Theses and Dissertations (Chemical Engineering)

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Browsing Theses and Dissertations (Chemical Engineering) by Subject "Adsorption"

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    The adsorption of Cu(II) ions by polyaniline grafted chitosan beads.
    (Vaal University of Technology, 2013-11-06) Igberase, Ephraim; Ofomaja, A., Dr; Osifo, P.O., Dr
    This work investigates the possible use of chitosan beads and polyaniline grafted chitosan beads (PGCB) for the adsorption of copper ions from copper contaminated water. For this purpose chitosan flakes were converted to chitosan beads. However, a variable from a number of reaction variables (aniline concentration, chitosan concentration, temperature, acid concentration, reaction time and initiator concentration) was varied while others was kept constant, in an attempt to determine the best conditions for grafting of polyaniline onto chitosan beads. Percentage (%) grafting and % efficiency were key parameters used to determine such conditions. The chitosan beads and PGCB were characterized using physical techniques such as Fourier transformed infra red (FTIR), X-ray diffraction (XRD), and scanning electron microscope (SEM). The beads were used as an adsorbent for copper ions removal. The effect of pH on the removal rate of copper (II) by PGCB was investigated on by varying the pH values from pH 3 to 8 at an initial concentration of 40 mg/l. The effect of contact time, initial concentration and temperature was also investigated. The Langmuir and Freundlich model were used to describe adsorption isotherms for chitosan beads and PGCB, with correlation coefficient (R2) as the determining factor of best fit model. The thermodynamics of adsorption of copper (II) onto PGCB was described by parameters such as standard Gibb’s free energy change (ΔGo), standard enthalpy change (ΔHo), and standard entropy change (ΔSo) while the pseudo first-order and pseudo second-order kinetic model was used to describe kinetic data for the PGCB, with R2 and chi- square test (  2) as the determinant factor of best fit model. From the desorption studies, the effect of eluants (HCl and HNO3) and contact time on percentage desorption of PGCB loaded copper (II) ion was investigated upon. In determining the reusability of the PGCB loaded copper (II) ion, three cycles of adsorption/desorption studies was carried out. The results obtained from determining the best conditions for grafting polyaniline onto chitosan beads revealed the following grafting conditions; [Aniline] 0.1 g/l, [temperature] 35oC, [chitosan] 0.45 g/l, [HCl] 0.4 g/l, [(NH4)2S2O8] 0.35 g/l, and [time] 1 h. These conditions were applied in the grafting of polyaniline onto chitosan beads. FTIR analysis showed increase intensity in the grafted beads which provided evidence of grafting, XRD measurement showed a decrease in crystallinity in the PGCB as against the partial crystalline nature of chitosan. In SEM analysis, evidence of grafting was revealed by the closed gap between the polysaccharide particles in the PGCB. From the investigation carried out on the effect of pH on the percentage removal of Cu(II) ions by PGCB, the optimal pH value was found to be pH 5 with a percentage removal of 100% and this value was used for all adsorption experiment. Also from the investigation performed on the effect of contact time and initial concentration, it was observed that there was a sharp increase in the amount of Cu(II) ions adsorbed by PGCB up until contact time of 30 min and thereafter, it increases gradually. From the experiment carried out on the effect of temperature on adsorption capacity, there was an increase in adsorption capacity with increase in temperature. Moreover, at temperatures of 25oC, 35 oC and 45oC the Langmuir model gave the best fit for the chitosan beads having R2 values that are equal and greater than 0.942 in contrast to Freundlich having R2 values that is equal and greater than 0.932. The maximum adsorption capacity (Qm) from Langmuir model at these temperatures were 30.3 mg/g, 47.6 mg/g and 52.6 mg/g respectively. Also, the Langmuir model gave the best fit for the PGCB having R2 values that are equal and greater than 0.956 in contrast to Freundlich model with R2 values that is equal and greater than 0.935. The Qm from Langmuir model at these temperatures were 80.3 mg/g, 90.9 mg/g and 100 mg/g respectively. The values of Qm for PGCB appears to be significantly higher when compared to that of chitosan beads and this makes PGCB a better adsorbent than chitosan beads. From the thermodynamic studies carried out on PGCB, the values of ΔGo were negative and this denotes that the adsorption of copper ions onto PGCB is favorable and spontaneous, the positive value of ΔHo shows the adsorption process is endothermic and the positive value of ΔSo illustrate increased randomness at the solid-liquid interface during the adsorption process. Also, from the kinetic studies carried out on the PGCB, the pseudo second-order kinetic model best described the kinetic data having R2 values that are equal and greater than 0.994 in contrast to the pseudo first-order kinetic model with R2 values that is equal and greater than 0.913. The  2 values for the pseudo first-order and pseudo second-order kinetic model were similar; however, there was a large difference for qe between the calculated (qeCal) values of the first-order kinetic model and experimental (qeExp) values. In the case of the pseudo second-order model, the calculated qe values agree very well with the experimental data. Desorption of the metal ions from PGCB was efficient. 0.5 M HCl was successfully used in desorbing the beads loaded with copper ions and a percentage desorption of 97.1% was achieved at contact time of 180 min. PGCB were successfully re-used for adsorption/desorption studies were a Qm of 83.3 mg/g, 83.3 mg/g and 76.9 mg/g was achieved in the first, second and third cycle respectively.
