Pusat Pengajian Kejuruteraan Kimia - Tesis

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A comprehensive study on developing neural network models for predicting the coagulant dosage and treated water qualities for a water treatment plant.
(2019-07)
Jayaweera, Chamanthi Denisha
Determination of the optimum coagulant dosage for water treatment is traditionally carried out using the jar test, which is a time consuming procedure incapable of responding to sudden changes in water qualities. Therefore, data driven modeling techniques such as neural networks are used for developing predictive models for the coagulation process. In this work, three different neural network models, namely, the general regression neural network (GRNN), extreme learning machine single layer feed forward neural network (ELM-SLFN) and the extreme learning machine radial basis function neural network (ELM-RBF) were developed to predict the coagulant dosage, and their performances were compared with the commonly used multilayer perceptron neural network (MLP). It was shown that the ELM and the GRNN models consumed significantly lesser effort and time for training compared to the MLP. The ELM-RBF demonstrated the best tradeoff between prediction accuracy and computational requirement. Therefore, the ELM-RBF was used to develop models for predicting the coagulant dosage, treated water (TW) turbidity and residual aluminum with R values of 0.9752, 0.8239 and 0.9019 respectively. The input parameters required to develop each model was determined using a global exhaustive search algorithm as it was shown that the Pearson correlation coefficient and the principal component analysis were not suitable techniques for selecting input parameters for this study. Thus, inputs used for predicting the coagulant dosage were raw water (RW) turbidity, RW color and alum (t-1). The effectiveness of the coagulant dosage and the TW quality models were improved using an imputation model and a genetic algorithm. The imputation model was developed using K means clustering with an imputation accuracy similar to a self-organizing map, to cope with failures in hardware sensors causing downtime in fully automated water treatment plants and ensure the continual use of the coagulant dosage model. The imputation model reconstructed missing values of RW turbidity and RW color with R values of 0.9075 and 0.8250 respectively. Subsequently, the reconstructed RW turbidity and RW color were used to predict the coagulant dosage with R values of 0.9742 and 0.9809 respectively, which are highly satisfactory. Meanwhile, the GA improved the R value of the TW turbidity model to 0.8294. The GA significantly improved the ability of the ELM-RBF to identify the required response of TW turbidity to the alum dosage.
Synthesis of molecularly imprinted polymer-ordered mesoporous silica adsorbent for batch and fixed-bed column adsorption of chloramphenicol
(2024-09-01)
Zulkarnain Bin Mohamed Idris
This study describes a novel synthesis of a surface-imprinted polymer-ordered mesoporous silica adsorbent for highly selective chloramphenicol (CAP) adsorption using activator regenerated by electron transfer atom transfer radical polymerization (ARGET ATRP). Initially, ordered mesoporous silica was synthesized by the sol-gel method and functionalized to prepare a silica-ATRP initiator (SiO2@Br) for polymer grafting. CAP was used as the template molecule for imprinting via precipitation polymerization. The effects of varying polymerization reaction parameters, such as template to functional monomer molar ratio (1:2 – 1:10), template to cross-linker molar ratio (1:4 – 1:20), solvent types (acetonitrile and toluene) and their mixtures (0 – 100%), catalyst to ligand ratio (1:2 – 1:10), catalyst to reducing agent ratio (1:2 – 1:10), reaction temperature (313 – 353 K), and reaction time (6 – 30 h) on imprinting factor (IF) values and adsorption capacities (Qt) were studied. The physical and chemical properties of the resulting adsorbent were analyzed using FTIR, TGA, EDX, SEM, HRTEM, and nitrogen sorption techniques. The SiO2@Br had a specific surface area of 638.31 m².g-1 and a total pore volume of 0.4152 cm³.g-1. Post-polymerization, the specific surface area and pore volume of the adsorbent (SiO2@MIPs-CAPcr) decreased to 11.91 m².g-1 and 0.019 cm³.g-1, indicating successful grafting. Adsorption performance was investigated through batch and fixed-bed column studies. Batch experiments investigated the effects of initial solute concentration (10 – 50 mg.L-1), adsorbent dosage (5 – 25 mg), temperature (293 – 313 K), and initial pH (3 – 11) on CAP adsorption. The adsorption equilibrium data for SiO2@MIPs-CAPcr were well fitted by the Sips models, with a maximum adsorption capacity (Qs) of 19.68 mg.g-1. The adsorption kinetic followed pseudo second-order behaviour. Thermodynamic analysis indicated an exothermic process with entropy change due to reduced molecule movement. Selectivity studies involved antibiotics ciprofloxacin (CIP) and thiamphenicol (TAP) as model adsorbates. Fixed-bed column experiments tested initial concentrations (10 – 50 mg.L-1), volumetric inlet flow rates (0.1 – 0.5 mL.min-1), and bed heights (0.5 – 1.0 cm). The Thomas model best described the fixed-bed column adsorption behaviour. The SiO2@MIPs-CAPcr adsorbent demonstrated remarkable selectivity for CAP and excellent adsorption capabilities in both batch and fixed-bed operations.
