17 research outputs found

    Biosynthesis and characterization of gold and silver nanoparticles by pink guava (psidium guajava) waste extract / Norashikin Ahmad Zamanhuri, Mohamed Syazwan Osman and Rasyidah Alrozi

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    There is an increasing commercial demand for nanoparticles due to their wide applicability in various areas such as electronics, catalysis, chemistry, energy and medicine. Metallic nanoparticles are traditionally synthesized by wet chemical techniques, where the chemicals used are quite often toxic and give impact to the human health and environment. Metal nanostructures have unusual physicochemical properties and biological activities compared to their bulk parent materials. In this study, silver and gold nanoparticles (AgNPs and AuNPs) were synthesized from aqueous silver nitrate and auric acid solution respectively, through a simple and eco-friendly route using pink guava waste extract (PGWE) as reductant and stabilizer. The resulting silver and gold nanoparticles were characterized by using Ultraviolet-visible (UV-vis) spectroscopy, Fourier transform infrared (FTIR) spectroscopy and transmission electron microscopy (TEM). AgNPs and AuNPs vary in size according to different amount of PGWE and silver nitrate and auric acid concentration used for the synthesis. Formation of AgNPs and AuNPs was confirmed by the color changed and by surface Plasmon spectra by using Uv-Vis spectrometer as well as absorbance peaks lie between 400 to 500 nm. The silver and gold nanoparticles obtained using this source have particles size in the range of 0- 50 nm. It was found that the increase in silver nitrate and uric acid concentration leads to the increasing size of AgNPs and AuNPs produced

    Preparation of chemically treated rambutan (Nepheuum lappaceum L.) peel for the removal of basic and reactive dyes from aqueous solution / Rasyidah Alrozi, Norashikin Ahmad Zamanhuri and Mohamed Syazwan Osman

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    Commercially available adsorbents are still considered expensive due to the use of non-renewable and relatively expensive starting material such as bituminous coal. Therefore, this study investigates the potential use of tropical fruit waste such as rambutan peel (RP) that available in Malaysia, as the precursor for the preparation of chemically treated adsorbent which can be applied for the removal of two types of dyes, which are basic Methylene Blue (MB) and reactive Remazol Brilliant Blue R (RBBR) from aqueous solution. Impregnation with hydrochloric acid (HCI) and sodium hydroxide (NaOH) was used in order to modify the surface characteristics of the prepared adsorbent. In this study, adsorption of MB and RBBR dye by NaOH-treated rambutan peels (N-RP) and HCI-treated rambutan peels (H-RP) were examined. The adsorption experiments were carried out under different conditions of initial concentration (25-500 mg/L), solution pH 2-12 and adsorbent dose (0.05-1.0 g). The influence of these parameters on the adsorption capacity was studied using the batch process. MB and RBBR adsorption uptake were found to increase with increase in initial concentration and contact time. The MB adsorption was unfavourable at pH4. Langmuir, Freundlich and Temkin isotherm models were used to illustrate the experimental isotherms and isotherms constant. The equilibrium data were best represented by Langmuir isothem model, showing maximum monolayer adsorption capacity of 231.34 and 112.69 mg/g for MB and RBBR dye, respectively. The rates of adsorption were found to obey the rules of pseudo-second order model with good correlation for both dyes. The result suggested that the N-RP and H-RP would be an excellent alternative for the removal of MB and RBBR dye by adsorption process

    Predicting Kereh River's Water Quality: A comparative study of machine learning models

