Displaying publications 1 - 20 of 189 in total

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  1. Henna Lu, F.S., Tan, P.P
    MyJurnal
    This aim of this research is to investigate thermal stability of virgin coconut oil, (VCO) which was heated at 190°C upon 40 days storage as compared to extra virgin olive oil (EVOO). The changes in fatty acids composition through (GC), Fourier Transform Infrared (FTIR) spectra, iodine value (IV) and total phenolic content were determined throughout the period of study. Results from GC showed that there was significant changes (P
    Matched MeSH terms: Fourier Analysis
  2. Hassan N, Ahmad T, Ashaari A, Awang SR, Mamat SS, Wan Mohamad WM, et al.
    Results Phys, 2021 Jun;25:104267.
    PMID: 33968605 DOI: 10.1016/j.rinp.2021.104267
    Complex systems require rigorous analysis using effective method, in order to handle and interpret their information. Spectrum produced from Fourier transform infrared (FTIR) instrument is an example of a complex system, due to their overlapped bands and interactions within the spectrum. Thus, chemometrics techniques are required to further analyze the data, in particular, chemometrics fuzzy autocatalytic set (c-FACS). The c-FACS is initially used to analyze the FTIR spectra of gelatins. However, in this study, the c-FACS is generalized and implemented for analysis of Coronavirus disease 2019 (Covid-19), particularly, the pandemic outbreak in Malaysia. The daily Covid-19 cases in states in Malaysia are modeled and analyzed using c-FACS, to observe the trend and severity of the disease in Malaysia. As a result, the classification of severity of zones in Malaysia are identified. The obtained results offer descriptive insight for strategizing purposes in combating the Covid-19 outbreak in Malaysia.
    Matched MeSH terms: Fourier Analysis
  3. Khuzaimah Arifin, Wan Ramli Wan Daud, Mohammad B. Kassim
    Sains Malaysiana, 2014;43:95-101.
    A novel bimetallic double thiocyanate-bridged ruthenium and tungsten metal complex containing bipyridyl and dithiolene co-ligands was synthesized and the behavior of the complex as a dye-sensitizer for a photoelectrochemical (PEG) cell for a direct water splitting reaction was investigated. The ligands and metal complexes were characterized on the basis of elemental analysis as well as uv-Vis, Fourier transform infrared ( Pim) and nuclear magnetic resonance (11I and 13C NMR) spectroscopy. Cyclic voltammetry of the bimetallic complex showed multiple redox couples, in which half potentials E 112 at 0 .625 , 0.05 and 0.61 V were assigned as the formal redox processes of Ru(III)IRu(II) reduction, W(IV)IW(V) and W(V)IW(VI) oxidations, respectively. Photocurrent measurements were performed in homogeneous system and TiO2 was used as the photoanode for photocurrent measurements. Current density generated by the bimetallic complex was higher than that of N3 commercial dye which suggested that the bimetallic complex donated more electrons to the semiconductor.
    Matched MeSH terms: Fourier Analysis
  4. Se KW, Ghoshal SK, Wahab RA, Ibrahim RKR, Lani MN
    Food Res Int, 2018 03;105:453-460.
    PMID: 29433236 DOI: 10.1016/j.foodres.2017.11.012
    In this study, we propose an easy approach by combining the Fourier transform infrared and attenuated total reflectance (FTIR-ATR) spectroscopy together with chemometrics analysis for rapid detection and accurate quantification of five adulterants such as fructose, glucose, sucrose, corn syrup and cane sugar in stingless bees (Heterotrigona itama) honey harvested in Malaysia. Adulterants were classified using principal component analysis and soft independent modeling class analogy, where the first derivative of the spectra in the wavenumber range of 1180-750cm-1 was utilized. The protocol could satisfactorily discriminate the stingless bees honey samples that were adulterated with the concentrations of corn syrup above 8% (w/w) and cane sugar over 2% (w/w). Feasibility of integrating FTIR-ATR with chemometrics for precise quantification of the five adulterants was affirmed using partial least square regression (PLSR) analysis. The study found that optimal PLSR analysis achieved standard error of calibrations and standard error of predictions within an acceptable range of 0.686-1.087% and 0.581-1.489%, respectively, indicating good predictive capability. Hence, the method developed here for detecting and quantifying adulteration in H. itama honey samples is accurate and rapid, requiring only 7-8min to complete as compared to 3h for the standard method, AOAC method 998.12.
