Advancing energy storage through solubility prediction: leveraging the potential of deep learning.

Solubility prediction plays a crucial role in energy storage applications, such as redox flow batteries, because it directly affects the efficiency and reliability. Researchers have developed various methods that utilize quantum calculations and descriptors to predict the aqueous solubilities of organic molecules. Notably, machine learning models based on descriptors have shown promise for solubility prediction. As deep learning tools, graph neural networks (GNNs) have emerged to capture complex structure-property relationships for material property prediction. Specifically, MolGAT, a type of GNN model, was designed to incorporate n-dimensional edge attributes, enabling the modeling of intricacies in molecular graphs and enhancing the prediction capabilities. In a previous study, MolGAT successfully screened 23 467 promising redox-active molecules from a database of over 500 000 compounds, based on redox potential predictions. This study focused on applying the MolGAT model to predict the aqueous solubility (log S) of a broad range of organic compounds, including those previously screened for redox activity. The model was trained on a diverse sample of 8494 organic molecules from AqSolDB and benchmarked against literature data, demonstrating superior accuracy compared with other state of the art graph-based and descriptor-based models. Subsequently, the trained MolGAT model was employed to screen redox-active organic compounds identified in the first phase of high-throughput virtual screening, targeting favorable solubility in energy storage applications. The second round of screening, which considered solubility, yielded 12 332 promising redox-active and soluble organic molecules suitable for use in aqueous redox flow batteries. Thus, the two-phase high-throughput virtual screening approach utilizing MolGAT, specifically trained for redox potential and solubility, is an effective strategy for selecting suitable intrinsically soluble redox-active molecules from extensive databases, potentially advancing energy storage through reliable material development. This indicates that the model is reliable for predicting the solubility of various molecules and provides valuable insights for energy storage, pharmaceutical, environmental, and chemical applications.

Site suitability assessment for the development of wind power plant in Wolaita area, Southern Ethiopia: an AHP-GIS model.

The primary driver of economic growth is energy, predominantly derived from fossil fuels, the demand for which has experienced a significant increase since the advent of the Industrial Revolution. The emissions of hazardous gases resulting from the utilization of these fuels have been well acknowledged, therefore exerting a notable impact on the environment. In the context of Ethiopia, it is observed that despite the presence of ample renewable resources, the accessibility to power continues to be constrained. In order to effectively tackle this issue, it is imperative to redirect attention towards the utilization of renewable sources, such as wind energy, as a means of enhancing the existing power grid infrastructure. The present study used geospatial tools to evaluate the appropriateness of the Wolayita region for the establishment of a wind power facility. The process of site selection is guided by multiple factors, and a multi-criteria approach is facilitated through the utilization of Geographic Information System (GIS). The evaluation of seven characteristics was conducted utilizing the Analytical Hierarchy Process (AHP) methodology, which involved pairwise comparisons and weighted scoring. The process of suitability mapping involves the classification of locations into four distinct categories, which range from the most suitable to the least suitable. The findings demonstrate that the area of 0.628% (28.00 km2) is deemed the most suitable, while 54.61% (2433.96 km2) is considered somewhat acceptable. Additionally, 0.85% (37.85 km2) is identified as the least suitable, leaving a remaining 43.91% (1060.00 km2) that is deemed unsuitable. The central, northwestern, and southern regions are identified as optimal geographic areas. The results of this study facilitate the process of investing in renewable energy, thereby assisting Ethiopian authorities and organizations in promoting sustainable development. This report serves as a crucial reference point for the wind energy industry.

High-Throughput Screening of Promising Redox-Active Molecules with MolGAT.

