde; Kayode Solomon Idowu
Abstract
In this work, activated carbon (AC) was prepared from Raphia taedigera seed and modified with sodium hydroxide (0.1 M) solution. The activated carbon (RTB) and the untreated Raphia taedigera raw (RTR) seed powder were characterised and engaged to remove Methylene blue (MB) dye from aqueous solution. ...
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In this work, activated carbon (AC) was prepared from Raphia taedigera seed and modified with sodium hydroxide (0.1 M) solution. The activated carbon (RTB) and the untreated Raphia taedigera raw (RTR) seed powder were characterised and engaged to remove Methylene blue (MB) dye from aqueous solution. Both materials were characterized by Fourier-transform infrared spectroscopy (FTIR) and Scanning electron microscopy (SEM). FTIR revealed the presence of functional groups such as hydroxyl, carboxylic, alkenes, aldehydes, and ketonic groups. SEM image showed the surface morphology of the material is characterized by aggregated structure with pores. The performances evaluation of the materials gave the highest percentage of MB dye removal of 84.21 and 97.00% were observed for RTR and RTB, respectively, at pH 5. The adsorption modelling showed that the MB dye adsorption onto both adsorbents could best be represented by Langmuir isotherm and followed the pseudo-second-order kinetic model. The thermodynamic studies predicted exothermic, feasible, spontaneous, and physisorption nature of MB dye adsorption onto the RTR and RTB within the temperature range for this study.
Chemistry
Shakiba Sharifi
Abstract
Well testing entered petroleum engineering in 1937 as a tool to understand the actual behavior of the reservoir in the face of changes in the well. Artificial neural networks with a hidden layer have the ability to solve most nonlinear problems. In this study, an artificial neural network with a hidden ...
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Well testing entered petroleum engineering in 1937 as a tool to understand the actual behavior of the reservoir in the face of changes in the well. Artificial neural networks with a hidden layer have the ability to solve most nonlinear problems. In this study, an artificial neural network with a hidden layer was used to determine the reservoir model from pressure-derived diagrams. The number of neurons in the output layer is equal to the number of reservoir models considered, while the number of hidden layer neurons is an optimization problem and the problem is complexity, the complexity of the relationship between input and output, the amount of data available for network training, and the amount of noise. Educational data depends. A small number of them may not be able to converge the network to the desired error, while a large number may lead to the network not becoming popular. The minimum data required for network training based on an exploratory method should be ten times the number of links in the network. In leading networks, if the mean relative error and the square error of the test data are plotted against the number of hidden layer neurons, a structure that provides the minimum measurement error value and the appropriate value of the regression coefficient is selected as the optimal structure. The appropriate training algorithm is determined by identifying the algorithm that requires the least time for training. In other words, an algorithm with the minimum required training.
Chemistry
Nabil Vaeli
Abstract
In this study, Carvacrol or Cymophenol as a combination, as the number of reports of antibiotic-resistant pathogenic microorganisms increases and considering that plant-derived products can potentially treat microbial growth in different conditions and in specific cases of the disease. Very strong anti-cancer ...
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In this study, Carvacrol or Cymophenol as a combination, as the number of reports of antibiotic-resistant pathogenic microorganisms increases and considering that plant-derived products can potentially treat microbial growth in different conditions and in specific cases of the disease. Very strong anti-cancer and also an antibacterial treatment of yeast infections from Oliveria decumbens plant by supercritical fluid CO2 with the help of ultrasound at 150,180,210 bar and temperatures of 55, 45 and 65 ° C. The compounds were examined by GC / MS device. The method is about 37% more than the distillation method with Clevenger apparatus. Also, to increase the extraction rate, C65 temperature, 180 bar pressure and 37 kHz frequency were determined as optimal conditions, in which about 26% compared to the case without ultrasound without extraction.
Chemistry
Nabil Vaeli
Abstract
In this research, the Oliveria decumbens native and medicinal plant has been used. The extract of this plant contains anti-inflammatory compounds, very strong antioxidants, Allergic reduction compounds and antiviral and anticancer compounds. Extraction of this plant was investigated using supercritical ...
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In this research, the Oliveria decumbens native and medicinal plant has been used. The extract of this plant contains anti-inflammatory compounds, very strong antioxidants, Allergic reduction compounds and antiviral and anticancer compounds. Extraction of this plant was investigated using supercritical extraction system using supercritical CO2 fluid in two stages with ultrasound waves and without ultrasound waves, which the research showed that the highest percentage of effective compounds was extracted by supercritical fluid through the ultrasound process. In this study, the extractive effect of two compounds of Octanoic acid and Nonadecanoic Acid as two compounds with the highest drug effect was investigated due to the anticancer and antiviral properties. This amount for the active substance Octanoic Acid in SCF state is 0.02 and in the USCF is 0.14. and for Nonadecanoic Acid in the SCF state is 0.11 and in the USCF state it is 0.86. Also, the extraction in the supercritical device was investigated in both states with ultrasound and without it, at pressures of 190, 170 and 210 bars and the temperatures of 55,45 and 65 Centigrade and frequencies of 37 and 80 kHz. The results showed that the percentage of product (gram of active ingredient / gram of sample) at the pressure of 210 bar and 37 kHz frequency had the highest extraction rate.