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    Production of adsorptive material from modified nanocrystals cellulose for industrial application
    (Vaal University of Technology, 2022-05) Banza, Musamba Jean Claude; Seodigeng, Tumisang, Prof.; Rutto, Hilary Limo, Prof.
    Water is the essence of life, yet it is progressively polluted by dyes, heavy metal ions, food additives, medicines, detergents, agrochemicals, and other toxins from industrial, municipal, and agricultural sources. Among the different wastewater treatment technologies, adsorption is a technique that, when used in conjunction with a welldesigned system, produces high-quality treated water at a reasonable cost. For water treatment, activated carbon is the most often employed adsorbent. Its manufacture, on the other hand, is energy demanding, costly, and creates greenhouse emissions. As a result, finding low-cost alternative adsorbents from industrial and agricultural waste and biomass has attracted a lot of interest. In this context, developing sustainable platforms for wastewater treatment using sustainable nanomaterials such as cellulose nanocrystals (CNCs) is a unique technique with a low carbon footprint. CNCs, which are made by hydrolyzing pulp fibers in sulfuric acid, are rod-like nanomaterials with a lot of remarkable qualities including high specific surface area, high specific strength, hydrophilicity, biodegradability, and surface functionalization. These characteristics, as well as their accessibility, make them suitable candidates for water treatment applications. However, because of their great colloidal stability and nano-dimensions, extracting these CNCs after usage in water treatment is difficult. To overcome this problem, including these CNCs into nanocomposite systems that can be readily separated after usage in batch and continuous water treatment processes is a great concept. Furthermore, pure CNCs have low selectivity towards a wide range of water pollutants, necessitating surface functionalization to provide this selectivity. As a result, this thesis investigates the extraction of CNCs from millet husk waste and waste papers, the development of CNC-incorporated nanocomposites and evaluation of their adsorption characteristics using batch and fixed bed column adsorption studies, and (ii) the evaluation of the selective adsorption characteristics of surface functionalized CNCs and their ability to tailor the nanocomposites' characteristics for use in water treatment applications. The response surface methodology, artificial neural network, and adaptive neuro-fuzzy inference systems were also applied to model the removal of heavy metal ions. The first part of the research (cellulose nanocrystals extraction and optimization) The cellulose nanocrystals were extracted from millet husk residue waste using a homogenized acid hydrolysis method. The effects of the process variables homogenization speed (A), acid concentration (B), and acid to cellulose ratio (C) on the yield and swelling capacity were investigated and optimized using the Box Behnken design (BBD) method in response surface methodology. The numerical optimization analysis results showed that the maximum yield of CNCs and swelling capacity from cellulose was 93.12 % and 2.81 % obtained at homogenization speed, acid concentration, and acid to cellulose ratio of 7464.0 rpm, 63.40 wt %, and 18.83 wt %, respectively. ANOVA revealed that the most influential parameter in the model was homogenization speed for Yield and acid concentration for swelling capacity. The TGA revealed that cellulose had greater heat stability than CNCs. The functional groups of CNCs and cellulose were identical according to the FTIR data. When compared to cellulose, the SEM picture of CNCs is porous and shows narrow particle size with needle-like shape. The XRD pattern revealed an increase in CNC intensity. The second part of the research (CNCs modification for selective removal) A novel type of recyclable adsorbents with outstanding adsorption capability was produced using CNCs with succinic anhydride and EDTA. and their adsorption properties were studied in detail utilizing batch adsorption experiments of Chromium (VI) in aqueous solution. The effects of several factors on Cr (VI) adsorption were examined, including contact duration, adsorbent dose, starting concentration, pH, and temperature. The cellulose nanocrystals treated with succinic anhydride and EDTA possessed a needle-like form, high porosity, and a narrow particle size distribution. The carboxylate transition of the carboxyl group of cellulose was verified by FTIR. XRD analysis of particles after modification revealed the presence of additional phases, which were attributed to succinic anhydride and EDTA modification. A spontaneous exothermic adsorption process was validated by the observed thermodynamic characteristics. The best model for describing adsorption kinetics and mechanism was a pseudo-second order kinetic and intra-particle diffusion model. The Langmuir adsorption isotherm was seen in equilibrium