Redox flow batteries (RFBs) have emerged as a promising option for large-scale energy storage, owing to their high energy density, low cost, and environmental benefits. However, the identification of organic compounds with high redox activity, aqueous solubility, stability, and fast redox kinetics is a crucial and challenging step in developing an RFB technology. Density functional theory-based computational materials prediction and screening is a time-consuming and computationally expensive technique, yet it has a high success rate. To speed up the discovery of new materials with desired properties, machine-learning-based models can be trained on large data sets. Graph neural networks (GNNs) are particularly well-suited for non-Euclidean data and can model complex relationships, making them ideal for accelerating the discovery of novel materials. In this study, a GNN-based model called MolGAT was developed to predict the redox potential of organic molecules using molecular structures, atomic properties, and bond attributes. The model was trained on a data set of over 15,000 compounds with redox potentials ranging from -4.11 to 2.56. MolGAT outperformed other GNN variants, such as the Graph Attention Network, Graph Convolution Network, and AttentiveFP models. The trained model was used to screen a vast chemical data set comprising 581,014 molecules, namely OMDB, QM9, ZINC, CHEMBL, and DELANEY, and identified 23,467 potential redox-active compounds for use in redox flow batteries. Of those, 20,716 molecules were identified as potential catholytes with predicted redox potentials up to 2.87 V, while 2,751 molecules were deemed potential anolytes with predicted redox potentials as low as -2.88 V. This work demonstrates the capabilities of graph neural networks in condensed matter physics and materials science to screen promising redox-active species for further electronic structure calculations and experimental testing.

The potential of industrial sludge and textile solid wastes for biomass briquettes with avocado peels as a binder.

Producing biomass briquettes from industrial solid wastes is a more environmentally friendly way to provide alternative energy and is essential for Ethiopia to satisfy its growing energy needs while also ensuring efficient waste management in the expansion of industrial parks. The main objective of this study is to produce biomass briquettes from a mixture of textile sludge and cotton residue using avocado peels as a binder. Textile solid waste, avocado peels, and sludge were dried, carbonized, and turned into powder to make briquettes. Briquettes made from the mixture of industrial sludge and cotton residue were combined in various ratios: 100:0, 90:10, 80:20, 70:30, 60:40, and 50:50 with the same amount of the binder. Briquettes were then made using a hand press mold followed by sun-drying for two weeks. The moisture content, calorific value, briquette density, and burning rate of biomass briquettes ranged from 5.03 to 8.04%, 11.19 to 17.2 MJ/kg, 0.21 to 0.41 g/cm3, and 2.92 to 8.75 g/min, respectively. The results revealed that the briquette produced from a 50:50 ratio of industrial sludge to cotton residue was the most efficient. The inclusion of avocado peels as a binder enhanced the briquette's binding and heating properties. Thus, the findings suggested that mixing various industrial solid wastes with fruit wastes could be an effective means of making sustainable biomass briquettes for domestic purposes. Additionally, it can also promote proper waste management and provide young people with employment prospects.

Effect of chemical and biological additives on production of biogas from coffee pulp silage.

Energy is the foundation of the global economy and is essential to human survival. Nevertheless, more than 60% of it comes from fossil fuels. That is not a replenished and scarce source. However, a sizable amount of organic waste is generated every minute throughout the world and can be used as a raw material to produce renewable energy. Among them, Coffee processing generates a huge amount of solid and liquid waste that is organic and can serve as raw material for biofuel production. Since coffee beans and powder are Ethiopia's main exports, coffee pulp is easily accessible. Therefore, the main goal of this project is to convert this waste, which largely consists of organic materials, into a valuable product called Methane. The purity and yield of methane productivity are significantly influenced by the type of additives we use. This work systematically investigates the effect of chemical and biological additives on the productivity and purity of the Biogas from the coffee pulp silage in batch systems under mesophilic temperature (38 °C) for different ensiling periods and additive proportions. The chemical additives recorded the maximum biogas production (2980 ml) at an ensiling period of 40 days with high purity of about 70% biogas. The minimum Biogas was recorded at the ensiling period of 10 days by the control (T1) treatments, which was 634 ml. This work proves that biological additives produced the highest quality and quantity of Biogas from coffee silage.

Maximizing biodiesel production from waste cooking oil with lime-based zinc-doped CaO using response surface methodology.

Biodiesel is one of the alternative fuels, commonly produced chemically from oil and methanol using a catalyst. This study aims to maximize biodiesel production from cheap and readily available sources of waste cooking oil (WCO) and lime-based Zinc-doped calcium oxide (Zn-CaO) catalyst prepared with a wet impregnation process. The Zn-CaO nanocatalyst was produced by adding 5% Zn into the calcinated limestone. The morphology, crystal size, and vibrational energies of CaO and Zn-CaO nanocatalysts were determined using SEM, XRD, and FT-IR spectroscopy techniques, respectively. The response surface methodology (RSM), which is based on the box-Behnken design, was used to optimize the key variables of the transesterification reaction. Results showed that when Zn was doped to lime-based CaO, the average crystalline size reduced from 21.14 to 12.51 nm, consequently, structural irregularity and surface area increased. The experimental parameters of methanol to oil molar ratio (14:1), catalyst loading (5% wt.), temperature (57.5 °C), and reaction time (120 min) led to the highest biodiesel conversion of 96.5%. The fuel characteristics of the generated biodiesel fulfilled the American (ASTM D6571) fuel standards. The study suggests the potential use of WCO and lime-based catalyst as efficient and low-cost raw materials for large-scale biodiesel production intended for versatile applications.

