Biodiesel is a renewable transportation fuel consisting of fatty acid methyl esters (FAME), generally produced by transesterification of vegetable oils and animal fats. In this review, the fatty acid ...(FA) profiles of 12 common biodiesel feedstocks were summarized. Considerable compositional variability exists across the range of feedstocks. For example, coconut, palm and tallow contain high amounts of saturated FA; while corn, rapeseed, safflower, soy, and sunflower are dominated by unsaturated FA. Much less information is available regarding the FA profiles of algal lipids that could serve as biodiesel feedstocks. However, some algal species contain considerably higher levels of poly-unsaturated FA than is typically found in vegetable oils.
Differences in chemical and physical properties among biodiesel fuels can be explained largely by the fuels’ FA profiles. Two features that are especially influential are the size distribution and the degree of unsaturation within the FA structures. For the 12 biodiesel types reviewed here, it was shown that several fuel properties – including viscosity, specific gravity, cetane number, iodine value, and low temperature performance metrics – are highly correlated with the average unsaturation of the FAME profiles. Due to opposing effects of certain FAME structural features, it is not possible to define a single composition that is optimum with respect to all important fuel properties. However, to ensure satisfactory in-use performance with respect to low temperature operability and oxidative stability, biodiesel should contain relatively low concentrations of both long-chain saturated FAME and poly-unsaturated FAME.
Biodiesel is a good alternative to fossil fuels for conventional engines, but determining the properties of biodiesel can be a time-consuming and resource-intensive process. Therefore, the ...development of models capable of predicting these properties would be of great importance. In this work, different machine learning models were investigated for predicting the Iodine Value (IV) based on the distribution of fatty acid methyl esters (FAME). For this purpose, a database with 266 examples of biodiesel from different feedstocks (1st, 2nd and 3rd generation) was used along the leave-one-out methodology. The main results of the work are: the double bonds and the distribution of FAMEs are the best attributes for predicting IV and the XGBoost algorithm gives an absolute mean error of 11.4 units; the machine learning models for predicting biodiesel properties need to be trained on a large number and variety of biodiesel examples to better predict and generalize; the use of both ANNs and the hold-out approach of dividing the dataset into train/validate/test are not recommended due to the risk of overfitting and the algorithm's dependence on which examples form each group given the currently available data. The leave-one-out method is most appropriate for estimating model performance.
•Double bonds and FAMEs distribution are the best attributes to predict IV.•The XGBoost algorithm gives the best results when predicting IV.•Models must be trained on a large number and variety of biodiesel examples.•The use of ANNs is at risk of overfitting given the data currently available.•The train/validate/test approach also perform bad with the current data.
The study was carried out to investigate the effect of storage time at ambient temperature on pH and iodine value of palm oil and groundnut oil using appropriate standard methods. The iodine value of ...palm oil decreased from 45.69 ± 0.01a to 45.11± 0.00k while that for groundnut oil decreased from 56.72 ± 0.01a to 56.22 ± 0.01k during the period of storage indicating loss of unsaturation due to oxidation. On the other hand, the pH of both palm and groundnut oils showed a more impressive decrease from 6.85 ± 0.05a to 4.19 ± 0.00j and 6.40 ± 0.00a to 4.40 ± 0.00h., respectively, due to autoxidation of the oils. A trend of decreasing order of iodine and pH value as the number of days of storage increases for both oils (palm and groundnut oil) was observed. This study shows that the storage time has a high significant effect on the iodine Value and pH value of both oil (palm and groundnut oil) with p ˂ 0.00 as against p ≤ 0.05. It was also observed that there was loss of unsaturation in both oils but higher in palm oil. However, groundnut oil had a higher iodine value, implying that groundnut oil had more of unsaturated fatty acid than palm oil which tends towards saturation due to high level of decreasing iodine value. However, from literature, it has been stated that groundnut oil is likely to be healthier for consumption due to the presence of unsaturated fat it contains.