    Matched MeSH terms: Fourier Analysis
  5. Reza MS, Ahmed A, Caesarendra W, Abu Bakar MS, Shams S, Saidur R, et al.
    Bioengineering (Basel), 2019 Apr 16;6(2).
    PMID: 30995765 DOI: 10.3390/bioengineering6020033
    To evaluate the possibilities for biofuel and bioenergy production Acacia Holosericea, which is an invasive plant available in Brunei Darussalam, was investigated. Proximate analysis of Acacia Holosericea shows that the moisture content, volatile matters, fixed carbon, and ash contents were 9.56%, 65.12%, 21.21%, and 3.91%, respectively. Ultimate analysis shows carbon, hydrogen, and nitrogen as 44.03%, 5.67%, and 0.25%, respectively. The thermogravimetric analysis (TGA) results have shown that maximum weight loss occurred for this biomass at 357 °C for pyrolysis and 287 °C for combustion conditions. Low moisture content (<10%), high hydrogen content, and higher heating value (about 18.13 MJ/kg) makes this species a potential biomass. The production of bio-char, bio-oil, and biogas from Acacia Holosericea was found 34.45%, 32.56%, 33.09% for 500 °C with a heating rate 5 °C/min and 25.81%, 37.61%, 36.58% with a heating rate 10 °C/min, respectively, in this research. From Fourier transform infrared (FTIR) spectroscopy it was shown that a strong C-H, C-O, and C=C bond exists in the bio-char of the sample.
    Matched MeSH terms: Fourier Analysis
  6. Silakhori M, Naghavi MS, Metselaar HSC, Mahlia TMI, Fauzi H, Mehrali M
    Materials (Basel), 2013 Apr 29;6(5):1608-1620.
    PMID: 28809232 DOI: 10.3390/ma6051608
    Microencapsulated paraffin wax/polyaniline was prepared using a simple in situ polymerization technique, and its performance characteristics were investigated. Weight losses of samples were determined by Thermal Gravimetry Analysis (TGA). The microencapsulated samples with 23% and 49% paraffin showed less decomposition after 330 °C than with higher percentage of paraffin. These samples were then subjected to a thermal cycling test. Thermal properties of microencapsulated paraffin wax were evaluated by Differential Scanning Calorimeter (DSC). Structure stability and compatibility of core and coating materials were also tested by Fourier transform infrared spectrophotometer (FTIR), and the surface morphology of the samples are shown by Field Emission Scanning Electron Microscopy (FESEM). It has been found that the microencapsulated paraffin waxes show little change in the latent heat of fusion and melting temperature after one thousand thermal recycles. Besides, the chemical characteristics and structural profile remained constant after one thousand thermal cycling tests. Therefore, microencapsulated paraffin wax/polyaniline is a stable material that can be used for thermal energy storage systems.
    Matched MeSH terms: Fourier Analysis
  7. May Z, Alam MK, Nayan NA, Rahman NAA, Mahmud MS
    PLoS One, 2021;16(12):e0261040.
    PMID: 34914761 DOI: 10.1371/journal.pone.0261040
    Corrosion in carbon-steel pipelines leads to failure, which is a major cause of breakdown maintenance in the oil and gas industries. The acoustic emission (AE) signal is a reliable method for corrosion detection and classification in the modern Structural Health Monitoring (SHM) system. The efficiency of this system in detection and classification mainly depends on the suitable AE features. Therefore, many feature extraction and classification methods have been developed for corrosion detection and severity assessment. However, the extraction of appropriate AE features and classification of various levels of corrosion utilizing these extracted features are still challenging issues. To overcome these issues, this article proposes a hybrid machine learning approach that combines Wavelet Packet Transform (WPT) integrated with Fast Fourier Transform (FFT) for multiresolution feature extraction and Linear Support Vector Classifier (L-SVC) for predicting corrosion severity levels. A Laboratory-based Linear Polarization Resistance (LPR) test was performed on carbon-steel samples for AE data acquisition over a different time span. AE signals were collected at a high sampling rate with a sound well AE sensor using AEWin software. Simulation results show a linear relationship between the proposed approach-based extracted AE features and the corrosion process. For multi-class problems, three corrosion severity stages have been made based on the corrosion rate over time and AE activity. The ANOVA test results indicate the significance within and between the feature-groups where F-values (F-value>1) rejects the null hypothesis and P-values (P-value<0.05) are less than the significance level. The utilized L-SVC classifier achieves higher prediction accuracy of 99.0% than the accuracy of other benchmarked classifiers. Findings of our proposed machine learning approach confirm that it can be effectively utilized for corrosion detection and severity assessment in SHM applications.
