MEP Showcase 2023 Department of Chemical and Environmental Engineering 30 May 2023
1 Foreword The Master of Engineering Project (MEP) Showcase marks the end of journey for all MEng students in the Department of Chemical and Environmental Engineering, University of Nottingham Malaysia (UNM). The MEP is a 60-credit module, which contributes to 50% of the total credit in the Year 4 study. Hence, it is not surprising to hear that most students have spent long hours and sleepless nights in front of their computers in order to get the various elements of MEP completed; these include advanced design project, research proposal, research papers and poster, etc. Some of them also spent long hours in the laboratories with their experimental research works. I am sure all these hard work and dedication form part of their unforgotten memory during the 4 years study at UNM. We often hear that at work place, most graduates only make use of less than 5 – 10% of what they have learnt in the university. Hence, what is more important is the training of soft skills during the entire duration of MEP, e.g. presentation, teamwork, adhering to deadlines and professional conducts, which will assist our graduates to progress well in their career. We hope that your future employers will appreciate the training that we have provided to all of you. To all future engineers, we wish you all the best for future undertakings. Please do pay us a visit when there is an opportunity in the future. Best of luck! Professor Dominic C. Y. Foo PhD, FASc, FIChemE, FHEA, FIEM, PEng, CEng, ACPE Head, Department of Chemical and Environmental Engineering
2 Table of content FOREWORD ................................................................................................................................................ 1 TABLE OF CONTENT .................................................................................................................................... 2 PROGRAMME ............................................................................................................................................. 3 ABSTRACTS – SESSION A1 ........................................................................................................................... 6 GROUP 5................................................................................................................................................................ 7 GROUP 8.............................................................................................................................................................. 10 GROUP 16............................................................................................................................................................ 12 GROUP 17.......................................................................................................................................................... 134 GROUP 20............................................................................................................................................................ 16 GROUP 21 ..………………………………………………………………………………………………………………………………………………...18 ABSTRACTS – SESSION B1 .......................................................................................................................... 20 GROUP 3.............................................................................................................................................................. 21 GROUP 4.............................................................................................................................................................. 23 GROUP 13............................................................................................................................................................ 25 GROUP 22............................................................................................................................................................ 27 GROUP 28............................................................................................................................................................ 29 GROUP 2……………………………………………………………………………………………………………………………………………………..31 ABSTRACTS – SESSION A2 .......................................................................................................................... 33 GROUP 9.............................................................................................................................................................. 34 GROUP 14............................................................................................................................................................ 36 GROUP 15............................................................................................................................................................ 38 GROUP 19............................................................................................................................................................ 41 GROUP 23............................................................................................................................................................ 43 GROUP 18……………………………………………………………………………………………………………………………………………………45 GROUP 10……………………………………………………………………………………………………………………………………………………47 ABSTRACTS – SESSION B2 .......................................................................................................................... 49 GROUP 6.............................................................................................................................................................. 50 GROUP 7.............................................................................................................................................................. 52 GROUP 11............................................................................................................................................................ 55 GROUP 12............................................................................................................................................................ 58 GROUP 27............................................................................................................................................................ 60 GROUP 26……………………………………………………………………………………………………………………………………………………………63 GROUP 24……………………………………………………………………………………………………………………………………………………………66
3 Programme Time (F1A13) 8:00 – 9:00 am Arrival of Guests and VIPs, followed by breakfast 9:00 – 9:10 am Opening speech by HOD, Ir Prof Dominic Foo Session A1 (F1A13) 9:15 – 9:35 am Group 5: Methyl orange dye adsorption-desorption using 3Dprinted and polymer-derived ceramics (PDC) monoliths grafted with chitosan-based adsorbents via silane modification 9:35 - 9:55 am Group 8: Adsorption of rhodamine 6G and methylene blue dyes by a three-dimensional zirconia-based graphene composite: Synthesis, characterisation and optimisation studies 9:55 - 10:15 am Group 16: Development of heteroatom-grafted graphene aerogels for effective pharmaceutical pollutants removal: adsorption and optimisation studies 10:15 - 10:35 am Group 17: Removal of doxycycline and tetracycline by novel graphene oxide composites: Synthesis, photodegradation and optimisation studies 10:35 - 11:05 am Group 20: Synthesis and optimization of natural dye from plant derived colourants and its application on cotton fabric using ultrasonic-assisted method 11:05 - 11:35 am Group 21: Biosorption of heavy metals Session B1 (F1A15) 9:15 – 9:45 am Group 3: Machine learning-based optimisation and economic analysis of industrial-scale anaerobic co-digestion (ACoD) of palm oil mill effluent (POME) and decanter cake (DC) 9:45 -10:15 am Group 4: Design of membrane polymers for gas separation by combining machine learning tools with computer-aided molecular design 10:15 - 10:45 am Group 13: Optimisation of household food waste cocomposting with biochar integrated with internet of things (IoT) 10:45 - 11:05 am Group 22: Application of machine learning and deep learning models for the prediction of microalgae’s various growth parameters 11:05 - 11:25 am Group 28: Development of a machine learning-based prediction tool and a life cycle assessment for biogas emissions from POME anaerobic digestion process 11:25 - 11:45 am Group 2: Modelling of thermochemical energy recovery processes from biomass
