Optimization Of Biodiesel Production Research Articles

Modelling and optimisation of biodiesel production using waste cooking oil using the response surface methodology

ABSTRACT Modelling the effect of reaction time, catalyst concentration, and oil-to-methanol ratio on the waste cooking oil biodiesel was studied using response surface methodology. Biodiesel was made using three different heterogeneous catalysts. Analysis showed catalysts 2 and 3 to be significant in transesterification. However, all catalysts had second-degree significance for esterification yield. For catalysts 1 and 2 there was a clear interaction between catalyst concentration and oil-to-methanol ratio. Clear interaction was also noticed between reaction time and oil-to-methanol ratio for all catalysts. There was moderate to no interaction between the effects of time and catalyst concentrations for all catalysts. The best yield was found at lower oil-to-methanol ratios (nearly 0.02) and higher catalyst concentrations (at 10%). Reaction times close to 7 hours for catalyst 1 and close to 5 for the other catalysts were the optimum values for best yield and lowest acid value.

Evaluation of environmental parameters for optimal cell density, biomass, lipid, and biodiesel production in scenedesmus: Focus on suspension and biofilm methods

The study focused on investigating the impact of various environmental parameters on the production of Scenedesmus, a unicellular alga known for its industrial and food value. The parameters studied included production method, temperature, lighting period, light intensity, and pH, with a particular emphasis on suspension and biofilm production methods. The results highlighted optimal conditions for different aspects of production, such as cell density, biomass production, lipid production, and biodiesel production. Specifically, the findings indicated that the highest cell density was achieved at a temperature of 25 °C, light intensity of 3000 lux, lighting period of 16 h, and pH of 8. For biomass production, the optimal conditions were a temperature of 25 °C, light intensity of 3000 lux, lighting period of 18 h, and pH of 9. The greatest lipid production was observed at a temperature of 20 °C, light intensity of 4000 lux, lighting period of 18 h, and pH of 8. Moreover, the highest biodiesel production was recorded at a temperature of 25 °C, light intensity of 3000 lux, lighting period of 18 h, and pH of 8. Notably, the study found that the biofilm production method outperformed the suspension method across various parameters, including cell density, biomass production, lipid production, and biodiesel production. These results contribute to the existing knowledge of optimal conditions for microalgae production and underscore the potential of Scenedesmus in industrial and food applications.

Optimization of biodiesel production parameters for hybrid oil using RSM and ANN technique and its effect on engine performance, combustion, and emission characteristics

The increased need for renewable energy sources and growing concerns about environmental pollution has driven the need for alternative fuels (particularly biodiesel) in the transportation industry. The most used technique for producing biodiesel is transesterification, which involves the oil reacting with alcohol in the presence of a catalyst. This study looks at the usage of artificial neural network (ANN) and response surface methodology (RSM) to optimize biodiesel synthesis factors for a hybrid oil feedstock (30% cottonseed and 70% spirulina microalgae oil). The parameters that were optimized were the methanol/oil ratio, reaction time, and catalyst concentration. Cottonseed oil was combined with spirulina microalgae oil to minimize its higher free fatty acid content to less than 1% and prevent soap formation during the transesterification process. The optimal biodiesel production was 94.37%, with 106.4 minutes of reaction time, 1.612% catalyst loading, and a methanol/oil ratio of 20:1. The optimized findings, when confirmed with experiments, gave a biodiesel yield of 91.03% with an error of 3.6%. To provide vital insights into the potential environmental benefits of using this alternative fuel, the study further investigates how the optimized biodiesel blend influences engine performance and emission characteristics. Testing was done at 1500 RPM and 17.5 CR for maximum loading conditions, diesel, HBD20, and HBD fuel produced 0.2746, 0.2805, and 0.288 kg/kWh of specific fuel consumption (SFC), respectively. The CO2 emissions of HBD and HBD20 were 2.49% and 8.30% lower, respectively, than pure diesel. NOx emissions increased by 14% and 18.3%. The highest cylinder pressure was 66.87 at 363 °C.

