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The increase of motor vehicles results in a rapid increase in fuel supply and generates high emissions, which then affects the environment and human health in general. Replacement of nonrenewable fuels can be achieved by using alternative energy sources. Viewing fuel properties and production routes, biodiesel is deemed as one preferred alternative fuel for diesel engines. This work focuses on biodiesel production using waste cooking oil through a catalyst made of mixed multi-fruits' peel ash and titanium dioxide nanoparticles through a transesterification process. Further, the produced biodiesel was used to evaluate the engine performance by analyzing brake thermal efficiency and brake-specific fuel consumption. Emission characteristics due to biodiesel combustion, namely carbon monoxide and nitrogen oxides, was our main focus in this study. Both engine performance and emissions levels were optimized through Taguchi L16 orthogonal array. Highest brake thermal efficiency of 36.19% was achieved by the influence of 450°C of calcination temperature, 30°C of reaction temperature, 4% of catalyst loading, and 3 hr time of reaction. The lowest brake-specific fuel consumption obtained is 0.23 kg/kWh by involving 300°C of calcination temperature, 60°C of reaction temperature, 4% of catalyst loading, and 5 hr time. The statistical analysis based on ANOVA shows that the studied parameters does contribute to the developed regression model. In emission analysis, calcination temperature greatly influenced both CO and NOx. [ABSTRACT FROM AUTHOR]

Abstract In this study, a novel modeling approach (artificial neural networks (ANN) and ant colony optimization (ACO)) was used to optimize the process variables for alkaline-catalyzed transesterification of CI40CP60 oil mixture (40 wt% of Calophyllum inophyllum oil mixed with 60 wt% of Ceiba pentandra oil) in order to maximize the biodiesel yield. The optimum values of the methanol-to-oil molar ratio, potassium hydroxide catalyst concentration, and reaction time predicted by the ANN-ACO model are 37%, 0.78 wt%, and 153 min, respectively, at a constant reaction temperature and stirring speed of 60 °C and 1000 rpm, respectively. The ANN-ACO model was validated by performing independent experiments to produce the CI40CP60 methyl ester (CICPME) using the optimum transesterification process variables predicted by the ANN-ACO model. There is very good agreement between the average CICPME yield determined from experiments (95.18%) and the maximum CICPME yield predicted by the ANN-ACO model (95.87%) for the same optimum values of process variables, which corresponds to a difference of 0.69%. Even though the ANN-ACO model is only implemented to optimize the transesterification of process variables in this study. It is believed that the model can be used to optimize other biodiesel production processes such as seed oil extraction and acid-catalyzed esterification for various types of biodiesels and biodiesel blends. Graphical abstract Image 1 Highlights • CICPO is a potential feedstock for biodiesel production. • ANN-ACO is a reliable tool to optimize the transesterification process variables. • Methanol-to-oil molar ratio has the most significant effect on the CICPME yield. • The optimum CICPME yield predicted by the ANN-ACO model is 95.87%. • The optimum CICPME yield obtained from independent experiments is 95.18%. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Biodiesel is produced from waste cooking oil and Calophyllum inophyllum oil. • The optimum process parameters maximize the WC70CI30 biodiesel yield (94.12%). • The WC70CI30 biodiesel has high oxidation stability (22.4 h). • The WC70CI30 biodiesel has good cold flow properties comparable to diesel. • The WC70CI30 biodiesel has physicochemical properties superior to WC biodiesel. Abstract Recycling waste cooking vegetable oils by reclaiming and using these oils as biodiesel feedstocks is one of the promising solutions to address global energy demands. However, producing these biodiesels poses a significant challenge because of their poor physicochemical properties due the high free fatty acid content and impurities present in the feedstock, which will reduce the biodiesel yields. Hence, this study implemented the following strategy in order to address this issue: (1) 70 vol% of waste cooking vegetable oil blended with 30 vol% of Calophyllum inophyllum oil named as WC70CI30 used to alter its properties, (2) a three-stage process (degumming, esterification, and transesterification) was conducted which reduces the free fatty acid content and presence of impurities, and (3) the transesterification process parameters (methanol/oil ratio, reaction temperature, reaction time, and catalyst concentration) were optimized using response surface methodology in order to increase the biodiesel conversion yield. The results show that the WC70CI30 biodiesel has favourable physicochemical properties, good cold flow properties, and high oxidation stability (22.4 h), which fulfil the fuel specifications stated in the ASTM D6751 and EN 14214 standards. It found that the WC70CI30 biodiesel has great potential as a diesel substitute without the need for antioxidants and pour point depressants. [ABSTRACT FROM AUTHOR]

