•Preparation and characterization of clay.•Detailed predictive modeling of the EBT adsorption process utilizing RSM, ANN and ANFIS models.•Critical comparative analysis of the three ...models.•Evaluation of mechanistic modeling of the adsorption process.•Optimization using genetic algorithm.
The application of artificial neural network (ANN), response surface methodology (RSM), and adaptive neuro-fuzzy inference system (ANFIS) in modeling the uptake of Eriochrome black-T (EBT) dye from aqueous solution using Nteje clay was the focus of this work. Acid activation with hydrochloric acid (HCl) was used to prepare the adsorbent while Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) were utilized in the characterization of the adsorbent. The ANN, RSM, and ANFIS models were analyzed by considering the adsorbent dosage, contact time, solution temperature, and pH of the adsorption process. Sensitivity analyses involving six statistical error functions were further used to compare the acceptability of the models. Four mechanistic models (Weber and Morris, Film diffusion, Bangham, and Dummwald-Wagner models) were used to determine the mechanism of the EBT uptake. The result showed that the activation process enhanced the adsorption capacity of the clay. The ANFIS, ANN, and RSM models gave a high accuracy in predicting the adsorption of the EBT dye with correlation coefficients of 0.9920, 0.9910, and 0.9541, respectively. Further statistical indices lent credence to ANFIS as the best predictive model and RSM the least in adsorption of EBT dye. Process optimization using genetic algorithm gave optimum adsorption efficiency of 95.8%. Mechanistic modeling indicated film diffusion as the rate-limiting mechanism. The maximum amount of EBT adsorbed was 24.04 mg/g. The HCl-modified clay could be utilized as an efficient adsorbent in EBT uptake from wastewater.
Cellulose nanocrystals isolated from water hyacinth fiber (WHF) have been studied as a reinforcement for polyvinyl alcohol (PVA)-gelatin nanocomposite. Central composite design was used to study and ...optimize effects of the PVA, gelatin and cellulose nanocrystal (CNC) concentration on tensile strength and elongation of formed films. The results of this study showed that WHF CNC had a diameter range of 20–50 nm produced films reaching 13.8 MPa tensile strength. Thermal stability of the films was improved from 380 °C to 385 °C in addition of CNCs and maximum storage modulus of 3 GPa were observed when 5 wt% CNC was incorporated. However, water absorption, water vapour permeability (WVP) and moisture uptake of the films decreased in addition of CNC to the PVA-gelatin blends. Moisture uptake decreased from 22.50% to 19.05% while the least WVP when 10 wt% CNC added was 1.64 × 10–6 g/(m•h•Pa). These results show possibility for industrial application of WHF CNC and PVA-gelatin blends in biodegradable films for on-the-go food wrappers.
The use of artificial intelligence models in predicting the moisture content reduction in the drying of potato (Ipomoea batata) slices was the focus of this work. The models used were adaptive neuro ...fuzzy inference systems (ANFIS), artificial neural network (ANN) and response surface methodology (RSM). The parameters considered were drying time, drying air speed and temperature. The capability and sensitivity analysis of the three models were evaluated using the correlation coefficient (R2) and some statistical error functions such as the average relative error (ARE), root mean square error (RMSE), Hybrid Fractional Error Function (HYBRID) and absolute average relative error (AARE). The result showed that the three models demonstrated significant predictive behaviour with R2 of 0.998, 0.997 and 0.998 for ANFIS, ANN and RSM respectively. The calculated error functions of ARE (RSM = 1.778, ANFIS = 1.665 and ANN = 4.282) and RMSE (RSM = 0.0273, ANFIS = 0.0282 and ANN = 0.1178) suggested good harmony between the experimental and predicted values. It was concluded that though the three models gave adequate predictions that were in good agreement with the experimental data, the RSM and ANFIS gave better model prediction than ANN.
•Investigation of moisture reduction of potato slices in a drying process.•RSM, ANN and ANFIS were used in the predictive modeling of the drying process.•Drying time and temperature were the most significant factors that affect the drying process.•RSM and ANFIS gave a better predictions when compared with the experimental values.•The optimal drying conditions were validated.
•Esterification-transesterification (MTCKOt) and epoxidation-esterification (MTCKOe) methods were used to modify Terminalia catappa kernel oil (TCKO).•Sample obtained by MTCKOe method gave better ...transformer oil properties than MTCKOt.•Physicochemical properties like dielectric strength and pour point of MTCKOt and MTCKOe, were (48.55 KV and ̶ 5) and (50.05 KV and ̶ 8), respectively.•There was improvement in the percentage saturated fatty acid composition of TCKO after the modification.
This work is centered on the chemical modification and characterization of Terminalia catappa kernel oil (TCKO) for possible use as replacement for mineral transformer fluid. Solvent extraction method was used for the extraction of TCKO. Transesterification and epoxidation-esterification methods were used for the modification of the TCKO. The physicochemical characteristics of the TCKO and Modified Terminalia catappa kernel oil (MTCKO) were determined using standard methods. Fourier Transform Infrared (FTIR) spectrometry, Scanning Electron Microscope (SEM) and Differential Scanning Calorimetric (DSC), were respectively, used to determine the functional groups, surface morphology and oxidative stability of TCKO and MTCKO samples. At 55 °C, 150 min and 0.5 mm particle size, kernel oil yield was 60.45% (by weight). The dielectric strength of MTCKO obtained by transesterification and epoxidation-esterification methods were 48.55 KV and 50.05 KV, respectively. The ANOVA and the Tukey’s post hoc analyses indicated that time, mole ratio and temperature effects were significant for the transesterification process; while time, molar ratio of H2O2 and temperature effects were significant for the epoxidation process. Physicochemical properties of TCKO and MTCKO samples indicated their potential for use as transformer fluid.