Experimental and simulation analysis of biogas production from beverage wastewater sludge for electricity generation.

This study assessed the biogas and methane production potential of wastewater sludge generated from the beverage industry. The optimization of the biogas production potential of a single fed-batch anaerobic digester was operated at different temperatures (25, 35, and 45 ℃), pH (5.5, 6.5, 7.5, 8.5, and 9.5), and organic feeding ratio (1:3, 1:4, 1:5, and 1:6) with a hydraulic retention time of 30 days. The methane and biogas productivity of beverage wastewater sludge in terms of volatile solid (VS) and volume was determined. The maximum production of biogas (15.4 m3/g VS, 9.3 m3) and methane content (6.3 m3/g VS, 3.8 m3) were obtained in terms of VS and volume at 8.5, 35 ℃, 1:3 of optimal pH, temperature, and organic loading ratio, respectively. Furthermore, the maximum methane content (7.4 m3/g VS, 4.4 m3) and biogas production potential (17.9 m3/g VS, 10.8 m3) were achieved per day at room temperature. The total biogas and methane at 35 ℃ (30 days) are 44.3 and 10.8 m3/g VS, respectively, while at 25 ℃ (48 days) increased to 67.3 and 16.1 m3/g VS, respectively. Furthermore, the electricity-generating potential of biogas produced at room temperature (22.1 kWh at 24 days) and optimum temperature (18.9 kWh) at 40 days was estimated. The model simulated optimal HRT (25 days) in terms of biogas and methane production at optimum temperature was in good agreement with the experimental results. Thus, we can conclude that the beverage industrial wastewater sludge has a huge potential for biogas production and electrification.

Mechanistic study on the coupling reaction of CO2 with propylene oxide catalyzed by (CH3 )4 PI·MgCl2.

The mechanistic study of CO2 coupling with propylene oxide (PO) into cyclic carbonate catalyzed by (CH3 )4 PI has been investigated using the B3 LYP/6-311++G (d, p)/B3 LYP/6-31G (d) level of theory for non-iodine atoms and LANL2DZ was used, together with its associated basis set for the iodine atom. Two hypothetical reaction mechanisms were proposed for the studied reaction and thermodynamic and kinetic parameters were computed for each step to determine the more favorable route. The density functional theory (DFT) study reveals that the reaction prefers to proceed through a three-step mechanism (pathway II) than a tri-molecular intermediate (pathway I) where the CO2 and the catalyst act simultaneously on the PO ring. The rate-determining step of the catalytic reaction is found to be the ring-opening step with an energy barrier of 27.1 kcal/mol (pathway II) in the gas phase, which is kinetically more favorable than that of non-catalytic CO2 fixation with a relatively higher barrier of 63.7 kcal/mol. The synergetic effect of MgCl2 is tested as a cocatalyst for the (CH3 )4 PI/MgCl2 catalyzed reaction and it gave a better result and minimized the activation energy for the reaction and the rate-determining step was the ring closure with the free energy of activation 18.8 kcal/mol in the gas phase. The polarizable continuum model was used to account for the solvent effect, obtaining the best results of 23.1 kcal/mol in water for pathway I and 16.5 kcal/mol and 14.9 kcal/mol in dimethyl sulfoxide for pathway II and binary system, respectively.

Pyridinic-Type N-Doped Graphene on Cobalt Substrate as Efficient Electrocatalyst for Oxygen Reduction Reaction in Acidic Solution in Fuel Cell.