4 Time (F1 Foyer) 12:00 – 2.00 pm Lunch break & Poster Evaluation Session A2 (F1A13) 2:00 - 2:20pm Group 9: Drying, baking kinetics and simulation of biscuit enriched with cricket powder and quality evaluation 2:20 - 2:50pm Group 14: Drying of Phaleria macrocarpa 2:50 - 3:20pm Group 15: Study of N-acetylnueraminic acid (NANA) from edible bird’s nests (EBN) with extraction and drying kinetics, regression analysis of extraction concentration and EBN beverage analysis 3:20 - 3:50pm Group 19: Nutrient enrichment of palm kernel cakes as poultry feed with Moringa oleifera leaf 3:50 - 4:10pm Group 23: Investigation on the cultivation and extraction of Cphycocyanin from Spirulina platensis with various parameters 4:10 - 4:30pm Group 18: Microwave-dried chitosan-phycocyanin membranes for wound healing 4.30 - 4.50pm Group 10 – Passive radiative cooling effects of BaSO4 and CaCO3-based paint under Malaysia’s tropical climate Session B2 (F1A15) 2:00 – 2:20pm Group 6: Pinch-based approach for the optimisation of enhanced weathering and biochar application networks 2:20 – 2:40pm Group 7: Optimal reaction pathways synthesis using P-graph attainable region technique (PART) 2:40 – 3:00pm Group 11: Synthesis and optimisation of sustainability performance for palm oil biomass waste-to-wealth supply network with P-graph approach 3:00 – 3:20pm Group 12: Integrated synthesis pathway of plastic for hydrogen production for a sustainable energy transition: A Pgraph approach 3:20 – 3:40pm Group 27: A two stage fuzzy-game theory optimisation framework and a mathematical synthesis model for wastewater treatment plant (WWTP) in eco-industrial park (EIP) for palm oil industry 3:40 – 4:10pm Group 26: Characterisation of co-precipitated nickel manganese oxide catalysts: Effects of preparation and ultrasonic conditions with nickel recovery optimisation through acid leaching 4:10 – 4:30pm Group 24: Hydrothermal operations for biofuel and gas sensor applications
5 Time (F1A13) 5.00 – 5.20 pm Closing Speech by HoD Ir. Prof. Dominic Foo Chwan Yee
6 Abstracts – Session A1 Abstracts Session A1
7 Group 8 L-R: Qisya Izanti, Ir Ts Dr Chong Chien Hwa and Gloria Yong Tung Xin Group 5
8 Methyl orange dye adsorption-desorption using 3Dprinted acrylate and polymer-derived ceramics (PDC) monoliths grafted with chitosan-based adsorbents via silane modification Qisya Izanti Binti Mohammad Amirul Mursyid, Gloria Yong Tung Xin, Chong Chien Hwa, Nurul Husna Mohd Yusoff Abstract: Synthetic dyes in textile wastewater are difficult to remove and can affect photosynthetic activity of marine life and aesthetic view of treated waters. The objective of this study is to fabricate methyl orange dye adsorbents using 3D-printed monolithic structure supports grafted with chitosan-based composites through silane modification. Two types of adsorbents using different materials were synthesized - 3D-printed PEG200DA-based monolithic support grafted with magnetic chitosan fluid (MCF), and 3D-printed silicon oxycarbide (SiOC) polymer-derived ceramic monolithic support grafted with chitosan-graphene oxide (GO) composite. In terms of the MCF grafted PEG200DA monolith, the method of magnetite dispersion, MCFcoating viscosity, methyl orange (MO) dye pH and addition of crosslinker were investigated. All parameters had a major impact on the stability and adsorptiondesorption performance of the MCF-coated monolith support. Adsorption studies for MO dye resulted in an 82% adsorption rate for 50 ppm dye at temperature 25ºC, pH 4.0 conditions. The reusability was confirmed at 74.2% retention after 4 adsorptiondesorption cycles, with desorption under the influence of 50 mT magnetic field. The adsorption-desorption were governed by chemisorption and physisorption. It possessed excellent mechanical and rheological properties supported by textural and thermal analysis. The thermal stability and fraction of volatile components were determined by thermogravimetric analysis and differential scanning calorimetry (TGA-DSC). The grafting of MCF coat and presence of magnetite were confirmed by field emission scanning electron microscopy and energy dispersive X-ray analysis (FESEM-EDX) with functional groups, crystalline structure and element composition verified by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) analysis respectively. In terms of the chitosan-GO grafted PDC monolith, the optimum pyrolytic conversion parameters of the PDC and mass ratios of GO to chitosan of the composite were studied. Adsorption studies for 50 ppm MO dye using GO to chitosan mass ratio of 0.1 adsorbent resulted in a removal efficiency (R%) of 91.16% and uptake capacity () of 182.33 (mg/g) at temperature 30°C, pH 3.0 conditions. The crosslinked chitosan-GO composite
9 provided a strong adsorption property for methyl orange due to combined impacts of the large amino groups on the chitosan and the structural conjugation of the graphene oxide. The crosslinking and grafting mechanisms were studied and confirmed through characterisation tests including FTIR, FESEM-EDX, XRD, TGA and Raman spectroscopy. Both the grafted PEG200DA and PDC monoliths possessed considerable mechanical properties and stability, potentially viable for real applications. Keywords: 3D printing; Wastewater Treatment; Polymer-derived Ceramics; Silanegrafting; Chitosan-graphene Oxide Composite; Magnetic-Chitosan Fluid; Adsorption; Desorption; Chemisorption-Physisorption
10 L-R: Dr Lee Lai Yee, Yeo Yen Seng, Chai Yi Ni, Prof Gan Suyin Group 8
11 Adsorption of rhodamine 6G and methylene blue dyes by a three-dimensional zirconia-based graphene composite: Synthesis, characterisation and optimisation studies Yi Ni Chai, Yen Seng Yeo, Suyin Gan, Lai Yee Lee Abstract: Water pollution caused by synthetic dyes, such as Rhodamine 6G (R6G) and Methylene Blue (MB) dyes, is an escalating environmental issue due to their high toxicity and non-biodegradability features that can cause damages of the environment and livelihood of mankind. To address this issue, a new three-dimensional (3D) graphene adsorbent reinforced with zirconia was developed via freeze-casting approach in this study. The adsorption efficiency of the newly fabricated adsorbent was evaluated for the removal of R6G and MB dyes through batch adsorption tests. The process parameters manipulated included initial dye concentration, adsorbent dosage, temperature and contact time. Various characterisation techniques such as thermogravimetric analysis, Fourier transform infrared, energy dispersive X-ray spectroscopy and scanning electron microscopy were conducted to determine the thermal stability, surface active groups and morphology of the 3D graphene adsorbent. The optimum adsorption conditions were determined using response surface methodology with a central composite design approach. The adsorption kinetics were evaluated by fitting the experimental data to the pseudo-first-order, pseudo-secondorder and Elovich models, while the equilibrium data were fitted to the Langmuir, Freundlich, Temkin and Dubinin-Radushkevich isotherms. Both kinetics and isotherm modeling allowed for a further understanding of the mechanisms behind the adsorption process. The thermodynamic study assessed the spontaneity and feasibility of the dyes adsorption. The regeneration potential of the graphene composite was evaluated through multiple cycles of adsorption-desorption tests. Overall, the studies exhibited high adsorption and regeneration efficiencies of the 3D graphene adsorbent, hence suggesting its high potential applications in dye wastewater treatment. Keywords: Adsorption; Graphene oxide; Methylene Blue; Rhodamine 6G; Zirconia; Response surface methodology
