Pusat Pengajian Kejuruteraan Kimia - Monograf

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Effect of membrane selectivity and configuration on purity and recovery of hydrogen from syngas
(2021-01-01)
Thamudoran, Mohashiniee
In this thesis, simulation of a membrane gas separation system for purification of hydrogen from syngas has been discussed. The simulation was done to study the effects of membrane selectivity, flow configuration, stage cut and feed pressure on the purity and recovery of hydrogen from syngas. In order to model the membrane, a complete mixing model was applied to study these effects. The mathematical modelling involved in the simulation was done in Mathcad and the results were analysed using the analysis of variance (ANOVA) under the Response Surface Methodology (RSM) method. In order to produce high purity hydrogen that is accepted as commercial industrial grade hydrogen, we studied two types of flow configuration models. Configuration 1 involves a carbon dioxide permeable membrane while configuration 2 model involves a hydrogen permeable membrane. As a result, it is noticed that in the first configuration, at the stage cut of 0.2, feed pressure of 5 bar and CO2/H2 selectivity of 1500, the highest purity of hydrogen at 52.24% and recovery of 59.58% at the permeate stream is achieved. Meanwhile in the retentate stream, the purity and recovery of carbon dioxide achieved is 52.21% and 55.53% respectively. The second configuration is when a hydrogen permeable membrane is applied. This configuration results in the highest possible purity of hydrogen of 100% with recovery of 32.52% and carbon dioxide purity and recovery at 27.35% and 90.42% respectively, at stage cut of 0.2, feed pressure of 25 bar and H2/CO2 selectivity of 500.
Conentrating of phosphate with simultaneous removal of sodium chloride via nanofiltration
(2021-01-01)
Vengedesweren, Durgashene
Recovery of phosphorus has been gaining importance due to its natural scarcity and high economical value. Aquaculture and poultry effluent with significant phosphate content required further treatment before discharging to the environment. However, its trace quantity makes the whole process not feasible. Moreover, the presence of salt (NaCl) makes the effort to recover the phosphate as fertilizer less attractive due to its unwanted salinity. In this study. nanofiltration had been tested to recover/concentrate the phosphate ions and at the same time removing the sodium chloride. The study was conducted using Desal DK5 membrane in dead-end mode using Dead End Stirred Cell at different pressures and concentration to investigate the effect of transmembrane pressure (TMP) and feed concentration on the rejection of phosphate ions, average permeate flux and concentrating factor. The highest phosphate ion rejection, 99.86%, was achieved at the lowest pressure, 2 bar, and lowest concentration of potassium dihydrogen phosphate solution (20 ppm). However, in the same parameter, the permeate flux and the concentrating factor (CF) obtained were the lowest compared to other sets of experiment which are 20.15 L/m2 .h and 1.55 respectively. The maximum CF of could be achieved at 6 bar. The removal of NaCl increases with pressure, however the presence of NaCl further reduce the phosphate ion rejection, lowering the average permeate flux and concentrating factor. The results obtained is very promising in terms of harvesting the nutrient from aquaculture effluent and at the same time removing the unwanted salinity.