In this study, we use density functional theory to investigate the catalytic activity of graphene (G), single vacancy defective graphene (GSV), quaternary N-doped graphene (NGQ), and pyridinic N-doped graphene (NGpy, 3NGpy, and 4NGpy) on Co(0001) substrate for an oxygen reduction reaction (ORR) in proton exchange membrane fuel cells (PEMFCs). The results show pyridinic N-doped graphene on a Co support exhibited better performance than the NGQ on a Co support and free-standing systems. According to the results, ORR intermediates (*OOH, *O, and *OH) become more stable due to the presence of a Co substrate. The single pyridinic (3NGpy) layer placed on Co(0001) is the most active site. The overpotential for Co/3NGpy is rather higher compared to pure Pt(111) catalyst (0.65 V). Therefore, pyridinic N-doped graphene with a cobalt support could be a promising strategy to enhance the ORR activity of N-doped graphene in PEMFCs.

Improved biodiesel production from waste cooking oil with mixed methanol-ethanol using enhanced eggshell-derived CaO nano-catalyst.

In this report, the utilization of mixed methanol-ethanol system for the production of biodiesel from waste cooking oil (WCO) using enhanced eggshell-derived calcium oxide (CaO) nano-catalyst was investigated. CaO nano-catalyst was produced by calcination of eggshell powder at 900 °C and followed by hydration-dehydration treatment to improve its catalytic activity. The particle size, morphology, and elemental composition of a catalyst were characterized by using XRD, SEM, and EDX techniques, respectively. After hydration-dehydration the shape of a catalyst was changed from a rod-like to honeycomb-like porous microstructure. Likewise, average particle size was reduced from 21.30 to 13.53 nm, as a result, its surface area increases. The main factors affecting the biodiesel yield were investigated, accordingly, an optimal biodiesel yield of 94% was obtained at 1:12 oil to methanol molar ratio, 2.5 wt% catalyst loading, 60 °C, and 120-min reaction time. A biodiesel yield of 88% was obtained using 6:6 equimolar ratio of methanol to ethanol, the yield even increased to 91% by increasing the catalyst loading to 3.5 wt%. Moreover, by slightly increasing the share of methanol in the mixture, at 8:4 ratio, the maximum biodiesel yield could reach 92%. Therefore, we suggest the utilization of methanol-ethanol mixture as a reactant and eggshell-derived CaO as a catalyst for enhanced conversion of WCO into biodiesel. It is a very promising approach for the development of low-cost and environmentally friendly technology. Properties of the biodiesel were also found in good agreement with the American (ASTM D6571) fuel standards.

Characterization and recycling of textile sludge for energy-efficient brick production in Ethiopia.

In recent years, an enormous amount of sludge is generated every day from zero liquid discharge treatment plant due to rapid expansion of industrial parks in Ethiopia. About 30,000 tons of partially dried sludge discharged to the environmental without proper waste management from all industrial parks. Thus, posing serious environmental problems. One of the most plausible means to recycle the excess sludge resource is converting it into energy-efficient brick by combining with clay. Bricks were prepared by incorporating textile sludge at different proportions (10-40%) and temperature (600, 900 and 1200 °C). Clay and sludge samples were collected from the Addis Ababa brick factory PLC and Hawassa Industrial Park. Results revealed that 10 and 20% sludge bricks satisfied criteria of class "A" bricks as per Ethiopia standards, with the compressive strength of 30.43 and 29.10 Mpa, respectively, at 1200 °C. About 26 and 50% of energy were saved during firing of 10 and 20% sludge-containing bricks, respectively, compared with pristine clay bricks. Moreover, too low concentrations of selected heavy metals found in the brick leachate, showing the sludge, were effectively stabilized in the burnt clay bricks. Thus, based on the results, we suggest the rapid utilization of huge amount of partially dried sludge resources for low-cost and efficient large-scale brick production. This will mutually benefit both the industrial parks and brick production industries. In addition, this will create thousands of jobs to the local people. Above all, the solid waste will be managed properly at textile industrial parks.

Fast 3D-lithium-ion diffusion and high electronic conductivity of Li2MnSiO4 surfaces for rechargeable lithium-ion batteries.