Fatty acid composition and stability of vegetable oils have taken more attention as an essential source of biologically active compounds in a good balanced diet. The purpose of the study was to ...determine peroxide value, free fatty acids, unsaponifiable matter, total carotenoid content, iodine value and fatty acid composition of sunflower, rapeseed, mustard, peanut and olive oils. Rapeseed and peanut oils had the highest peroxide values, while sunflower oil had the lowest peroxide values. The free fatty acid value of the tested oils varied between 0.43 and 1.36% oleic. The peanut oil had the highest free acid value and the mustard oil had the lowest one. Total carotenoid contents of mustard and rape seed oil were higher than those of the other oils tested. Palmitic acid (C16:0), oleic acid (C18:1) and stearic acid (C18:0) were the common main fatty acid components of the vegetable oils tested. Followed by linoleic acid, the amount of oleic acid was the highest among other fatty acid components. Mustard oil had the highest erucic acid (C22:1) with the amount of 11.38%, indicating that it cannot be used for human consumption. Among the oils investigated, sunflower and mustard oils were more stable than rapeseed, peanut and olive oils.
► Activated carbon was prepared from date pits by ferric chloride activation (FAC). ► FAC was used to remove methylene blue (MB) from aqueous solutions. ► Surface area of 780.06m2/g was characterized ...for FAC. ► Maximum MB capacity of 259.25mg/g was reported using Sips isotherm. ► The kinetic data were well described by pseudo-second order model.
Ferric chloride has been utilized as an activator for preparation of activated carbon from an agricultural solid waste, date pits. The characteristics of prepared activated carbon (FAC) were determined and found to have a surface area and iodine number of 780.06m2/g and 761.40mg/g, respectively. Experiments were carried out to evaluate the batch adsorption isotherms and kinetics of methylene blue (MB) on FAC at different temperatures. Experimental equilibrium data were analyzed by the Langmuir, Freundlich and Sips isotherm models. The results show that the best fit was achieved with the Sips isotherm equation with a maximum MB adsorption capacity of 259.25mg/g. Pseudo-first order, pseudo-second order and intraparticle diffusion models were used to analyze the kinetic data obtained at different initial MB concentrations. The adsorption kinetic data were well described by the pseudo-second order model. The calculated thermodynamic parameters, namely ΔG, ΔH, and ΔS showed that adsorption of MB onto date pits was spontaneous and endothermic under examined conditions.
Lipid oxidation is a spontaneous process in fats and, consequently, in products with significant fat content. Many cosmetics fall into this category, presenting an intrinsic relationship between the ...productʼs quality, oxidation capacity, and market value. This study comprehensively investigated the aging of body lotions, accentuating the role of their chemical formulations. Sensory analysis clarified that controlled temperature-induced aging significantly altered the lotions' appearance, texture, color, and, to a lesser extent, odor, hinting at the onset of rancidity. As lipid peroxidation unfolds, the emergence of secondary oxidation products like aldehydes, ketones, and alcohols becomes prominent. These secondary products indicate a potential degradation in the lotion's quality and efficacy. Quantifying the primary oxidation products was possible using methods like the quantification of Conjugated Dienes (CD) expressed in percentage and the Peroxide Index (PI) method expressed in meqO2/kg of a dry sample. On the other hand, methods such as the p-Anidisine Index (pAi) and the thiobarbituric acid reactive substances (TBARS) with malonaldehyde (MDA) expressed as malonaldehyde concentration (mg/g of dry sample) provided the quantification of secondary oxidation products. Regarding lipid oxidation, lotions containing sunflower and soybean oils emerged as notably susceptible. Conversely, samples that demonstrated minimal oxidation, were attributed to protective elements such as Aloe barbadensis and Calendula officinalis extracts. Examining into secondary oxidation, four samples displayed the highest TOTOX values, indicating extensive oxidation. A discernible correlation was observed between TOTOX values and natural extracts' presence (or lack), underscoring their protective or exacerbating roles. Certain natural ingredients, including A. barbadensis leaf juice powder and C. officinalis flower extract, were recognized as supporters against oxidation. Yet, components like PEG-40 hydrogenated castor oil can, paradoxically, seem to intensify the oxidative cascade. This research provides crucial insights into the interplay between natural extracts and lipid oxidation in body lotions. The elucidated results accentuate the necessity for judicious ingredient selection, balancing the inclusion of natural extracts to ensure product quality, longevity, and safety.