12 L-R: Prof Gan Suyin, Yong Jia En, Jasmine Chua, Dr Lee Lai Yee Group 16
13 Development of heteroatom-grafted graphene aerogels for effective pharmaceutical pollutants removal: adsorption and optimisation studies Jia En Yong, Jasmine Chua, Suyin Gan, Lai Yee Lee Abstract: Exposure of aquatic environment to pharmaceutical residues has threatened the marine biodiversity and human health via the consumption of the pharmaceuticalcontaminated water. These chemical compounds pose health and safety risks due to their recalcitrant and bioaccumulation nature. The current work focused on the development of new boron- and phosphorus-grafted graphene oxide aerogels as ecofriendly adsorbents for the removal of imipramine and amitriptyline in aqueous systems. The physicochemical properties of the graphene-based adsorbents were determined by field emission scanning electron microscopy, energy-dispersive X-ray spectroscopy, Fourier-transform infrared spectroscopy and thermogravimetric analysis. The effects of single-parameter such as dosage, initial pharmaceutical concentration, contact time and temperature were investigated through batch adsorption and fixed-bed column setup. Further study on the interactive influences of multi-parameters on the removal percentages of both imipramine and amitriptyline was performed by response surface methodology. Optimisation of the adsorption parameters to attain maximum adsorption capacities were executed by central composite design of response surface methodology. The adsorption isotherm, kinetic and fixed-bed column performances were studied via relevant models to validate the adsorption behaviour of the pharmaceutical pollutants on the surface of the adsorbents. Spontaneity and feasibility of the adsorption process were examined by the thermodynamic study. Regeneration performance of the exhausted adsorbents were evaluated using various chemical eluting agents based on the regeneration and adsorption efficiencies. Conclusively, the outcomes strongly advocate the developed graphene aerogels as highly effective and feasible graphene-based adsorbents for imipramine and amitriptyline sequestration from pharmaceutical wastewater. Keywords: Graphene aerogel; Pharmaceutical Residue; Imipramine; Amitriptyline; Batch and fixed-bed adsorption; Central composite design
14 Group 17 L-R: Dr Lee Lai Yee, Jasmine Jill Yong Jia Yi, Brandon Goh Zi Hao, Prof Gan Suyin
15 Removal of doxycycline and tetracycline by novel graphene oxide composites: Synthesis, photodegradation and optimisation studies Brandon Zi Hao Goh, Jasmine Jill Yong Jia Yi, Suyin Gan, Lai Yee Lee Abstract: Pharmaceutical pollution has drawn major concerns lately due to its harmful effects on the environment on a global scale. Specifically, the widespread use of tetracycline and doxycycline in healthcare and livestock husbandry has increased the emission of such antibiotics into wastewater. Long-term exposure to these pharmaceutical residues can lead to detrimental health and environmental effects, including the rise of antibiotic resistance genes as secondary pollutants. Photocatalysis based on graphene oxide is a potential remediation technique for pharmaceuticalpolluted water owing to its large surface area, abundant oxygenated functional groups and high electron mobility. To enhance the photocatalytic activity of graphene oxide, semiconductors such as manganese dioxide (MnO2) and vanadium pentoxide (V2O5) can be grafted into the graphene network, forming heterojunction photocatalysts. Herein, the main aim of the research was to develop novel graphene oxide/MnO2/V2O5 composites for enhancing the photodegradation of tetracycline and doxycycline in aqueous systems. The as-synthesised graphene composites were thermally stable as supported by the thermogravimetric result, while the participation of hydroxyl, carbonyl, carboxyl, manganese- and vanadium-based groups in the photocatalytic activity was confirmed by the Fourier transform infrared results. The removal of tetracycline and doxycycline was optimised by response surface methodology. Remarkable removal of the pharmaceuticals was observed under the optimised conditions and potential recyclability of the graphene composites was successfully performed via photo-regeneration. The kinetics of the process were well correlated to the pseudo-second-order kinetic model. A step-scheme charge mobility mechanism was postulated for the graphene oxide/MnO2/V2O5 heterojunction structure. The results suggest the as-synthesised graphene composites as effective photocatalysts for the removal of tetracycline and doxycycline in pharmaceutical wastewater. Keywords: Graphene oxide; Doxycycline; Tetracycline; Photodegradation; Optimisation; Wastewater
16 Group 20 L-R: Chuah Shang Jee, Dr Vasanthi Sethu, Muhamad Asyraf and Mohamed Nadeem Adjie
17 Synthesis and optimisation of natural dye from plant derived colourants and its application on cotton fabric using ultrasonic-assisted method Chuah Shang Jee, Mohamed Nadeem Adjie, Muhamad Asyraf Mohd Rushdan, Vasanthi Sethu Abstract: Natural dyes are becoming increasingly popular in the textile industry due to their eco-friendliness and sustainability. This study focuses on optimizing the dyeing parameters of three natural dyes: beetroot, black tea leaves, and turmeric to achieve the greatest colour strength on cotton fabrics using ultrasonic-assisted dyeing. The parameters varied in this study include pH, dye concentration, time of dyeing, concentration of salt, and temperature. Beetroot is a lesser-known natural dye that has the potential to produce vivid shades of pink and red on cotton fabrics depending on the colour strength. Black tea leaves are another interesting natural dye sources that produce brown shades on cotton fabrics and turmeric is a commonly used natural dye producing a yellow-orange hue on cotton fabrics. The choice of dyeing parameters plays a critical role in determining the colour strength of the dyed fabrics. pH affects the ionization of the dye molecules and the degree of protonation of the fabric fibres, which, in turn, affects dye uptake. Dye concentration and time of dyeing affect the availability of dye molecules to penetrate the fabric fibres and the duration of time they are in contact with the fibres. Salt concentration affects the ionic strength of the dye bath, potentially increasing dye uptake and colour development. Temperature affects the rate of dye diffusion into the fabric fibres and the degree of aggregation of dye molecules in the dye bath. The optimized dyeing parameters for turmeric were found to be a dye concentration of 0.0075g/mL, pH of 7, 70°C, 40 mins of dyeing, and a salt concentration of 0.0075g/mL. For beetroot, the optimal parameters were found to be 70°C, 80 mins of dyeing, a dye concentration of 0.03g/mL, a salt concentration of 0.005g/mL, and a pH of 5. The optimized parameters for black tea leaves were found to be a dye concentration of 0.08 g/mL, 60°C, 140 mins of dyeing, a salt concentration of 0.015 g/mL, and a pH of 4. These optimized dyeing parameters aim to provide a sustainable and eco-friendly alternative to synthetic dyes in the textile industry while achieving high colour strength. Keywords: Ultrasonic-assisted Extraction; Beetroot; Turmeric Powder; Black Tea Leaves
