The present study investigates the transesterification of corn oil with methanol over two oxides of MgO and ZnO at 65 ͦC and 1 atm. These two catalysts have been prepared via a conventional co-precipitation process. As for MgO, the corresponding mixed metal nitrate solution has been mixed and heated at the presence of urea. ZnO has also been synthesized by co-precipitation of metal acetate at the presence of oxalic acid and ethanol. The catalysts then have been characterized by means of X-Ray Diffraction (XRD) and Scanning Electron Microscope (SEM). XRD results indicate high purity for both catalysts. Also, catalytic activity has been evaluated in methanol reflux temperature through corn oil transesterification, with the impacts of reaction variables, like catalyst amount, methanol/oil molar ratio, and reaction time on biodiesel yield, investigated by means of HNMR spectrum. Under appropriate transesterification conditions at 65 °C (catalyst amount= 5%, methanol/ oil ratio= 20, and reaction time= 10 hr), an ME content of 62.61% can be achieved, using MgO catalyst. Similarly, the experiments have been repeated to achieve the best yield, using ZnO catalyst, with the highest rate, equal to 53.1%, obtained in 9% of catalyst and methanol/oil ratio of 30 over 10 hr. Furthermore, reusability of ZnO and MgO has been evaluated in transesterification reaction.

We performed toxicological study of mice exposed to lead by quantifying fatty acids in brain of the mice. This study suggests that the introduced analytical method had an extremely high tolerance against impurities such as water and extractives; thus, it led to the enhanced resolution in visualizing the spectrum of fatty acid profiles in animal brain. Furthermore, one of the biggest technical advantages achieved in this study was the quantitation of fatty acid methyl ester profiles of mouse brain using a trace amount of sample (e.g., 100 μL mixture). Methanol was screened as the most effective extraction solvent for mouse brain. The behavioral test of the mice before and after lead exposure was conducted to see the effect of lead exposure on fatty acid composition of the mice’ brain. The lead exposure led to changes in disease-related behavior of the mice. Also, the lead exposure induced significant alterations of fatty acid profile (C16:0, C 18:0, and C 18:1) in brain of the mice, implicated in pathology of psychiatric diseases. The alteration of fatty acid profile of brain of the mice suggests that the derivatizing technique can be applicable to most research fields associated with the environmental neurotoxins with better resolution in a short time, as compared to the current protocols for lipid analysis.

A method based on phospholipid fatty acid (PLFA) analysis for profiling microbial communities in offshore produced water was optimized. The operation parameters affecting final PLFA profiling performance from the solid phase extraction (SPE) purification and fatty acid methyl esters (FAMEs) yielding process were investigated. Under the selected conditions, 92.9%, 96.3% and 92.8% of the spiked phospholipid standards C16:1 (cis-9) PC, C18:1 (cis-9) PC, and C19:0 PC were recovered, respectively, using 10mL methanol as elution solvent on a non-commercial SPE column. Over 90% of spiked C19:0 PC was recovered before sample transesterification. Four parameters including alkaline reagent, volume of acid for neutralization, time and temperature for FAMEs derivatization were examined. Gas Chromatography-Mass Spectrometry (GC-MS) was used to analyze FAMEs and the method linearities, recoveries of 29 FAMEs during transesterification, detection limits, relative standard deviations were presented. The results provided valuable information for biological reservoir souring control.

Lipases are utilized in biodiesel production utilizing various types of substrates. The use of lipase in bioenergy production aims to reduce energy crises and environmental pollution. Lipase-producing indigenous bacteria Bacillus licheniformis (Accession no. OP56979) and Bacillus rugosus (Accession no. OP56980) were isolated from various oil-contaminated sites. The isolated potential lipolytic bacteria were screened for maximum lipase production. Then, the bacteria showing the highest lipolytic activity were subjected to identification using the 16s rRNA technique while other isolated were identified biochemically. Lipase [LipBL-WII(c)] from Bacillus licheniformis having the highest lipolytic activity expressed various characteristics. Characterization of crude LipBL-WII(c) expressed that it showed stability in a wide range of pH (4 to 10) with optimum lipolytic activity observed at pH 8. It was then found to be active at a temperature range from 20°C to 80°C with optimal at 50°C. Lipase activity was also stimulated in metal ions such as Ca+1, Mg2+, and Zn2+ the most. Furthermore, LipBL-WII(c) retained lipolytic activity in the presence of various organic solvents and surfactants. The kinetic parameters (Km and Vmax) for LipBL-WII(c) were ascertained using Lineweaver- Burk plot. LipBL-WII(c) showed a potential for biodiesel production using olive oil as a source. Lipase gave 84% yield of biodiesel production from olive oil. Thus, it could be employed as a potential candidate for green biodiesel production using oil sources.

Over the past several decades, people from many nations have adopted and supported using biodiesel energy sources due to their accessibility and advantages in reducing CO2 and H.C. emissions to the environment. Today, biodiesel is recognized as a sustainable alternative energy source. Commercially, biodiesel was produced by converting homogenous oil treated with a catalyst like NaOH or KOH in Alcohol. These homogeneous catalysts are hazardous to the environment and cannot be recycled. As an alternative, this research article focuses on biodiesel production from a 1:1 blend of Simarubha glauca (Laxmitharu in Kannada) and Azadirachta indica (Neem) triglyceride via acid-base catalyzed transesterification reaction. The heterogeneous-based graphene-doped CaO was used as a catalyst obtained through the calcination method by doping it with graphene oxide by the hummers’ method. SEM, FTIR, and XRD were used to characterize the GaO-CaO catalyst. The results predict that the prepared catalyst yielded a high percentage of ASFAME (94.0%) and meets the quality as per ASTM standards 6751D.