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    This study introduces a machine learning-based approach to forecast the water quality of the Kereh River and categorize it into 'polluted' or 'slightly polluted' classifications. This work employed three machine learning algorithms: decision tree, random forests (RF), and boosted regression tree, leveraging data spanning from 2010 to 2019. Through comparative analysis, the RF model emerged as the most efficient, boasting an accuracy of 97.30%, sensitivity of 100.00%, specificity of 94.74%, and precision of 95.00%. Notably, the RF model identified dissolved oxygen (DO) as the paramount variable influencing water quality predictions. Keywords: Water quality; machine learning; decision tree; random forest   eISSN: 2398-4287 © 2023. The Authors. Published for AMER and cE-Bs by e-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under the responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), and cE-Bs (Centre for Environment-Behaviour Studies), College of Built Environment, Universiti Teknologi MARA, Malaysia DOI: https://doi.org/10.21834/e-bpj.v8iSI15.509

    Thioflavin dye degradation by using magnetic nanoparticles augmented PolyvinylideneFlouride (PVDF) microcapsules / Mohamed Syazwan Osman ... [et al.]

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    Microcapsule has remarkable advantages in engineering application for pollutants removal and biomedical field for transportation. It has obviously drawn attention from the research community. Undeniably, it does have shortages but the key is to balance both the advantages and limitations to enhance microcapsule benefits. In environmental engineering applications, microcapsules could serve as encapsulation agents of nanoparticles (NPs) to drastically reduce the risk associated to nano-toxicity when it is indirect contact with surroundings. In addition, this technique could improve the physical contact and promote catalytic degradations of pollutants while exhibit better recyclability without loss of activity after multiple catalytic degradation cycles. Even though magnetic responsiveness of capsules can be used for ease of separation, one of the constraints is that the encapsulated particles will restrict the performance of capsules materials in pollutants removal. However, encapsulated magnetite particles interact with polymeric matrix chains and thus tying up the chains as knot which can restrict the expansions of whole capsules. Some-times, capsules shell is designated to remove certain target contaminants and so does for encapsulated particles. This may possibly reduce or increase the removal performance of integrated capsules which depends on the target contaminants and the underlying mechanism involved in pollutant removal. Hence, this work primarily focuses on the synthesis of magnetic nanoparticles augmented microcapsule with dual functionalities namely adsorptive and catalytic activities using membrane material, PolyvinylideneFlouride (PVDF). Feasibility study using Thioflavin dye as the representable model system for degradation will be explored

    Low-cost colorimetric setup for concentration measurement of manganese ions based on optical absorbance

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    This study presents a cost-effective setup for measuring the concentration of Mn2+ ions using colorimetry. The current method involves a calibration curve created with expensive and large commercial laboratory-based instruments, limiting its use in financially constrained situations. To address this issue, the study proposes a low-cost setup consisting of a light-emitting diode and photodiode that utilizes colorimetric and absorbance effects for Mn2+ concentration measurement. Mn2+ colorimetric samples were prepared using the 1-(2-pyridylazo)-2-naphthol (PAN) method with concentrations ranging from 0.2 to 1.0 mg/L. The samples were tested using the proposed setup, followed by a spectrophotometry test to determine the optimal configuration for the setup. The validity of the setup was confirmed by measuring the voltage and calculating the optical absorbance, which exhibited a good correlation with the concentration, consistent with the initial expectation. The correlation coefficient for voltage and absorbance against Mn2+ concentration was found to be 0.9976 and 0.9987, respectively, indicating good linearity and suitability as a calibration curve for Mn2+ detection and measurement. Consequently, the study’s objectives were successfully achieved, and the proposed setup is considered a viable platform for more complex applications, such as real-time monitoring activities

    Unveiling the noxious effect of polystyrene microplastics in aquatic ecosystems and their toxicological behavior on fishes and microalgae