Modelling of gas diffusion in mesoporous tin dioxide (sno2) as gas sensor in detecting acetone vapour
(2021-01-01)
Mohan, Khamini
Mesoporous semiconductor based gas sensors have been extensively researched and employed in the detection of traces poisonous and flammable gases such as nitrogen dioxide (NO2), carbon monoxide (CO), sulphur dioxide (SO2) and volatile organic compounds (VOCs) such as ethanol, methanol and acetone which are dangerous to both people and the environment. In this research, mesoporous tin dioxide based gas sensor, SnO2 is utilized due to its low cost, high sensitivity and quick response. In order to determine the most effective techniques for optimising the gas sensing properties of mesoporous SnO2, the effect of acetone concentration and operating temperature on the sensitivity of a gas sensor was investigated using a diffusion mechanism model. The gas detecting mechanism was controlled by Knudsen diffusion of the target gas through the porous film and its interaction with adsorbed oxygen, which followed a first-order reaction kinetic. In the diffusion mechanism model equation, a general expression of sensitivity, S (Ra/Rg) as a function of pre-exponential constants, α0 and k0, reaction activation energy for gas dependent, Ea, universal gas constant, R, temperature, T, concentration, 𝐶𝐴𝑠, film thickness, L, reaction activation energy for temperature dependent, Ek, pore radius, r and molecular weight of target gas, M was derived under steady state condition. Theoretically, the variations of sensitivity with the sensor operating temperature resulted in a bell-shaped curve with optimum temperature, whereas increasing gas concentration resulted in increased sensitivity before saturation was attained. When comparing the previous result with the MATLAB simulation, it is clear that the sensitivity increases as the temperature rises, resulting in a linear line rather than a bell shape curve. This can be said the developed model is not suited for the stimulated various operating temperature. The model was used to do a sensitivity analysis based on film thickness, L, and pore radius, r. According to simulation results, sensitivity improved with decreasing layer thickness at 300oC because of greater interaction between the gas to be detected and the sensor surface. The sensitivity of the gas sensor increased with increasing pore radius in the model at a given temperature of 300 oC, which can be explained adequately by the equation of Knudsen diffusion coefficient, Dk.
Modelling of reactive distillation for the production of methyl tert-butyl ether (mtbe) parametric sensitivity study on kinetic model
(2021-05-01)
Mohamed Zubir, Mohamed Fahim
Modelling of reactive distillation for the production of MTBE has been presented in this thesis. A reactive distillation column modelled by using RADFRAC module in the Aspen Plus V10 software for the production of MTBE. The simulation was done on an equilibrium basis. Prior to running the simulation, all the necessary data were collected. The kinetic data which is the coefficients of the equilibrium equation were collected from the equilibrium equation. The values obtained were 357.094, -1492.77, -77.4002 and 0.507563.These values were entered into the Aspen Plus V10 built-in Keq expression. The simulated model was verified by comparing to the published data. Once it was verified, the simulation was then used to carry out parametric sensitivity study on kinetic model. The effect of changes in the kinetic data and four different operating conditions of choice such as the feed flowrate of methanol, the feed flowrate of mixed butenes, the reflux ratio and the composition of isobutylene on the simulation results in terms of MTBE purity and isobutylene conversion were studied in detail. The individual best values for each operating conditions were determined. Then optimization carried out. The optimized values were 209.3 mol/s for methanol feed flowrate, 583.2 mol/s for mixed butenes feed flowrate, 7 for reflux ratio and 0.357 for isobutylene mole fraction. From these set of values, a MTBE purity and isobutylene conversion of 100.00 % obtained successfully. This study shows that the changes in parameters influences the performance of reactive distillation process for the production of MTBE.
Air pollution index estimation model based on artificial neural network
(2021-06-01)
Mohammed Nasser, Al-Subaie
Environmental conservation efforts are always dealing with a complex problem because it involves a large number of variables. However, choosing a correct model structure, and optimum training algorithm with minimum complexity is crucial. Therefore, a dimensional reduction method was implemented based on the multiway principal component analysis (MPCA) method. Three models were built in first part; ozone estimation model, particulate matter 10 (PM10) estimation model, and air pollution index (API) estimation model. Six inputs were used in ozone and PM10 models, which are nitrogen oxides( NOx), carbon monoxide (CO), sulphur dioxides (SO2), wind speed, air temperature, and relative humidity. After that, ozone and PM 10 were used as input to the API estimation model. The result shows that the implementation of the MPCA has insignificant improvement on the overall correlation factor due to the high nonlinearity of data.
