Optimum Process Parameters for Activated Carbon Production from Rice Husk for Phenol Adsorption

Background: The adsorptive removal of anionic dye (Bromocresol green) from aqueous solution was investigated using activated carbon prepared from rice husk. Place of Study: The research work took place at Nnamdi Azikiwe Univeristy Awka, Nigeria. Methods: The rice husk which was obtained from rice mills in Awka was activated with tetraoxophosphoric acid and carbonized in a furnace. The adsorption process was investigated by varying the contact time, temperature, dosage, pH and initial concentration in a batch process. Five isotherm models (Langmuir, Freundlich, Temkin, Halsay and Harkin-Jura) were employed in the equilibrium studies. Thermodynamics and kinetics of the adsorption were carried out. Results: The result indicated that increase in contact time, adsorbent dosage and temperature increased the percent uptake of the Bromocresol green dye. Maximum percentage adsorption of about 93% was obtained. Langmuir and Harkin-Jura isotherm models best described the equilibrium data of the adsorption process. Pseudo second-order kinetic model best correlates the kinetics of the experimental data. The thermodynamic study showed that the Gibbs free energy (ΔG), enthalpy change (ΔH) and entropy change (ΔS) were –2.541 kJ/mol, -7.401 kJ/mol and –15.52 kJ/mol K respectively. Conclusion: This work has shown that activated carbon prepared from rice husk can be used in adsorptive removal of bromocresol green dye from solution and that the adsorption process was spontaneous and exothermic.

Section: Resultssupporting

confidence: 71%

“…The rice husk which was obtained from rice mills in Awka, Nigeria was first washed and sun dried It was then modified by activation and carbonization according to the method of Iheanacho, et al [12]. The rice husk were reduced to smaller sizes and dried so as to reduce the moisture content.…”

Section: Activated Carbon Preparationmentioning

confidence: 99%

Application of Modified Agricultural Waste in the Adsorption of Bromocresol Green Dye

Elijah

Collins

Obumneme³

et al. 2020

“…The reducing sugar yield from the enzymatic hydrolysis of CC-DFPF blends was presented in Table 4 and the statistical analysis (ANOVA) of the result was presented in Table 5 which quantified the relative effects of the factors being studied on the enzymatic process [28]. The ANOVA aids in analysis and validating the experiment result of any process [29]. The ANOVA table showed that at 5% confidence level X 1 , X 2 and X 3 were all significant while X 4 was not significant because its variance ratio, F 4 was less than F 0.05 (3,6) from F-distribution table [19].…”

Section: Analysis Of Variance (Anova)mentioning

confidence: 99%

Enzymatic Hydrolysis of Blend of Lignicellulosic Materials for Reducing Sugar Production: Screening of Significant Process Factors

Amadi

Igbokwe

Onu

2020

The screening of the process parameters on the enzymatic hydrolysis of a blend of two lignocellulosic materials - corn cob (CC) and deseeded fluted pumpkin fruit (DFPF) using Trichoderma reesei was the focus of the present study. Four process parameters – time, temperature, substrate blend ratio and pH were screened for statistical significance using a 4 x 4 matrix of Graeco-Latin square design of experiment. The reducing sugar yield was determined using the dinitrosalisylic acid (DNS) method and maximum reducing sugar yield of 57.92mg/ml obtained in 2days at 40oC, blend ratio of 0.2:0.8 (CC:DFPF) and pH 5.5. Result of the Analysis of Variance (ANOVA) obtained showed that with 3 degrees of freedom and 6 residual degree of freedom at 95% confidence level (i.e. 0.05 significance), time, temperature and substrate blend ratio significantly affected the enzymatic hydrolysis process whereas the effect of pH was not significant. However, only time was significant at 99% confidence level (0.01 significance) while temperature, substrate blend ratio and pH were not significant. This study has highlighted the significant factors among the process variables in emzymatic hydrolysis of a blend of CC and DFPF.

“…It is used to generate a mathematical model that can significantly establish optimum operating conditions for any process. It requires few experimental runs to establish the optimum conditions [18][19][20]. The optimization of the drying operation leads to an improvement in the quality of the output product, a reduction in the cost of processing as well as the optimization of the throughput [21].…”

Section: Introductionmentioning

confidence: 99%

Optimum Process Parameters and Thermal Properties of Moisture Content Reduction in Water Yam Drying

Henry

Jospeh

Chijioke

et al. 2021

The determination of optimum process parameters for moisture content reduction in water yam drying using a hot air dryer was the aim of this work. Gravimetric method was used to determine the moisture content. Design of experiment was used with slice thickness, airspeed and temperature as the independent factors. Thermal properties such as effective moisture diffusivity and activation energy were determined. The result showed that slice thickness, airspeed and temperature have significant influence on the moisture content reduction. The effective moisture diffusivity ranged from 2.84 x 10-5 m2/s to 8.10 x 10-5 m2/s. The activation energy was 30.592kJ/mol. Minimum moisture content value of 11.98% was obtained at slice thickness of 2mm, airspeed of 2 m/s and temperature of 70oC. The quadratic model best described the drying process. The hot air dryer can conveniently be used for moisture content reduction in water yam slices which will increase its shelf life.