Copper oxide nanocrystals based electrospun nanofibrous membrane for solar water evaporation
(2024-03-01)
Zhao, Jianghu
Solar water evaporation has attracted widespread research, which narrowed the huge gap between inadequate clean water supply and human needs. For membrane evaporators, improving the solar absorption, water supply ability, and thermal management are critical to photothermal performance. Developing a suitable structure of light absorbing material could be a feasible approach to address these problems and to enhance evaporation performance. Yet there is limited research focus on this topic. In this study, three different structural CuO-based membrane evaporators were developed to adjust the membrane properties for improving solar evaporation performance. First of all, a triple-layer P/CuO-nanocluster nanofibrous membrane was fabricated through electrospinning, heating and hydrothermal processes. The top and bottom hydrophilic layers of CuO-nanocluster can effectively absorb sunlight, transport water, and suppress salt accumulation on the membrane surface. The middle layer of nanofibrous PVDF-HFP thin-film can support the whole system. The resultant membrane showed an evaporation rate of 1.21 kgm−2h−1 and efficiency of 83.57% for 3.5 wt.% saline water, which is higher than control group without membrane of 0.24 kgm−2h−1 and 16.26%, respectively. The next membrane structure design was core-shell structural P/CuO-Ag NPs nanofibrous membrane. During the electrospinning process, hydrophilic PVP was introduced to help more CuO growth media penetrating into the membrane interior during hydrothermal process. The Ag NPs incorporation enhanced membrane light absorption and wettability. The resultant core-shell P/CuO-Ag membrane achieved better evaporation rates of 1.31 kgm−2h−1 and efficiency of 90.77% for 3.5 wt.% saline water. The final membrane structure was hollow structural P/CuO-C nanofibrous membrane synthesized through coaxial electrospinning. During the fabrication process, the spinning precursor mixed with C NPs in the shell layer to enhance the light absorption while the hydrophilic PVP in the core layer was removed in the hydrothermal step to form a hollow structure. The formation of the hollow structure not only enhanced light absorption but also improved thermal management capacity of the membrane. As a result, the hollow structural P/CuO-C membrane achieved the best evaporation rate of 1.36 kgm−2h−1 and efficiency of 93.07% for 3.5 wt.% saline water as compared to the previous two structures. The outcome of this work will inspire subsequent research to construct of suitable architecture materials for potential applications in water treatment, thermal insulation, energy generation, energy storage, and other related fields.