    Matched MeSH terms: Fourier Analysis
  8. Akinpelu AA, Chowdhury ZZ, Shibly SM, Faisal ANM, Badruddin IA, Rahman MM, et al.
    Int J Mol Sci, 2021 Feb 19;22(4).
    PMID: 33669883 DOI: 10.3390/ijms22042090
    This study deals with the preparation of activated carbon (CDSP) from date seed powder (DSP) by chemical activation to eliminate polyaromatic hydrocarbon-PAHs (naphthalene-C10H8) from synthetic wastewater. The chemical activation process was carried out using a weak Lewis acid of zinc acetate dihydrate salt (Zn(CH3CO2)2·2H2O). The equilibrium isotherm and kinetics analysis was carried out using DSP and CDSP samples, and their performances were compared for the removal of a volatile organic compound-naphthalene (C10H8)-from synthetic aqueous effluents or wastewater. The equilibrium isotherm data was analyzed using the linear regression model of the Langmuir, Freundlich and Temkin equations. The R2 values for the Langmuir isotherm were 0.93 and 0.99 for naphthalene (C10H8) adsorption using DSP and CDSP, respectively. CDSP showed a higher equilibrium sorption capacity (qe) of 379.64 µg/g. DSP had an equilibrium sorption capacity of 369.06 µg/g for C10H8. The rate of reaction was estimated for C10H8 adsorption using a pseudo-first order, pseudo-second order and Elovich kinetic equation. The reaction mechanism for both the sorbents (CDSP and DSP) was studied using the intraparticle diffusion model. The equilibrium data was well-fitted with the pseudo-second order kinetics model showing the chemisorption nature of the equilibrium system. CDSP showed a higher sorption performance than DSP due to its higher BET surface area and carbon content. Physiochemical characterizations of the DSP and CDSP samples were carried out using the BET surface area analysis, Fourier-scanning microscopic analysis (FSEM), energy-dispersive X-ray (EDX) analysis and Fourier-transform spectroscopic analysis (FTIR). A thermogravimetric and ultimate analysis was also carried out to determine the carbon content in both the sorbents (DSP and CDSP) here. This study confirms the potential of DSP and CDSP to remove C10H8 from lab-scale synthetic wastewater.
    Matched MeSH terms: Fourier Analysis
  9. Nurul Najwa Abd Malek, Rusdin Laiman
    Science Letters, 2018;12(1):63-76.
    MyJurnal
    The aim of this study was to investigate the potential of treated rice husk ash (RHA) as adsorbent to adsorb acidic SO2 gas. The treated RHA was prepared using a water hydration method by mixing the RHA, Calcium oxide (CaO) and Sodium Hydroxide (NaOH). The addition of NaOH is to increase the dissolution of silica from the RHA to form reactive species responsible for higher desulfurization activity. The untreated and treated RHA were subjected to several characterizations and the characteristics of the adsorbents were compared. The functional groups present on the surface of the adsorbent were determined using Fourier Transform Infrared (FTIR). The chemical composition of the untreated and treated RHA was analyzed by using X-ray Fluorescence (XRF). Scanning electron microscope (SEM) analysis showed that the treated RHA has higher porosity compared to untreated RHA. Based on the SO2 adsorption analysis, it was found that the treated RHA has higher adsorption capacity, 62.22 mg/g, compared to untreated RHA, 1.49 mg/g.
    Matched MeSH terms: Fourier Analysis
  10. Noh, C.H.C., Azmin, N.F.M., Amid, A., Asnawi, A.L.
    MyJurnal
    Bioactive compounds are one of the natural products used especially for medicinal, pharmaceutical and food application. Increasing research performed on the extraction, isolation and identification of bioactive compounds, however non to date has explored on the identification of flavonoids classes. Therefore, this study was focused on the development of algorithm for rapid identification of flavonoids classes which are flavanone, flavone and flavonol and also their derivatives. Fourier Transform Infrared (FTIR) spectroscopy coupled with multivariate statistical data analysis, which is Principal Component Analysis (PCA) was utilized. The results exhibited that few significant wavenumber range provides the identification and characterization of the flavonoids classes based on PCA algorithm. The study concluded that FTIR coupled with PCA analysis can be used as a molecular fingerprint for rapid identification of flavonoids.
    Matched MeSH terms: Fourier Analysis
  11. Chook SW, Chia CH, Zakaria S, Ayob MK, Chee KL, Huang NM, et al.
    Nanoscale Res Lett, 2012;7(1):541.
