Study of the properties of polymers obtained from vegetable oil derivatives by light scattering techniques

Nicolau, Aline; Mariath, Rúbia Martignago; Samios, Dimitrios

doi:10.1016/j.msec.2008.08.039

Cited by 18 publications

(14 citation statements)

References 28 publications

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“…The predicted values were compared against real values for I.V. The criteria for accepting the calibration model are based on lowest values for standard error of calibration (SEC) and highest coefficient of determination ( R 2 ). 63 The accuracy of the calibration model was preliminary assessed by using “leave-one-out” cross-validation.…”

Section: Methodsmentioning

confidence: 99%

“…The cross-validation evaluates the data by leaving one of the calibration samples from the regression model and performing a new model for the remaining calibration samples. The external validation of the model was based on the spectra of batch B samples (totally 50 spectra), and assessed by the standard error of prediction (SEP) and coefficient of determination ( R 2 ).…”

Section: Methodsmentioning

confidence: 99%

“…Faced with limitations of fossil oil reserves, alternative resources for a future generation of plastics are urgently needed. Vegetable oils are good candidates for energy production 1 or sustainable materials design 2,3 and may lead to the creation of new economic markets. A reasonable exploitation of their potential is important in emerging countries with growing populations.…”

Section: Introductionmentioning

confidence: 99%

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Quality and Statistical Classification of Brazilian Vegetable Oils Using Mid-Infrared and Raman Spectroscopy

et al. 2012

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Palm oil, soy oil, sunflower oil, corn oil, castor oil, and rapeseed oil were analyzed with Fourier transform infrared (FT-IR) and FT-Raman spectroscopy. The quality of different oils was evaluated and statistically classified by principal component analysis (PCA) and a partial least squares (PLS) regression model. First, a calibration set of spectra was selected from one sampling batch. The qualitative variations in spectra are discussed with a prediction of oil composition (saturated, mono- and polyunsaturated fatty acids) from mid-infrared analysis and iodine value from FT-Raman analysis, based on ratioing the intensity of bands at given wavenumbers. A more robust and convincing oil classification is obtained from two-parameter statistical models. The statistical analysis of FT-Raman spectra favorably distinguishes according to the iodine value, while the mid-infrared spectra are most sensitive to hydroxyl moieties. Second, the models are validated with a set of spectra from another sampling batch, including the same oil types as-received and after different aging times together with a hydrogenated castor oil and high-oleic sunflower oil. There is very good agreement between the model predictions and the Raman measurements, but the statistical significance is lower for mid-infrared spectra. In the future, this calibration model will be used to check vegetable oil qualities before using them in polymerization processes.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Quality and Statistical Classification of Brazilian Vegetable Oils Using Mid-Infrared and Raman Spectroscopy

et al. 2012

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“…The reactants were stirred for 3h 30 min at 150°C. The polymer obtained was presented as a yellowish and translucent product [23,26]. This material was named as oleic acid polymer (OAP).…”

Section: Polimerization Reactionmentioning

confidence: 99%

Iron Oxide Nanoparticles Coated with Polymer Derived from Epoxidized Oleic Acid and Cis-1,2-Cyclohexanedicarboxylic Anhydride: Synthesis and Characterization

S¹,

D²

2016

J Material Sci Eng

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This study investigated the use of polymer derived from oleic acid for coating iron oxide nanoparticles. The purpose of this study was to provide the magnetic nanoparticles an appropriate surface for stabilization in organic solution. The magnetic nanoparticles coated were produced by mixing of the polymer solution with the ferromagnetic fluid by mechanical stir, followed by magnetic separation. These nanoparticles generated a core-shell behavior, in which the core provides the magnetic properties and the external layer formed by the polymer. The interaction between iron nanoparticles and oleic acid polymer occurred by the affinity of carboxylic group. This interaction makes the nanoparticles hydrophobic, moving to the organic media. The carbon content of the coated nanoparticles was approximately 14%, when analyzed by scattering electron microscopy (SEM-EDX), and 12%, when analyzed by Elemental Analysis of carbon, hydrogen and nitrogen. This percentage confirms the presence of the polymer on the surface of magnetic nanoparticles. The average diameter of the coated and uncoated nanoparticles obtained by transmission electron microscopy was around 13 nm and 11 nm and the average diameter of crystallite by X-ray diffraction was around 8 nm and 12 nm respectively. Averaging all this values we obtain 11 ± 2 nm. The thermogravimetric analysis showed the degradation temperatures starting from 200°C to 500°C, attributed to the polymer, and another one degradation temperature between 650-750ºC, relative to the polymer-nanoparticles interaction. Furthermore, the vibrating sample magnetometer indicated that coated nanoparticles remain magnetic, with increasing saturation magnetization value, when a magnetic field was applied.

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“…Número de artigos publicados de 1989 a maio de 2011, nos quais é utilizado ELSD para análise de produtos naturais. Fonte: ISIknowledge molecular do analito, ao contrário da detecção por espalhamento de luz não evaporativa, 5 que é utilizada na análise da massa molar de polímeros. A quantidade de luz dispersada é proporcional somente à quantidade de amostra na pilha.…”

Section: Princípios Da Técnicaunclassified

Utilização de detecção por espalhamento de luz evaporativo para a análise de produtos naturais

Urano¹,

Rodrigues²,

Berlinck³

2012

Quím. Nova

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Recebido em 13/9/11; aceito em 14/12/11; publicado na web em 23/3/12 EVAPORATIVE LIGHT-SCATTERING DETECTOR FOR ANALYSIS OF NATURAL PRODUCTS. The interest in the use of evaporative light scattering detector (ELSD) for the analysis of different classes of natural products has grown over the years. This is because this detector has become an excellent alternative compared to other types of detectors, such as the refractive index detector and the ultraviolet (UV) detector. This review describes the basic principles of ELSD functioning and discusses the advantages and disadvantages in using an ELSD for the analysis of organic compounds. Additionaly, an overview, covering the last 23 years, of ELSD applications in natural products analysis (saponins, terpenes, carbohydrates, glycosides, alkaloids, steroids, flavonoids, peptides, polyketides, coumarins and iridoids) is presented and discussed.

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Study of the properties of polymers obtained from vegetable oil derivatives by light scattering techniques

Cited by 18 publications

References 28 publications

Quality and Statistical Classification of Brazilian Vegetable Oils Using Mid-Infrared and Raman Spectroscopy

Quality and Statistical Classification of Brazilian Vegetable Oils Using Mid-Infrared and Raman Spectroscopy

Iron Oxide Nanoparticles Coated with Polymer Derived from Epoxidized Oleic Acid and Cis-1,2-Cyclohexanedicarboxylic Anhydride: Synthesis and Characterization

Utilização de detecção por espalhamento de luz evaporativo para a análise de produtos naturais

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