High theoretical capacity, high thermal stability, the low cost of production, abundance, and environmental friendliness are among the potential attractiveness of Li2MnSiO4 as a positive electrode (cathode) material for rechargeable lithium-ion batteries. However, the experimental results indicated poor electrochemical performance in its bulk phase due to high intrinsic charge transfer resistance and capacity fading during cycling, which limit its large-scale commercial applications. Herein, we explore the surface stability and various lithium-ion diffusion pathways of Li2MnSiO4 surfaces using the density functional theory (DFT) framework. Results revealed that the stability of selected surfaces is in the following order: (210) > (001) > (010) > (100). Moreover, the Wulff-constructed equilibrium shape revealed that the Li2MnSiO4 (001) surface is the most predominant facet, and thus, preferentially exposed to electrochemical activities. The Hubbard-corrected DFT (DFT + U, with U = 3 eV) results indicated that the bulk insulator with a wide band gap (E g = 3.42 eV) changed into narrow electronic (E g = 0.6 eV) when it comes to the Li2MnSiO4 (001) surface. Moreover, the nudged elastic band analysis shows that surface diffusion along the (001) channel was found to be unlimited and fast in all three dimensions with more than 12-order-of-magnitude enhancements compared with the bulk system. These findings suggest that the capacity limitation and poor electrochemical performance that arise from limited electronic and ionic conductivity in the bulk system could be remarkably improved on the surfaces of the Li2MnSiO4 cathode material for rechargeable lithium-ion batteries.

The effect of brewery sludge biochar on immobilization of bio-available cadmium and growth of Brassica carinata.

Biochar has gained an attention in reducing the bio-availability of toxic heavy metals and minimize threat of entering into food chain from contaminated soil. This study was aimed at evaluating the potential use of brewery sludge biochar (BSB) as a soil amendment for reducing cadmium bio-availability and uptake by Brassica carinata in a pot experiment. In this pot experiment, artificially cadmium spiked, moderately fertile, and slightly basic silty-loam soil was used. The biochar was produced by pyrolyzing of the brewery sludge at 500 °C. The obtained biochar was sieved with 0.5 mm mesh size and applied at the rate of 4 % (w/w) on the Brassica carinata grown cadmium spiked soil. The additions of BSB to the soil contributed a significant reduction of the bio-availability of cadmium in the soil and its accumulation in the shoot of Brassica carinata by 86% and 93%, respectively. Besides, it remarkably increased the dry weight of the edible part of Brassica carinata by 228%. The results revealed that BSB is very effective additive in cadmium immobilization, in turn, significantly (p-value = 0.00) promoting vegetable (Brassica carinata) growth. Therefore, BSB can be used as agricultural soil remedy for cadmium contamination and as safe disposal of brewery sludge.

The effect of CO2 contamination in rechargeable non-aqueous sodium-air batteries.

Metal-air batteries have higher theoretical specific energies than existing rechargeable batteries including Li-ion batteries. Among metal-air batteries, the Na-O2 battery has gained much attention due to its low discharge/charge overpotentials (∼100 mV) at relatively high current densities (0.2 mA/cm2), high electrical energy efficiency (90%), high theoretical energy density, and low cost. However, there is no information reported regarding the effect of CO2 contamination in non-aqueous Na-air batteries. Density functional theory has, here, been applied to study the effect of low concentrations of CO2 contamination on NaO2 and Na2O2 growth/depletion reaction pathways and overpotentials. This was done on step surfaces of discharge products in non-aqueous Na-air batteries. Adsorption energies of CO2 at various nucleation sites for both step surfaces were determined, and results revealed that CO2 preferentially binds at the step valley sites of (001) NaO2 and 11¯00 Na2O2 surfaces with binding energies of -0.65 eV and -2.67 eV, respectively. CO2 blocks the step nucleation site and influences the reaction pathways and overpotentials due to carbonate formation. The discharge electrochemical overpotential increases remarkably from 0.14 V to 0.30 V and from 0.69 V to 1.26 V for NaO2 and Na2O2 surfaces, respectively. CO2 contamination is thus drastically impeding the growth/depletion mechanism pathways and increases the overpotentials of the surface reaction mechanism, hampering the performance of the battery. Avoiding CO2 contamination from intake of gas and electrolyte decomposition is thus critical in development of Na-air batteries.

Oxygen reduction reaction on Pt-skin Pt3V(111) fuel cell cathode: a density functional theory study.