adsorption data, with a maximum adsorption capacity (qmax) of 387.25± 0.88 mgL-1. We showed that the removal effectiveness of Cr (VI) maintained at 220± 0.78 mg.g-1 after 6 adsorption-desorption cycles, and that the CNC-ALG hydrogel beads are excellent adsorbents for the selective removal of Cr (VI) from wastewaters. The third part of the research (modeling of removal of heavy metal ions using RSM, ANN and quantum mechanism studies) The effects of contact time , pH, nanoparticle dose, and beginning Cd2+ concentration on Cd2+ removal were examined using the central composite design (CCD) technique. The performance and prediction capabilities of Response Surface Methodology (RSM) and Artificial Neural Network (ANN) modelling methodologies were explored, as well as their performance and prediction capacities of the response (adsorption capacity). The process was also described using the adsorption isotherm and kinetic models. Statistical data, on the other hand, revealed that the RSM-CCD model beat the ANN model technique. The optimum conditions were determined to be a pH of 5.73, a contact time of 310 minutes, an initial Cd2+ concentration of 323.04 mg/L, a sorbent dosage of 16.36 mg, and an adsorption capacity of 440.01 mg/g. The spontaneous adsorption process was well characterized by the Langmuir model, and chemisorption was the dominant regulator. The binding energy gaps HOMO-LUMO were used to find the preferred adsorption sites. The fourth part of research (optimization of removal using ANN and ANFIS) An artificial neural network and an adaptive neuro-fuzzy inference system were utilized to predict the adsorption capability of mix hydrogels in the removal of nickel (II) from aqueous solution. Four operational variables were evaluated in the ANFIS model to determine their influence on the adsorption study, including starting Ni (II) concentration (mg/L), pH, contact time (min), and adsorbent dosage (mg/L) as inputs and removal percentage (percent) as the single output. In contrast, 70% of the data was employed to develop the ANN model, while 15% of the data was used in testing and validation. To train the network, feedforward propagation with the Levenberg-Marquardt algorithm was used. To optimise, design, and develop prediction models for Ni (II) adsorption using blend hydrogels, (ANN) and (ANFIS) models were employed for trials. The results demonstrate that the ANN and ANFIS models are viable prediction techniques for metal ion adsorption. The fourth part of research (mechanistic modeling and optimization of removal using ANN, RSM and ANFIS) An artificial neural network, response surface methodology and an adaptive neuro-fuzzy inference system were utilized to predict the adsorption capability of modified cellulose nanocrystals and sodium alginate for the removal of Cr (VI) from aqueous solution. Four variables such as time, pH, concentration, and adsorbent dose were evaluated to determine their influence on the adsorption study. To examine the viability of the models, five statistical functions ( RMSE, ARE, SSE, MSE, and MPSD) were applied. absorption mechanism was described via four mechanistic models (Film diffusion, Weber and Morris, Bangham, and Dummwald-Wagner models. Further statistical indices supported ANFIS as the best prediction model for adsorption compared to ANN and RSM. Film diffusion was identified as the rate-limiting process via mechanistic modelling. The sixth part of research (continuous fixed-bed column study) The hydrogel's technical feasibility for adsorption of Cu2+, Ni2+, +Cd2+, and Zn2+ ions from the packed bed column's produced AMD was assessed. The hydrogel was considered to have a high potential for significant interactions with dangerous metal ions. This characteristic, together with the adsorbent's availability, low cost, and efficient regeneration of the spent adsorbent, distinguishes it from the many other adsorbents described in the literature by other researchers. With a bed height of 25 cm, an influent metal ion concentration of 10 mg/l, and a flow velocity of 10 ml/min, the bed performed better. As a consequence, the breakthrough curve for the packed bed experiment shows that the breakthrough points were approached sooner by increasing the flow rate and influent concentration, and later by increasing the bed height. The experimental results were satisfactorily described by the BDST, Yoon–Nelson, and Thomas models. The hydrogels had a net-work structure and more homogeneous porosity, according to the SEM, TGA, XRD, and FTIR results for CNCs. The hydrogels revealed varied degrees of opacity and heavy metal ions absorption capacity depending on the temperature of the analysis. Diffraction confirmed the existence of crystalline structures and the presence of carboxyl and amide groups.
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    Solar photocatalytic degradation and adsorption of emerging pharmaceutical contaminants in wastewater
    (Vaal University of Technology, 2014-09-15) Akach, John Willis Juma Pesa; Onyango, Maurice S., Prof.; Aoyi, Ochieng, Prof.
