Artificial neural network (ANN) and Response Surface Methodology based on a 25â1 fractional factorial design were used as tools for simulation and optimisation of the dissolution process for Azaraegbelu clay. A feedforward neural network model with LevenbergâMarquard back propagating training algorithm was adapted to predict the response (alumina yield). The studied input variables were temperature, stirring speed, clay to acid dosage, leaching time and leachant concentration. The raw clay was characterized for structure elucidation via FTIR, SEM and X-ray diffraction spectroscopic techniques and the result indicates that the clay is predominantly kaolinite. Leachant concentration and dosage ratio were found to be the most significant process parameter with p-value of 0.0001. The performance of the ANN and RSM model showed adequate prediction of the response, with AAD of 11.6% and 3.6%, and R2 of 0.9733 and 0.9568, respectively. A non-dominated optimal response of 81.45% yield of alumina at 4.6Â M sulphuric acid concentration, 214Â min leaching time, 0.085Â g/ml dosage and 214Â rpm stirring speed was established as a viable route for reduced material and operating cost via RSM. Keywords: Alumina dissolution, ANN modelling, Azaraegbelu, Clay, RS

The synthesis of oxy-polymerizable alkyd from non-drying palm kernel oil was studied. Three alkyd resins of medium oil length were prepared using phthalic anhydride, maleic anhydride, and glycerol at stipulated ratios. The prepared alkyd resins were copolymerized with styrene using benzoyl peroxide (BPO) as the free radical generator at 150 °C for 3 h. The styrenated alkyds and palm kernel oil-modified alkyds were all characterized for their physico-chemical properties following standard methods. The styrenated and unstyrenated alkyds were tested for drying schedule, solubility, adhesion, abrasion resistance and chemical resistance. All the resins showed good properties. The styrenated alkyds gave faster drying time, better adhesion, abrasion resistance, and chemical resistance. Unlike the unstyrenated alkyd which was only resistant to water, brine, and acidic media, the styrenated alkyds were also resistant to alkalis. Structural elucidation of the raw materials and their copolymers was done with Fourier Transform Infrared (FTIR) and GC–MS instrumental technique. It can be concluded that styrenated alkyds offer improved potential applications in surface coating purposes.

The kinetics and optimization of oil extraction from gmelina seed was studied. The effect of various process variables such as temperature, time, volume of solvent, particle size, and their interaction on oil yield was investigated. A predictive model describing the oil yield in terms process variables was derived from multiple regression analysis. Optimum yield of 49.90 % was predicted at extraction temperature of 60 °C, extraction time of 60 min, seed particle size of 150 µm and 150 ml volume of solvent, for the process. It was found that oil yield increased with increase in temperature, time and volume of solvent but decreased with increase in seed particle size. The extract was analyzed to examine its physico-chemical properties (acid value, iodine value, peroxide value, viscosity, saponification value, moisture and ash content, refractive index, smoke, flash and fire points, and specific gravity) and structural elucidation by standard methods and instrumental techniques. Results revealed that the oil is not edible but find potential in biodiesel production. The kinetic study showed that the extraction process follows a second order mechanism with a rate constant of 1.26 × 10¹¹ (dm³ mol⁻¹)³ S⁻¹.