Research Publications
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Publication Embargo Assessing the Efficacy of Machine Learning Algorithms in Predicting Critical Properties of Gold Nanoparticles for Pharmaceutical Applications(Springer, 2025-07-08) Fernando, H; Mohottala, S; Jayanetti, M; Thambiliyagodage, CAu nanoparticles are increasingly used in pharmaceuticals, but their synthesis is costly and time-intensive. Machine Learning can help optimize this process. In this research, eight distinct Machine Learning models were implemented and optimized on a dataset comprising 3000 records of gold nanoparticles. The performance of these models was assessed using four accuracy metrics and the time required for training and inference. The results are promising, with all seven models demonstrating high accuracy and low time requirements. Notably, the XGBoost and Artificial Neural Network models exhibited exceptional performance, with Mean Squared Error values of 0.0235 and 0.0098, Mean Absolute Error values of 0.1021 and 0.0674, Mean Absolute Percentage Deviation values of 0.4945 and 0.3590, R2 scores of 0.9995 and 0.9998, and inference times of 0.0029 and 0.4299 s, respectively. The Explainable Artificial Intelligence analysis of the resulting models revealed some interesting insights into how the models make the predictions and what factors heavily contribute to the nanoparticle AVG_R, allowing chemists to optimize the synthesis for gold nanoparticles better. The key contributions of the research include the design and development of eight Machine Learning models using industry-standard frameworks, the training, tuning, and evaluation of these eight models using five different metrics, and further assessment of these trained models using Explainable Artificial Intelligence. The findings indicate a substantial potential for applying neural networks in the design phase of nanoparticle synthesis, which could lead to significant reductions in both the time and cost required for synthesizing Au nanoparticles for pharmaceutical applications.Publication Embargo Assessing the Efficacy of Machine Learning Algorithms in Predicting Critical Properties of Gold Nanoparticles for Pharmaceutical Applications(Springer Nature Link, 2025-07-08) Fernando, H; Mohottala, S; Jayanetti, M; Thambiliyagodage, CAu nanoparticles are increasingly used in pharmaceuticals, but their synthesis is costly and time-intensive. Machine Learning can help optimize this process. In this research, eight distinct Machine Learning models were implemented and optimized on a dataset comprising 3000 records of gold nanoparticles. The performance of these models was assessed using four accuracy metrics and the time required for training and inference. The results are promising, with all seven models demonstrating high accuracy and low time requirements. Notably, the XGBoost and Artificial Neural Network models exhibited exceptional performance, with Mean Squared Error values of 0.0235 and 0.0098, Mean Absolute Error values of 0.1021 and 0.0674, Mean Absolute Percentage Deviation values of 0.4945 and 0.3590, R2 scores of 0.9995 and 0.9998, and inference times of 0.0029 and 0.4299 s, respectively. The Explainable Artificial Intelligence analysis of the resulting models revealed some interesting insights into how the models make the predictions and what factors heavily contribute to the nanoparticle AVG_R, allowing chemists to optimize the synthesis for gold nanoparticles better. The key contributions of the research include the design and development of eight Machine Learning models using industry-standard frameworks, the training, tuning, and evaluation of these eight models using five different metrics, and further assessment of these trained models using Explainable Artificial Intelligence. The findings indicate a substantial potential for applying neural networks in the design phase of nanoparticle synthesis, which could lead to significant reductions in both the time and cost required for synthesizing Au nanoparticles for pharmaceutical applications.Publication Embargo Efficiency Enhanced by Chelation of Al3+ Metal Ions with Erythrina Fusca Flower Dye Harnessing Bathochromic Shift(SLIIT, Faculty of Engineering, 2024-10) Mannawadu, M.W.M.K; Perera, V.P.S.Utilization of natural dyes in dye-sensitized solar cells (DSSCs) presents a sustainable approach towards enhancing photovoltaic efficiency. This study explores the bathochromic shift exhibited by Erythrina fusca (Erabodu) flower dye upon chelation with Al3+ ions, offering an innovative strategy for improving DSSC performance. 