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Spectroscopy approach to methanol detection in waste fat methyl esters
摘要： Second-generation biodiesel manufactured from waste cooking oils (WCO) and inedible animal fats (AF) are one of the alternatives to the first generation (1G) vegetable oil-based biodiesel. In this study, a quality control method is proposed to evaluate methanol content in waste fat methyl esters and is based on near infrared spectroscopy (NIR) combined with multivariate analysis. More specifically, calibration models are constructed using partial least squares regression (PLS) for the prediction of methanol content in rapeseed oil methyl ester (ROME), waste cooking oil methyl ester (WCOME), chicken fat methyl ester (CFME) and pork fat methyl ester (PFME) by Vis-NIR spectrometer. The calibration models are based on the absorbance spectra and computed data from five wavelength regions of 400–2170 nm, 780–2170 nm, 1400–2170 nm, 1400–1600 nm and 1970–2170 nm. For the cases with the highest prediction ability obtained in this study, the coefficient of determination of the model's goodness-of-fit for methanol concentrations range 0–5% (v/v) was R2 N 0.990, and for concentrations 0–1% (v/v) was R2 N 0.994, indicating the spectroscopic approach effectiveness in methanol content detection relevant to the biofuel quality assessment. A pseudo-univariate limits of detection (LODpu) and quantification (LOQpu) as well as ratio of performance to deviation (RPD) were used to confirm the validity and to evaluate the practical applicability of developed models. In addition, the obtained results indicate the possibility of developing a transmission sensor for online monitoring of the production process and the quality of biofuel.
关键词： PLS calibration models,Waste cooking oil,Animal fat biofuel,Vis-NIR spectroscopy
更新于2025-09-23 15:21:21
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Monitoring of Microwave-Assisted Acid-Catalyzed Transesterification for Biodiesel Production Using FT-NIR Spectroscopy with Continuous-Flow Cell
摘要： The homogeneous microwave-assisted sulfuric acid-catalyzed transesterification of soybean oil, waste Brazil nut oil, sunflower oil and chicken fat for ethylic and methylic biodiesel production is described herein. The experiments were carried out in pilot-scale multimode reactors. The effects of the alcohol to oil molar ratio, catalyst concentration and irradiation time on the conversion to biodiesel were investigated. The transesterification reactions were performed at relatively small alcohol to oil molar ratios (9:1, 8:1 and 6:1) affording near 100% of conversion in reaction times of 60 to 120 min. Partial least squares (PLS) regression analysis using FT-NIR spectroscopy was performed to monitor the progress of the acid-catalyzed methanolysis of soybean oil. The NIR spectra were collected during the transesterification reaction with a spectrophotometric continuous-flow cell. 1H NMR spectroscopy was employed to determine the conversion percentage and used as a reference to build the PLS calibration model employing NIR spectroscopy data.
关键词： vegetable oils,sulfuric acid,FT-NIR spectroscopy,Animal fat,homogeneous acid catalysis,microwave-induced transesterification
更新于2025-09-23 15:21:01
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EXPRESS: Signal Enhancement Evaluation of Laser Induced Breakdown Spectroscopy of Extracted Animal Fats Using a Principal Component Analysis Approach
摘要： In this work, principal component analysis (PCA) was utilized to analyze laser-induced breakdown spectroscopy (LIBS) signals of extracted chicken fat, lamb fat, beef fat, and lard froze using two different freezing methods. The frozen samples were ablated using a neodymium-doped yttrium aluminum garnet (Nd:YAG) laser with a wavelength of 1064 nm, 170 mJ pulse energy, and 6 ns pulse duration to produce plasma on target surfaces. The samples were ablated using 30–60 shots of the laser beam at different spots. Stronger LIBS signals from extracted chicken fat and lamb fat were obtained with liquid nitrogen (LN2) method. However, LIBS signals obtained from the freezer freezing method were found to be stronger for extracted beef fat and lard. The PCA was then used to visualize the LIBS spectra of extracted animal fats into a score plot. Data points of each extracted animal fat were divided into three groups representing LIBS spectra collected at the early, middle and end part of the ablation process. The score plot revealed that the data points of the three groups of frozen extracted animal fats using the LN2 method were more closely clustered than those frozen in the freezer. Good discrimination with 97% of the variance was achieved between extracted the chicken fat, lamb fat, beef fat ,and lard using the LN2 method in the 3D score plot. LIBS signals of extracted animal fats produced from the LN2 method were found to be more stable than those from the freezer method.
关键词： Laser induced breakdown spectroscopy,LIBS,PCA,principal component analysis,liquid,animal fat,plasma
更新于2025-09-19 17:13:59