In this study, microwave irradiation-assisted alkaline-catalysed transesterification was used to produce W70CI30 biodiesel from a mixture of waste cooking oil and Calophyllum inophyllum oil. The methanol/oil ratio, catalyst concentration, stirring speed, and reaction time were optimized using response surface methodology based on the Box-Behnken experimental design in order to maximize the biodiesel yield. The quadratic response surface regression model was used to predict the biodiesel yield. It is found that the optimum methanol/oil ratio, catalyst concentration, stirring speed, and reaction time are 59.60 (v/v)%, 0.774 (w/w)%, 600 rpm, and 7.15 min, respectively, and the predicted biodiesel yield is 97.40%. Experiments were conducted using the optimum process parameters and the average biodiesel yield is 97.65%, which is in excellent agreement with the predicted value. The physicochemical properties of the W70CI30 biodiesel produced using the optimum process parameters were measured and it is found that the biodiesel has significantly higher oxidation stability (18.03 h) compared with the waste cooking oil biodiesel (4.61 h). In addition, the physicochemical properties and cold flow properties of the biodiesel fulfil the fuel specifications stipulated in the ASTM D6751 and EN 14214 standards. It can be concluded that microwave irradiation-assisted transesterification is effective to boost the biodiesel yield and produce biodiesel of superior quality. In addition, this method significantly reduces the reaction time of the transesterification process to 9.15 min and the process is energy-efficient. It is believed that the findings of this study will be beneficial for microwave irradiation-assisted biodiesel synthesis on the industrial scale. [ABSTRACT FROM AUTHOR]

Biofuels productions from microalgae received wide attention recently and have high potential to replace fossil fuels. This paper served as a platform to critically review current production technologies of microalgae, ranging from cultivation, harvesting, extraction and several biofuels conversion processes. In addition, due to the high photosynthetic efficiency of microalgae, mass cultivation of microalgae is believed to be able to efficiently reduce the carbon dioxide emission to atmosphere and thus, reducing the impact of global warming. This is because microalgae have high growth rate and is able to develop maximum of 70% of lipid content within their cells depending on species. Apart from that, microalgae have the ability to survive under harsh condition and occupied smaller cultivation land area than other land crops. The harvested microalgae biomass can be used for electrical generation, while its crude lipid can be used as transportation fuel as it has 80% average energy content of petroleum. In the present paper, a detailed discussion to produce biodiesel, fuel gas, bio-oil, methane, hydrogen and alcohol from microalgae biomass are also included. Besides, updated research, challenges and the way forward of microalgae biofuels are also presented. In future, biofuels production from microalgae can be economical viable at some scale, which is then profitable in terms of economics and also environment. [ABSTRACT FROM AUTHOR]

Waste cooking oil is a sustainable feedstock that can be utilised to produce biojet fuel via the hydrodeoxygenation process. However, the need for hydrogen for the hydrodeoxygenation process incurs high cost. In the present work, a type of bimetallic catalyst that can deoxygenate and selectively crack free fatty acids under hydrogen-free conditions was developed. The NiCo/TiO 2 catalyst was prepared via the impregnation of varying amounts of Ni and Co salts onto TiO 2. Optimisation of the production conditions was performed via response surface methodology based on the Box-Behnken experimental design to maximise the deoxygenation and biojet fuel yield. A maximum deoxygenation yield of 83.13 % with 44.5 % biojet fuel selectivity was obtained from the experiment and optimisation based on Box-Behnken design (R2 > 0.9). Incorporation of Ni and Co onto TiO 2 reduced the surface area of the catalyst, but active metal dispersion significantly improved the deoxygenation performance and biojet fuel selectivity. The viscosity, flash point, freezing point and net heat of combustion value of the liquid product were within the jet fuel standard specifications. Overall, the study shows the potential of bimetallic NiCo/TiO 2 catalyst in waste cooking oil deoxygenation for biojet fuel production. • Deoxygenation occurs primarily through the decarboxylation pathway. • Catalyst concentration dominates as primary factor in regression model analysis. • Optimised parameters produced 83.13 % deoxygenation with 44.5 % biojet fuel selectivity. • Deoxygenated hydrocarbons show suitable biojet fuel properties. [ABSTRACT FROM AUTHOR]