Modelling and optimizing the transesterification process of shea butter via CD-BaCl-IL catalyst using soft computing algorithms

Shortage and environmental threats posed by fossil fuel have become a critical issue requiring searching for alternative energy sources. This study utilized clay-doped barium chloride and ionic liquid (CD-BaCl-IL) as a catalyst for optimizing biodiesel production from shea butter. 10% barium chloride and ionic liquid were blended with clay, dried, and then calcined for 4 h at 600 °C to develop the catalyst. The synthesized catalyst and the biodiesel were suitably characterized. Response surface methodology (RSM) implementing Central Composite Design (CCD) and Genetic Algorithm (GA) were employed to model and optimize the effect of the process parameters on the response. The model's capabilities were evaluated using coefficient of determination (R2) and mean square error (MSE). The second-order polynomial model is shown in the Analysis of Variance (ANOVA) with an (R2 -0.9945, Adjusted R2-0.9846, Predicted R2-0.8694) demonstrating the model's acceptance. Artificial Neural Network (ANN) and Adaptive Neurofuzzy Inference System (ANFIS) were used to assess the model's capability. The obtained statistical results - (R2 = 0.8694, MSE = 0.7035), ANN (R2 = 0.999, MSE = 0.0001026), ANFIS (R2 = 0.99, MSE = 0.000041), showed that ANFIS had the best prediction with the lowest MSE. ANFIS integrated with GA (GA-ANFIS) gave the best optimization with a biodiesel yield (96.72%) at a catalyst concentration of 4 wt%, a methanol/mol ratio of 10:1, a time of 2.5 h, a temperature of 70 °C, and an agitation speed of 400 rpm. The optimal developed biodiesel properties were successfully evaluated within the ASTM D 6751 standards.

Unveiling the innovation: Optimized biodiesel production from emerging Acer truncatum Bunge seed oil using novel and highly effective alkaline ionic liquid catalyst

Herein, three novel alkaline ionic liquids (ILs) with nitrogen-containing heterocycles were prepared via a two-step method, which were then utilized as excellent catalysts for biodiesel synthesis through transesterification of emerging Acer truncatum Bunge seed oil (ATBSO) and methanol. The alkaline ILs exhibited favorable catalytic performance, with 1-(2,3-dihydroxy)-propyl-1,5,7-triazabicyclo[4.4.0]dec-5-ene) hydroxide ([DPTD][OH]) exhibiting the highest catalytic efficiency among them. Furthermore, the effect of the independent variables and their interactions on biodiesel yield were assessed and optimized using response surface methodology (RSM). Under the optimal parameters, which consisted of a reaction temperature of 71 °C, a reaction time of 137 min, a substrate molar ratio of methanol to ATBSO of 12:1, and a catalyst loading of 1.3 wt%, the biodiesel yield reached a maximum of 97.3 %. The catalytic transesterification of ATBSO for the preparation of biodiesel exhibited an activation energy (Ea), enthalpy (ΔH), entropy (ΔS) and the Gibbs free energy (ΔG) of 35.14 kJ·mol−1, 32.37 kJ·mol−1, −178.80 J·mol−1·K−1 and 93.70 kJ·mol−1 at 343 K, respectively. It is worth noting that, after the reaction, an automatic phase separation between biodiesel and the catalyst occurred, minimizing the processes of product isolation and purification. Additionally, [DPTD][OH] exhibited favorable reusability over the four reaction cycles, providing a sustainable and environmentally friendly approach for biodiesel production. The biodiesel obtained from ATBSO demonstrated excellent physicochemical properties, such as good cold flow property and flash point, which conform to the biodiesel standards outlined in ASTM D6751 and EN 14212.

