Determination of methyl ester contents in biodiesel blends by FTIR-ATR and FTNIR spectroscopies

Oliveira, Jefferson Soares de; Montalvão, Rafael; Daher, Leila; Suarez, Paulo A. Z.; Rubim, Joel C.

doi:10.1016/j.talanta.2006.01.002

Cited by 144 publications

(73 citation statements)

References 11 publications

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“…Partial least square regression (PLS) and artificial neural network (ANN) combined to attenuated total reflection Fourier Transform Infrared (ATR-FTIR) and NIR spectroscopies were used by Oliveira et al [12] to design calibration models for the determination of methyl ester content in biodiesel blends with fossil diesel. Methyl esters were obtained by the methanolysis of soybean, babassu, dende, and soybean used frying oils.…”

Section: Introductionmentioning

confidence: 99%

FTIR Analysis for Quantification of Fatty Acid Methyl Esters in Biodiesel Produced by Microwave-Assisted Transesterification

Rabelo¹,

Ferraz²,

Oliveira³

et al. 2015

IJESD

137

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Abstract-Biodiesel was produced by microwave-assisted transesterification of soybean oil with methanol as esterifying agent and sodium methoxide as catalyst. Fourier transform infrared spectroscopy was employed as a fast and reliable analytical technique for the quantification of fatty acid methyl ester content in the produced biodiesel. The quantification was done with the use of a partial least squares model developed based on the infrared spectra obtained. It was shown that microwave irradiation is capable of reducing the reaction time when compared to conventional mechanically stirred reactors used for biodiesel production. In addition, quantification of fatty acid methyl ester content in biodiesel by Fourier transform infrared spectroscopy coupled to multivariate statistics was demonstrated feasible.

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Section: Introductionmentioning

confidence: 99%

FTIR Analysis for Quantification of Fatty Acid Methyl Esters in Biodiesel Produced by Microwave-Assisted Transesterification

Rabelo¹,

Ferraz²,

Oliveira³

et al. 2015

IJESD

137

View full text Add to dashboard Cite

show abstract

“…The raw spectra ( Figure 1a) showed bands characteristic of first overtone of CdH stretching (5550-6100 cm À1 ) and of combination of CdH and C]O stretching modes (4640-4700 cm À1 ) [34]. The bands around 4262 and 4334 cm À1 can be associated to the second overtone of CdH bending and to combination of CdH and C]C stretching modes, respectively [35].…”

Section: Database Acquisition and Preprocessingmentioning

confidence: 99%

Applications of Artificial Neural Networks in Biofuels

Filho¹,

Viegas²

2018

Advanced Applications for Artificial Neural Networks

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This chapter is focused on the application of artificial neural networks (ANNs) in the development of alternative methods for biofuel quality issues. At first, the advances and the proliferation of models and architectures of artificial neural networks are highlighted in the text by the characteristics of robustness and fault tolerance, learning capacity, uncertain information processing and parallelism, which allow the application in problems of complex nature. In this scenario, biofuels are contextualized and focused on issues of quality control and monitoring. Therefore, this chapter leads to a study of prediction and/or classification of biofuels quality parameters by the description of published works on the topic under discussion. Afterwards, a case study is performed to demonstrate, in a practical way, the steps and procedures to build alternative models for predicting the oxidative stability of biodiesel. The procedure goes from the processing of the data obtained by the near infrared until the evaluation of the alternative method developed by the neural network. In addition, some evaluation parameters are described for the assessment of the alternative method built. As a result, the feasibility and practicality of the application of neural networks to the quality of biofuels are proven.

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“…FT-IR spectrometry identifies the main functional groups presence at both the optimum produced biodiesel sample and its parent waste vegetable oil [24].…”

Section: Fourier Transform Infrared Spectroscopy Ft-irmentioning

confidence: 99%

Production of Biodiesel from Waste Vegetable Oil via KM Micro-mixer

Zaatout¹

2015

J Pet Environ Biotechnol

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The production of biodiesel to substitute fossil fuels has been challenging to apply in many countries especially developing countries. Given the importance of this fact, this study includes the production of biodiesel from waste vegetable oils by pre-treatment followed by transesterification reaction with methanol using a KM micro-mixer reactor. KM micro-mixer happened to give noticeable enhancement for the production of biodiesel quality compared to the normal batch reactor at optimum conditions. The parameters affecting biodiesel production process such as alcohol to oil molar ratio, catalyst concentration, the presence of tetra-hydrofuran (THF) as a co-solvents and the volumetric flow rates of inlet fluids were optimized. The properties of the produced biodiesel were compared with its parent waste oil through different characterization techniques. The presence of methyl ester groups at the produced biodiesel was confirmed using both the Gas chromatography-mass spectrometry (GC-MS) and infrared spectroscopy (FT-IR). Moreover, the thermal analysis of the produced biodiesel and the comparable waste oil indicated that the product after the transesterification process began to vaporize at 120ºC which makes it lighter than its parent oil which started to vaporize at around 300ºC. The maximum biodiesel production yield of 97% was recorded using 12:1 methanol to oil molar ratio in presence of both 1% NaOH and THF/methanol volume ratio 0.3 at 60 mL/h flow rate.

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Determination of methyl ester contents in biodiesel blends by FTIR-ATR and FTNIR spectroscopies

Cited by 144 publications

References 11 publications

FTIR Analysis for Quantification of Fatty Acid Methyl Esters in Biodiesel Produced by Microwave-Assisted Transesterification

FTIR Analysis for Quantification of Fatty Acid Methyl Esters in Biodiesel Produced by Microwave-Assisted Transesterification

Applications of Artificial Neural Networks in Biofuels

Production of Biodiesel from Waste Vegetable Oil via KM Micro-mixer

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