Fatty Acid Ester Composition Research Articles

Prediction of cetane number of biodiesel from its fatty acid ester composition using Artificial Neural Networks

Models for estimation of the cetane number of biodiesel from their methyl ester composition using artificial neural networks were obtained in this work. An experimental data that covers 48 and 15 biodiesels in the modeling step and validation step respectively were taken. The selection of biodiesel samples took into account a wide range of ester compounds with different unsaturation characteristics and number of carbon atoms. A model to predict cetane number using artificial neural networks was obtained with better accuracy than 95 %. The best neural network for predict the cetane number was a backpropagationnetwork(11:4:1)using a Conjugate Gradient Descend algorithm for the second training step and showing 96.3 % of correlation for the validation data and a mean absolute error of 1.5.The proposed network is useful for prediction of the cetane number of biodiesel in a wide range of composition but keeping the percent of total unsaturations lower than 80 %. The use of the artificial neural networks in this case let to study and understands the effect of individual fatty acids in the cetane number. Therefore they can be used for improving some biofuel properties related to the combustion process and its efficiency.

Biodiesel production potential of Eichhornia crassipes (Mart.) Solms: comparison of collection sites and different alcohol transesterifications

Renewable resources have stood out as raw materials in producing biofuels. This study aimed to evaluate the parameters of alcohol transesterification (ethanol and methanol) and localization of collection of aquatic macrophyte Eichhornia crassipes (Mart.) Solms in the production of biodiesel by in situ transesterification. E. crassipes was collected in Dourados and Corumbá (Brazil) municipalities. The fatty acid ester composition of the biodiesel was characterized and quantified by gas chromatography. The biodiesel properties were estimated using the BiodieselAnalyzer© program prediction. The ethyl transesterification resulted in higher yields, but the localization of collection was the most relevant parameter in biodiesel production according to the Permutation Multivariate Analysis of Variance. The simulation and comparison of the physical–chemical properties of E. crassipes biodiesel and BD 100 (commercial biodiesel) were promising for commercial application.

Prediction of cetane numbers of pure biodiesels based on various fuel properties using multiple non-linear correlations

Biodiesel has received considerable attention in recent years owing to its advantages over diesel fuel. Density, viscosity, flash point, heating value, and cetane number are among the most critical fuel properties of biodiesel. In the literature, using multiple linear regression, machine learning methods, and group contribution methods, some correlations have been derived to predict the cetane number of pure biodiesels depending on their properties (composition of fatty acid esters, number of carbon atoms, number of double bonds, molecular weight of the fatty acid esters, chain length, saponification number, iodine value, etc.). However, fewer researchers have attempted to establish a correlation between cetane number and other important fuel properties. Therefore, this study aims to employ multiple non-linear regression method for predicting the cetane number of pure biodiesels depending on the density, viscosity, flash point, and heating value. To obtain correlations, experimental data on fuel properties from the literature covering 100 different biodiesels (methyl and ethyl esters) were collected. The prediction performances of the suggested multiple non-linear correlations were compared to the multiple linear correlation frequently suggested in the literature. Reliable correlations with errors lower than 5% and high coefficient of determination values (r2) were derived.

Measurement and prediction of the volumetric and acoustic properties of two biodiesel fuels up to 200 MPa

This work presents experimental data on sound velocities and densities for two biodiesel fuels, namely sunflower methyl ester and a blend of Palm, Rapeseed, and Soybean methyl esters at pressures ranging from atmospheric to 200 MPa and temperatures from 293.15 to 393.15 K. Speed of sound data were obtained up to 200 MPa using a pulsed echo method. Density was determined by measuring the period of a vibrating tube up to 100 MPa and by integrating the sound velocity between 100 and 200 MPa. These measurements were coupled to determine other properties, such as isothermal compressibility, isentropic compressibility, and acoustic impedance, which strongly influence the injection process in diesel engines. The experimental data were compared with a set of models previously developed to predict the density and sound velocity of biodiesels under high pressure based on their fatty acid ester composition.

Improved Quantification by Nuclear Magnetic Resonance Spectroscopy of the Fatty Acid Ester Composition of Extra Virgin Olive Oils.