18 Group 21 L-R: Goh Qianyan, Dina Maged Salah Mohamed Tawfiq, Celine Ta Su Qing and Dr Vasanthi Sethu
19 Biosorption of heavy metals Goh Qianyan, Celine Ta Su Qing, Dina Maged Salah Mohamed Tawfik, Vasanthi Sethu Abstract: Heavy metals are regularly used in industries; hence the growing rate of industrialization has resulted in increasing levels of industrial effluents with high levels of heavy metal contamination. These heavy metals exist naturally in the environment however the added anthropogenic discharge will increase the concentration to toxic levels. These heavy metals, can be removed through economical and effective methods such as biosorption. Biosorbents are derived from Mango leaves (ML), Lemon peels (LP) and sugarcane bagasse (SCB), after which they were tested on the adsorption of different appropriate heavy metals. Fourier transformation infrared spectrometry and scanning electron microscopy analysis were conducted to show the surface texture of biosorbents and metal binding of functional groups to further elaborate the biosorption mechanism. Whereas BET was conducted to measure the surface area and pore volume. The removal of copper at 100 mg/L using 0.4 g/L ML powder at pH 4.5 for 120 minutes found an adsorption capacity of 206.85 mg/g, facilitated by Freundlich isotherm under pseudo second order kinetic model through chemisorption film diffusion at low concentrations and intraparticle diffusion otherwise. The same copper concentration was adsorbed using 1g/L of SCB powder at pH 7 for 100 minutes which resulted in a removal efficiency of 54.86%. Modifications were made to the SCB powder in order to alter its surface morphology and functional groups in order to increase adsorption capacity. Moreover, the adsorption of nickel through the usage of Lemon peel powder was observed to have a removal efficiency of 68.18% at pH 5 with the maximum adsorption after 45 minutes and temperature 50˚C. The adsorption follows the Freundlich isotherm and did not fit with either kinetic model. Furthermore, the desorption and regeneration were assessed and found to successful, presenting by capturing 77.28% of nickel after regeneration. The biosorption was measured under different parameters for pH, dosage and temperature to find the optimal parameters to identify the mentioned results. After which to allow for further optimization, Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) integrated predictive techniques are revised to predict the adsorption capacity using different embedded parameters within a range of 10-20% accuracy. The ANN has successfully captured non-linear behavior of the system and simultaneously predicted the output with Levenberg-Marquardt training algorithm and 10 neurons in the hidden layer. Keywords: Heavy metal remediation, biosorption technique, characterisation of adsorbents, batch experiments, data optimization, ANN predictive modelling, RSM in Minitab
20 Abstracts – Session B1 Abstracts Session B1
21 L-R: Pang Bo Yang, Jessy Hoon Yee Theng, Ir Dr Chan Yi Jing, Elicia Gan Yee Ting Group 3
22 Machine learning-based optimization and economic analysis of industrial-scale anaerobic co-digestion (ACoD) of palm oil mill effluent (POME) and decanter cake (DC) Elicia Gan Yee Ting, Jessy Hoon Yee Theng, Pang Bo Yang, Yi Jing Chan Abstract: Palm oil production generates a significant amount of wastewater known as palm oil mill effluent (POME), which requires treatment before being discharged into the environment. The production of biogas can be enhanced by anaerobic codigestion (ACoD) of palm oil mill effluent (POME) and decanter cake (DC) as it increases the efficiency of the digestion process by the improvement of BOD removal, COD removal and methane yield. Recently, machine learning (ML) techniques have been developed for the prediction of the performance of ACoD processes, however, these techniques have not been practically applied to industrial-scale facilities. This study employs ML algorithms, including Artificial Neural Network (ANN), Decision Tree (DT), Elastic Net (EN), Gradient Boosting Machines (GBM), K-Nearest Neighbours (KNN), Multiple Linear Regression (MLR), Random Forest (RF) and Support Vector Regression (SVR) to predict the biogas production, BOD removal, COD removal and methane yield from the ACoD of POME and DC in an industryscale anaerobic covered lagoon. The fitness of all models was evaluated based on performance metrics, namely R2 , MAE, RMSE and MSE. The results showed that the RF model produced the most reliable prediction results of biogas production and COD removal from the ACoD of POME and DC, with the highest coefficient of determination (R2 ) of 0.9961, along with the lowest RMSE of 0.110. The optimisation was conducted using response surface methodology (RSM) and the optimal condition range of dilution ratio of DC, OLR, pH, and temperature of the anaerobic digester was found to be 0.09 – 0.11, 0.82 – 0.83 kg COD/m3 .day, 6.83 – 7.1 and 40 – 41.4°C respectively. The economic analysis showed that co-digestion of POME and DC in the biogas plant was more economically viable than mono-digestion of POME. The proposed machine learning approach enables accurate prediction models and effective optimisation of the ACoD process in industrial-scale systems, offering a potential solution to the issue of inconsistent biogas production during low crop seasons. Further research could explore the application of the proposed approach in other types of ACoD systems for sustainable biogas production. Keywords: palm oil mill effluent (POME); decanter cake (DC); biogas production; BOD removal; COD removal; methane yield; artificial neural network (ANN); decision tree (DT); elastic net (EN); gradient boosting machines (GBM); k-nearest neighbours (KNN); multiple linear regression (MLR); random forest (RF); support vector regression (SVR)
23 Group 4 L-R: Tan Qian Ying, Joshua Yeh Loong Liew, Prof Nishanth, Cheun Jie Ying