Catalytic reactions in producing biofuels often face issues such as low product yield, low selectivity to preferred products and serious environmental issues which leads to the exploration of green technologies. Microwave technology is one of the green technologies that is widely applied in the field such as medical, food, signal processing or navigation, and has been reviewed for its potential in the catalytic reactions for biofuel production. With the application of microwave technology, its unique heating mechanism consists of magnetic field energy and electric field energy that enables the selective heating of materials, allowing rapid reaction and enhancement of catalytic performance of catalysts. In general, this review has discussed on the fundamentals and mechanisms of microwave technology with an in-depth discussion on the application of microwave-absorbing catalysts for biofuel production, especially in ammonia synthesis, bio-oil and 5-HMF production as well as methanation. Lastly, the challenges and future prospect of microwave-absorbing catalysts are included as well. [ABSTRACT FROM AUTHOR]

Microwave plasma as a potential tool to convert CO 2 has been extensively studied in recent years. A simulated study on the plasma parameters via the variation of the operating pressure of a microwave plasma model has been performed in this study. The establishment of the model was based on the finite element method to analyse the spatial distribution of plasma parameters in the plasma torch over a period of time. Plasma parameters such as electron potential, density, and temperature were investigated at three different pressures, and the growth of electron potential and density were associated with time. The distribution of molecular ions was observed to be located more on the enter port of the microwave or waveguide near the location of the magnetron at the initial stage. The electron density was found to be constant after it reached maximum value for all the determined pressures. However, the electron temperature behaved differently as compared to the electron potential and density, the distribution of high electron temperature did not enhance during the processing time. The analysis of microwave plasma parameters is beneficial for plasma reactor designing, particularly for CO 2 conversion. • Argon is used due to the low threshold for energetic particle production. • Low operating pressure leads to the formation of plasma with lower electron density. • Electron density, temperature and electrical potential are affected by gas pressure. • Electric field mostly distributed at the connection of waveguide and quartz tube. [ABSTRACT FROM AUTHOR]

[Display omitted] • Rice bran biodiesel is produced using ultrasound and infrared radiation. • ANN-GWO is a reliable tool to optimize the transesterification process. • The predicted rice bran yield is 98.16%. • The optimum yield obtained from the experiment is 97.74%. • The FAME content of the optimized biodiesel is 95%. A system combining ultrasound and infrared radiation was used to increase the chemical reactions between incompressible reactants by enhancing their mass transfers with the aim to reduce the energy usage and reaction time. In this study, biodiesel from RBO was produced via transesterification, and the process variables were optimized using the combination of ANN and GWO algorithm. Process parameters considered in this study are ratio of methanol to oil, catalyst concentration, and reaction time. Based on the ANN-GWO algoritm used, the optimum conditions for the process parameters were (1) methanol to oil ratio: 60%, (2) concentration of catalyst: 1 wt%, (3) time: 7.76 min, leading to the metyl ester yield of 98.16 wt%. The algoritm was verified by conducting a triplicate independent experiments using the suggested optimum values, resulting in an average methyl ester yield of 97.74 wt%. Subsequently, properties of rice bran biodiesel were compared to ASTM D6751 and EN 14214 standards, and the obtained values met both the standards. [ABSTRACT FROM AUTHOR]