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    Microplastic (MP) particles are considered noxious pollutants due to their presence in aquatic habitats at almost every level of the food chain. Thus, the entry of MP particles into marine waterbodies has triggered a common research interest. Until recently, the toxicity of polystyrene towards aquatic creatures in comparison to other polymers has not been widely investigated. This article provides an extensive overview of the occurrence of microplastic particles, the route of polystyrene (PS) in the aquatic ecosystem, the PS properties characterization, and its noxious effects on the aquatic biota, particularly fishes and microalgae. Alarming high levels of polystyrene were found in urban, coastal, and rural surface waters and sediments. The fast-screening technique began with a stereoscope to determine the polystyrene particles’ shape, size, and color on the organism. SEM and complemented by micro FTIR or Raman spectroscopy were used to evaluate MP’s polymer structures. The findings present evidence suggesting that polystyrene buildup in fish can have long-term and unknown consequences. Meanwhile, the presence of polystyrene on microalgae causes a decrease in chlorophyll concentration and photosynthetic activity, which may disrupt photosynthesis by interfering with the electron characters and leading to the production of reactive oxygen species (ROS)

    Supercritical CO2 extraction of red butterfly wing leaves: process parametric study towards extraction yield

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    This research illustrates the parametric studies for determining the relationship between the operating parameters used in the supercritical fluid extraction (SFE) and the extraction yield of Red Butterfly Wing (RBW) leaves. In this study, SFE used carbon dioxide (CO2) as the main solvent and ethanol as the co-solvent. SFE was operated by manipulating few parameters such as temperature, pressure and also particle size in order to determine the extraction yield. The RBW leaves were purchased from the local supplier and then undergone cleaning, drying, grinding as well as sieving processes. 5 grams of grinded leaves was then run through SFE machine. For the temperature, it was observed that the extraction yield increased starting from 40°C to 50°C and dropped after that. The optimum temperature was 50°C with extraction yield of 2.94%. For the pressure, the trend of the extraction yield was directly proportional to the pressure. As the pressure increased, the extraction yield also increased. The optimum extraction yield was 2.45 % at 375 bar. Meanwhile, the particle size was inversely proportional to the extraction yield. The optimum extraction yield was 3.26 % at 63 μm

    Supercritical CO

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    This research illustrates the parametric studies for determining the relationship between the operating parameters used in the supercritical fluid extraction (SFE) and the extraction yield of Red Butterfly Wing (RBW) leaves. In this study, SFE used carbon dioxide (CO2) as the main solvent and ethanol as the co-solvent. SFE was operated by manipulating few parameters such as temperature, pressure and also particle size in order to determine the extraction yield. The RBW leaves were purchased from the local supplier and then undergone cleaning, drying, grinding as well as sieving processes. 5 grams of grinded leaves was then run through SFE machine. For the temperature, it was observed that the extraction yield increased starting from 40°C to 50°C and dropped after that. The optimum temperature was 50°C with extraction yield of 2.94%. For the pressure, the trend of the extraction yield was directly proportional to the pressure. As the pressure increased, the extraction yield also increased. The optimum extraction yield was 2.45 % at 375 bar. Meanwhile, the particle size was inversely proportional to the extraction yield. The optimum extraction yield was 3.26 % at 63 μm

    Directed Assembly of Bifunctional Silica–Iron Oxide Nanocomposite with Open Shell Structure

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    The synthesis of nanocomposite with controlled surface morphology plays a key role for pollutant removal from aqueous environments. The influence of the molecular size of the polyelectrolyte in synthesizing silica–iron oxide core–shell nanocomposite with open shell structure was investigated by using dynamic light scattering, atomic force microscopy, and quartz crystal microbalance with dissipation (QCM-D). Here, poly­(diallydimethylammonium chloride) (PDDA) was used to promote the attachment of iron oxide nanoparticles (IONPs) onto the silica surface to assemble a nanocomposite with magnetic and catalytic bifunctionality. High molecular weight PDDA tended to adsorb on silica colloid, forming a more extended conformation layer than low molecular weight PDDA. Subsequent attachment of IONPs onto this extended PDDA layer was more randomly distributed, forming isolated islands with open space between them. By taking amoxicillin, an antibiotic commonly found in pharmaceutical waste, as the model system, better removal was observed for silica–iron oxide nanocomposite with a more extended open shell structure
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