Nakawajana, Natrapee

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Nakawajana, Natrapee
Alternative Name
Nakawajana, N.
Main Affiliation
Email
natrapee.na@kmitl.ac.th

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    Characterization and Application of Biochar Derived from Snake Fruit Peel for Lead Adsorption
    (2024-01-01)
    Maneesri, Wisit
    ;
    Choolaaied, Orasa
    ;
    Phanchindawan, Naree
    ;
    Ketpimol, Nopadol
    ;
    Limmun, Warunee
    Lead (Pb(II)) is a prominent contaminant in industrial wastewater, causing environmental and health risks. Traditional treatment methods often encounter limitations, including high operational costs and low efficiency in dilute solutions. This study presents an innovative, cost-effective solution utilizing biochar derived from snake fruit peels. Two biochar materials, SB500 and SB700, were produced via pyrolysis at 500 °C and 700 °C, respectively. The results indicate that the physicochemical properties of biochar change with increasing pyrolysis temperature. In addition, adsorption kinetics experiments showed that the two biochars displayed rapid adsorption within the first 60 min, with adsorption capacities of 28.08 mg/g for SB500 and 26.68 mg/g for SB700. This behavior can be attributed to a combination of physisorption and chemisorption mechanisms. These findings highlight the significance of the surface properties of biochar, especially its mesoporous structures and functional groups. Furthermore, this study suggested developing an efficient approach to mitigating the environmental and health impacts of Pb(II) contamination while addressing the issue of agricultural waste management.
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    Comparison of Analytical Ability of PLS and SVM Algorithm in Estimation of Moisture Content, Higher Heating Value, and Lower Heating Value of Cassava Rhizome Ground using FT-NIR Spectroscopy
    (2019-09-09)
    Nakawajana, Natrapee
    ;
    Posom, Jetsada
    FT-NIR spectroscopy coupled with chemometrics analysis was used for nondestructive estimation of moisture content (MC), higher heating value (HHV) and lower heating value (LHV) of cassava rhizome ground. The goal of this study was compared to the analytical ability of both algorithm between PLS and SVM. The purpose was to find the effective modelling technique. The outcome was found that PLS and SVM provided good accuracy in evaluation of energy properties, and could be utilized for quality assurance. PLS algorithm gave slightly higher accuracy than SVM algorithm for the prediction of MC, HHV, and LHV. PLS regression generated no difference between measured and predicted value. PLS and SVM regression showed R<sup>2</sup> between 0.90-0.98 and 0.84-0.90 for all parameters, respectively. The pre-processing of 2<sup>nd</sup> derivative was suitable for the PLS and SVM regression to the modelling.
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    Gross calorific value estimation for milled maize cob biomass using near infrared spectroscopy
    (2018-08-14)
    Posom, Jetsada
    ;
    Nakawajana, Natrapee
    The maize cob biomass is one of important biomass crops in Thailand. Nowadays, the use of the biomass as renewable resource is increasing, especially residue agriculture waste. As we know that the biomass properties impact combustion, in order to achieve boiler efficiency, its energy characteristics of biomass was required immediately before burning. This work uses the FT-near infrared spectroscopy to estimate gross calorific value (GCV) of maize cob as the rapid method. Each sample was scanned using diffuse reflectance mode at a wavenumber range between 12500-3600 cm<sup>-1</sup>. The scanning was done with a resolution of 8 cm<sup>-1</sup> and completed 32 scans per sample, then averaged to be one spectrum. The results showed that this technique could decrease a processing time to 1-2 minutes per sample to determine GCV whereas alternatively the current method used a processing time of 25-30 minutes per sample. The capacity of the model gave root mean square error of cross validation (RMSECV) of 91.1 Jg<sup>-1</sup>, which was low. Hence, the model was acceptable and cloud be used for screening.