This study focuses on the optimization of ultrasound-assisted oil extraction from Carica candamarcensis seed using response surface methodology. The process parameters considered were extraction time (30–60 min), ultrasound amplitude level (20–40%), and solvent to seed ratio (10–20 mL/g). These were varied as suggested by Box-Behnken experimental model. Optimum values of these process parameters were given by the regression model, with the corresponding extraction yield. The model was validated experimentally to ensure its reliability. Physicochemical properties and fatty acid compositions of the extracted oil were evaluated accordingly. Furthermore, the extracted oil was then converted into biodiesel via ultrasound-assisted transesterification, using potassium hydroxide as the catalyst. FAME contents of the produced biodiesel were measured using gas chromatography. In addition, physicochemical properties of the biodiesel were also determined accordingly. Hence, findings from this study would be beneficial in further exploration on the usage of Carica candamarcensis as a potential feedstock for biodiesel production. [Display omitted] [ABSTRACT FROM AUTHOR]

This review provides the recent advances in triglyceride catalytic pyrolysis using heterogeneous dolomite catalysts for upgrading biofuel quality. The production of high-quality renewable biofuels through catalytic cracking pyrolysis has gained significant attention due to their high hydrocarbon and volatile matter content. Unlike conventional applications that require high operational costs, long process times, hazardous material pollution, and enormous energy demand, catalytic cracking pyrolysis has overcome these challenges. The use of CaO, MgO, and activated dolomite catalysts has greatly improved the yield and quality of biofuel, reducing the acid value of bio-oil. Modifications of the activated dolomite surface through bifunctional acid–base properties also positively influenced bio-oil production and quality. Dolomite catalysts have been found to be effective in catalyzing the pyrolysis of triglycerides, which are a major component of vegetable oils and animal fats, to produce biofuels. Recent advances in the field include the use of modified dolomite catalysts to improve the activity and selectivity of the catalytic pyrolysis process. Moreover, there is also research enhancement of the synthesis and modification of dolomite catalysts in improving the performance of biofuel yield conversion. Interestingly, this synergy contribution has significantly improved the physicochemical properties of the catalysts such as the structure, surface area, porosity, stability, and bifunctional acid–base properties, which contribute to the catalytic reaction's performance. [ABSTRACT FROM AUTHOR]

Global warming in relation to fossil fuel pollution and their environmental impacts have become a major global concern. Biodiesel has entered the scene as an alternative fuel but it also generated controversy associated with increased residual fuel, increased acidity, oxidation, and corrosion. The main objective of this study was to observe the corrosion behavior of the mild steel immersed in J50C50 biodiesel-diesel fuel blends for up to 800 h at ambient temperature. The results showed corrosion rate at 800-h immersion are 0.0103, 0.0044, 0.0117, 0.0155, 0.2283 and 0.02524 mm/year, respectively, for B0, B10, B20, B30, B40 and B50. Mild steel coupon surface observation using SEM showed corrosion attacks are characterized by round holes on the metal surface. The addition of J50C50 biodiesel into diesel fuel accelerated the corrosion rate and acid value. Overall, corrosion observations conducted on mild steel suggested J50C50 biodiesel-diesel fuel blend is more corrosive compared with diesel fuel. [ABSTRACT FROM AUTHOR]

Driven by the depletion of fossil fuels, there is a pressing need for clean alternative fuels for energy applications. Biomass pyrolysis, utilizing biomass as a feedstock, has emerged as a promising sustainable alternative. However, the presence of oxygen-containing compounds and high acidity in the biofuel produced through pyrolysis necessitate further upgrading. Mesoporous catalysts, with their high surface area, tunable pore size, and catalytic activity, have shown great potential in improving the quality of biofuels derived from biomass pyrolysis. This review explores the recent advancements and challenges associated with employing mesoporous catalysts in the upgraded pyrolysis of biomass for biofuel production. It delves into the various types of mesoporous catalysts utilized and the catalytic mechanisms at play during the upgrading process. The review further discusses the progress made and the challenges encountered in the application of mesoporous catalysts. Strategies to enhance catalyst stability and activity, such as catalyst modification and the use of co-catalysts, are also examined. Additionally, the review emphasizes the critical properties of the mesoporous structure for optimal catalyst design. By providing a comprehensive overview of the current state of knowledge, this review serves as a valuable resource for researchers and practitioners interested in the development and application of mesoporous catalysts in pyrolysis for biofuel production. It highlights the promise of mesoporous catalysts while also acknowledging the challenges that need to be addressed for their successful implementation. • Mesoporous structures offer broad applications in catalyst design, particularly for enhancing biofuel quality. • Mesoporous structures can be combined with other materials like metals, metal oxides, and bimetallic compounds, expanding their potential applications. • Incorporating mesopores in hierarchical structures improves uniformity of metal distribution, allows for higher metal loading, and provides a larger reaction area, enhancing catalytic activity. • The use of mesoporous catalysts in pyrolysis upgrading reduces carbon formation, increasing biofuel heating value. [ABSTRACT FROM AUTHOR]