Analysis of foods, which are typically highly complex mixtures, by 1H NMR can be difficult because the prevalence of signal overlap complicates characterization and quantification. The various components of a food sample may have a wide range of concentrations, leading to a high dynamic range NMR spectrum and complicating the analysis of less concentrated species. One source of this complication is the presence of 13C satellites, peaks that appear either side of a parent peak with ∼0.56% of its intensity. Satellites of concentrated species can easily be comparable in intensity to the signals of minor components, and can partly or wholly obscure them. This is commonly seen in olive oil samples, leading to inaccurate calculation of the fatty acid ester composition of the oil, used for determining the quality of edible oils and for detecting adulteration. Here, we show that the recently introduced Destruction of Interfering Satellites by Perfect Echo Low-pass filtration (DISPEL) experiment is able to suppress 13C satellites and can substantially improve the accuracy of integration of minor signals. The DISPEL experiment does not require any complicated optimization, working “out of the box” with standard parameters, and incurs no significant loss of sensitivity. It has the potential to become the default experiment, replacing conventional 1D 1H NMR, for quantitative analysis of olive oil.

Prospects for the use of a drug based on a complex of fatty acid esters in models of laboratory animals in vivo

In this work we carried out studies of the first obtained micellar composition of fatty acid esters with allantoin on a water basis to determine its local irritant effect and therapeutic efficacy in the treatment of burns. It was found that there was a sequential change in the phases of the burn wound process in all groups. During the observation period, wound suppuration was not observed; there were 4 cases of a complicated course of the wound process and a fatal outcome in the control group. When conducting studies of local irritant effects, the assessment was carried out in points, in the experimental group it was on average 2 points as for the animals of the control group. The conducted studies allow us to conclude that the drug, when applied to the skin according to the interstate standard GOST ISO 10993-10—2011, has a weak degree of response to irritation in guinea pigs. The application of a permissive dose of the drug to sensitized guinea pigs does not cause a response from the skin, which indicates the absence of allergenic properties in this composition.

Predicting the phase equilibria of esters/alcohols mixtures and biodiesel density from its fatty acid composition using the modified group-contribution PC-SAFT

An empirical approach proposed recently (Fluid Phase Equilibria, 434 (2017) 176–192) to distinguish different isomer molecules is extended in this paper aiming to apply for alkyl-esters. The vapor pressure, saturated liquid density of heavy unsaturated and branched alkyl-ester are predicted using the transferred parameters of groups from n-alkanes, branched alkane, cis-alkenes and alkyl-ester. For pressures up to 2100 bar, density data for esters, ranging from C8:0 to C18:0, with up to two unsaturated bonds, are predicted with deviations inferior to 3%.Different binary ester + ester systems were investigated. Furthermore, the VLE of methanol/ethanol + ester mixtures are predicted using a transferable cross-association parameters approach. The general agreement between mg-SAFT and experimental data is very good (within 2–3% deviation on pressure).Finally, in order to validate the predictive ability of the model to be applied in the biodiesel groundwork, the mg-SAFT was then applied to predict the liquid density of 74 biodiesel mixtures based on its fatty acid ester composition. Overall average prediction errors at atmospheric pressure data were 0.71% for 64 multi-component mixtures, and that of 1.36% compared to experimental data for 10 biodiesel systems at high pressure up to 1300 bar.

Investigation of the effects of the fatty acid profile on fuel properties using a multi-criteria decision analysis

The structural features of fatty acids in biodiesel, including degree of unsaturation, percentage of saturated fatty acids and average chain length, influence important fuel properties such as cetane number, iodine value, density, kinematic viscosity, higher heating value and oxidation stability. The composition of fatty acid esters within the fuel should therefore be in the correct ratio to ensure fuel properties are within international biodiesel standards such as ASTM 6751 or EN14214. This study scrutinises the influence of fatty acid composition and individual fatty acids on fuel properties. Fuel properties were estimated based on published equations, and measured according to standard procedure ASTM D6751 and EN 14214 to confirm the influences of the fatty acid profile. Based on fatty acid profile-derived calculations, the cetane number of the microalgal biodiesel was estimated to be 11.6, but measured 46.5, which emphasises the uncertainty of the method used for cetane number calculation. Multi-criteria decision analysis (MCDA), PROMETHEE–GAIA, was used to determine the influence of individual fatty acids on fuel properties in the GAIA plane. Polyunsaturated fatty acids increased the iodine value and had a negative influence on cetane number. Kinematic viscosity was negatively influenced by some long chain polyunsaturated fatty acids such as C20:5 and C22:6 and some of the more common saturated fatty acids C14:0 and C18:0. The positive impact of average chain length on higher heating value was also confirmed in the GAIA plane.

