Browsing by Author "Dasanayake, N. L."

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Binder effects on CO2 gas sensitivity of Mn-doped copper oxide films: A comparative study using PEG, CMC, MEG
(Faculty of Science, University of Kelaniya Sri Lanka, 2024) Weerasooriya, R. M. A. U.; Dasanayake, N. L.; Sivakumar, V.
In today's world, with rising air pollution levels, it is essential to detect air quality, ensuring both environmental safety and public health. Gas sensors detect air quality, with sensor material as the main component. A binder is used to hold the sensor material together and ensure it sticks to the conductive glass plate, creating a uniform and stable sensing layer. However, the addition of binders can affect gas sensitivity because they modify the microstructure of the sensing layer. Therefore, it is important to identify which binder is the most suitable for sensor material for gas sensing purposes. The aim of this work was to examine the effects of three distinct binders; polyethylene glycol (PEG), carboxymethyl cellulose (CMC), and monoethylene glycol (MEG), on the surface morphological changes and carbon dioxide (CO2) gas sensitivity of Mn-doped (4%) copper oxide as a gas sensing material. Some previous studies had investigated binders for various sensor materials to detect different gases, but the novelty of this research lies in specifically comparing the CO2 gas sensitivity of Mn-doped (4%) copper oxide with the above mentioned binders separately. The film was prepared using the doctor blade method and coated samples were heated at 120 °C for 30 minutes. UV-visible absorption spectroscopy, XRD and SEM analysis were conducted to determine the optical and structural properties of the sample. The XRD analysis confirms the presence of both cuprous oxide (Cu₂O) and cupric oxide (CuO) in the sample, with CuO being the most dominant phase. The sample with the MEG binder had the lowest optical band gap of 2.93 eV, while the other two samples had the same optical band gap of 2.95 eV, demonstrating that there is no significant impact of the chosen binders on the optical band gap of Mn-doped (4%) copper oxide. The arithmetic average roughness (Ra) increases when CMC and MEG binders are added to the sample but decreases when PEG is added. Furthermore, the gas sensitivity, response time, and recovery time of Mn-doped copper oxide were measured for CO2 detection at room temperature. The flow rate of CO2 gas was varied from 10 SCCM to 20 SCCM for three different samples. Additionally, it shows less than 6% variation in results across multiple measurements. The sample with PEG quickly responded to CO2 gas in 90 s with a recovery time of 300 s and a CO2 gas sensitivity of 57.35%. The sample with CMC had the lowest gas sensitivity of 48% and also showed the best recovery time for CO2 gas in 280 s. High gas sensitivity is particularly important for breath analysis used in medical diagnostic procedures. For this purpose, the MEG added sample can be chosen because it has a comparatively high CO2 gas sensitivity of 62.23%. In conclusion, choosing the right binder with a copper oxide sample is essential for creating the optimal sensing layer to fulfill CO2 gas sensing purposes.
Effect of pH on the morphology of chemical bath deposited ZnO nanowires
(Faculty of Science, University of Kelaniya Sri Lanka, 2023) Jayathilaka, A. P. S. P.; Abeykoon, Y. K.; Dassanayake, B. S.; Dasanayake, N. L.
ZnO is a non-toxic chemical compound that forms nanostructures like nanoparticles, nanowires, nanotubes, and so on. Among these nanostructures, ZnO nanowires have shown the potential for use in applications like light-emitting diodes (LED), lasers, light detectors, chemical and biological sensors, photovoltaic cells, field-effect transistors (FET), nanogenerators, and so forth. ZnO nanowires can be synthesised using a variety of techniques, such as chemical vapour deposition (CVD), chemical bath deposition (CBD), and hydrothermal methods. Among these methods, CBD is a cost-effective, simple method to fabricate well-crystalline ZnO nanowires. The morphology of the ZnO nanostructures greatly varies with the alteration of growth parameters like growth temperature, growth time, precursor concentration, and pH level of the precursor. Herein, pH is an easily controllable parameter that has a significant effect on the morphology of ZnO nanowires as well. In this research, we synthesised ZnO nanowires using the CBD method and investigated the effect of the pH level of the precursor on the morphology of the assynthesised ZnO nanowires. The pH values 2, 4, 6, 6.5, 7, 8, and 10 were selected for the study, and the nanowires were grown on a seed layer for better crystallinity. First, the seed layer was deposited on a borosilicate glass slide by spraying the seed solution (3.69 g of Zn(CH3COO)2, 18.9 ml of Ethanol, 0.1 ml of Monoethanolamine, 100 ml of deionised water) using the spray pyrolysis technique. Then, the sample was annealed at 300 ̊C for 1 hour. Next, the precursor solution (3.83 g of Zn(NO3)2, 2.82 g of Hexamethylenetetramine, 200 ml of deionised water) was subjected to pH alteration using dil. HCl or dil. NH4OH and was then heated to 90 ̊C while magnetic stirring at 700 rpm. After that, the seed-layered glass slide was submerged in the solution for the chemical bath deposition for 2 hours. Finally, the sample was annealed at 300 ̊C for 30 minutes. The above-mentioned process was repeated for all the understudied pH values. Characteristics of the ZnO nanowire samples, such as average values of height, width, aspect ratio (height/width), surface-to-volume ratio, and wire density, were analysed using scanning electron microscopic (SEM) images. The outlook and the quantitative analysis of the SEM images showed that the most crystallised nanowires (hexagonal wurtzite shape) corresponded to pH 6.5, with the highest aspect ratio (10.308) and the lowest nanowire density (44 nanowires per μm2). The highest surface-to-volume ratio was reported for the nanowires grown at pH 7 (1.049), followed by pH 6.5 (1.037). In general, ZnO nanowires grown at pH 6.5 showed the highest crystallinity in the understudied pH range.