Model development for turbine energy yield (tey), carbon monoxide (co) and nitrogen oxide (nox) from gas turbine power plant
(2021-06-01)
Wan Anuar, Wan Ahmad Aizat
In order to combat the environmental issues that have been constantly rising since the start of the first Industrial Revolution in the 18th century, many solutions have been introduced and been applied around the world. One of the approaches for overcome air pollution issues from greenhouse gas emissions is by monitoring their release from its most abundant sources, for example, gas turbine power plants.Predictive emission monitoring system (PEMS) is one of the methods for monitoring these greenhouse gas emissions. It is powered by an artificial neural network (ANN)by taking into account the collected data from Kaya et al. (2019) such as ambient temperature, ambient pressure, ambient humidity and many more from selected gas turbine power plants for the emission prediction purpose. Several models will be developed and will be classified according to their responding outputs. Multi input single output (MISO), where carbon monoxide (CO), nitrogen oxide (NOx) and turbine energy yield (TEY) will be operated as separate output and multiple inputs multiple outputs where CO, NOx and TEY will be its output simultaneously. For each model’s type, it will be further classified into the model with input selection and the model without input selection. The performance of the model will be demonstrated by the value of its respective mean squared error (MSE), R and R2. The model with input selection is having almost the same performance as the model without input selection although having fewer input variables compared to the latter. R2 values for each training model with input selection are 0.5094, 0.8260, 0.7573 and 0.6922 for the model with CO, NOx, TEY as output and MIMO model respectively compare to the R2 values for each training model without input selection are 0.5382, 0.8278, 0.7627 and 0.6950 for model with CO, NOx, TEY as output and MIMO model respectively. MIMO model is the better model compared to MISO, even though it combines 3 outputs and could be more complex, but ANN still able to predict accurately. Therefore, developing MIMO model could be better than developing MISO model as it will reduce model times (one model for 3 outputs rather than a separate model for each output).
Conceptual study of enzymatic wax ester synthesis in the batch reactor at steady state and isothermal conditions
(2021-06-01)
Ngu, Hung Hui
Wax ester is one of the most important ingredients with its many potential applications in the food industry, cosmetic industry, and pharmaceutical industry. Enzymatic esterification is preferable over chemical reaction due to its mild reaction and being more environmentally friendly. A mathematical model based on the mol balance in the batch reactor and Ping Pong Bi Bi enzymatic rate equation was developed to study the kinetic parameter, thermodynamic parameter and operational parameter of enzymatic esterification in batch reactor. POLYMATH software (version 6) was used for the simulation of this mathematical model. The model was validated with experimental data obtained from literature sources while the values of certain parameters were estimated. From the validation, the experimental and theoretical data shows a good agreement (0.88 ≤ R2 ≤ 0.98) which proves that the model and the estimated kinetic and thermodynamic parameters are accurate to represent the actual process as R2 greater than 0.8. According to the findings and simulation results, a lower value of Km and ∆Gcat leadsto a higher production yield as it indicates lower energy is required for substrate binding and to catalyze the reaction. On the other hand, a higher value of Ki and ∆Ginac are recommended for an enzyme because it indicates the enzyme is less affected by the inhibitor and resistance to deactivation at a higher temperature. Based on POLYMATH, optimum esterification conditions were 50°C temperature, 1.0×10-5 mol/L enzyme concentration and 1:2 fatty acid – fatty alcohol mole ratio. Profiling of enzyme is performed to study the inhibitory pattern. It found that, fatty alcohol shows more severe inhibition effect over fatty acid toward rate of reaction. Overall, my work on simulation is sufficiently adequate and has improved my understanding on the implementation of the production process on an industrial scale from laboratory scale.
Steady state multiplicity in the reactive distillation of methyl tert-butyl ether (mtbe) synthesis stability analysis
(2021-06-01)
Adnan, Fietriey Atiera Shahida
Reactive distillation (RD) has garnered a lot of attention due to its tremendous potential for process intensification. Due to that, the methyl tert-butyl ether (MTBE) synthesis in reactive distillation (RD) column was studied and an equilibrium model was developed by using Aspen Plus V10. The proposed model was validated by comparing the simulation results with the published simulation results from the literature. The model obtained high isobutene conversion and MTBE purity for heterogenous catalyzed system, which is desirable in the industrial MTBE production process. The comparisons on temperature profiles and liquid composition profile of RD column also yielded promising results. The proposed model can be used as a tool for the analysis of multiple steady state in RD column of MTBE. It is concluded that only single steady state of MTBE synthesis that can be found when using the same column configuration in Aspen Plus V10. Sensitivity analysis is conducted to study the influence of reflux ratio on the isobutene conversion. From this analysis, it was shown that MTBE purity and isobutene conversion were maximum at reflux ratio of 7. Stable reactive distillation of MTBE can be achieved since the equilibrium modelling has developed higher steady state solution.