    PMID: 23020815 DOI: 10.1186/1556-276X-7-541
    Silver nanoparticles and silver-graphene oxide nanocomposites were fabricated using a rapid and green microwave irradiation synthesis method. Silver nanoparticles with narrow size distribution were formed under microwave irradiation for both samples. The silver nanoparticles were distributed randomly on the surface of graphene oxide. The Fourier transform infrared and thermogravimetry analysis results showed that the graphene oxide for the AgNP-graphene oxide (AgGO) sample was partially reduced during the in situ synthesis of silver nanoparticles. Both silver nanoparticles and AgGO nanocomposites exhibited stronger antibacterial properties against Gram-negative bacteria (Salmonella typhi and Escherichia coli) than against Gram-positive bacteria (Staphyloccocus aureus and Staphyloccocus epidermidis). The AgGO nanocomposites consisting of approximately 40 wt.% silver can achieve antibacterial performance comparable to that of neat silver nanoparticles.
    Matched MeSH terms: Fourier Analysis
  12. Xu D, Gao Y, Lin Z, Gao W, Zhang H, Karnowo K, et al.
    Front Chem, 2019;7:943.
    PMID: 32117859 DOI: 10.3389/fchem.2019.00943
    In this study, biochars derived from waste fiberboard biomass were applied in tetracycline (TC) removal in aqueous solution. Biochar samples were prepared by slow pyrolysis at 300, 500, and 800°C, and were characterized by ultimate analysis, Fourier transform infrared (FTIR), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), Brunauer-Emmett-Teller (BET), etc. The effects of ionic strength (0-1.0 mol/L of NaCl), initial TC concentration (2.5-60 ppm), biochar dosage (1.5-2.5 g/L), and initial pH (2-10) were systemically determined. The results present that biochar prepared at 800°C (BC800) generally possesses the highest aromatization degree and surface area with abundant pyridinic N (N-6) and accordingly shows a better removal efficiency (68.6%) than the other two biochar samples. Adsorption isotherm data were better fitted by the Freundlich model (R2 is 0.94) than the Langmuir model (R2 is 0.85). Thermodynamic study showed that the adsorption process is endothermic and mainly physical in nature with the values of ΔH0 being 48.0 kJ/mol, ΔS0 being 157.1 J/mol/K, and ΔG0 varying from 1.02 to -2.14 kJ/mol. The graphite-like structure in biochar enables the π-π interactions with a ring structure in the TC molecule, which, together with the N-6 acting as electron donor, is the main driving force of the adsorption process.
    Matched MeSH terms: Fourier Analysis
  13. Mas Ezatul Nadia Mohd Ruah, Nor Fazila Rasaruddin, Fong, Sim Siong, Mohd Zuli Jaafar
    MyJurnal
    This paper outlines the application of chemometrics and pattern recognition tools to classify palm oil using Fourier Transform Mid Infrared spectroscopy (FT-MIR). FT-MIR spectroscopy is used as an effective analytical tool in order to categorise the oil into the category of unused palm oil and used palm oil for frying. The samples used in this study consist of 28 types of pure palm oil, and 28 types of frying palm oils. FT-MIR spectral was obtained in absorbance mode at the spectral range from 650 cm -1 to 4000 cm -1 using FT-MIR-ATR sample handling. The aim of this work is to develop fast method in discriminating the palm oils by implementing Partial Least Square Discriminant Analysis (PLS-DA), Learning Vector Quantisation (LVQ) and Support Vector Machine (SVM). Raw FT-MIR spectra were subjected to Savitzky-Golay smoothing and standardized before developing the classification models. The classification model was validated through finding the value of percentage correctly classified by test set for every model in order to show which classifier provided the best classification. In order to improve the performance of the classification model, variable selection method known as t-statistic method was applied. The significant variable in developing classification model was selected through this method. The result revealed that PLSDA classifier of the standardized data with application of t-statistic showed the best performance with highest percentage correctly classified among the classifiers.