Relating the cetane number of biodiesel fuels to their fatty acid composition: A critical study

The cetane number is one of the most significant properties to specify the ignition quality of a fuel for use in a diesel engine. The cetane number of biodiesel fuels is considerably influenced by their fatty acid methyl ester composition. The determination of cetane number of biodiesel is an expensive and time-consuming process. The objective of the present work is to predict the cetane numbers of different biodiesels using their fatty acid ester composition. Fifteen different biodiesel (including three blends) fuels were prepared and their cetane numbers were experimentally measured. An extensive literature review was made and the measured cetane numbers were compared with the reported values. To predict the cetane numbers of biodiesel fuels from their fatty acid methyl ester composition, a multiple linear regression model was developed. The cetane numbers and fatty acid compositions of 57 biodiesel fuels and 7 pure fatty acid methyl esters from the available literature were given as inputs. The experimentally measured cetane numbers and fatty acid compositions of four biodiesel fuels were also given as inputs to develop the regression model. The regression model has yielded an R2 value of 0.953 and a standard deviation of 2.271. The predicted cetane numbers are comparable with the experimentally measured cetane numbers. The maximum prediction error from the present model was found to be 8 per cent. Similarly, the present model was compared with the available litrature models. The maximum prediction error from the literature models was found to be 15 per cent. The present model also shows a good agreement with the measured cetane numbers.

Combustion, performance and emission characteristics of a DI CI engine using biodiesel with varied fatty acid composition

Five Biodiesel produced from different vegetable oils were tested on a diesel engine to study the effect of biodiesel fatty acid composition specifically unsaturated composition on the engine combustion. The results from fuel analysis show that biodiesel (93% unsaturated fatty acid ester composition) with 55% linolenic ester has a higher density of 0.89 kg/m³, lower viscosity of 3.8 cSt, heating value of 39 MJ/kg and cetane number of 49. The engine combustion results exhibits a longer premixed and shorter diffusion burning phase with higher peak pressure of 72 bars and higher cumulative heat release compared to other fatty ester composition. The performance and emission results show that emits more oxides of nitrogen of 16.83 g/kWh and exhibits higher thermal efficiency of 29.76% compared to diesel of 12.83 g/kWh and 28.41% respectively. Biodiesel with 45% saturated ester and 55% unsaturated ester composition shows a NOX neutral fuel with a penalty of 1.75% in thermal efficiency. No significant differences in unburnt hydrocarbon (UBHC), carbon monoxide (CO) and smoke emissions among the biodiesel fuels were noticed except linseed oil methyl ester.

Predicting the temperature dependent viscosity of biodiesel fuels

The purpose of this work was to develop a method for predicting temperature dependent viscosities of biodiesel based on fatty acid ester composition. The Grunberg–Nissan equation combined with a group contribution method was used as the mixing rule to calculate viscosities of mixtures of fatty acid esters. Prediction errors at 25 °C were less than 2.5% for 22 mixtures of fatty acid ethyl esters. Compared with experimentally measured viscosities at 20–100 °C, predicted viscosities of soybean oil and yellow grease methyl esters were within 3%. For coconut, palm and canola oil methyl esters, maximum errors were underestimations at approximately 7%.