24 Design of membrane polymers for gas separation by combining machine learning tools with computer-aided molecular design Jie Ying Cheun, Joshua Yeh Loong Liew, Qian Ying Tan, Nishanth Chemmangattuvalappil Abstract: The rapid proliferation of membrane-based technology in various gas separation processes such as air separation, natural gas sweetening and hydrogen purification has highlighted the need for a methodical approach towards identifying promising membrane molecules. However, the development of membrane molecules is still heavily dependent on trial-and-error experimental techniques, which pose a risk of disregarding superior polymer molecules that could be utilised for membrane fabrication. To address this issue, a systematic approach based on mathematical programming, known as computer-aided molecular design (CAMD) was developed to facilitate the design of membrane molecules that possess desirable attributes. To fully leverage the potential of CAMD, reliable and accurate models were developed using an inherently interpretable machine learning (ML) technique, known as rough setbased machine learning (RSML) to predict the target properties of candidate molecules based on their topological indices (TIs). The target properties used in this framework included the glass transition temperature (Tg), molar volume (Vm), cohesive energy (Ecoh), permeability and selectivity. Deterministic rules were generated from RSML based on molecular topology to establish a structure-property relationship of membrane molecules. The rules generated from RSML were analysed empirically and justified accordingly using scientific reasonings. Subsequently, the most prominent rules were integrated as constraints in the CAMD framework to enable the effective identification of promising membrane candidates. This study demonstrated the practical applications of the newly proposed design methodology to design membrane molecules that satisfy both structural feasibility constraints and technical requirements. The results of this study have proven that this novel methodology can be implemented for gas separation processes to effectively identify optimal membrane molecules that possess desirable attributes yet may not have been discovered through empirical methods. Keywords: Membrane molecules; Gas separation; Topological indices; Rough set-based machine learning; Computer-aided molecular design
25 Group 13 L-R: Dr Lau Phei Li, Yun Meizi, Low Chi Kei, Ong Wen Xin
26 Optimisation of household food waste co-composting with biochar integrated with internet of things (IoT) Wen Xin Ong, Chi Kei Low, Meizi Yun, Phei Li Lau Abstract: Food waste is a growing problem globally, with one-third of food produced from human consumption being wasted each year. The amount of food waste discarded in Malaysian landfills results in 33,129 tonnes of CO2 equivalent emissions of greenhouse gases daily. To address this issue, the circular economy philosophy can be applied to food waste management, with composting being a controlled process of converting organic materials into nutrient-rich soil amendments through natural decomposition. Bokashi composting (BC), a two-step process that relies on inoculated Bokashi bran for fermentation of food waste before burying it in soil for further decomposition, is an ideal option for households due to its low maintenance and suitability for small spaces. Biochar, a carbon-rich solid material from the thermochemical decomposition of carbonaceous materials, can be added to BC to improve its performance, humification process, and greenhouse gases reduction. The ratio of bokashi bran to biochar is 1:1. In this research, the roles of different food wastes on BC are investigated, with eggshells, coffee grounds and orange peels being the selected food wastes. IoT sensors are employed to monitor the internal conditions of the composting bin because BC is an anaerobic process requiring a closed bin environment. The sensors collect necessary parameters that can affect BC, including temperature, humidity, and moisture content. Laboratory analyses were conducted to determine NPK (nitrogen, phosphorus, potassium) values and C/N (carbon to nitrogen) ratios of each sample to investigate how various types of food waste can affect the soil compost quality. Once BC process is completed, planting studies are conducted to monitor the plant growth performances based on their germination period, height, and leaves number. The main objective of this research is to determine the optimal ratio of bokashi bran to food wastes for effective composting and the impact of biochar addition to BC. Based on the plant height studies, the optimal ratios of bokashi bran and biochar for each food waste that yields the tallest plant are as follows: 25 g of bokashi without biochar for eggshells, 10g of bokashi with biochar for coffee grounds, and 30g of bokashi with biochar for orange peels. For each optimal result of the compost, the C:N ratios are 6:1, 50:1, and 46:1 respectively. The NPK values are 0.39% N, 0.135% P and 0.102% K for eggshells; 0.204% N, 0.137% P, and 0.149% K for coffee grounds; 0.316% N, 0.0719% P, and 0.0785% K for orange peels. Keywords: Bokashi composting; Biochar; Internet of Things (IoT); Food waste
27 Group 22 L-R: Top: Dr Jerry Khoo, Wong Jun Kit L-R Bottom: Chong Jun Wei Roy, Jagathish Rajasolan and Ir Ts Prof Show Pau Loke
28 Application of machine learning and deep learning models for the prediction of microalgae’s various growth parameters Wong Jun Kit, Jagathish A/L S. Rajasolan, Show Pau Loke Abstract: In this work, the method of improving the current growth parameters monitoring of two different microalgae species, Haematococcus Pluvialis and Chlamydomonas Reinhardtii, were proposed by utilizing the combination of machine learning and image-processing techniques. For H. Pluvialis, various machine learning models (i.e., linear regression, support vector regressor, gradient boosting regressor, and convolutional neural networks) and different extracted features (i.e., RGB and HSV colour models) were used to identify the best combination of models and features from cultivating H. pluvialis’ pictures taken with a smartphone in different lightning conditions. When no disturbances were present, the findings showed that gradient boosting regressor with HSV value provided the highest R2 value of 98.74%. However, addition of lightning disturbances into the dataset showed an overall reduction of 0.5% - 5.0% in R2 value for all models, with statistical model showing that the reduction in accuracy is considered as significant. Nevertheless, models like convolutional neural networks and gradient boosting regressor with HSV features have showed higher robustness, hence raising its potential to be used for transfer training and finally to be able to be replacing the monitoring process of the microalgae cultivation in the production environment. For Chlamydomonas sp, a CNN model was built in order to train 100 images to predict the number of cells in the images. The most important hyperparameters that are used to construct the model are epoch = 100, batch size = 20, image size = 128 x 128 pixels and the learning rate is set to 0.001. The model shows a slight difference between the actual cell count and the predicted cell count. The growth curve and biomass productivity of the Chlamydomonas sp are 0.2427g.d-1 and 0.3048g.d-1 respectively. The average height and width of the Chlamydomonas sp cells were found to be 0.69cm and 0.65cm respectively. Overall, the CNN model can make a reasonable prediction of the total number of cells, but it still needs improvement to produce definitive results. The accuracy of the CNN model comes up to 93%. Keywords: Haematococcus Pluvialis; Chlamydomonas Reinhardtii; Machine learning; biomass productivity monitoring
29 Group 28 L-R: Dr Sara Kazemi Yazdi, Ong Qian Yee and Kiew Xin Yun