Optimization of biodiesel production in a high throughput branched microreactor

Biodiesel as a renewable and environmentally friendly fuel can be considered an alternative to fossil fuel in industries, and one of the promising approaches to developing biodiesel yield is its production in microreactors. However, the produced quantity from microreactors is limited which necessitates higher throughput microreactors to be produced, maintaining the high yield of biodiesel. Therefore, this study investigated the transesterification of waste cooking oil (WCO) with methanol in the presence of sodium hydroxide as the catalyst using a novel branched microreactor, used for higher throughput applications. Thus, a novel four-micro serpentine-based microreactor was designed and fabricated with no external tubing. Biodiesel is produced in the fabricated microreactor and the Box-Behnken Design method (BBD) in Minitab software was used to design the experiments with different operating conditions: methanol to oil molar ratio (6:1–12:1), catalyst concentration (0.5–1.5 wt%), and reaction temperature (55–65 °C) to optimize the biodiesel volume yield in the designed microreactor. The optimum biodiesel yield using GC–MS analysis was found to be 82.8 % at a methanol to oil molar ratio of 12:1, 1.5 wt% catalyst concentration, and reaction temperature of 59.4 °C while maintaining the reactants’ inlet flow rate of 20 µL/s. Production of up to 35 mL biodiesel was collected in 30 min only. In addition, the microreactor achieved up to 97 % conversion at inlet flow rates of 8.5 µL/s.

Optimizing biodiesel production from waste with computational chemistry, machine learning and policy insights: a review

AbstractThe excessive reliance on fossil fuels has resulted in an energy crisis, environmental pollution, and health problems, calling for alternative fuels such as biodiesel. Here, we review computational chemistry and machine learning for optimizing biodiesel production from waste. This article presents computational and machine learning techniques, biodiesel characteristics, transesterification, waste materials, and policies encouraging biodiesel production from waste. Computational techniques are applied to catalyst design and deactivation, reaction and reactor optimization, stability assessment, waste feedstock analysis, process scale-up, reaction mechanims, and molecular dynamics simulation. Waste feedstock comprise cooking oil, animal fat, vegetable oil, algae, fish waste, municipal solid waste and sewage sludge. Waste cooking oil represents about 10% of global biodiesel production, and restaurants alone produce over 1,000,000 m3 of waste vegetable oil annual. Microalgae produces 250 times more oil per acre than soybeans and 7–31 times more oil than palm oil. Transesterification of food waste lipids can produce biodiesel with a 100% yield. Sewage sludge represents a significant biomass waste that can contribute to renewable energy production.

Maximizing the potential of commercial zinc stearate for one-pot esterification and transesterification for high-acidity biodiesel production

Meeting the growing demand for energy while combating the adverse effects of global warming remains challenging today, and biodiesel offers a potential solution to help mitigate the impact of global warming. In this scenario, our primary goal was to optimize biodiesel production from highly acidic soybean oil using a one-pot esterification and transesterification process, addressing the challenges associated with high-acidity substrates. To start, X-ray Diffraction (XRD) guaranteed us just one phase for each commercial catalyst, and we conducted catalytic experiments to select the most suitable Zn-based material for the process, choosing zinc stearate (ZnSt2) as the best candidate. Our study demonstrated that a nano-sized zinc oxide (ZnO) catalyst, which was anticipated to be the most suitable choice, did not exhibit optimal performance. Subsequently, a Full Factorial Design of Experiments (DOE) was employed to optimize reaction parameters, specifically, the reaction temperature and the oil-to-methanol (O:M) molar ratio. The results consistently showed that increased O:M ratio and temperature promoted enhanced fatty acid methyl esters (FAME) production and reduced acidity. Then, experiments were conducted to maximize FAME production and minimize free fatty acid (FFA) content. The results showed that increasing the catalyst concentration from 5 wt% to 10 wt% did not significantly impact FAME production or acidity reduction. Also, while increased methanol should theoretically enhance FAME production and reduce acidity, the results were inconsistent across all experiments. Excess methanol interfered with glycerol separation, leading to decreased FAME yield. Thus, this study underscores the complexity of biodiesel production and highlights the importance of selecting suitable catalysts and optimizing process parameters.