Microwave irradiated rice husk based activated carbon for adsorption of chloramphenicol
(2021-06-01)
Mohd Shah, Izlan
Pharmaceutical industry was one of the main contributors of Chloramphenicol (CAP) to the water sources which can causes various environmental problems. In recent years, agriculture waste based activated carbon has been employed as an adsorbent in the treatment of antibiotics wastewater. The purpose of this study is to investigate the performance of activated carbon (AC) generated from rice husk (RH) for the removal of Chloramphenicol (CAP) by physical activation utilizing carbon dioxide (CO2) gasification and microwave irradiation technique. Response Surface Methodology (RSM) was used to optimize the rice husk based activated carbon’s(RHAC) preparation parameters of radiation power and activation time for adsorption of Chloramphenicol (CAP). The optimum conditions for RHAC preparation were observed to be 490 W of radiation power and 2 minutes of activation time which resulted 92.15% of CAP removal and 65.43% of RHAC’s yield. The CAP adsorption by RHAC increased as the initial CAP concentration and contact time increased. Adsorption equilibrium of CAP onto RHAC followed Freundlich isotherm. The kinetic studies of CAP adsorption onto RHAC was best represented by pseudo-second order kinetic models. According to the thermodynamic analysis, the value of ∆H° was negative, indicating that the adsorption was an exothermic process.
Almond shell based activated carbon prepared via microwave irradiated for chloramphenicol removal
(2021-06-01)
Saw, Wen Yi
In this study, low cost and efficient activated carbon (AC) was prepared from almond shell (AS) through microwave irradiation technique for chloramphenicol (CAP) removal. The optimization of almond shell based activated carbon (ASAC) preparation conditions of microwave irradiation power and radiation time for CAP adsorption was done by using Response Surface Methodology (RSM). The optimum preparation conditions determined were at radiation power and time of 490 W and 6 minutes, respectively, which resulted in 96.23% of CAP removal and 41.53% of ASAC yield. The optimized ASAC was characterised through Brunauer–Emmett–Teller (BET) surface area and pore structural analysis, proximate and elemental analysis, scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR). For batch adsorption study, various operational parameters such as initial concentration, contact time, solution temperature and pH on CAP adsorption were investigated. The experimental data were analyzed using three adsorption isotherm models: Langmuir, Freundlich and Temkin. It was found that the adsorption was best fitted with the Langmuir isotherm model, with maximum CAP adsorption capacity at 63.29 mg/g. Kinetic studies for CAP adsorption indicated that the adsorption process followed a pseudo second order (PSO) kinetic model. The thermodynamic parameters such as standard Gibbs free energy (∆𝐺°), standard enthalpy change (∆𝐻°) and standard entropy change (∆𝑆°) were determined. Based on the thermodynamic parameters, the adsorption of CAP onto ASAC was an endothermic and spontaneous process.
Magnetophoretic migration of magnetic nanoparticles through cellulose matrix
(2021-06-01)
Mohd Salleh, Muhammad Sufian
The migration of magnetic nanoparticles (MNPs) through cellulose matrix has been presented in this thesis. The experiment was carried out to study the influence of colloidal stability, aggregation of MNPs, concentration, the pore size of the cellulose matrix, and strength of magnetic field on the magnetophoresis of MNPs through the complex structure of cellulose. Magnetite, Fe3O4 were used as the MNPs to study the magnetophoresis under an Optical microscope. All the captured images of the magnetophoretic phenomena were analysed by using NIH ImageJ. A simple setup of the experiment was done by placing a magnet 2 cm away from the initial point of MNPs was injected on the Whatman chromatography paper. Based on the experiments conducted, 100 mg/L of poly (sodium (4) styrene sulfonate) polyelectrolyte (PSS) coated MNPs were able to migrate through grade 4 paper after 30 and 60 s of magnetophoresis with 0.007492 % and 0.0162 % of the area covered at 2 cm, respectively. As for naked MNPs with the same conditions, the area covered after 30 and 60 s is 0 and 0.00133 % respectively. It was found that the area covered for the magnetophoretic motion of MNPsthrough grade 5 paper was lower than grade 4 paper, whereas at 1.5 and 2 cm the area covered is 0.00245 % and 0.00294 % respectively. Besides, a higher concentration of MNPs solution will limit the magnetophoresis of MNPs through the matrix due to the formation of aggregation that inhibits the motion of the particles from passing through the pore of the cellulose matrix.
