Browsing by Author "Mustapha, K."

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    Kinetics of the Antioxidant Activities of Solanum macrocapon and Crassocephalum rubens by DPPH Radical Scavenging Method
    (Journal of Chemical Society of Nigeria, 2020-02-11) Yusuff, K. O.; Omotosho, K.; Mustapha, K.; Abdulraheem, A. M. O.
    Solanum macrocapon (S.macrocapon) and Crassocephalum rubens (C.rubens) was investigated. The methanolic extracts of the samples were tested with 2,2-diphenyl-1-picrylhydrazyl (DPPH) at different times (30, 50, 70 and 90 minutes). UV-Visible Spectroscopy technique was employed  to evaluate the ability of the plant extracts to scavenge DPPH radicals by measuring the absorbance at the various experimental times. The concentration of sample required to inhibit 50% of the DPPH free radical (IC50) and kinetic parameter (rate constant k2) were determined from the absorbances values. S.macrocapon and C.rubens had DPPH scavenging potency with IC50 values of 2.18 x 10-2 mgml-1 and 6.27 x 10-2 mgml-1 respectively. This implied that S.macrocapon is a more potent antioxidant than C.rubens. The rate constant for the hydrogen atom abstraction by DPPH (k2) in the presence of S.macrocapon is 2.70 x 10-3 ± 0.0006 mlmg- 1min-1 with R2 value of 0.709 while for C.rubens, the rate constant is 6.89 x 10-4 ± 0.03 x 10-4 mlmg-1min-1 with R2 value of 0.987 using Pseudo-first order kinetics model. However, under second order kinetics, the rate constant, k2, for S.macrocapon is 4.73 x 10-1 ± 0.020 mM-1min-1 with R2 value of 0.993 while C.rubens has k2 value of 5.55 x 10-2 ± 0.00236 mM-1min-1 with R2 value of 0.795. Thus, the depletion of DPPH by S.macrocapon followed a second order kinetics while that of C.rubens followed a Pseudo first order kinetics. Keywords: Kinetics, DPPH, Antioxidant, UV-Vis spectroscopy, IC50Â
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    Mechanical Properties, Durability and Microstructure of Palm Kernel Shell Concrete Produced from Different Grades of Portland Limestone Cement
    (Nigerian Research Journal of Engineering and Environmental Sciences, 2024-06-30) Odeyemi, S. O.; Adegolu, E.R.; Adisa, M.O; Atoyebi, O.D; Mustapha, K.; Adeniyi, A.G.
    The need for lightweight structures and to reduce environmental waste which leads to pollution has necessitated the utilization of agro-based materials as aggregates for concrete. Notable among these wastes is the Palm Kernel Shell (PKS). This study investigated the compressive and tensile strength, durability and internal structure of PKS concrete made with 32.5N and 42.5N grades of Portland Limestone Cement (PLC). A designed mix of Grade 20 culminating into a combined ratio of 1:1:1 for cement, sand and PKS batched by volume adopting a water-cement ratio (w/c) of 0.45. The compressive and tensile strengths of the concrete were tested, the durability of the concrete was determined using a water absorption test and Scanning Electron Microscopy (SEM) was conducted to correlate the test results. The outcome of investigations showed that PKS concrete from the cement of grade 42.5N has higher compressive and tensile strengths than grade 32.5N. Microstructural images from SEM showed non-uniformly distributed voids which are higher in concrete produced from 32.5N grade cement. Hence, the PKS concrete from grade 32.5N PLC absorbed more water than the concrete made from 42.5N PLC. Therefore, cement grade affects the strength, durability and microstructure of PKS concrete.
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    Optimization and Modelling of Bio-Oil Yield from the Pyrolysis of Jatropha Curcas Seed Using Optimal Design and Artificial Neural Networks
    (LAUTECH, 2023) Oladosu, K. O.; Amoloye, T. O.; Mustapha, K.; Oderinde, J. O.; Babalola, S.
    Better quality and quantity of pyrolysis products from biomass can be obtained by regulating the input parameters of the pyrolysis process. Pyrolysis of Jatropha Curcas seed mixed with alumina catalyst was carried out in a fixed bed reactor to study the effects of temperature, time, and particle size on bio char and bio-oil yield. The bio-oil yields were optimized using the Optimal Design (OD) under the Combined Methodology of the Design-Expert Software (12.0). The input and output parameters were modeled and validated using Artificial Neural Networks (ANN) based on 40 experimental data generated by the OD. The optimum bio-oil yield of 15.6 wt. % was obtained at 650 °C, 30 min, and 1 mm particle size. The Correlation Coefficient (R2) of the model for the bio-char and bio-oil yield under the OD were 0.998 and 0.996, respectively. The optimized ANN architecture employed the in-built Levenberg-Marquardt training algorithm in MATLAB software. Random division of the data into training, validation and testing sets followed 70:15:15 percentage proportions with 15 hidden layers. This resulted in the minimum Mean Square Error (MSE) of 2.15e-05 and (R2) of 0.96394 for the bio-oil yield. The FTIR spectra indicated that bio-oil contained phenols, esters, and acids compound while its Gas Chromatography analysis showed the presence of pyrrolidine, pyrimidine, and aldehydes. These properties signified the bioenergy and biochemical capabilities of the pyrolytic oil obtained. The prediction accuracy indicates that both the ANN and OD can be deployed for accurate prediction.