Optimization of biodiesel production from coconut oil using a bifunctional catalyst derived from crab shell and coconut shell

The utilization of renewable biomass resources for biofuel production has gained widespread popularity as an effective means of converting waste into a valuable resource. This study investigated the optimization of biodiesel production from coconut oil (CO) using a bifunctional catalyst derived from crab shell and coconut shell. The catalyst underwent characterization through Fourier transform infrared spectroscopy, scanning electron microscopy, X-ray diffraction, and Brunauer-Emmett-Teller. The acid precursor for the bio-based bifunctional catalyst was created from carbonized and sulfurized coconut shell, while the base precursor was obtained from calcined and KOH-treated crab shell. The experimental design was optimized using Box-Behnken design for the simultaneous esterification and transesterification of CO. Response surface methodology was employed to model and optimize the process. Under the determined ideal conditions, which included a methanol to oil ratio of 16.75:1, a 1.00% catalyst loading, a temperature of 58.19 °C, and a reaction time of 78.76 minutes, a CO methyl ester yield of 85.73% was achieved under experimental conditions. This yield closely aligned with the predicted range of 85.84% as per the model. The resulting methyl ester (biodiesel) obtained under these optimized conditions exhibited physicochemical properties well within the requirements specified by ASTM D6751 set by the International Organization of Standardization.

Evaluation of fuel properties for possible biodiesel output based on the fatty acid composition of oleaginous plants and microalgae

In the past decade, there has been a significant rise in sustainable biomass based biofuel production to address energy needs while mitigating environmental impacts. Traditionally, bioethanol was used for biofuel production, but concerns over food security and environmental preservation have led to growing interest in alternative sources such as neutral lipids from vegetable oil and microalgae for biodiesel production. This research paper evaluates the potential of various oleaginous plants and microalgae as feedstocks for biodiesel production, with a focus on their fatty acid composition and its impact on biodiesel properties. The study examines the fatty acid profiles of 43 different plant and microalgae species and employs various equations to estimate key physical properties of biodiesel. Additionally, the communication compares these properties to International Biodiesel Standards (EN 14214 and ASTM D6751–08) to assess the suitability of the derived biodiesel for commercial use. It is impossible to describe a single composition that is optimal in terms of all essential fuel properties due to the opposing effects of some structural features of the Fatty Acid Methyl Esters (FAME). However, biodiesel should contain relatively low concentrations of both long chain saturated and polyunsaturated FAME to ensure adequate efficiency in terms of low temperature operability and oxidative stability. The results reveal significant variations in properties amongst different feedstocks, highlighting the importance of feedstock selection in biodiesel production. The study also establishes correlations between various fuel properties, providing valuable insights in to optimizing biodiesel production processes, which will be of great use to researchers, engineers, and stakeholders involved in biodiesel production.

Optimization and kinetic study of biodiesel production from Jatropha curcas oil in supercritical methanol environment using ZnO/γ-Al2O3 catalyst

AbstractIn this study, the conversion of crude Jatropha curcas oil into biodiesel through transesterification was investigated in the presence of heterogeneous solid catalysts under supercritical methanol environment. The principal impetuses catalyzing the expansion in optimal biodiesel production are primarily attributed to the increasing demand for sustainable energy sources, the availability of raw materials, and innovations in production methodologies. To maintain the optimization, 6 wt% and 10 wt% of zinc oxide (ZnO) were incorporated into gamma-alumina (γ-Al2O3) through a wet impregnation method followed by calcination at 900 °C. Furthermore, the study examined the effect of alcohol/oil molar ratio, reaction temperature, and reaction time on the process to achieve maximum biodiesel production. The study revealed that a catalyst consisting of 10 wt% ZnO on γ-Al2O3 exhibited exceptional performance with a biodiesel yield of 95.64% under the reaction conditions of a molar ratio of 1:40 oil to methanol, a temperature of 300 °C, a pressure of 9 MPa, and a residence time of 3 min compared to the yield of 100% under same condition at residence time of 9 min. After thorough investigation, the kinetics of the catalytic transesterification reaction were elucidated, and suitable kinetic parameters were proposed.