Comparison of different rsm designs to predict and optimize the acid violet (av 7) adsorption using rha-cfa adsorbent
(2021-06-01)
Mohamad, Ahmad Aqil Asyraaf
In this study, the factors affecting the performance of rice husk ash (RHA)-coal fly ash (CFA) adsorbent in removing acid violet 7 (AV7) dye were analysed using different type of response surface methodology (RSM). Face-Centered Composite Design, D-Optimal Design and Historical Data Design were compared based on the R2 value, Mean Square Error (MSE) and error in optimization section (%). DOD had the highest accuracy (R2 = 0.9765) in predicting dye adsorption efficiency, while FCC and HDD have lower accuracy but still in good value range (R2= 0.9335). By using Expert Design software, the optimum RHA-CFA adsorbent preparation condition with the highest AV7 dye adsorption efficiency was obtained through the numerical optimization of RSM models. Optimization by FCC and HDD, maximum adsorption efficiency obtained were 45.1% and DOD was 44.4% with RHA/CFA ratio of 3.00 and 1.00 M of NaOH. An additional experiment of RHA/CFA ratio of 3.00 and 1.00 M of NaOH is obtained from the literature and the result from it is used to compare with predicted values of each RSM design. DOD had the lowest error at value of 2.93% and both FCC and HDD models were 4.43%.
Feasibility of screen printing carbon electrode to detect ascorbic acid
(2021-06-01)
Bohiran, Muhammad Fahim Azim
Screen-printed carbon electrodes (SPCE) used for electrochemical detection consist of three electrodes: auxiliary, working, and reference electrode. The working electrode is the principal electrode on which electrochemical reactions are performed, while the reference and auxiliary electrodes are used to complete the electronic circuit. The effect of varying the working electrode conductive ink thickness (2, 3, 4, 5, and 7 layers of SPCE) on the final electrochemical activity was investigated in this study. The depth of SPCE been submerged in 20mL of analyte is fixed at 1.5 cm since the exact length is unknown. It shows that by increasing the layer of conductive ink thickness, the oxidation peak is increasing too. Four-layer SPCE gives the optimum results for detection of AA at a concentration of 3mM to 10mM with the R2 value is almost 0.99. Besides, this report also investigates the selection of ascorbic acid (AA) from citric acid (CA) by using the four-layer SPCE.
Observing the parameter dependant system on the formation of lag phase curve in a bacteria growth
(2021-06-01)
Chang, Chee Wing
Predictive biology plays an important in forecasting the behaviour of the microorganism under the unpredictable environment condition such as temperature and pH. In order to precisely simulate the growth of the microorganism, several growth models had been proposed. Logistic model, modified Gompertz equation, Luedeking-Piret model and Monod model are the models that were studied in this work. These models composed of several growth parameters which have significant impact on the growth curve. Typically, growth curves are presented in the form of sigmoidal curve. Growth parameters such as maximum specific growth rate (µmax) and lag time (𝜆) can be affected by the environment condition. In this work, the effect of the variation of the growth parameters on the formation of sigmoidal curve especially the duration of lag phase had been studied. Simulation of this work was carried out using MATLAB® and data collection by Microsoft Excel®. Higher value of maximum specific growth rate (µmax) in Logistic model and Monod model shorten the duration of lag phase while the µmax in modified Gompertz model has no effect on the duration of lag phase but make the slope of the exponential phase steeper. Besides, higher yield coefficient (Ys) is found to that not only increase the yield concentration but also increase the duration of lag phase.