COMPARATIVE ANALYSIS OF THE ATOMIZATION CHARACTERISTICS OF FIFTEEN BIODIESEL FUEL TYPES

Engine results using biofuels have varied considerably in the reported literature. This article addresses twopotential sources of this variation, atomization differences and impurities due to lack of quality control during production.Atomization is the first process encountered during the combustion of fuels in a compression ignition engine and is largelydetermined by the fuels viscosity and surface tension. Previous work using five experimentally produced methyl esterbiodiesel fuels showed that the viscosity and surface tension could be predicted from their fatty acid ester composition,and the atomization characteristics in turn could be predicted from their viscosity and surface tension. This article utilizesthe results of that work to give a quantitative comparison of the atomization characteristics of fifteen biodiesel fuel typesusing the fuels viscosity and surface tension, predicted directly from the fatty acid composition of the fuels. Except forcoconut and rapeseed biodiesel fuels, all of the rest of the 15 biodiesel fuels had similar atomization characteristics. Sincethe most likely contaminant in the fuel from the processing was residual glycerides, their effect on viscosity and surfacetension was studied experimentally and their effect on the atomization characteristics was computed.

Predicting the viscosity of biodiesel fuels from their fatty acid ester composition

Viscosity is one of the most significant properties to affect the utilization of biodiesel fuels. This paper presents a method, which has been verified experimentally, for predicting the viscosities of biodiesel fuels from the knowledge of their fatty acid composition. The applicability of a logarithmic mixture equation was verified using controlled mixtures of standard fatty acid esters and natural biodiesels. Several binary, ternary and quaternary mixtures of fatty acid ethyl ester (FAEE) gas chromatography (GC) standards were formulated. Their viscosities were predicted from their component values and were within ±3.7% of their measured values. The fatty acid compositions of six typical oils were simulated by mixing fatty acid methyl ester (FAME) standards in appropriate amounts. Viscosities of these mixtures were also predicted within ±2.1% of their measured values. Five biodiesel types were produced from natural oils and the logarithmic equation was applied to predict their viscosities. An average prediction error of ±3% was obtained for these samples. The viscosities of fifteen biodiesel types were then predicted based on their fatty acid composition as published in the literature and were found to vary as much as 100% This is most likely a principal contributing factor to the variation in performance of some biodiesel fuel types. The viscosity of biodiesel fuels reduce considerably with increase in unsaturation. Contamination with small amounts of glycerides significantly affects the viscosity of biodiesel fuels.

Phospholipid fatty acid ester composition ofPasteurella multocida andActinobacillus lignieresii

Cell surface hydrophobicity properties vary dramatically, whereas cell envelope phospholipid composition is essentially identical among strains ofPasteurella multocida andActinobacillus lignieresii. Fatty acid ester composition of the major phospholipid fractions from cell surface hydrophobicity variants was examined to determine whether hydrophobic properties are influenced by cell envelope fatty acid content. Individual phospholipids were resolved by preparative thin-layer chromatography, and methanolysis was performed with boron trifluoride-methanol. Gas-liquid chromatographic analysis revealed the organisms to be similar qualitatively, whereas hydrophobic variants exhibited consistently, greater and more disparate C16:0+C16:1/C14:0 ratios in all fractions. Fatty acid composition of phospholipids may be related to surface hydrophobicity properties ofP. multocida variants. However, comparative data obtained forA. lignieresii revealed a degree of similarity withP. multocida that precludes use of this parameter as a means for differentiation of thesePasteurellaceae type species, thereby supporting their taxonomic relatedness.

Computerized quantitative analysis of methyl and ethyl esters of long chain fatty acids by gas-liquid chromatography using relative molar response

1. The possibility that the relative molar response method could be applied for quantitative analyses of saturated and unsaturated fatty acid methyl esters and ethyl esters into two double bonds was verified. This method was applied to quantitative analyses of fatty acids of individual lipid classes of blood serum. 2. Computerized calculations, rather than those made manually or with desk calculating machines, of the fatty acid ester composition substantially reduced working time; while the calculation of forty equations with a desk calculating machine took six to eight hours, computerized calculations, including the printing of results, were effected in less than one minute. 3. The main advantage of this method was its ability to obtain quantitative information about the fatty acid ester spectrum which in a pure state was unobtainable and could not be analyzed either by the internal standard or by the direct calibration method. 4. The accuracy of the relative molar response method was identical with other methods when all quantitative analysis conditions were carefully controlled. For components larger than 10% of the sample, the error was less than 2% (relative); for components constituting 5–10% of the sample, the error was 3–5% (relative); and for smaller components (especially with short elution times), the error might reach 10% (relative).