Synthesis of Nano-Calcium Oxide from Industrial Brine Sludge Waste with Nanocrystalline Cellulose (NCC) as Addictive/composites and Modelling using Artificial Neural Network (ANN) for Biodiesel Production

Biodiesel production as a fuel in diesel engines has expanded dramatically in recent years and is likely to increase more in the near future. Increasing biodiesel consumption requires optimized production techniques that allow for large production capacities, simplified operations, high yields, and the usage of more cost-effective feedstocks such as waste oils and fats. In this study, biodiesel was produced from waste vegetable oil (WVO) and Methanol (CH3OH) in the presence of a catalyst which was derived from industrial waste that mainly consists of Calcium Carbonate (CaCO3). The produced nano-particle catalyst was characterized by using Fourier Transform infrared (FTIR), Scanning Electron Microscope (SEM) and X-ray diffraction (XRD). The optimum operating conditions for the highest biodiesel yield after applying the artificial neural network (ANN) approach was found to be 96.41 % yield at a temperature of 55 °C, catalyst loading of 1.25 % w/v, Methanol to oil ratio of 1:5 w/w and reaction time of 75 min. The FTIR showed the presents of CaO and NCC functional group. SEM image revealed that the produced catalyst is more porous, with small particle size, and XRD pattern presented the presence of cellulose (NCC) and Calcium Oxide (CaO) nano particles in the synthesized catalyst. The R2 of 0.977 was found to be for the mathematical models to predict biodiesel production

The dissolution study of a South African magnesium-based material from different sources using a pH-stat

One of the main steps in the wet flue gas desulphurization (WFGD) process is the dissolution of either magnesite or limestone. Evaluating the magnesite dissolution rate is vital for the design and efficient operation of wet FGD plants. A study on the dissolution of magnesite from different sources in South Africa is presented in this work. The effect of reaction temperature (303.15-343.15K), solid-to-liquid ratio (0.5-2.5g/200 ml), particle size (25-125μm), pH (4-6) and HCl concentration (0.5-2.5 mol/l) on the dissolution rate was studied. It was found out that the dissolution reaction follows a shrinking-core model with the chemical reaction control as the rate-controlling step. The dissolution rate increased with an increase in concentration and reaction temperature and with a decrease in particle size and solid-to-liquid ratio. The activation energy of this dissolution process was found to be 45.685 kJ/mol

Urea-based moulding compounds for investment casting

Conventional urea-based moulding compounds for investment casting patterns are manufactured using a slow “cooking” process. Nowadays in industrial processes the use of a faster process is highly recommended to increase throughput levels. At the same time, for quality control purposes, the requirements of an investment caster must be met. This study is therefore focused on: Finding the appropriate conventional process and conditions to prepare urea-based investment casting moulding compounds. Optimising the composition variables to meet the mechanical, thermal, surface, flow and cost properties needed in investment casting. Characterising the moulding compounds to meet the requirements of an investment caster by comparing them with an industrial, “cooked” urea-based compound. Polyvinyl alcohol (PVOH) and ethylene vinyl acetate (EVA) urea-based moulding compounds were prepared using a two-roll mill and a conventional extrusion processes respectively. It was possible to injection mould PVOH urea-based moulding compounds with a urea content of up to 90 wt % which had been compounded using a two-roll mill. Using the conventional extrusion process, it was also possible to compound and injection mould EVA urea-based moulding compounds containing up to 70 wt % urea. The effects on composition variables on the properties of the moulding compound were studied and compared to those of the existing “cooked” urea-based moulding compound (Benchmark). The mechanical properties were characterised using the three-point bending test and Charpy impact test. The thermal properties were determined using simultaneous differential thermal analysis and thermogravimetric analysis (SDTA/TGA) and differential scanning calorimeter (DSC). The thermo-mechanical and visco-elastic properties were determined using a dynamic mechanical analyser. A scanning electron microscope was used to study the surface texture of the mouldings. The EVA urea-based moulding compounds showed two endothermic melting peaks and multiple exothermic crystallisation peaks in the DSC curves. The peak at ca. 55 - 66°C corresponds to the melting of the wax/EVA blend, while the large peak at 130 - 132°C corresponds to the melting of the urea. The DSC heating curve of the PVOH urea-based moulding compounds showed two endothermic peaks. The small peak corresponds to the melting of the wax, while the large peak corresponds to the melting of the urea/PVOH blend. PVOH urea-based moulding compound had better mechanical properties than the industrial benchmark. The mechanical properties of the EVA urea-based compound were generally lower. The effect of the wax and polymer content on the mechanical properties was as follows: Increasing polymer content produced weaker but tougher moulding compounds. Increasing wax content improved the strength and stiffness but gave compounds that were less tough. Two-way Analysis of Variance (ANOVA) indicated significant polymer-wax interactions. The urea content determined the stiffness (elastic modulus) of the compounds. PVOH mouldings had superior stiffness compared with the EVA and cooked urea-based mouldings. The Dynamic mechanical analysis (DMA) results confirmed the result obtained from the modulus of elasticity determination in the three-point bending test. The impact strength increased with an increase in polymer content and reduced with an increase in wax content. The linear thermal expansion coefficient decreased as the urea content was increased. Measured values (100 to 156x10-6°C) were comparable to those of the benchmark. The cooked urea-based moulding compound had the lowest melt viscosity at 110°C, as indicated by its melt flow index (MFI). Fluidity increased with the polymer content. The thermo gravimetric analysis (TGA) results confirmed that both the PVOH and EVA urea-based moulding compounds decomposed readily and left less than 1 wt % ash after combustion. From the SEM results apparent surface roughness appeared to increase with wax content. The EVA urea-based moulding compound had an irregular surface texture. Based on the criteria of cost-effectiveness and environmental friendliness, the synthesis of PVOH urea-based patterns is preferable. The use of a conventional extrusion process to prepare PVOH urea-based patterns is recommended.Thesis (PhD)--University of Pretoria, 2011.Chemical Engineeringunrestricte