    Pharmaceutical pollutants in wastewater have become an increasing concern in recent years. Adsorption and photocatalytic degradation of pharmaceutical pollutants have proved to be very efficient in the removal of pharmaceutical contaminants. In this study, a composite catalyst of powdered activated carbon (PAC) and TiO2 bound by silica xerogel (CTS composite) was synthesized and characterised using SEM, XRD and XRF. The composite catalyst was then used to adsorb and photodegrade the pharmaceuticals sulfamethoxazole (SMX), diclofenac (DCF) and carbamazepine (CBZ) in a three phase fluidised bed photocatalytic reactor using sunlight to activate the TiO2. The solar radiation intensity at the Vaal University of Technology and the hydrodynamic behaviour of the reactor were also investigated. Additionally, the effect of catalyst composition and loading, hydrodynamics and solution characteristics on the adsorption and photodegradation of the substrates was investigated. It was found that the solar radiation intensity varied with the hour of day, weather and seasons of the year. SEM showed that the porosity of the composite catalyst increased with increase in the PAC loading and a decrease in the silica xerogel loading. The XRD results showed that the silica xerogel and the PAC did not alter the composition of the P25 TiO2. XRF showed that the method used in the preparation of the substrates resulted in the desired composition of the catalyst. The optimum CTS composition was 60% silica xerogel loading and 10% PAC/TiO2 ratio. The best mass of the composite catalyst was 1.5 g/l. Using the optimal composite composition resulted in over 90% removal of the substrates with low residual solution turbidity of less than 3.5 formazin attenuation units (FAU). The optimum hydrodynamic condition was obtained when the reactor inclination angle and superficial air velocity were 75° and 0.014 m/s, respectively. However, a reactor inclination angle of 75° and a superficial velocity of 0.007 m/s gave the best adsorption and photodegradation of the substrates. Reducing the initial concentration of the substrates resulted in an increase in the efficiency of removal of the substrates. The adsorption and photodegradation of SMX was observed to increase with a decrease in pH and was maximum at pH 4. The adsorption of SMX and DCF was found to follow the Langmuir isotherm model. These results show that the use of the synthesised composite catalyst in the fluidised bed reactor provided a stable and efficient system capable of long term use. The results from this work also show that this system can be used for the removal of pharmaceutical substrates at low concentrations.
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    Synthesis of gelatin-cellulose hydrogel membrane for copper and cobalt removal from synthetic wastewater
    (Vaal University of Technology, 2021-04) Lukusa, Tresor Kabeya; Shoko, Lay, Dr.; Tshilenge, John Kabuba, Dr.
    Heavy metal ions are one of the most toxic materials in the environment. Adsorption is the most used process for the removal of heavy metals from wastewater. Much research has been conducted into processes to remove heavy metals using different adsorbents. Various adsorbents have been used to remove heavy metal ions from wastewater especially those that are harmful to mankind. Zeolite, clay, activated carbon and biopolymers are the most common adsorbents used. In this research, gelatin, and cellulose nanocrystals (CNCs) were used to synthesize a hydrogel membrane to remove Cu(II) and Co(II) metal ions from mining processes wastewater. The synthetic wastewater was prepared in the laboratory to conduct the experiments. Batch experiments were conducted to obtain the optimum conditions for the Cu(II) and Co(II) metal ions. The effect of parameters such as pH, ratio, contact time, and temperature were also determined. The optimum conditions obtained were 120 min contact time for both metal ions at the temperature of 30oC, pH 5 for copper and pH 7 for cobalt. The high removal of both metals ions was obtained using the ratio 3:1 (75% Gelatin and 25% CNCs) at the temperature of 303K. The maximum adsorption capacity of Cu(II) and Co(II) was 7.6923 mg/g and 10.988 mg/g, respectively. The high percentage removal of Cu(II) and Co(II) metal ions obtained was found to be 70.5% for Cu(II) at pH 5 and 74.5% for Co(II) at pH 7. The experimental data fit well to Pseudo-first-order kinetic and Freundlich isotherm models (KF= 1.89x103 mg/g for copper and 3.7x102 mg/g for cobalt) for both metal ions. The values of energy (E) from D-R model have shown that the adsorption of both metal ions was of physical nature (E<8kJ/mol) then confirmed by the thermodynamic results (ΔH°). The kinetic diffusion models have shown that the experimental data fit well with the film diffusion (R2= 0.977 and 0.989) for both metal ions at pH 5. Negative values of ΔG°obtained for both metal ions indicate that the adsorption process was spontaneous. The positive values of ΔH° obtained showed a physical adsorption process and also indicate that the adsorption process of both metal ions was endothermic. The positive values of ΔS° indicate an increase in randomness at the solid/solution interface during adsorption.