    Matched MeSH terms: Fourier Analysis
  14. Hafshejani MK, Ogugbue CJ, Morad N
    3 Biotech, 2014 Dec;4(6):605-619.
    PMID: 28324306 DOI: 10.1007/s13205-013-0192-7
    The decolorization and degradation of Direct Blue 71 were investigated using a mono culture of Pseudomonas aeruginosa. The bacterium was able to decolorize the dye medium to 70.43 % within 48 h under microaerophilic conditions. The medium was then aerated for 24 h to promote the biodegradation of the aromatic amines generated from azo bond cleavage. Reduction in total organic carbon in dye medium was 42.58 % in the microaerophilic stage and 78.39 % in the aerobic stage. The degradation metabolites formed were studied using UV-vis techniques, high performance liquid chromatography, Fourier transform infra red spectroscopy and nuclear magnetic resonance spectroscopy analysis. Data obtained provide evidence for the formation of aromatic amines and their subsequent oxidative biodegradation by a single strain of P. aeruginosa during successive microaerophilic/aerobic stages in the same flask. The influence of incubation temperature (20-45 °C), medium pH (5-10) and initial dye concentration (25-150 mg/L) on decolorization was evaluated to greatly influence decolorization extent. The optimal decolorization conditions were determined by response surface methodology based on three-variable central composite design to obtain maximum decolorization and to determine the significance and interaction effect of the variables on decolorization. The optimal conditions of response were found to be 35.15 °C, pH 8.01 and 49.95 mg/L dye concentration giving an experimental decolorization value of 84.80 %. Very high regression coefficient between the variables and the response (R(2) = 0.9624) indicated a good evaluation of experimental data by polynomial regression model.
    Matched MeSH terms: Fourier Analysis
  15. Nurrulhidayah, A.F., Che Man, Y.B., Shuhaimi, M., Rohman, A., Khatib, A., Amin, I.
    MyJurnal
    The use of Fourier transform infrared (FTIR) spectroscopy coupled with chemometric techniques to differentiate butter from beef fat (BF) was investigated. The spectral bands associated with butter, BF, and their mixtures were scanned, interpreted, and identified by relating them to those spectroscopically representative to pure butter and BF. For quantitative analysis, partial least square (PLS) regression was used to develop a calibration model at the selected fingerprint regions of 1500-1000 cm-1, with the values of coefficient of determination (R2) and root mean square error of calibration (RMSEC) are 0.999 and 0.89% (v/v), respectively. The PLS calibration model was subsequently used for the prediction of independent samples containing butter in the binary mixtures with BF. Using 6 principal components, root mean square error of prediction (RMSEP) is 2.42% (v/v). These results proved that FTIR spectroscopy in combination with multivariate calibration can be used for the detection and quantification of BF in butter formulation for authentication use.
    Matched MeSH terms: Fourier Analysis
  16. Wong JY, Chu C, Chong VC, Dhillon SK, Loh KH
    J Fish Biol, 2016 Aug;89(2):1324-44.
    PMID: 27364089 DOI: 10.1111/jfb.13039
    Combined multiple 2D views (proximal, anterior and ventral aspects) of the sagittal otolith are proposed here as a method to capture shape information for fish classification. Classification performance of single view compared with combined 2D views show improved classification accuracy of the latter, for nine species of Sciaenidae. The effects of shape description methods (shape indices, Procrustes analysis and elliptical Fourier analysis) on classification performance were evaluated. Procrustes analysis and elliptical Fourier analysis perform better than shape indices when single view is considered, but all perform equally well with combined views. A generic content-based image retrieval (CBIR) system that ranks dissimilarity (Procrustes distance) of otolith images was built to search query images without the need for detailed information of side (left or right), aspect (proximal or distal) and direction (positive or negative) of the otolith. Methods for the development of this automated classification system are discussed.
    Matched MeSH terms: Fourier Analysis
  17. Ali Z, Elamvazuthi I, Alsulaiman M, Muhammad G
    J Voice, 2016 Nov;30(6):757.e7-757.e19.
    PMID: 26522263 DOI: 10.1016/j.jvoice.2015.08.010
    BACKGROUND AND OBJECTIVE: Automatic voice pathology detection using sustained vowels has been widely explored. Because of the stationary nature of the speech waveform, pathology detection with a sustained vowel is a comparatively easier task than that using a running speech. Some disorder detection systems with running speech have also been developed, although most of them are based on a voice activity detection (VAD), that is, itself a challenging task. Pathology detection with running speech needs more investigation, and systems with good accuracy (ACC) are required. Furthermore, pathology classification systems with running speech have not received any attention from the research community. In this article, automatic pathology detection and classification systems are developed using text-dependent running speech without adding a VAD module.

    METHOD: A set of three psychophysics conditions of hearing (critical band spectral estimation, equal loudness hearing curve, and the intensity loudness power law of hearing) is used to estimate the auditory spectrum. The auditory spectrum and all-pole models of the auditory spectrums are computed and analyzed and used in a Gaussian mixture model for an automatic decision.