[Display omitted] • Ragi tapai and Chaetomorpha co-culture for bio-SA production and biogas upgrading. • Optimal condition: microwave dose1.45 W/g, Chaetomorpha ratio 0.9 & pH value 7.8. • Optimal biomethane and bio-SA production: 85.7 % & 0.65 g/L. • Microwave pretreatment enhance the proposed process, up to 2.0 W/g. This study represents the first investigation of bio-succinic acid (bio-SA) production with methane enrichment using carbon-dioxide-fixating bacteria in the co-culture of ragi tapai and macroalgae, Chaetomorpha. Microwave irradiation has also been introduced to enhance the biochemical processes as it could provide rapid and selective heating of substrates. In this research, microwave irradiation was applied on ragi tapai as a pre-treatment process. Factors such as microwave irradiation dose on ragi tapai, Chaetomorpha ratio in the co-culture, and pH value were studied. Optimal conditions were identified using Design-Expert software, resulting in optimal experimental biomethane and bio-SA production of 85.7 % and 0.65 g/L, respectively, at a microwave dose of 1.45 W/g, Chaetomorpha ratio of 0.9 and pH value of 7.8. The study provides valuable insights into microwave control for promoting simultaneous methane enrichment and bio-SA production, potentially reducing costs associated with CO 2 capture and storage and biogas upgrading. [ABSTRACT FROM AUTHOR]

High energy demand from the market due to the rapid increment of the human population worldwide has urged society to explore alternatives to replace non-renewable energy. Renewable diesel produced from biomass could be the next potential energy source for its high stability, long-term storage, and comparable performance with diesel fuels. In producing renewable diesel, the application of catalyst is essential, and the catalyst support is synthesized with the catalyst to enhance the reaction rate and catalytic properties. In this review, the type of catalyst support will be reviewed along with a brief introduction to biodiesel and renewable diesel production, especially focusing on zeolites as the catalyst support. The enhancement of catalyst support will be critically discussed to improve the catalytic performance of support in renewable diesel production and important aspects such as the stability and recyclability of the supported catalyst are included. The application of the supported catalyst in increasing the selectivity and yield of renewable diesel is significant, in which the catalytic properties depend on the interaction between catalyst and catalyst support. The supported catalyst as a favorable substance to assist in enhancing renewable diesel yield could lead to a sustainable and greener future for the biofuel industry in Malaysia. [ABSTRACT FROM AUTHOR]

To reduce dependency on fossil fuel, alternative fuel may be considered either to replace fossil fuel or to improve the characteristics of fossil fuel. Ethanol is one of the alternative fuels that has been used as an additive to gasoline fossil fuel in many countries, particularly for spark ignition engine system. This research aims to investigate the effect of ethanol and gasoline blending on the performance of a non-road small single cylinder engine. Ethanol–gasoline blends of different concentrations are considered in this paper, to experimentally compare their performances, under varying engine speed but constant engine load. The experimental results showed that the addition of ethanol to gasoline has improved the overall engine performance. High ethanol–gasoline fuel blend (E40) is suitable for low engine speed, while low ethanol–gasoline fuel blend (E10) can replace the neat gasoline without modification as their performance is very identical. [ABSTRACT FROM AUTHOR]