Simulation study of biodiesel production via transesterification process from waste cooking oil
(2021-06-01)
Mohamad, Nurul Hazirah
Biodiesel is an environmental-friendly and alternative liquid fuel that can be used to substitute conventional diesel. It can be produced by a variety of feed stocks such as animal fats, non-edible oils and by-product of the refining vegetable oils. Biodiesel becomes a spotlight as a renewable fuel that is non-toxic and is biodegradable. It is usually synthesised by the transesterification of vegetable oil or animal fat with short chain alcohol such as methanol or ethanol. Its high oxygen content makes it a better choice for diesel engines. Waste cooking oil is one of the feedstocks that can be converted into biodiesel. Therefore, in this simulation study, waste cooking oil has been used as the raw material that reacted with methanol. This study was done by using Matlab software to observe how the operating conditions affect on the yield, conversion and selectivity of biodiesel. It was found that the temperature of 60 ̊C exhibited the highest yield of methyl ester. Oil to alcohol ratio of 1:15 gives the highest yield at 59%and catalyst weight of 1.4 wt % leads to the maximum yield of biodiesel. The simulation results obtained reasonable with the literature results and within the range studied by the previous researchers.
Optimization and thermal degradation kinetics of cellulose nanoparticles (cnps) production from coconut fiber
(2021-06-01)
Tim, Mau Sean
Optimization and thermal degradation kinetics of the cellulose nanoparticles (CNPs) production from coconut fibers were presented in this research project. The research project was carried out by using the data collected from the thesis with the title of ‘Dissolution of Natural Fiber using Ionic Liquid for Production of Cellulose Nanoparticles’ by Nadzirah binti Yahya. For optimization part, the CNPs production from coconut fibers was simulated using the Response Surface Methodology (RSM) via Central Composite Design (CCD) in Design Expert software to determine the relationship between the affecting parameters (extraction time, extraction temperature and ratio of coconut fiber (CF) to ionic liquid (IL)) on the response (ultrafine CNPs distribution). The simulation results showed that both the extraction temperature and CF:IL ratio were more significant to the regression model. The maximum ultrafine CNPs distribution obtained through the optimization process was 58.074 %, under the operating conditions of 30 mins of extraction time, 69.518 °C of extraction temperature and 0.01 w/w of CF:IL ratio. For the thermal degradation kinetics study of CNPs produced from coconut fibers, both the model-free isoconversional Kissinger-Akahira-Sunose (KAS) and Flynn-Wall-Ozawa (FWO) methods were used to determine the activation energy, Ea of the CNPs. However, the calculated results of Ea were not satisfied, which were ranged from -0.039 to -3.134 kJ/mol. The values deviated very much from the Ea value of common CNPs, and the possible source of error was predicted to be from the inaccurate results from the collected data.
Synthesis of methyl acetate by lipase catalyzed esterification
(2021-06-01)
Izudin @ Mohamad, Muhammad Firdaus
The beginning of esterification process is mostly by using chemical synthesis with the help of chemical catalyst which often involved binary or tertiary azeotropic mixture which lead to difficulty in producing high purity of product and environmental issues. Hence, esterification with the aid of biocatalyst was introduced which is proven to have a better potential especially with lipase in producing esters through enzymatic esterification. In this study, methyl acetate which has high market demand due to its end uses was synthesise by direct esterification reaction catalysed by immobilized lipase from Candida rugosa by using n-hexane as organic solvent in batch system. Celite-545 was used as a support material on immobilized Candida rugosa lipase with catalytic activity of 0.6833 U/mg. One-Factor-at-One-Time (OFAT) method was studied in order to identify the effect of the optimizing parameters including reaction time, enzyme loading, agitation speed and substrate molar ratio of acetic acid and methanol. The optimal acid conversion for methyl acetate was 58% obtained at 2 hours incubation time with 10 U/ml of enzyme loading at 45 and 150 rpm of agitation speed with a substrate molar ratio of 1:3 (acetic acid to methanol). The comparison between kinetic models of enzyme catalysed esterification with the secondary data from the article was also performed by using non-linear regression analysis. (-rAc)fmax= 2.972 mmol/min.1.g, KmAc = 0.2488 mol/l, LmAl, KiAl = 0.953 x 10-3mol/l, KiAc = 1.03 x 10-3 mol/l.