    RESULTS: In the experiments using the Massachusetts Eye & Ear Infirmary database, an ACC of 99.56% is obtained for pathology detection, and an ACC of 93.33% is obtained for the pathology classification system. The results of the proposed systems outperform the existing running-speech-based systems.

    DISCUSSION: The developed system can effectively be used in voice pathology detection and classification systems, and the proposed features can visually differentiate between normal and pathological samples.

    Matched MeSH terms: Fourier Analysis
  18. Zabidi A, Khuan LY, Mansor W, Yassin IM, Sahak R
    PMID: 22254916 DOI: 10.1109/IEMBS.2011.6090759
    Hypothyroidism in infants is caused by the insufficient production of hormones by the thyroid gland. Due to stress in the chest cavity as a result of the enlarged liver, their cry signals are unique and can be distinguished from the healthy infant cries. This study investigates the effect of feature selection with Binary Particle Swarm Optimization on the performance of MultiLayer Perceptron classifier in discriminating between the healthy infants and infants with hypothyroidism from their cry signals. The feature extraction process was performed on the Mel Frequency Cepstral coefficients. Performance of the MLP classifier was examined by varying the number of coefficients. It was found that the BPSO enhances the classification accuracy while reducing the computation load of the MLP classifier. The highest classification accuracy of 99.65% was achieved for the MLP classifier, with 36 filter banks, 5 hidden nodes and 11 BPS optimised MFC coefficients.
    Matched MeSH terms: Fourier Analysis
  19. Yaradoddi JS, Banapurmath NR, Ganachari SV, Soudagar MEM, Mubarak NM, Hallad S, et al.
    Sci Rep, 2020 12 15;10(1):21960.
    PMID: 33319818 DOI: 10.1038/s41598-020-78912-z
    The main goal of the present work was to develop a value-added product of biodegradable material for sustainable packaging. The use of agriculture waste-derived carboxymethyl cellulose (CMC) mainly is to reduce the cost involved in the development of the film, at present commercially available CMS is costly. The main focus of the research is to translate the agricultural waste-derived CMC to useful biodegradable polymer suitable for packaging material. During this process CMC was extracted from the agricultural waste mainly sugar cane bagasse and the blends were prepared using CMC (waste derived), gelatin, agar and varied concentrations of glycerol; 1.5% (sample A), 2% (sample B), and 2.5% (sample C) was added. Thus, the film derived from the sample C (gelatin + CMC + agar) with 2.0% glycerol as a plasticizer exhibited excellent properties than other samples A and B. The physiochemical properties of each developed biodegradable plastics (sample A, B, C) were characterized using Fourier Transform Infra-Red (FTIR) spectroscopy and Differential Scanning Calorimetry (DSC), Thermogravimetric analysis (TGA). The swelling test, solubility in different solvents, oil permeability coefficient, water permeability (WP), mechanical strength of the produced material was claimed to be a good material for packaging and meanwhile its biodegradability (soil burial method) indicated their environmental compatibility nature and commercial properties. The reflected work is a novel approach, and which is vital in the conversion of organic waste to value-added product development. There is also another way to utilize commercial CMC in preparation of polymeric blends for the packaging material, which can save considerable time involved in the recovery of CMC from sugarcane bagasse.
    Matched MeSH terms: Fourier Analysis
  20. Taufiq-Yap YH, Nurul Fitriyah Abdullah, Mahiran Basri
    Sains Malaysiana, 2011;40:1179-1186.
    Due to the increase in price of petroleum and environmental concerns, the search for alternative fuels has gained importance. In this work, biodiesel production by transesterification of palm oil with methanol has been studied in a heterogeneous system using sodium hydroxide loaded on alumina (NaOH/Al2O3). NaOH/Al2O3 catalyst was prepared by impregnation of alumina with different amount of an aqueous solution of sodium hydroxide followed by calcination in air for 3 h. The prepared catalysts were then characterized by using x-ray diffraction (XRD), Fourier transform infrared spectrometer (FT-IR), Brunner-Emmett-Teller surface area measurement (BET), scanning electron microscopy (SEM) and temperature-programmed desorption of CO2 (CO2-TPD). Moreover, the dependence of the conversion of palm oil on the reactions variables such as the molar ratio of methanol/oil, the amount of catalysts used, reaction temperatures and reaction times were performed. The conversion of 99% was achieved under the optimum reaction conditions. The biodiesel obtained was characterized by FT-IR and the pour point was measured.
    Matched MeSH terms: Fourier Analysis
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