It is known that biodiesel and bioethanol are viable alternative fuels to replace diesel for compression ignition engines. In this study, an experimental investigation is carried out to evaluate the performance and exhaust emissions of a single cylinder diesel engine fuelled with biodiesel-bioethanol-diesel blends. The engine performance parameters evaluated are the brake specific fuel consumption and brake thermal efficiency whereas the exhaust emission parameters evaluated are carbon monoxide, nitrogen oxide, and smoke opacity. Kernel-based extreme learning machine is used to predict the engine performance and exhaust emission parameters of the fuel blends at full throttle conditions. Based on the experimental results, the brake specific fuel consumption is lower while the brake thermal efficiency is higher for the biodiesel-bioethanol-diesel blends. The carbon monoxide emissions and smoke opacity are also lower for these fuel blends. The mean absolute percentage error of the brake specific fuel consumption, brake thermal efficiency, carbon monoxide, nitrogen oxide, and smoke opacity is 1.363, 1.482, 4.597, 2.224, and 2.090%, respectively. Thus, it can be concluded that K-ELM is a reliable method to estimate the engine performance and exhaust emission parameters of a single cylinder compression ignition engine fuelled with biodiesel-bioethanol-diesel blends to reduce fuel consumption and exhaust emissions. [ABSTRACT FROM AUTHOR]

Bioethanol can potentially replace gasoline because of its lower exhaust emissions. The purpose of this study was to investigate the engine performance and exhaust emissions of Manihot glaziovii bioethanol–gasoline blends at different blend ratios (5%, 10%, 15%, and 20%). Tests were performed on a single-cylinder, four-stroke spark-ignition engine with engine speed was varied from 1600 to 3400 rpm, and the properties of the Manihot glaziovii bioethanol–gasoline blends were measured and analysed. The vapour pressure increased for fuel blends with low concentrations of bioethanol due to the oxygen within the bioethanol molecules and the contribution of the flame speed which can enhance the combustion and improved the engine efficiency. In addition, the engine torque, brake power, and brake-specific fuel consumption (BSFC) were measured, as well as the carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide emissions. For a fuel blend containing 20% bioethanol at an engine speed of 3200 rpm, the BSFC decreased, with maximum values of 270.7 g/kWh. The CO and HC emissions were lower for the Manihot glaziovii bioethanol–gasoline blends. In addition, an extreme learning machine (ELM) model was developed for application in the automotive and industrial sectors. This tool reduces the cost, time, and effort associated with experimental data. The blend ratio of the bioethanol–gasoline blends and the engine speed were used as the input data of the model, and the engine performance and exhaust emissions parameters were used as the output data. The coefficient of determination ( R 2 ) was within a range of 0.980–1.000, and the mean absolute percentage error was within a range of 0.411%−2.782% for all the parameters. The results indicate that the ELM model is capable of predicting the engine performance and exhaust emissions of bioethanol–gasoline fuel blends. [ABSTRACT FROM AUTHOR]

The depletion of oil reserves as well as environmental pollution resulting from the burning of fossil fuels has led to ongoing research and development of biodiesels in order to substitute fossil fuels. The objective of this study is to investigate the performance and exhaust emissions of a single-cylinder direct injection diesel engine fueled with Jatropa curcas - Ceiba pentandra biodiesel-diesel blends. The Jatropa curcas - Ceiba pentandra biodiesel (J50C50) is produced by mixing the crude oils at an equal volume ratio, followed by degumming, acid-catalyzed esterification, and alkaline-catalyzed transesterification. The B10, B20, B30, B40, and B50 blends are produced by blending 10, 20, 30, 40, and 50 vol% of J50C50 biodiesel with diesel. In general, the engine performance of B10 is close to that of diesel fuel, and facilitates achieving higher engine torque, brake power, and brake thermal efficiency comparable to other blends. Blending J50C50 biodiesel with diesel reduces the carbon dioxide emissions and smoke opacity, but increases the nitrogen oxide and carbon monoxide emissions. In addition, artificial neural network models are developed to predict the engine performance and exhaust emission parameters, and the models give excellent results, whereby the coefficient of determination is more than 98% and the mean absolute percentage error is less than 5% for all parameters. In general, the artificial neural network models give accurate and reliable results, without the need for an explicit mathematical representation. Based on the results, it can be concluded that the J50C50 biodiesel-diesel blends qualify as alternative fuels in diesel engines. [ABSTRACT FROM AUTHOR]