Response surface methodology for optimization of biodiesel production by the Penicillium commune NRC 2016 and its mutants

AbstractWith increasing energy requirements and limited fuel resources, finding cheap renewable sources is essential. The objective of our current economic study is to enhance biodiesel production from the Penicillium commune, NRC 2016. Four mutagenic agents were used to improve the lipid production from P. commune NRC 2016: gamma radiation, ethyl methanesulfonate (EMS), ethidium bromide (Et Br), and sodium azide (NaN3). The Inter-Simple-Simplece Repeats molecular (ISSR) marker was used to compare the wild type of P. commune NRC 2016 and the resulting mutants. The results showed a major difference between the wild type and its mutants. Response surface methodology was used to optimize the culture conditions for lipid production by P. commune NRC 2016, and the induced mutants used hydrolysate that was produced from bagasse using Bacillus cereus 3SME. The maximum lipid content (g/l) for P. commune NRC 2016, P. commune NRC 2016–1, P. commune NRC 2016–2, and P. commune NRC 2016–3 were 2.01, 2.55, 1.71, and 2.27, respectively. Gas chromatographic analysis was used for biodiesel produced from P. commune NRC 2016 wild type, and its mutants were mainly C16–C18, which is suitable for transesterification. The physical properties, such as density, viscosity, cloud point, pour point, and cetane number, of the biodiesel from P. commune NRC 2016 and its mutants were similar to those of standard biodiesel and could be applied on a large scale. The biodiesels produced through P. commune NRC 2016 and its mutants can be utilized on a broad scale as eco-friendly products obtained from a low-cost carbon source.

A Comprehensive Analysis of Oil Extraction Technologies for Optimized Biodiesel Production

There is a critical need for energy diversification due to over depended on fossil fuel and its daunting challenges. These impediments linked with fossil fuels have stirred the search for another energy sources and biodiesel is one of the potential alternatives. Biodiesel is renewable, non-toxic, environmental-friendly and an economically viable choice to solve the diminishing fossil fuels and its harmful environmental effect. It can be made from seeds oil plant, vegetable oils, animal fats, waste oils and algae. Here are various means for the production of the biodiesel oil which comprises; mechanical, chemical/solvent and enzymatic oil extraction methods etc. Report from the open literatures revealed that, all the extraction methods have its own advantages and disadvantages but in all, oil expeller machine which is based on mechanical means of extracting oil from the common wastage seeds oil plant prove to be efficient especially for large scale extraction. Thus, for efficient oil extraction from wastage seeds oil plant, oil expeller machine is appropriate. This research seeks to discuss an improve ways of maximum oil yield with an expeller machine from the wastage seeds oil plant commonly available in our environment.

Response Surface Methodology Process Optimization of Biodiesel Production from Castor Seed Oil

The increasing demand for energy and the depletion of fossil fuel resources has led to the search for an alternative energy source. The search for such alternative fuel sources has oriented biodiesel synthesis as the ultimate alternative energy resource of the future. The purpose of this study was to produce castor oil and optimize biodiesel production using full factorial central composite design (CCD) through the response surface methodology (RSM) approach. The castor oil was extracted using a mechanical press, and free fatty acids were reduced with acid esterification and biodiesel produced through the transesterification process using homogeneous catalysts. The physicochemical properties of extracted castor oil and biodiesel including density, kinematic viscosity, saponification number, free fatty acid, acid number, cetane number, and iodine number were determined. The ideal conditions for producing biodiesel from castor oil are anticipated to be a reaction period of 105 min at a temperature of 50°C, a catalyst loading weight of 1.5%, and a methanol-to-oil ratio of 5 : 1. The biodiesel yield obtained was 95.0%, and the results of the measured parameters of biodiesel were compared with the international standards of the European norms (EN14214) and the American Society Test Material (ASTM) D6751. The weight composition of both fatty acid and methyl ester was determined by gas chromatography-mass spectroscopy (GC-MS). The study concluded that the results of this research are beneficial in optimizing the parameters for making biodiesel from extracted castor oil.

