Transesterification of waste cooking oil by heteropoly acid (HPA) catalyst: Optimization and kinetic model

Talebian‐Kiakalaieh, Amin; Amin, Nor Aishah Saidina; Zarei, Alireza; Noshadi, Iman

doi:10.1016/j.apenergy.2012.07.018

Cited by 174 publications

(52 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the technology based on these base catalysts requires using crude oils with low free fatty acids (FFAs) to avoid saponification [9]. So, solid acid catalysts, such as macroporous cation exchange resin [10], heteropoly acid [11] and sulfonated metallic oxides (e.g., zirconia, tin and titanium oxide) [12][13][14] are studied to produce biodiesel from high FFA oils.…”

Section: Introductionmentioning

confidence: 99%

Biodiesel production direct from high acid value oil with a novel magnetic carbonaceous acid

2015

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Biodiesel production direct from high acid value oil with a novel magnetic carbonaceous acid

2015

View full text Add to dashboard Cite

“…Besides, most heterogeneous catalysts required residence time prior to their activity; especially, in low temperature reaction [7]. For example, HPA catalyzed methanolysis of waste cooking oil completed only after 14 h with 88.6 % yield [27]. The reaction time used for all further experiments employing So-DES was 3 h, to enable us capture the effects of all catalysts properly in spite of some slight variations on the products conversions.…”

Section: Effects Of Reaction Conditions On Biodiesel Productionmentioning

confidence: 99%

Single Step Biodiesel Production from Pongamia pinnata (Karanja) Seed Oil Using Deep Eutectic Solvent (DESs) Catalysts

Alhassan

Kumar

2016

Waste Biomass Valor

View full text Add to dashboard Cite

This paper reports the production of biodiesel from Pongamia pinnata seed oil via single step process. The efficiency of deep eutectic solvents (DESs) synthesized from the mixture of choline chloride and para toluene solfonic acid (PTSA), was used with silica support (So-DES) and without support (Un-DES) as heterogeneous and homogeneous catalysts, respectively. The oil esterification with methanol and methyl tert-butyl ether as solvents was conducted. From the results, the optimum reaction conditions for esterification of P. pinnata seed oil with Un-DES are; catalyst loading 1 (wt%/v), reaction time was 120 min and temperature was 343 K. maximum total acid number (TAN) reduction obtained under these conditions was 0.57 mg/KOH/g and a corresponding biodiesel conversion of 97.53 %. The optimal reaction conditions for esterification with So-DES using methanol as solvent are; temperature of 353 K, catalyst loading was 5 (wt%/v) and reaction time was 240 min. The optimum TAN reduction obtained under these conditions was 1.42 mg/KOH/g with corresponding biodiesel conversion of 89.3 %. Catalysts reuse was between four to seven reuses for Un-DES and So-DES respectively. Physico-chemical properties studies indicated that, viscosity, density and calorific values were within acceptable standard limits. It could be concluded that, DES synthesized from choline chloride and PTSA either with or without supporting material, could effectively produce biodiesel with acceptable fuel quality via single step process.

show abstract

“…Basri et al also found that, for optimizing the lipase-catalyzed synthesis of a palm-based wax ester, ANN superiorly outperformed RSM [58]. More comparative studies using RSM and ANN can be found in References [59][60][61][62][63][64][65].…”

Section: Prediction Of Reaction Descriptorsmentioning

confidence: 99%

Application of Artificial Neural Networks for Catalysis: A Review

2017

View full text Add to dashboard Cite

Abstract:Machine learning has proven to be a powerful technique during the past decades. Artificial neural network (ANN), as one of the most popular machine learning algorithms, has been widely applied to various areas. However, their applications for catalysis were not well-studied until recent decades. In this review, we aim to summarize the applications of ANNs for catalysis research reported in the literature. We show how this powerful technique helps people address the highly complicated problems and accelerate the progress of the catalysis community. From the perspectives of both experiment and theory, this review shows how ANNs can be effectively applied for catalysis prediction, the design of new catalysts, and the understanding of catalytic structures.

show abstract

Transesterification of waste cooking oil by heteropoly acid (HPA) catalyst: Optimization and kinetic model

Cited by 174 publications

References 53 publications

Biodiesel production direct from high acid value oil with a novel magnetic carbonaceous acid

Biodiesel production direct from high acid value oil with a novel magnetic carbonaceous acid

Single Step Biodiesel Production from Pongamia pinnata (Karanja) Seed Oil Using Deep Eutectic Solvent (DESs) Catalysts

Application of Artificial Neural Networks for Catalysis: A Review

Contact Info

Product

Resources

About