In this study, an artificial neural networks (ANN) model is developed to investigate the relationship between bioethanol production and the operating parameters of enzymatic hydrolysis and fermentation processes. The operating parameters of the hydrolysis process which influence the reducing sugar concentration are the substrate loading, α-amylase concentration, amyloglucosidase concentration and strokes speed. The operating parameters of the fermentation process which influence the ethanol concentration are the yeast concentration, reaction temperature and agitation speed. The desirability function of the model is integrated with ant colony optimization (ACO) in order to determine the optimum operating parameters which will maximize reducing sugar and ethanol concentrations. The optimum substrate loading, α-amylase concentration, amyloglucosidase concentration and strokes speed is determined to be 20% (w/v), 109.5 U/g, 36 U/mL and 50 spm, respectively. The reducing sugar obtained at these optimum conditions is 175.94 g/L, which is close to the average value from experiments (174.29 g/L). The optimum yeast concentration, reaction temperature and agitation speed is found to be 1.3 g/L, 35.6 °C and 181 rpm, respectively. The ethanol concentration obtained from the fermentation of sorghum starch by Saccharomyces cerevisiae yeast at these optimum conditions is 82.11 g/L, which is in good agreement with the average value from experiments (81.52 g/L). Based on the results, it can be concluded that the model developed in this study model is an effective method to optimize bioethanol production, and it reduces the cost, time and effort associated with experimental techniques. [ABSTRACT FROM AUTHOR]

[Display omitted] • Pure Jatropha oil with high acid value is not suitable for direct transesterification. • Esterified Jatropha oil and waste cooking oil were blended to produce biodiesel. • Transesterification of WO/EJO produced 90.9 % biodiesel with suitable properties. • The biodiesel-diesel blend improved the calorific value and oxidation stability. • Antioxidants increased the acid value and kinematic viscosity of biodiesel. Fatty acids from non-edible bioresources are highly sought after as biofuel feedstock and the use of multi-stream feedstock for biodiesel production is of interest. This study explores the potential of using blended feedstock consisting of inedible jatropha oil (JO) and waste cooking oil (WO) for biodiesel production. Prior to blending, the unfavourable high acid value of jatropha oil was esterified under the most optimal conditions of 60 °C, 1% H 2 SO 4 catalyst and alcohol to oil molar ratio of 11:1 to maximise the esterified yield (81.1 %). Based on the acid value measurement, the optimum volumetric blend of WO/EJO was determined to be 90/10 with the lowest acid value of 1.9 mg KOH g−1, which was then utilised as feedstock for base-catalysed transesterification. The KOH catalysed transesterification was optimised at 60 °C, 1 wt% KOH catalyst and alcohol to oil molar ratio of 6:1 to produce biodiesel with low acid value (0.2 mg KOH g−1), high calorific value (38.4 MJ kg−1), high oxidation stability (∼11 h) and favourable viscosity (4.7 mm2 s−1). The results show that the produced biodiesel has acceptable physicochemical properties but its properties can further be improved by blending with petroleum diesel and antioxidant. Among those produced blend derivatives, petroleum diesel and biodiesel blend (80:20) or B20 showed the best improvement with high calorific value (46.6 MJ/kg), high oxidation stability (∼37 h) and low acid value (0.3 mg KOH g−1). Based on the study, in situ feedstock blending of WO/EJO can improve the physicochemical properties of the produced biodiesel and reduce the dependency on single feedstock. Biodiesel blending with commercial diesel can enhance the biodiesel fuel properties and such derivatives can be directly applied in an existing engine. [ABSTRACT FROM AUTHOR]

Optimizing the process parameters of biodiesel production is the key to maximizing biodiesel yields. In this study, artificial neural network models integrated with ant colony optimization were developed to optimize the parameters of the two-step Cerbera manghas biodiesel production process: (1) esterification and (2) transesterification. The parameters of esterification and transesterification processes were optimized to minimize the acid value and maximize the C. manghas biodiesel yield, respectively. There was excellent agreement between the average experimental values and those predicted by the artificial neural network models, indicating their reliability. These models will be useful to predict the optimum process parameters, reducing the trial and error of conventional experimentation. The kinetic study was conducted to understand the mechanism of the transesterification process and, lastly, the model could measure the physicochemical properties of the C. manghas biodiesel. [ABSTRACT FROM AUTHOR]