Optimization of microwave-assisted extraction in the purification of triglycerides from non-edible crude Calophyllum inophyllum oil as biodiesel feedstock using artificial intelligence

Crude nyamplung Calophyllum inophyllum is a potential non-edible feedstock for biodiesel production. Calophyllum Inophyllum oil (CCIO) is a non-edible oil that has a high content of triglyceride (TG) and free fatty acid (FFA). This study aims to optimize microwave-assisted power and extraction time of triglyceride purification from C. inophyllum crude oil for biodiesel. This work deployed Artificial Intelligence (AI) algorithms consisting of eight Machine Learning (ML) algorithms and found the most accurate model, then optimized using the Particle Swarm Optimization (PSO) algorithm.The result of machine learning modelling Random Forest achieved higher accuracy in R-Square and lower Mean Square Error (MSE) than any other models. Overall, in R-Square average across all variables was 0.949 ± 0.026 and the MSE average of 0.097 ± 0.068. This result can be interpreted as a mean deviation between the predicted value and an accurate value of less than 0.1 for all variables. The optimum of the TG compound resulted in the power of 462.3 W and time of 39.12 min that equalled at 84.02% and FFA equalled at 6.92%. The TG have increased by 11% from the reference range, which states conventional methods from crude oil. Comparison with the MAE method has a minimum fitness value difference of 0.0006 but has a smaller accuracy of less than 1%. Implementing this prediction and optimization method can shorten the extraction time by 5.8 min and reduce energy consumption or system work by 130 kJ. This method can be used for input parameter model prediction and parameter optimization in purification for biodiesel feedstock. Further research can be carried out using other artificial intelligence methods to optimize biodiesel production.

Experimental and CFD simulation studies of biodiesel production in an in-house Tesla-shaped microreactor

Continuous flow microreactors have been shown to be effective for biodiesel production, and the Tesla-shaped microreactor, in particular, is one of the proposed microreactors for this application. However, its applicability in the industry is still limited. Therefore, comprehensive simulation studies that agree with the real processes need to be performed to allow a deep understanding of the process. A 2D CFD simulation model is constructed in COMSOL Multiphysics software to study the performance of a Tesla-shaped microreactor fabricated in-house- for biodiesel production from waste cooking oil (WCO). The model is thoroughly analyzed and validated experimentally at different operating conditions. The percentage yield values resulting from the simulation were found to be 84.13% at a temperature of 50 °C, 90.79% at a temperature of 55 °C, and 94.85% at a temperature of 60 °C, which deviated from the experimental values by 2.73%, 1.15%, and 1.98%, respectively. On the other hand, an alcohol-to-oil molar ratio of 12:1 resulted in a simulation percentage yield of 94.85% which deviates from the experimental values by 1.98%, while at a molar ratio of 9:1, the simulation yielded 93.67% with a deviation of 3.33% from the experimental results. At a lower ratio of 6:1, the simulation percentage yield was found to be 69.89%, and it deviated by 18.82% from the experimental results. This study presents a novel combination of simulation and experimental validation for the Tesla-shaped microreactor in biodiesel production from waste cooking oil., which is a topic with limited existing research although it significantly contributes to understanding the process at different operating conditions. The high agreement between simulation and experimental results demonstrates the accuracy and suitability of the simulation for studying the% conversion, and potential investigation such as the molar flow rate variations, and reaction rates under different conditions. This approach offers a cost-effective and efficient solution for optimizing biodiesel production, reducing the need for extensive experimental trials, and saving significant time and effort.