Removal of Copper (II) and Lead (II) from hydrometallurgical effluent onto cellulose nanocomposites: mechanistic and Levenberg-Marquardt in Artificial Neural Network modelling

A well-designed adsorption system should meet the requirements for high efficiency while remaining cost and time effective. nanocellulose materials have a proven track record as viable adsorbent alternatives. Cellulose is a renewable raw material that can be used to develop an adsorbent for heavy metal ions removal. In this study, CNCs were modified with EDTA and used as adsorbents to remove Pb(II) and Cu (II) ions from a mixture of metal ions synthesized solution. The modified CNCs were characterized using Fourier transform infrared (FTIR), X-ray diffraction (XRD), Scanning electron microscopy (SEM) and thermogravimetric analysis (TGA) surface area.  SEM results showed that CNCs are porous, have narrow particles size, and FTIR results revealed that the functional group responsible for the lead ions removal was mainly carboxylates (-COO2-). The XRD diffraction pattern showed that the CNCs possessed the cellulose crystalline configuration. The effects of the sorbent dosage, contact time, pH, and initial on the removal efficiency of the metal cations were examined. The absorption mechanism was described via four mechanistic models: Film diffusion, Weber and Morris, Dummwald-Wagner, and Bangham. The Artificial Neural Network (ANN) model predicted the adsorption of heavy metal ions with incredible accuracy, with an adsorption capacity of 250 mg/g for Copper and 270 mg/g for lead. Film diffusion was identified as the rate-limiting process via mechanistic modelling

Production of Biodiesel from Waste Vegetable Oil (WVO) using Nano CaO-NCC catalyst: Modelling and Optimization using Central Composite Design (CCD) in Response Surface Methodology (RSM)

Biodiesel production as a fuel in diesel engines has expanded dramatically in recent years and is likely to increase more in the near future. Increasing biodiesel consumption requires optimized production techniques that allow for significant production capacities, simplified operations, high yields, and the usage of more cost-effective feedstocks such as waste oils and fats. In this study, biodiesel was produced from waste vegetable oil (WVO) and Methanol (CH3OH) in the presence of a nanoCaONCC catalyst that was derived from industrial waste that mainly consists of Calcium Carbonate (CaCO3). The produced nanoparticle catalyst was characterized by using FTIR, SEM, and XRD. Response surface methodology (RSM) was used to determine the optimum operating conditions for the highest biodiesel yield. After applying the RSM methods using the CCD experimental design, the optimum biodiesel production was found to be at a temperature of 55 °C, catalyst loading of 1.25 % w/v, Methanol to oil ratio of 1:5 w/w, and reaction time of 75 min with an average yield of 94.01 %. The FTIR showed the presence of the CaO and NCC functional groups. SEM image revealed that the produced catalyst is more porous, with a small particle size. The XRD pattern presented the presence of cellulose (NCC) and Calcium Oxide (CaO) nanoparticles in the synthesized catalyst. The R2 of 0.963 was found to be for the mathematical models to predict biodiesel production