Investigating the ability to purify wastewater by using Activated Porous Carbon (APC) produced from waste surgical masks
(Faculty of Science, University of Kelaniya Sri Lanka, 2023) Wellalage, D.K.; Bandara, L. R. A. K.; Dasanayake, N. L.
Since the early days of the year 2020, most people have been wearing face masks to protect themselves from COVID 19 pandemic. As a result of that, another environmental problem arises with waste face masks all over the world. Therefore, this study aims to convert commonly used, waste polypropylene surgical masks, into Activated Porous Carbon (APC) and compare its wastewater treatment applications with commercially available activated carbon (AC). Waste polypropylene surgical masks can be converted into APC through the two main processes called sulfonation and carbonization. First, waste masks were mixed with concentrated H2SO4 and heated under the temperature of 110 °C for the sulfonation. Then, the collected samples were carbonized by mixing with KOH in different mass ratios 1:1, 1:1.5 and 1:2 (samples: APC 1, APC 2 and APC 3 respectively) and again these samples were heated under the temperature of about 400 °C. Adsorption ability of activated carbon depends on porosity, surface area of the sample and also size of the substance that we want to remove from wastewater. According to the Scanning Electron Microscope (SEM) images of the samples, even though there is no any considerable porous structure on the all APC samples, roughly surface area of the APC 1 sample is higher than the other APC samples. This can be caused to the higher adsorption of the APC 1 sample. Here, the adsorption ability of the APC samples was tested by using two chemical dyes, four cations and four anions. According to the concentration reduction results of commercial AC sample and APC samples, a high concentration reduction was obtained from APC 1 for both Congo red and Methylene blue dyes. Molecular size of the two types of dyes can be caused to those results. Even though these two dyes are organic and aromatic compounds molecule size of the Congo red is larger than the Methylene blue. It allows to adsorb Congo red more effectively than the Methylene blue. When considering the results obtained for the cations and anions adsorption, APC samples showed lower capability compared to commercial AC. Among the tested APC samples, again APC 1 had the best adsorption ability. Further, obtained results for the ion adsorption clearly indicated there is high capability to adsorb large substances effectively than small substances. Ions in the solution directly affect the conductivity of the solution. Therefore, in this work conductivity values of three collected water samples were measured by changing the contacted time with the sample. According to the decrement of conductivity values, there is a considerable effect on the adsorption rate from the contacted time. Further, those conductivity results also showed the best ion adsorption ability of APC sample1 than the other samples. Hence, APC 1 sample with a 1:1 KOH mass ratio can be identified as the best adsorbent with good surface structure.
Non-destructive detection of internal defects in trees using infrared thermography
(Faculty of Science, University of Kelaniya Sri Lanka, 2024) Baduge, P. B. K. G. W.; Jayalath, J. A. C. P.; Dasanayake, N. L.
Trees are vital to ecosystems, playing a key role in regulating the natural environment, climate, and urban forestry. However, trees can pose risks in urban areas due to potential property damage from falling branches or entire trees. This is especially true when these trees have internal defects that threaten their stability and health. Monitoring tree health is essential for understanding these risks and making informed decisions about tree management. Internal axial tree cavities, often caused by timber decay or termite attacks, are a primary cause of tree failures. Trees can adapt by reinforcing tissue around these voids, but large cavities can eventually compromise structural integrity. Visual inspections often fail to detect hidden internal defects, and current techniques used for defect detection can be invasive. This study aims to address the problem of detecting internal defects in trees qualitatively using nondestructive infrared thermography. By comparing the surface temperatures of healthy and unhealthy tree trunk sections, this study evaluates the efficacy of the method used, and analytical coding is simplified in the image processing stage. Sap circulation influences the temperature differential along a tree trunk, enabling the differentiation between functional and dysfunctional tissue. Temperature variations on the tree surface may indicate deteriorating tissue, cavities, or defects. Because of this favorable thermal profile, live tree imaging can be performed using the passive method. A total of 45 trees representing 40 species were selected for the study, 38 from the Royal Botanical Gardens and 7 from the University of Peradeniya. The FLUKE TI-105 camera was used to capture both infrared and digital images, and thermograms were processed using MATLAB and Fluke Connect Desktop software. A two-week survey identified defective trees, with detailed records of each tree's common name, scientific name, and diameter at breast height (DBH) while GPS coordinates were used to map tree locations. The defects included cankers, external deterioration, internal cavities, and cracks. Image acquisition was conducted on a low-rainfall day to ensure data integrity, considering unusually heavy rains during the study period. Observations included distance, ambient temperature, and relative humidity, with the camera's emissivity value set to 0.95. The study conclusively demonstrates that some internal defects in trees can be detected using thermograms. Defected areas were typically in lower temperatures than the surrounding areas and capturing images at optimal times is crucial to avoid altered temperature profiles caused by direct sunlight or rain. Moss on the trunk surface was found to cause misleading thermal profiles. Since images were captured from a distance, background masking was essential for effective analysis. Higher-contrast thermal images were beneficial for pinpointing defects. When this was not feasible, k-means clustering was preferred despite its limitation of generalizing temperature profiles, particularly with low-temperature spots in lighter colors. Combining k-means clustering with edge detection improved defect identification. The study emphasized that such analysis is case-specific, as influencing factors vary. Further research is needed, especially in regions like Sri Lanka where local tree species have been minimally studied in this context.