Pt-non-precious transition metals (Pt-NPTMs) alloy electrocatalysts have gained considerable attention to develop cheaper and efficient electrocatalysts for oxygen reduction reaction (ORR) in proton exchange membrane fuel cells (PEMFCs). In this report, density functional theory (DFT) has been applied to study the catalytic activity of Pt-skin Pt3V(111) electrocatalyst for ORR in PEMFCs. The results revealed that the ORR intermediates (O, OH and OOH) have lower binding energies on Pt-skin Pt3V(111) compared to pure Pt(111) surface. The ORR on Pt-skin Pt3V(111) surface proceed via OOH dissociation with an activation energy of 0.33 eV. The formation of OH is found to be the rate determining step with an activation energy of 0.64 eV, which is even lower than in pure Pt(111) surface (0.72 eV). This indicates a better performance of Pt-skin Pt3V(111) for ORR compared to pure Pt(111) surface. Moreover, the DFT results revealed that the negative formation energy of the Pt3V alloy and the positive dissolution potential shift of the surface Pt atoms revealed the better stability of Pt-skin Pt3V(111) surface over pristine Pt(111) surface. Due to the improved activity and better stability, the new Pt3V alloy electrocatalyst is very promising for the development of low-cost and efficient PEMFCs.

Boron and pyridinic nitrogen-doped graphene as potential catalysts for rechargeable non-aqueous sodium-air batteries.

In this work, we performed density functional theory (DFT) analysis of nitrogen (N)- and boron (B)-doped graphene, and N,B-co-doped graphene as potential catalysts for rechargeable non-aqueous sodium-air batteries. Four steps of an NaO2 growth and depletion mechanism model were implemented to study the effects of B- and N-doped and co-doped graphene on the reaction pathways, overpotentials, and equilibrium potentials. The DFT results revealed that two-boron- and three-nitrogen (pyridinic)-doped graphene exhibited plausible reaction pathways at the lowest overpotentials, especially during the charging process (approximately 200 mV), thus, significantly improving the oxygen reduction and oxidation reactions of pristine graphene. In addition, pyridinic nitrogen-doped graphene meaningfully increased the equilibrium potential by approximately 0.30 eV compared to the other graphene-based materials considered in this study. This detailed DFT study provides valuable data that can be used for the successful development of low-cost and efficient graphene-based catalysts for sodium-air battery systems operating with non-aqueous electrolyte.

Microwave-Assisted Biodiesel Production from Microalgae, Scenedesmus Species, Using Goat Bone-Made Nano-catalyst.

The production of biodiesel from Scenedesmus algal oil is one of the best alternative forms of liquid fuel production from biomass to petrol diesel. Biodiesel plays a significant role in the carbon sequestration process during cultivation. Scenedesmus algal species was isolated and cultured in a bold basal medium by using nonheat releasing white florescence (2500 lx) for a 12:12-h dark and light cycle. Algae oil was extracted from dried microalgae biomass through a microwave digester-assisted solvent extraction method. Consequently, about 20.8% algal oil per gram was obtained. A waste-based calcium oxide (CaO) nano-catalyst prepared from goat bone was used in the transesterification process. The catalyst was calcinated at 900 °C and characterized using FTIR, SEM, EDX, and XRD techniques. The results revealed a mean particle size of 43.96 nm with an irregular shape, porous structure, and possession of many active sites. The optimized transesterification process offers an optimum biodiesel yield of 92% at the experimental conditions, i.e., at a reaction temperature of 60 °C, 2% (Wt.) catalyst loading and 11:1 methanol to algal oil molar ratio, 1500 rpm stirring speed, and 3 h reaction duration. The physicochemical properties of the produced biodiesel were tested according to ASTM D6751 standards and are in good agreement.

Optimized Biodiesel Production from Waste Cooking Oil (WCO) using Calcium Oxide (CaO) Nano-catalyst.

Biodiesel production from waste cooking oil (WCO) provides an alternative energy means of producing liquid fuels from biomass for various uses. Biodiesel production by recycling WCO and methanol in the presence of calcium oxide (CaO) nano-catalyst offers several benefits such as economic, environmental and waste management. A nano-catalyst of CaO was synthesized by thermal-decomposition method and calcinated at 500 °C followed by characterization using x-ray diffraction (XRD) and scanning electron microscope (SEM) techniques. The XRD results revealed nano-scale crystal sizes at high purity, with a mean particle size of ~29 nm. The SEM images exhibited morphology of irregular shapes and porous structure of the synthesized nanocatalysts. The highest conversion of WCO to biodiesel was estimated to be 96%, at optimized experimental conditions i.e., 50 °C, 1:8 WCO oil to methanol ratio, 1% by weight of catalyst loading rate and 90 minutes reaction time, which is among few highest conversions reported so far. Biodiesel properties were tested according to the American (ASTM D6571) fuel standards. All reactions are carried-out under atmospheric pressure and 1500 rpm of agitation.