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•Aloe barbadensis and Calendula officinalis extracts show protection against oxidation.•PEG-40 hydrogenated castor oil accelerates lipid oxidation acting as a pro-oxidant.•Accelerated aging tests show changes in lotion appearance, texture, color, and odor.•Sunflower and soybean oils exhibited heightened vulnerability to lipid oxidation.•A correlation between TOTOX values and antioxidant-rich natural extracts emerged.
The increasing glycerol consumption will result in an issue for further applications of methyl esters, which are produced together with glycerol by transesterification of vegetable oils/animal fats ...on industrial scale. One possibility is the formation of bio-epoxides, which can be used for bio-lubricants, precursors for chemicals or CO2 capture, and so they can replace products from crude oil. Therefore, the mathematical models describing epoxidation of methyl esters, i.e., the influence of reaction conditions (time, temperature, etc.) on the properties of epoxides (iodine and epoxide values, relative conversion to oxirane, etc.) were created/calculated to decrease the production cost. It was found that (i) higher initial iodine value of esters, (ii) higher reaction temperature, (iii) higher concentration of formic acid and (iv) longer reaction time caused more formed epoxides. In contrast, a higher concentration of hydrogen peroxide caused epoxide ring opening and the formation of side products. The catalyst (H2SO4) and the intensity of stirring were statistically insignificant. The drying of epoxides was carried out by distillation and improved by the addition of a small amount of methanol. The models allow the synthesis of epoxides with desired properties, which are biodegradable and nontoxic with variety of applications.
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Biodiesel is a sustainable fuel, which consists of a mixture of fatty acid alkyl esters obtained by the transesterification of vegetable oils or animal fats. Due to the diversity of raw materials ...used in its production, the biofuel can show significant differences in its physicochemical properties, which causes severe matrix effects in biodiesel analysis. In this work, a calibration strategy recently proposed for atomic spectrometry, named multi-energy calibration (MEC), was evaluated as a tool to circumvent matrix effects in molecular spectrometry. The strategy yielded more accurate results in the spectrophotometric determination of the iodine value and free glycerol in biodiesel produced from different raw materials (root mean square error of prediction, RMSEP, values of 6.0 and 8.0, respectively), than both external standard calibration (EC, RMSEP as high as 45.6) and the standard additions method (SAM, RMSEP as high as 25.3). Moreover, results agreed with those obtained by the reference procedures at the 95% confidence level, which was not observed for EC (free glycerol determination) and SAM (iodine value determination). Coefficients of variation (n = 8) and limits of detection (99.7% confidence level) were, respectively, estimated at 1.7% and 5 g I2/100 g iodine value and 3.0% and 10 mg kg−1 free glycerol in biodiesel, which are comparable to or better than those achieved using previously proposed procedures. Thus, MEC is a viable alternative for biodiesel quality control, with outstanding minimization of matrix effects, simplicity, practicality, and environmental friendliness.
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•Multi-energy calibration overcame matrix effects in molecular absorption spectrometry.•Accurate results for determination of biodiesel quality parameters.•Better accuracy than external calibration and the standard additions method.•A simple, practical, and more environmental friendly approach.
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•LSSVM-PSO model has been developed for estimation of fatty acid methyl ester based biodiesel properties.•Pour point, cloud point, iodine value and kinematic viscosity are modeled as ...a function of fatty acids composition.•Good predictions are obtained by the suggested approach.
Biodiesel as an environmental friendly and renewable fuel assigns a great potential to substitution of petroleum diesel. The biodiesel characteristics are highly dependent on the structure of its basis oil. The main aim of the present work was to develop an accurate model based on LSSVM-PSO algorithm to estimate biodiesel properties, i.e., pour point, cloud point, iodine value and kinematic viscosity as a function of fatty acids composition. The temperature, molecular weight, weight percent of saturated acids, poly unsaturated fatty acids and mono unsaturated fatty acids, number of double bonds, and carbon number are involved variables for development of the models. The performance of LSSVM-PSO model is evaluated using different statistical criteria which result in the coefficients of determination of 0.99995, 0.99981, 0.99848 and 0.99930 for pour point, cloud point, iodine value and kinematic viscosity, respectively. In addition, the outcomes of the proposed model are compared with those from an ANFIS model indicating the great potential of the LSSVM-PSO model to estimate the biodiesel properties.
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