The primary motivation for researching biofuels is to meet the world’s energy requirements. Demand for fossil fuels is rising significantly due to population expansion. Biodiesel is a promising renewable energy source that, if implemented effectively, has the potential to reduce the dependency on fossil fuels. Because biodiesel is a cleaner fuel that requires no engine modification, its implementation is not complicated. It can directly be used in diesel engines or as a blended diesel with fossil diesel. Seven different vegetable oils were utilized to replicate restaurant waste cooking oil in the laboratory to make biodiesel. The qualities of biodiesel produced were investigated and compared to determine how they vary depending on the chemical composition of the oil source. The physical appearance of biodiesel varies slightly depending on the oil source. Density, kinematic viscosity, flash point, and acid levels, on the other hand, are all within acceptable biodiesel criteria for all types of oil sources used.

High volumes of wastewater with high pollutant concentration form in the transesterification stage of the process applied for biodiesel production from waste vegetable oils. In this study, application of the advanced electrocoagulation process following acidification was investigated in the biodiesel wastewater treatment. Through the acidification step of the sequential process, respectively, 25.4%, 68.7%, and 50.0% removal efficiencies for COD, oil-grease, and volatile fatty acids (VFAs) were obtained. Electro-activated persulfate (EAP) oxidation was modeled and optimized by using the response surface methodology and Box–Behnken design. The effect of independent variables (current, persulfate/COD ratio, time) on COD, oil-grease, VFAs removal, and total cost and the interaction of the variables of the process were determined. The maximum oil-grease removal efficiency predicted by using the model was 98.3% under the optimum conditions (current: 4 A, persulfate/COD: 4.4, and time: 15 min), whereas oil-grease removal efficiency obtained by the verification experiments performed at optimum conditions was found to be 97.2%. Sequential acidification–EAP process is an appropriate treatment method for biodiesel wastewater with high oil-grease concentration, and response surface methodology is a powerful tool for optimizing the operational conditions of EAP oxidation for COD, oil-grease, VFAs removal, and total cost.

This work examines the effect of ultrasound irradiation (UI) on biodiesel properties and transesterification parameters. Methanol content, reaction time, reaction temperature, and catalyst concentration are varied, and the optimum condition for maximum possible yield was held constant for both processes. Biodiesel obtained from non-edible oils is the most promising alternative fuel for conventional diesel fuel. In this study, sterculia foetida seed oil was used for biodiesel production. Sterculia foetida oil was transesterified to lower its FFA using UI and compared with the conventional process. Both heating processes were optimized to yield a maximum of 94.3% at a six molar ratio, 50 °C, (water temp), 1% wt of catalyst (KOH), and 75 min reaction time. Transesterification by UI reduced the total reaction time to 4 min compared to 75 min at the conventional process. Further UI influenced the properties of biodiesel (SOBD) from SO. UI lowered viscosity by 7.3% and density by 5.5% and facilitated using oxygen content of SOBD.

The presented study discusses biodiesel synthesis by utilizing two wastes: Mesua ferrea Linn (MFL) seed shells (inert support for developing catalysts) and used cooking oil (feedstock). The MFL shells were used for heterogeneous acid and base catalyst development through carbonization, steam activation and subsequent doping of H₂SO₄ or KOH, which upon instrumental examination showed effective doping of functional groups on the MFL char. The conversion approach uses methanol with sulfonated char (SC) for esterification, while the second stage utilizes 2-propanol for transesterification with KOH-doped char (KC) as a catalyst. Both stages optimize 5 controlling parameters such as mixing intensity, duration of reaction, catalyst load, alcohol concentration and reaction temperature in an L16 Taguchi experimental matrix. Thus, the obtained biodiesel has an ester content of 99.16%, while 97.35% of the free fatty acids (FFA) were converted, resulting in the product showing improved physico-chemical properties as assessed through fuel characterization tests. Reusability tests for the catalysts showed 4 reuses for acid catalyst compared to 9 reuses for base catalyst. Catalyst development costs were only $1.27/kg for activated char, while due to reuse, the prepared catalysts cost only $0.53/kg of biodiesel. Hence, the catalytic process holds great potential for commercialization if scaled up appropriately.

This paper for the first time synthesizes novel biodiesel experimentally using low-cost feedstocks of coconut oil, caustic soda, and fermented palm wine contaminated by microorganisms. The alkaline catalyzed transesterification method was used for biodiesel production with minimal glycerol. The produced biodiesel was biodegradable and effective in cleaning a shoreline oil spill experiment verified by our developed oil spill radial numerical simulator. For the first time, an adaptive neuro-fuzzy inference system (ANFIS) was hybridized with invasive weed optimization (IWO), imperialist competitive algorithm (ICA), and shuffled complex evolution (SCE-UA) to predict biodiesel yield (BY) using obtained Monte Carlo simulation datasets from the biodiesel experimental seed data. The test results indicated ANFIS-IWO (MSE = 0.0628) as the best model and also when compared to the benchmarked ANFIS genetic algorithm (MSE = 0.0639). Additionally, ANFIS-IWO (RMSE = 0.54705) was tested on another coconut biodiesel data in the literature and it outperformed both response surface methodology (RMSE = 0.72739) and artificial neural network (RMSE = 0.68615) models used. The hybridized models proved to be robust for biodiesel yield modeling in addition to the produced biodiesel serving as an environmentally acceptable and cost-effective alternative for shoreline bioremediation.