High-performance titaniumfunctionalised Sba-15 adsorbent for carbon dioxide adsorption
(2024-03)
Shalini a/p Mahendran
The adverse effects of global warming have attracted the attention of the world’s public and are becoming increasingly important today. This is a consequence of the greenhouse effect, in which greenhouse gases, especially CO2, trap heat near the Earth’s surface. Despite this, CO2 has several advantages, including the ability to generate electricity and fuel. Therefore, the use of one of the three primary methods of carbon capture is crucial to remove CO2 from the environment. CO2 adsorption when paired with a suitable adsorbent, presents itself as a promising technology for addressing the challenges posed by the rising CO2 levels and global climate change. In the sol-gel method, Santa Barbara Amorphous-15 (SBA-15) was produced using TEOS, a source of silica, and Pluronic P123, a non-ionic surfactant, with hydrochloric acid (HCl) serving as the catalyst. However, the synthesised adsorbent's potential has not yet been completely maximised, as a result, titanium isoproproxide modification was carried out, producing titanium modified SBA-15 (Ti-SBA-15). The synthesized and modified adsorbent was utilized in a fixed-bed column adsorption system to study the impacts of various factors including CO2 adsorption temperature, inlet concentration of feed, adsorbent mass, and feed flow rate. The synthesized SBA-15 was subjected to a number of physicochemical analyses, including scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), atomic force microscopy (AFM), X-ray diffraction (XRD) analysis, Fourier transform infrared (FTIR), transmission electron microscopy (TEM), BET surface area analysis and Xray photoelectron spectroscopy (XPS). Based on experimental results, it can be concluded that the adsorbent’s ability to adsorb CO2 improved when it is modified with titanium isopropoxide. This is because titanium introduces new active sites called as the Lewis acid sites. These active sites interact with CO2 molecules through the Lewis acid-base interactions and therefore improving the CO2 adsorption capacity onto the adsorbent. Besides, the column’s ability to adsorb CO2 was enhanced when the CO2 content in the feed was raised while the adsorption temperature and feed flow rate were both lowered to 30oC. Pseudo- first-order and pseudo-second-order kinetics, as well as the Avrami model, were used to interpret the kinetics of the CO2 adsorption experiment. These three models help to understand and quantify the rate at which adsorption occurs over time and can provide insights into the adsorption mechanism and helps to optimize process conditions. This adsorbent’s ability to adsorb CO2 was improved as the CO2 feed concentration was raised, whereas it declined as feed flowrate, temperature, and adsorbent loading increased. This is due to the reduction in residence time when the flowrate is increased, the adsorption process being an exothermic process and the active sites being inaccessible to CO2 molecules. The kinetic model proposed by Avrami shows that it best fits the experimental data. Three fixed bed adsorption column models namely the Adam-Bohart model, Thomas model and Yoon-Nelson model were used to describe the behavior of an adsorption process occurring in the fixed bed. The Thomas and Yoon-Nelson models were successful in predicting how well SBA-15 adsorbs CO2 in a fixed-bed column while the Adam- Bohart model did not match the column data well, owing to the low R2 values of 0.6 and the weak correlation between experimental and model values.
Polyvinylidene fluoride/calcium carbonate membranes with the nonwetted and wetted surface for dual-phase separation
(2024-09)
Sarah Qistina binti Zaliman
Dual-phase separation using membranes involves the permeation of target compounds between gas-liquid and liquid-liquid phases. However, the permeation can be restricted by surface wetting important. In this work, poly(vinylidene fluoride) (PVDF) membranes with switchable surface wetting were developed through nanoparticle incorporation and 3D-imprinting, followed by drying or wetting after phase inversion. In order to achieve the nanoroughness, low cost and biocompatible calcium carbonate (CaCO3) nanoparticles were introduced into PVDF dope solution. A micro-roughness was imprinted on the membrane by phase inversion in a water bath after casting on a woven support. For nanotemplating, the nanoparticles were premodified using stearic acid to reduce surface energy or removed using ethylenediaminetetraacetic acid. Scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) were used to observe the presence of CaCO3 nanoparticles. As a result of the addition of CaCO3 and stearic acid-modified CaCO3 (SA-CaCO3), the membrane pore size and porosity were significantly improved due to demixing during phase inversion. Removing CaCO3 nanoparticles using ethylenediaminetetraacetic acid enlarged the pore size greatly. PVDF/CaCO3 and PVDF/SA- CaCO3 membranes attained superhydrophobic surface after drying. Working as the membrane gas contactor, the PVDF membrane incorporated with SA-CaCO3 reached a high CO2 permeation flux of 1.86 ±0.05×10-2 mol m-2 s-1 and slight changes in surface hydrophobicity after 50 h of being immersed in amine solution. On the other hand, the hydrophobic PVDF and PVDF/SA-CaCO3 membranes developed in this work were rinsed with absolute ethanol and immersed in distilled water to attain a wetted surface. The non-wetted and wetted membranes were then tested in the separation of oil in water (O/W) and water in oil emulsion (W/O), respectively. A dead-end filtration setup was used to examine their separation efficiency for the liquid-liquid phase under the operating pressure of 0.2 bar (O/W) or 1 bar (W/O). The oil (O/W) could be separated effectively without significant fouling due to the formation of an underwater oleophobic surface. However, the removal of water (W/O) was considerably inefficient slow due to the large pore size.

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