Thermo-mechanical properties of urea-based pattern molding compounds for investment casting

Urea is a low cost material with thermal and mechanical properties suitable for use in investment casting pattern molding compounds. Conventional compounds are made by a “cooking” process wherein the urea is added to and dissolved in an aqueous solution of a water soluble polymer followed by evaporation of the water. Here we describe novel formulations based on either polyvinyl alcohol (PVOH) plasticized by glycerol or ethylene vinyl acetate (EVA) resins together with wax that can be prepared by a facile twin-screw compounding process. The thermo-mechanical properties of these compounds were characterized using differential scanning calorimetry (DSC), thermo gravimetric analysis (TGA), dynamic mechanical analysis (DMA) and three bend point tests. The PVOH-based molding compounds featured better mechanical properties than those based on EVA. Increasing the polymer content produced weaker but tougher molding compounds. Increasing wax content improved stiffness but resulted in a loss of toughness. The TG results showed that both compounds decomposed readily at elevated temperatures and left less than 3 wt. % ash at 800°C.Financial support for this research from Xyris Technology, Ceracast and the THRIP program of the Department of Trade and Industry and the National Research Foundation of South Africa is gratefully acknowledged.www.polymer-process.co

Evaluation of Density-Based Models for the Solubility of Sclerocarya Birrea Kernel Oil in Supercritical Carbon Dioxide and the Formulation of a New Model

Solubility data obtained from literature for Sclerocarya birrea kernel oil in supercritical carbon dioxide (CO2) were correlated using six semi-empirical density-based models viz. Chastril, del Valle and Aguilera (DVA), Adachi and Lu (AL), Sparks et al., Kumar and Johnston (KJ), and Mendez-Santiago and Teja (MST). The determination coefficient values (R2) ranged from 0.72 to 0.95. The average absolute relative deviations (AARD%) ranged from 15.53 to 0.049. A comparison was made between all six semi-empirical density-based models, and it was concluded that the MST model provided an improved and better fit than the other models investigated. After examining each of the six models under investigation, an improved model is proposed, which can characterize most of the findings taken into account about Sclerocarya birrea kernel oil yield

Formulations, development and characterization techniques of investment casting patterns

Conventionally, unfilled wax has been used as a universal pattern material for the investment casting process. With increase in demand for accurate dimensions and complex shapes, various materials have been blended with wax to develop more suitable patterns for investment casting in order to overcome performance limitations exhibited by unfilled wax. The present article initially reviews various investigations on the development of investment casting patterns by exploring pattern materials, type of waxes and their limitations, the effect of filler materials and various additives on unfilled wax, wax blends for pattern materials, plastics and polymers for pattern materials and 3D-printed patterns. The superiority of filled and polymer patterns in terms of dimensional accuracy, pattern strength, surface and flow properties over unfilled wax is also discussed. The present use of 3D patterns following their versatility in the manufacturing sector to revolutionize the investment casting process is also emphasized. Various studies on wax characterization such as physical (surface and dimensions), thermal (thermogravimetric analysis and differential scanning calorimetry), mechanical (thermomechanical analysis, tensile stress testing, dynamic mechanical analysis) and rheological (viscosity and shearing properties) are also discussed.The Technology Innovation Authority, South Africa.https://www.degruyter.com/view/j/revce2020-04-01am2019Chemical Engineerin

Biodiesel production using Chlor-alkali brine sludge waste as a heterogeneous catalyst: optimisation using response surface methodology

Chlor-alkali process industries produce a million tonnes of brine sludge which are dumped in landfills. Brine sludge waste can be thermally modified and applied as a heterogeneous basic catalyst to synthesise biodiesel from waste cooking oil (WCO). In this work, an experimental design obtained by response surface methodology was used to study the effects of process parameters and hence, optimise the transesterification process. A quadratic model was generated to estimate the yield of biodiesel to its process variables. A biodiesel yield of value 97.8 wt % was optimally achieved using numerical optimisation method at a reaction period; methanol to oil weight ratio, a catalyst to oil weight ratio, and temperature of 1.53 hr, 29.8 wt %, 2.47 wt %, and 60.31°C, respectively. The brine sludge waste catalyst was reutilised up to four times without being deactivated. Morphological modifications of the brine sludge after calcination and transesterification were characterised using a scanning electron microscope (SEM) and X-ray diffraction (XRD). From the basic fuel properties specifications stipulated in the ASTM standard, it was found WCO biodiesel properties were within the acceptable range