30 Development of a machine learning-based prediction tool and a life cycle assessment for biogas emissions from POME anaerobic digestion process Ong Qian Yee, Kiew Xin Yun, Sara Kazemi Yazdi, Chen Zhi Yuen Abstract: Methane (CH4), carbon dioxide (CO2) and hydrogen sulphide (H2S) are the major biogas components produced from the anaerobic digestion (AD) of palm oil mill effluent (POME), which contributes to global warming. This study aims to develop an accurate POME biogas prediction tool using Python, optimise the AD process, and evaluate the environmental impacts with a life cycle assessment (LCA) using OpenLCA. As only 96 datasets was available from 4 local POMs, Synthetic Minority Oversampling (SMOTE) with an (N,_k) setting of (7,7) was applied to produce synthetic training datasets. Hyperparameter tuning was conducted on the ML models— Random Forest (RF), Extreme Gradient Boosting (XGBoost) and Gaussian Process Regression (GPR) using randomised search CV. GPR was found to be the best performing predictor, with an R2 of > 0.98 and RMSE of < 0.17 for biogas, CH4, CO2, H2S and sludge total solids (TS). A feature importance study on biogas prediction reflected the most sensitive input parameters to be temperature, COD and OLR. This information allowed a two-step optimisation of biogas and methane yield to commence, obtaining the optimal process conditions of COD (7.5—8.5 g/L), BOD5 (4.5 g/L), TS (4.5—5.5 g/L), pH (7.2—7.4) and OLR (1.1—1.3 kgCODin/m3day) at 46—47˚C. LCA on the optimised process for with and without repurposing biogas in terms of global warming potential (GWP), acidification potential (AP) and eutrophication potential (EP) was assessed. The optimised case was 27.2% better than the base case in terms of GWP impact and 23.4% for AP as the production of biogas-based electricity could better offset the GWP impacts of methane emissions whereas 23% for EP owing to the increase in sludge and POME COD. Several limitations of the study include: (1) SMOTE could not always accurately synthesise data as sampling was random.; (2) Process optimisation method did not account for a global maxima. Recommended actions to improve model accuracy is to consider advanced resampling techniques, employ other regression models and incorporate IoT sensors for real-time monitoring. LCA can also be conducted using endpoint method for more comprehensive interpretation on the environmental implications. Keywords: POME biogas; Machine Learning; Feature importance; Life Cycle Assessment; Optimisation; Online monitoring programme
31 L-R: Daffa Afif Wibawa, Dr Senthil Kumar Arumugasamy and Khin Maung Win Group 2
32 Modelling of thermochemical energy recovery processes from biomass Khin Maung Win, Daffa Afif Wibawa, Senthil Kumar Arumugasamy Abstract: This study focuses on the valorization of chestnut shells, a by-product of the chestnut industry, which poses a waste concern due to the increasing global chestnut production. Two processes, gasification, and pyrolysis were simulated using Aspen Plus to obtain biofuels and chemicals from chestnut shells. In the gasification simulation, steam and air were used as gasifying agents and optimum thermal efficiency of the syngas was obtained by utilizing sensitivity analysis tool. The parameters altered in the simulations were temperature and steam to air ratio. The results showed that higher temperature and steam to air ratio favored hydrogen and carbon monoxide production, which in turn increased the thermal efficiency of the syngas. The lower heating value of the final syngas was found to be 11.47 MJ/Nm3 at 1000°C and 1 atm with a steam to air ratio of 70/30. The final syngas consisted of mainly hydrogen and carbon monoxide, making up more than 95% of the total gas molar composition, with small amounts of CO2 and CH4. In the pyrolysis simulation, a detailed steady-state model was used, and a sensitivity analysis was performed to maximize the bio-oil yield obtained from the pyrolysis of the biomass by varying parameters such as pyrolysis temperature and flow rate of inert nitrogen gas into the reactor. Results showed that the pyrolysis temperature and inert nitrogen gas flow rate significantly affected product yields, while the maximum bio-oil (47%) was obtained at 342°C with 1 kg/h nitrogen gas, along with biogas (39.2%) and char (13.8%). The importance of the amount of levoglucosan and pyrolytic water was emphasized in this paper, as they are key markers in assessing the quality of bio-oil. The maximum amount of levoglucosan present in bio-oil was found at 330°C, while the minimum amount of bio-oil was obtained at 426°C. The optimal bio-oil quality depends on the intended application. Overall, this study demonstrates the potential of using chestnut shells as a renewable resource for the production of syngas and bio-oil. The simulated outcomes would be helpful in selecting the parametric conditions for renewable fuel production through pyrolysis of chestnut shells and gasification of the biomass. This research contributes to the development of sustainable practices in the chestnut industry by reducing waste and producing renewable resources. Further research can explore the economic feasibility of scaling up these processes for commercial production. Keywords: Chestnut shells; Aspen Plus; Gasification; Pyrolysis; Syngas; Bio-oil; Biogas; Biochar
33 Abstracts – Session A2 Abstracts Session A2
34 Group 9 L-R: Soo Weng Kit, Jojo Foo Xin and Ir Dr Hii Ching Lik
35 Drying, baking kinetics and simulation of biscuit enriched with cricket powder and quality evaluation Soo Weng Kit, Jojo Foo Xin, Hii Ching Lik Abstract: House cricket (Acheta domesticus) is a promising alternative protein source for baked products due to its high protein content. This study aimed at exploring the potential of cricket-based baked goods in addressing food insecurity and promoting sustainable agricultural practices. The cricket biscuit was processed by mixing the crickets in powder form into biscuit formulation. The study investigated the drying kinetics of cricket in a hot air oven, baking kinetics and quality attributes of cricketbased biscuits by analysing the proximate composition, texture properties, color attributes, effective diffusivities, and sensory evaluation. A simulation for baking process of biscuits formulated with cricket powder was carried out using COMSOL. To understand the drying kinetics of cricket and the baking kinetics of cricket biscuits, the research employed experimental methods to measure weight loss and product temperature over time while drying cricket at different temperatures. The drying kinetics of crickets and baked biscuits were investigated using Fick's law of diffusion, and the effective diffusivity values for crickets and baked biscuits were determined. The results showed that drying temperature had a crucial impact on the drying kinetics of cricket samples, with distinct curves observed at lower and higher drying temperatures. Three thin layer models were applied to model the drying curves of crickets and fitted to the experimental data using non-linear regression. Good fittings were determined for coefficient of determination (R2 ) between the experimental and predicted moisture ratio data (0.9854 to 0.999), χ2 (0.0009 to 0.0023), and RMSE (0.0077 to 0.0128). The addition of cricket powder to biscuit formulations significantly affected the baking process, with a distinct reduction in moisture ratio observed in biscuits without cricket powder. The simulation results showed that adjusting the hot air velocity could significantly affect the baking time and moisture evaporation, and the baking mould played a crucial role in facilitating heat conduction and accelerating heat transfer within the biscuit. The hardness of the biscuits increased from 1713.75 g to 2671.22 g. L*, a*, b* and H* values decreased while total colour change (∆E) increased due to higher content of cricket protein powder, leading to darker, redder, greener, and brownish colour of biscuits. Sensory evaluation assessed the appearance, colour, odour, and texture attributes of the biscuit products. The findings provide valuable insights into the baking process of cricket biscuits such as in scaling up or optimisation of industrial-scale processes. Keywords: drying kinetics; baking kinetics; house cricket; quality; simulation; sensory evaluation.