20g of chopped flower petals was boiled with 50ml of ethanol until flower petals become pale in colour in the dye extraction process. After that, 0.1 M, AlCl3 solution was added dropwise to 2ml of dye solution until the colour changed to purple. The pH value of Erabadu bare dye was recorded as 5.47 and with the Al3+ ion addition it was changed to 4.49. Through spectroscopic analysis and electrochemical characterization, the chelation mechanism and its impact on dye absorption spectra and electron transfer dynamics was elucidated. The Dye was coated on a thin film of TiO2 nanoparticles deposited on fluorine-doped tin oxide (FTO) glass plates. FTO glass which coated with platinum was used as the counter electrode and iodin/triiodide (I2 / I3 -) was used as the electrolyte. Solar cell was tested with a light source with an intensity of 100 mW/cm2. Al3+ ion chelated Erabadu dye exhibited higher efficiencies than bare dye which was 1.627%. The open circuit voltage (Voc) of this cell was 470mV, short circuit current density (Jsc) was 4.00 mA/cm2 and the fill factor of DSSC’s was 0.553. The Incident Photon to Current Conversion Efficiency (IPCE) of the cell further revealed the action spectrum was broadened between 300 nm – 500 nm enhancing the efficiency. Our findings unveil the potential of Al3+ ion chelated Erythrina fusca dye as a promising sensitizer for DSSCs, paving the way for eco-friendly and efficient solar energy conversion.Publication Open Access Antibacterial Activity of Zn Decorated TiO2 Nanocomposites(Faculty of Humanities and Sciences, SLIIT, 2023-11-01) Kumarasinghe, N.M.A,; Thambiliyagodage, C; Jayanetti, M; Liyanaarachchi, HBacterial infections have a significant public health impact. Infections are caused by bacteria in animals, plants as well as humans. Pathogenic bacteria can produce toxins, which are chemical poisons that interfere with cell function such as digestion of normal human enzymes, evasion of infection-fighting white blood cells, and immune clearance. Antibiotic prophylaxis is used to prevent bacterial infection. Antibiotic resistance is one of the most serious concerns in world health. Antibacterial nanoparticles are one possible answer to antimicrobial resistance. These nanomaterials not only kill antibiotic-resistant bacteria through various modes of action but, they can also be employed in conjunction with existing clinically relevant antibiotics to help overcome antimicrobial resistance mechanisms. In this study, anodized titanium dioxide (TiO2) nanorods were treated hydrothermally with zinc oxide (ZnO) nanoparticles to give titanium (Ti) antibacterial properties. The antibacterial activity of synthesized samples was investigated by Agar Well Diffusion method at 40 mg/ml concentration, against gram negative Klebsiella pneumoniae. To determine the antibacterial activity, the diameter of the zone of inhibition was measured, and the resulting data were statistically analyzed. Zn/TiO2 nano particles were characterized by using X-ray diffraction (XRD) Analysis.Publication Open Access Antibacterial Activity of Cu Decorated TiO2 Nanorods(Faculty of Humanities and Sciences, SLIIT, 2023-11-01) Nilaweera, G; Thambiliyagodage, C; Jayanetti, M; Liyanaarachchi, HGlobal public health is seriously threatened by the spread of infectious illnesses in general, particularly by the appearance of bacterial strains that are resistant to antibiotics. New antibacterial drugs are likely a result of recent developments in the field of nanobiotechnologies, particularly the ability to make metal oxide nanomaterials with specific morphologies. Using antibiotics for a long time period will show antibiotic resistance in host cells, which means the drug does not kill the pathogen anymore. As a solution to this problem, nanoparticles can be used. Researchers may find nanoparticles with high antibacterial activity which can kill the pathogen. This research shows the antibacterial activity of Cu decorated TiO2 nanoparticles against Klebsiella pneumoniae. In here the nanoparticles were synthesized in three weight ratios with TiO2 and CuO using hydrothermal method. Pure CuO and TiO2 were synthesized as controls. Then antibacterial activity was checked by the well diffusion method. After incubation the inhibition zones were measured, and the results were recorded. The antibacterial effect can be determined with the size of the inhibition zone. The synthesized nanoparticles were characterized using XRD to analyze physical properties such as phase composition, crystal structure. The value for inhibition zone of the best performing sample which the sample concentration is 40mg/ml is 13.17±1.53 mm which contains TiO2 : CuO (1:2) weight ratio. Therefore it can be determined that the best performing sample which has the highest antibacterial activity against Klebsiella pneumoniae is G3 which contains TiO2 : CuO (1:2) weight ratio.Publication Embargo One pot synthesis of α-Fe2O3/turbostratic carbon composites and their photocatalytic activity under sunlight(Elsevier, 2021-10-01) Thambiliyagodage, C. J; Nakandala, S; Siriwardana, B; Lansakara, BSucrose naturally obtained from sugar cane was catalytically graphitized by incorporation of varying amounts of iron (1, 5, 7.5 and 10%) as a one-pot synthesis. The weight of iron was varied relative to the weight of sucrose. Synthesized sucrose-Fe2O3 nanocomposites (FeGC) were characterized by X-ray diffractometry (XRD), Raman spectroscopy, and UV-Visible spectroscopy. It is observed that turbostratic carbon is produced upon the incorporation