Optimization of Methanolysis of Used Cooking Oil by the Taguchi Experimental Design Approach

AbstractThe goal of this study was to look into the catalytic activity of KOH‐modified CaO from eggshell as catalyst for the optimization of biodiesel production from used cooking oil (UCO), applying the Taguchi approach. The strong base catalyst (K/CE) was formulated by doping KOH on calcined chicken eggshell at various quantities (0–2.5 g), where 2 g of KOH doped on 5 g of calcined eggshell (2K/CE) and recalcined at 400 °C was found to represent the best catalyst formulation conditions. The optimal catalyst resulted in the maximum UCO biodiesel (UCOB) yield of 91.92 % at 70 °C for 1 h, using a 2K/CE dosage of 0.5 wt % and a methanol/UCO molar ratio of 15:1. The physicochemical properties of the optimal UCOB sample were in accordance with ASTM D6751 specifications, and gas chromatography‐mass spectrometry analysis confirmed the presence of methyl esters at an amount of 97.65 wt %.

Modelling and optimization of biodiesel production from waste fish oil using nano immobilized rPichiapastoris whole cell biocatalyst with response surface methodology and hybrid artificial neural network based approach

In this study, zinc oxide (ZnO) nano particle immobilized recombinant whole cell biocatalyst (rWCB) was used for bioconversion of waste fish oil in to biodiesel in a lab scale packed bed reactor (PBR). Central composite design and hybrid artificial neural network (ANN) models were explored to optimize the production of biodiesel. Developed rWCB exhibited maximum lipase activity at 15 % (v/v) of glutaraldehyde concentration and 6 % (w/v) of ZnO nanoparticles at pH of 7. Maximum biodiesel yield reached about 91.54 ± 1.86 % after 43 h in PBR using hybrid ANN model predicted process conditions of 13.2 % (w/v) of nano immobilized rWCB concentration and 4.7:1 of methanol to oil ratio at 33 °C. Importantly, developed nano immobilized rWCB was adequately stable for commercialization. Thus, production of biodiesel from waste fish oil using ZnO nano immobilized rWCB could become potential candidate for commercialization.

Using solar microreactors and photocatalysts to synthesize biodiesel

This paper investigates the transesterification of waste cooking oil using TiO2, CuO, and GO as catalysts in solar plain and helical glass microreactors. Catalyst properties were determined through XRD, SEM, and FT-IR analyses. Response surface methodology was employed to optimize biodiesel production, with GO catalyst and helical microreactor proving most effective due to their unique geometry. The highest biodiesel purity was achieved with GO at 99.98%, followed by TiO2 at 95.78% and CuO at 93.55%, all with a 3% catalyst dose, 200 s residence time, and oil-to-methanol volume ratio of 2. The study utilized solar energy and glass microreactors, resulting in a 94% reduction in energy consumption.

Process Optimization of Biodiesel Production Using Waste Snail Shell as a Highly Active Nanocatalyst

In this work, we reported the transesterification of soybean oil (SO) to biodiesel using a basic CaO nanocatalyst produced by sequential calcination, hydration, and dehydration of waste snail shells. Response-surface methodology (RSM) and a central composite design (CCD) were used to predict several optimization parameters. 1H-NMR confirmed that 98.5% of the SO was transformed into methyl ester biodiesel. Under the optimal reaction parameters of catalyst loading of 6 wt. %, methanol to oil molar ratio of 8 : 1, reaction duration of 3 h, and temperature of 70°C, an excellent biodiesel yield of 96.1% was obtained. The transesterification of SO to biodiesel displayed a significantly low activation energy (30.45 kJ mol-1), whereas, the turnover frequency of the transesterification reaction was found to be 0.0063 mol g-1 h-1. The catalyst showed excellent stability and was consecutively used for six cycles without a significant decline in catalytic activity. Based on life cycle cost analysis (LCCA), the estimated cost for producing 1 kg of biodiesel in this study comes out to be just $0.935, signifying its strong potential for widespread commercial use.