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The advent of nanotechnology has engineered great interest in synthetic biopolymer-based nanocomposites for use in tissue engineering scaffolds, automotives, pharmaceuticals, and so ...on, due to enhanced mechanical behavior, flexible biodegradation kinetics, and biocompatibility. Poly(lactic acid) (PLA), attained from natural materials, exhibit biodegradability, and bioabsorbability, with notable demand because of inherent versatility of applications in aforementioned fields. Nevertheless, due to minimal glass transition temperature, poor thermal dimensional stability, as well as mechanical ductility, its scope of application is restricted. Thus, microfillers and nanoparticles such as nanoclay, hydroxyapatite, carbon nanoarchitectures, metallic nanoparticles, and so on, offering superior mechanical, chemical, thermal, flame retardant properties, and so on, are used in enhancing PLA behavior. Therefore, this paper presents recently emerging trends in PLA bionanocomposites for multifunctional applications, including strategies for novel fabrication. Further insight on recent advancements in synthetic biopolymers or saturated poly(hydroxy esters) such as poly(glycolic acid) (PGA), poly (lactic acid-co-glycolic acid) (PLGA), and poly (caprolactone) (PCL) are presented.
The work focused on the kinetic modeling and half-life study of the bioremediation of crude oil dispersed by palm bunch enhanced stimulant. In this study, three bioremediation processes, namely; palm ...bunch enhanced stimulant (PES) stimulation, modified crude oil dispersant (MCD) stimulation and natural attenuated stimulation (NAS), were carried out at various petroleum hydrocarbon concentrations in polluted water media. Bacterial culture, isolations, and identification were carried out to isolate and identify the bacterial involved in the bioremediation. The process kinetics and half-life were investigated. Characterization of PES showed that PES has an appreciable quantity of potassium, phosphate, nitrate, sulphate and calcium required for cell growth and development. Bacillus pumilus, Micrococcus roseus, Micrococcus luteus, and Pseudomonas putida were the bacteria isolated from the culture. The optimum bio-stimulation efficiency of PES occurred on day 6, with BE values of 93.23%. The degradation rate constants for the PES enhanced bioremediation process decreased as the crude oil initial concentration increased from 100 to 300 mg/L. The result showed that the degradation rate constants for PES stimulated remediation were 0.11, 0.04 and 0.03 at 100, 200 and 300 mg/L of crude oil, respectively. The MCD stimulated remediation showed degradation rate constants of 0.04, 0.03 and 0.018, at crude oil concentrations of 100, 200, and 300 mg/L, respectively. The trend was the same for NAS. The longest half-life for 100 mg/L of crude oil was achieved after 79.67 days during the NAS stimulation. The results obtained from this report showed tremendous improvement to the degradation of crude oil due to the presence of PES. The degradation process was adequately described by the first order kinetic model and showed the effectiveness of PES in the remediation process. Therefore, the data obtained in this study could be applied in the design of a bioremediation system for potential application to remediation of crude oil polluted water.
The capability of response surface methodology (RSM), artificial neural network (ANN), and adaptive neuro‐fuzzy inference systems (ANFIS) in modeling and predicting moisture content reduction in the ...drying of cocoyam (Colocasia taro) slices was the purpose of this study. Design of experiment was utilized. Modified Fick's second law of diffusion was used to determine effective moisture diffusivity (Deff). Results indicated that drying time, air velocity, and temperature significantly affected the drying process. Deff values obtained ranged from 2.97 × 10−10 to 7.30 × 10−10m/s. Page model with R2 = 0.994, SSE = 0.0053, RMSE = 0.0611, best described the kinetics of the drying process. ANN, RSM, and ANFIS all showed significant modeling and predicting ability with R2 of 0.9583, 0.9519, and 0.9971, respectively. Genetic algorithm (GA) optimization showed minimum moisture content of 14.362%, 11.919%, and 11.293% for RSM‐GA, ANN‐GA, and ANFIS‐GA, respectively. Additional statistical analysis lent credence to ANFIS as the best in modeling and predicting the moisture content reduction of cocoyam slices.
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 × 10
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The effectiveness of Nando clay in the bleaching of palm oil was studied in this work. The clay was prepared by activating it with hydrochloric acid. The bleaching was carried out at different ...temperatures, adsorbent dosage and particle sizes. The result suggests that increase in temperature and adsorbent dosage increases the bleaching efficiency while the increase in particle size decreases the bleaching efficiency. Both the pseudo-first-order and the pseudo-second-order kinetic models describe efficiently the experimental data of the bleaching process. Intra-particle diffusion though involved in the adsorptive bleaching mechanism, is not the sole rate-limiting step in the bleaching of palm oil with activated Nando clay. The equilibrium data were described better by Langmuir and Freundlich models. The enthalpy, entropy and activation energy were determined to be 6.127 KJ/mol, 3.982 KJ/mol and 15.281 KJ respectively. The free energy was found to vary between- 3.999 to- 3.760 KJ/mol. The result indicates that bleaching efficiency of up to 96% can be obtained with the activated clay as an adsorbent.
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