Observing the limit of oscillation in autocatalytic reaction system
(2021-06-01)
Nordin, Mohammad Juhairi
Autocatalytic reaction was one of the reactions where the concentrations of reactants intermediates form as products with periodicity. The presented by this thesis was using the Brusselator model which was one of the autocatalytic reaction systems. Autocatalysis has been widely explored in the form of models for the origin of life as a basis for self-organization. Chemical oscillation was analogous to oscillation where autocatalysis replaces positive feedback. In general, these reactions proceed evenly with varying the rates until at one point where it reaches equilibrium. Complex dynamical phenomena such as bistability, oscillations, deterministic instability, and random forming of spatial patterns or waves may occur in autocatalytic systems, which were undesirable in chemical production. The differentiation between first order and higher-order autocatalysis proved to be extremely useful. Both situations in which a single autocatalytic particle was active on the reactant side were classified as first-order autocatalysis.
Microwave – assisted extraction (mae) of rhizome kaempferia parviflora crude and its biological activity
(2021-06-01)
Mohammad Gial, Mohamad Anwar
Extraction is a process to separate the desired natural products from the raw materials. It has been used in various industry such as food and pharmaceutical industries to achieve certain level of nutrients in the products. However, traditional extraction method required a large volume of solvents and longer extraction time. Hence, advanced extraction which is microwave-assisted extraction was carried out. This research study focusses on green extraction technique where the solvent used is water. Microwave-assisted extraction (MAE) was optimized by Response Surface Methodology (RSM) to enhance the extraction of rhizome K. Parviflora crude. The optimization was done to get the optimum microwave power, microwave extraction time and solvent to feed ratio with maximum response. Central Composite Design (CCD) was selected as a model for RSM to evaluate the first and second-order polynomial model. The analysis of variance was used to evaluate the model fitness and optimal condition. Considering the maximum content of extracted yield, total phenolic content and antioxidant activity, the optimal conditions for all investigated response were obtained at microwave power of 360 W, microwave time of 2 min and solvent feed ratio of (10:1). Under the optimal condition, obtained K. Parviflora crude extract contained 16.72% yield of crude extract, 18.24 μg /ml of total phenolic content and 142.681 μg/ml of antioxidant activity. The study revealed that the response surface methodology (RSM) is an efficient statistical method for preparing appropriate empirical model related to the independent variables and predicting the optimum conditions influencing K. Parviflora crude extract. Microwave-assisted extraction is an environmental-friendly technique for extractions of bioactive compounds and an attractive alternative procedure in industry food and traditional herb.
Amphoteric adsorbent coating for pharmaceutical waste (diclofenac sodium) removal
(2021-06-01)
Abdul Taib, Muhammad Haziq
The removal of diclofenac sodium (DCF) using a novel amphoteric absorbent coating (AAC) has been presented by this thesis. The formulation of the adsorbent was through a formation of a layer on the surface of a cotton cloth through facile method application using acrylic polymer emulsion (APE), smectite-based clay powder, and cationic polyelectrolyte (EPIDMA). SEM and EDX analysis were conducted for the characterization of the adsorbent coating. The experiments were carried out to study the effect of EPIDMA dosage, concentration, contact time, temperature, and pH of DCF solution on the removal efficiency of the DCF. The optimized percentage removal of DCF is at 77.06% at DCF concentration of 50 mg/L, temperature of 30°C and pH of 3 for 5 hours. Adsorption isotherms were developed to study the adsorption mechanism of the adsorption. This study has shown that the aforementioned parameters influence the performance of the AAC for DCF removal. With high removal efficiency and reusability, AAC was found to be a promising adsorbent for DCF removal from pharmaceutical wastewater system.

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