of iron and the percentage of graphitization increase with increasing loading of iron as revealed by XRD analysis. Quantitative analysis of Raman spectra confirm that the ordering of carbon increase with increasing loading of iron. The equilibrium adsorption capacity of carbon with the highest iron loading (10FeGC), 0.50 mg/g is higher than that with carbon without any metal, AC (0.2 mg/g), and the highest adsorption capacity (0.58 mg/g) resulted in carbon with 5% iron (5FeGC). Methylene blue adsorption to AC and carbon with 1% iron (1FeGC) followed pseudo-first-order kinetics and carbon materials with 5, 7.5 and 10% iron followed pseudo-second-order kinetics. The initial rate constant for the photodegradation of methylene blue in the presence of AC was 0.001 min−1 and that of 1FeGC (0.005 min−1) increased with increasing loading of iron where the highest initial rate constant (0.158 min−1) was obtained with 10FeGC. Ordered carbon enhances photocatalytic activity by being photoactive and increasing the separation of charges generated at α-Fe2O3.Publication Open Access Photocatalytic activity of Go/Fe3O4 fabricated by Sri Lankan graphite under visible light irradiation(Faculty of Science, University of Kelaniya, Sri Lanka, 2021-10) Usgodaarachchi, L; Thambiliyagodage, C. JGraphene oxide (GO) was synthesized using Sri Lankan naturally available graphite by modified Hummer’s method. Fe3O4 nanoparticles were synthesized successfully by co-precipitation of Fe3+ and Fe2+ in a 2:1 molar ratio via the addition of NH4OH. Magnetically separable GO/Fe3O4 nanocomposite was fabricated by synthesizing Fe3O4 nanoparticles in the presence of GO. The synthesized nanocomposites were characterized by X-ray diffractometry (XRD), Scanning electron microscopy (SEM), and FT-IR spectroscopy. The formation of GO was confirmed by the C(002) peak at 9.39° in the XRD pattern. XRD pattern of the nanoparticles confirms the formation of crystalline Fe3O4 nanoparticles, and the diffraction peak corresponds to graphene oxide disappear in the GO/ Fe3O4 due to the absence of the folded structure of graphene oxide. SEM image of GO shows the crumpled and wrinkled lamellae structure of graphene oxide, and the images of GO/ Fe3O4 show the distribution of Fe3O4 nanoparticles with an average size of 107 nm on GO where the folded structure of GO was not present while restacking of the nanosheets, was observed. FT-IR spectrum of GO shows the presence of polar oxygenated functional groups such as carboxylic acid (-COOH), hydroxyl (-OH), and epoxy (-COC-). The photocatalytic performance of the photocatalysts was evaluated on photodegradation of methylene blue under visible light irradiation. The GO/ Fe3O4 shows better adsorption behaviour and excellent photocatalytic activity where it could be successfully used for three cycles without significant activity loss. The rate constant for the degradation of MB (0.0187 min-1 ) at the first cycle decreased to 0.0101 min-1 at the third cycle. The conversion of MB decreased from 98.31% at the first cycle to 92.15% at the third cycle. The drop in the conversion is only 6.16% going from cycle 1 to 3, which could be due to the accumulation of the MB molecules at the pore structure. The obtained high photocatalytic activity could be due to the enhanced charge separation resulted due to the presence of GO sheets and better interactions between GO and Fe 3O4.Publication Embargo Exploration of Electrical and Optical Characteristics of Cuprous Oxide Synthesized Using Benedict’s Reagent(Faculty of Humanities and Sciences,SLIIT, 2021-09-25) Wickramasinghe, G.C; Perera, V.P.S; Senthilnithy, RIn the current study, cuprous oxide (Cu2O) nanoparticles were synthesized using Benedict’s reagent. In this reaction, glucose was used to reduce copper(II)−citrate complex to obtain yellow, orange and red colour Cu2O by varying the reaction time and temperature. The synthesized Cu2O nanoparticles were fabricated on Fluorinedoped Tin Oxides glass plates by using doctor bade method to obtain thin films for characterization. The electrochemical impedance and UV-Visible spectra were used to characterize the three cuprous oxide films for electrical conductivity and calculate their direct energy band gap to test the suitability of material for diverse applications. Nyquist plot of thin films of Cu2O were characterized by electrochemical impedance spectroscopy. Simulated results of Nyquist plots clearly revealed that charge transfer resistance of the red colour Cu2O thin film was lower than that of yellow and orange colour thin films. The maximum absorption peak at 300 nm confirmed the presence of Cu2O in all the samples. The board absorption peak around 610 nm in the UV-visible spectra of red cuprous oxide was an evidence for the presence of copper nanoparticles in this sample. The direct energy band gaps of samples of Cu2O were calculated from tauc plots using the results of UV-visible spectra. Values of direct band gap of yellow, orange and red colour cuprous oxides nanoparticles found to be 2.15, 2.72 and 2.45 eV respectively.