36 Group 14 L-R: Phang Eng Kai, Zaynah Fairooz Zabed and Muhammad Afiq Azahar
37 Drying of Phaleria Macrocarpa Phang Eng Kai, Zaynah Fairooz Zabed, Muhammad Afiq Bin Azahar Abstract: Mahkota Dewa fruit, scientifically known as Phaleria Macrocarpa (Scheff) Boerl is an indigenous fruit in Indonesia having excellent medicinal properties. Four different drying techniques were experimented on the fruit, i.e., freeze drying (FD), sun drying (SD), oven drying (OD) and heat pump-assisted drying (HPD). The purpose of this study is to investigate and understand the impact of different drying methods applied to the fruit quality of the Mahkota Dewa. The effective moisture diffusivity was determined for graphical method and using Fick’s 2nd law analytical solution. The effective diffusivity values for graphical method ranged from 3.63 x 10- 9 to 8.91 x 10-9 m2/s and for using Fick’s 2nd law analytical method, it ranged from 9.54 x 10-11 to 1.065 x 10-9 m2/s. Furthermore, a new semi-empirical theoretical drying model was developed with a combination of Page and Henderson-Pabis model as both models show a close resemblance with the experimental value. The proposed new model as a relatively high R2 value of 0.993-0.998; Chi-square value of 0.003- 0.009 and RMSE value of 0.0042-0.0072. This further proves that the proposed new model can best describe the drying kinetics of MDF followed by Page Model. In addition, physical attributes like colour and size of the fruits were recorded at intervals to study any visible changes that may occur. It was found that the fruit shrinkage is linear to the moisture ratio. It was also found that freeze-drying was the best option when maintaining the colour of the fruit where the dE was recorded at 11.35. In terms of size reduction, freeze-drying was the best option as it showed little to no size reduction whereas the fruit reduction was only 16%. Sun drying showed the poorest result for colour change with a dE recorded of 31.69. In terms of shrinkage, oven drying was the worst with a result of 98.2%. In conclusion, Freeze-Drying method was the best at maintaining the quality of the fruit due to a low shrinkage value and low total colour change at 16% and 11.35, respectively. Keywords: Mahkota Dewa Fruit, Phaleria Macrocarpa, Drying, Quality Attribute, Semi-Empirical Formula, Effective Diffusivity
38 Group 15 L-R: Jung Tae Min, Kan Kar Weng and Junior Wong Weibing
39 Study of N-acetylneuraminic acid (NANA) from edible bird’s nests (EBN) with extraction and drying kinetics, regression analysis of extraction concentration and EBN beverages analysis Jung Tae Min, Junior Wong Weibing, Kan Kar Weng Abstract: Edible bird’s nest (EBN) is a highly valuable traditional Chinese food rich in bioactive compounds, especially N-acetylneuraminic acid (NANA) which is known to provide many health benefits. The present review focused on investigating the impacts of temperature and stewing time on the extraction of NANA from EBN at different temperature (60 – 100 °C) and time intervals (1 – 5 hours). The concentration of NANA from the extraction solution was then determined using the UV-Vis spectrophotometer. Regression analysis was performed throughout the study of the extraction kinetics to understand the relationship between the extraction concentration, time, and temperature. The regression analysis proved that time and temperature affect the extraction concentration significantly. However, the temperature was found to be a greater factor in the extraction kinetics than the time factor. Extrapolations were performed to predict the maximum extraction concentration of the EBN through extended period of time. In addition, hot air drying was used to investigate the drying kinetics of EBN, which is a commonly used method to preserve EBN. However, the effects of drying temperature on the retention of NANA are not well understood. Therefore, this study investigated the hot air-drying characteristics of EBN at different drying temperatures and the concentration of NANA extracted from dried EBN. Experimental results revealed that low drying temperatures are able to retain a higher concentration of NANA. Furthermore, as NANA is a quality marker of EBN, three different commercialized EBN drinks were also tested to determine whether the commercialized products contain NANA, the core essence of the Edible Bird’s Nests.
40 The results showed that NANA exists in a significant amount in the drinks. It was found that there is a significant variance of NANA content amongst different brands using ANOVA statistical approach, which might be due to different quality control measures, production methods, and use of different raw materials. Economic analysis was performed in terms of NANA content and the results indicated that some of these brands have higher cost whilst having low NANA content, which is due to other expensive ingredients present in the drinks. The outcome of this study will provide insights into the optimal conditions of NANA extraction. This study could assist food industries in the development of EBN related products which can provide valuable insights into quality manufacturing processes. Keywords: edible bird’s nest; extraction of N-acetylneuraminic acid; Nacetylneuraminic acid concentration; UV-Vis spectroscopy; ANOVA; hot air drying kinetics; effective moisture diffusivities; analysis of commercialized EBN drinks
41 Group 19 L-R: Sivesh Bharathi Dasan, Ir Dr Ong Sze Pheng, Lim Jie Vei and Yow Shuen Geng
42 Nutrient enrichment of palm kernel cake as poultry feed with Moringa oleifera leaf Jie Vei Lim, Shuen Geng Yow, Sivesh A/L Bharathi Dasan, Sze Pheng Ong Abstract: This study purports to investigate the potential of Moringa oleifera leaves as a nutritional supplement for Palm Kernel Cake (PKC) meal, which is a by-product of the palm kernel oil extraction process and is commonly used as poultry feed in Malaysia. The low protein content of PKC restricts its use as a protein source, and, therefore, fortification with Moringa oleifera leaves, known for their high protein content, is a promising remedy. However, it is crucial to critically evaluate the efficacy of such fortification strategies in terms of their nutritional impact, economic feasibility, and ecological implications, as well as the potential side effects on animal health and welfare. Besides, the rising of imported soy bean meal is also an important issues. To address this issue, an alternative poultry feed could be PKC which is a byproduct from palm kernel oil extraction process, can be used as an alternative to conventional soya bean-based poultry feed due to its availability and low cost in Malaysia. One of the limitations of PKC as poultry feed is its low protein content. To enrich its nutritional value, fortifying PKC meal with Moringa oleifera leaves, which have high crude protein content ranging from 21% to 26%, is a promising solution. However, before fortification, moringa leaves must be dried to remove the moisture content. The optimal parameters such as drying air temperature, air velocity, and drying methods must be studied to explore the drying characteristics and maximum nutrient preservation of moringa leaves. In this study, the effects of three drying methods, hot air (HA), microwave (MW), and microwave-combined hot air (MWHA), on the drying kinetics and physicochemical properties of Moringa leaves were evaluated. Additionally, the aim of this study included investigating the impact of oven drying at 50°C on formulated palm kernel cake (PKC), with a focus on extraction temperature set at 42°C, to evaluate the potential bioavailability of phenolic compounds and antioxidant capacity by chickens. Keywords: Palm Kernel Cake; Moringa oleifera; Drying Methods; Physicochemical Properties; Nutrient Values
43 Group 23 L-R: Shazia Ali, Foo Hui Thung, Tham Pei En and Ts Ir Prof Show Pau Loke
44 Investigation on the cultivation and extraction of Cphycocyanin from Spirulina platensis with various parameters Foo Hui Thung, Shazia Ali, Show Pau Loke Abstract: Spirulina platensis has the ability to develop and absorb pigment which can be affected by a variety of environmental conditions, including the culture medium, bicarbonate content, light spectrum, and extraction of c-phycocyanin using phosphate buffer. In this study, three different growing media known as Zarrouk, BG-11, and BBM was compared for C-phycocyanin extraction performance. According to the findings, the growth was greatest at Zarrouk and BG-11 while biomass production was lowest on the BBM medium. The outcomes demonstrated that nitrates as a source of nitrogen, a pH of 7.8, and a light intensity of 6000 lux offered the best conditions for development of C-phycocyanin. Zarrouk medium produced the highest yield, measuring 15.846 mg/g at pH 7.8 while lowest yield of 5.724 mg/g for BBM. Employing field emission scanning electron microscopy to analyze the absorbance of C-phycocyanin over time and at various pH levels (6.2, 6.8, and 7.8), its stability was assessed. The findings demonstrated that C-phycocyanin had the least amount of degradation over a 72-hour period at pH 6.6. The stability of C-phycocyanin considerably declined at pH levels below 6.0 and above 7.0. pH 6.6 may not be the best choice for the extraction pH because it is near the upper limit of the pH range where C-phycocyanin is stable, but the yield is not sufficient. In terms of bicarbonate concentration, the optimum result obtained is 18 g/L which yielded a C-phycocyanin concentration of 0.4627 mg/ml and C-phycocyanin purity of 1.1738, observing a 27.8% and 13.5% increase in comparison to the lowest bicarbonate concentration of 9 g/L and highest bicarbonate concentration of 27 g/L respectively. Whereas, under the influence of different light spectrum, the highest yield of the C-phycocyanin with a value of 17.138 mg/g was achieved under the illumination of red spectrum while the highest purity of 1.1472 and a yield of 0.463 mg/ml was attained under the illumination of red spectrum as well. Under the influence of red spectrum, there is a 25% increase in purity ratio and a 14% increase in C-phycocyanin concentration compared to white spectrum, while under the influence of blue spectrum, there is a slight increase of 2.86% and 1.54% percent in purity ratio and C-phycocyanin concentration, respectively. The study ultimately concludes that C-phycocyanin can be enhanced by adjusting a variety of variables, which can raise the productivity and quality of the final product. Keywords: C-phycocyanin, Spirulina Platensis, Sustainability, Light
45 Group 18 L-R: Ir Dr Hii Ching Lik, Dr Lim Siew Shee, Lim Yu Xuan and Shehryar Ahmed
46 Microwave-dried chitosan-phycocyanin membranes for wound healing Shehryar Ahmed, Yu Xuan Lim, Siew Shee Lim, Ching Lik Hii Abstract: Traditional wound dressing has limitations such as inferior biocompatibility and requires regular replacement to avoid infections. Hence, this study proposes the synthesis of microwave-dried chitosan-phycocyanin (PC) membranes as a potential solution to address the limitations. Chitosan membranes were synthesized using microwave drying and functionalized with spirulina derived PC through direct blending and adsorption for wound healing. The protein was first extracted from spirulina powder and freeze dried. The functional groups and protein bands of freezedried protein were verified to be similar to PC. Chitosan membranes were microwave dried at 180 W, 300 W and 450 W and characterized in terms of functional groups, surface morphology, swelling ratio and degradation rate. Drying kinetics were also investigated for both pure chitosan and chitosan-PC membranes. Spectral analysis revealed that microwave drying at 180 W resulted in a loss of functional groups in the chitosan membranes. Notably, the membranes dried at 300 W preserved the functional groups of chitosan the most and showed moderate swelling ratio and lower degradation percentage. Drying rates were found to increase with microwave power. Effective diffusivity values ranged from 4.54 x 10-11 ms-1 to 5.15 x 10-11 ms-1 for pure chitosan membranes and from 2.89 x 10-11 ms-1 to 1.43 x 10-10 ms-1 for chitosan-PC membranes. The activation energies for both types of membranes ranged from 2.53 to 35.71 Wg-1. Only chitosan-PC membranes with a protein concentration of 2 mg/mL showed similar functional groups to those of the protein itself, indicating the need for higher protein concentrations in direct blending of chitosan and PC to promote wound healing. The surface morphology of pure chitosan membranes using FESEM showed that the quality of the membrane microwave dried at 450W was compromised. These results suggest that microwave drying at 300 W could be a promising method to produce chitosan-PC membranes. The adsorption of PC was mainly conducted onto pure chitosan membranes dried at 300 W at concentration of 1, 0.5, 0.25 and 0.1 mg/mL. The adsorption of PC onto chitosan membranes was verified as Type VI isotherm and fitted well with Freundlich isotherm with R2 = 0.9721. PC adsorbed onto the microwave-dried chitosan membranes were reported in a random manner and the functional groups of adsorbed PC onto microwave dried chitosan membranes were preserved. Microwave dried chitosan membranes with PC could be a promising wound healing material. Keywords: Microwave heating; Chitosan membranes; Phycocyanin; Drying kinetics; Diffusivity; Adsorption isotherm; Wound healing
47 Group 10 L-R: Dr Apurav Krishna Koyande, William Raphael Joseph, Tan Jun Yeang and Dr Ianatul Khoiroh
48 Passive radiative cooling effects of BaSO4 and CaCO3- based paint under Malaysia’s tropical climate William Raphael Joseph, Tan Jun Yeang, Apurav Krishna Koyande, Ianatul Khoiroh Abstract: Global cooling requirements are increasing at an unprecedented rate due to rapid urbanization and population growth, further aggravating climate concerns. Passive radiative cooling is a unique phenomenon that can be utilized to reduce global cooling, energy consumption and alleviate the urban heat island effect. Paints can act as passive cooling devices that are able to reflect incoming sunlight and emit radiation in the atmospheric window (8-13 µm), where it propagates directly into deep space without any interference. This reduces the heat content stored within the painted surface and in turn reduces its temperature significantly. Alternative white paints can achieve this effect due to their high reflectivity and high atmospheric window emissivity. Barium sulphate (BaSO4) and limestone (CaCO3) are two compounds that have shown potential to be alternative white paint pigments to achieve passive radiative cooling, as opposed to the typically used titanium dioxide (TiO2) found in most commercial white paints. In this work, we have successfully fabricated and tested two different types of cooling paints, consisting of BaSO4 and CaCO3 as their respective pigments under Malaysia’s tropical climate. The Malaysian climate is characterized by hot weather and high humidity, both of which will affect the cooling performances of the paints. Different types of paint binders, solvents, and pigment concentrations were tested to obtain the optimum cooling paint configuration. Field test results proved that both cooling paints were able to achieve remarkable subambient temperatures throughout the entire day, especially under direct solar irradiation. The BaSO4 cooling paint was able to achieve sub-ambient temperature reductions of up to -6.1°C and a mean net cooling power of 71.0 W/m2 while the CaCO3 cooling paint achieved a maximum sub-ambient temperature reduction of - 6.0°C and a mean net cooling power of 69.9 W/m2 . When compared to commercial white paint, the BaSO4 cooling paint was able to achieve a maximum surface temperature reduction of -8.9°C while the CaCO3 cooling paint achieved a maximum -6.3°C reduction. The impact of the humidity levels, wind speeds, and solar irradiance on the cooling effects of the paint were all considered in this study. Keywords: passive radiative cooling; barium sulfate; calcium carbonate; paint; Malaysian climate.
49 Group 18 Abstracts – Session B2 Abstracts Session B2