Catalytic activity of CaO-based catalyst in transesterification of microalgae oil with methanol

Çakırca, Emine Emel; Tekin, Gizem N; İlgen, Oğuzhan; Akın, Ayşe Nilgün

doi:10.1177/0958305x18787317

Cited by 23 publications

(4 citation statements)

References 34 publications

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“…A FAME yield of 85.3% was obtained at 60 • C for 3 h of reaction using 10 wt% CaMgO/Al 2 O 3 , compared with 75.2% of FAME yield given by 20 wt% CaMgO [93]. The 30.0% CaO/dolomite catalyst, with a catalyst amount of 3.0%, MeOH/microalgae oil molar ratio of 6:1, at a reaction temperature of 65 • C for 3 h, generated a FAME yield of 90.0% from Chlorella protothecoides [94]. Heterogeneous Acid Catalysts Heterogeneous acid catalysts, such as zirconium oxide (ZrO 2 ), titanium oxide (TiO 2 ), zeolites, and ion exchange resins, are commonly used in the transesterification of lipids [90].…”

Section: Heterogeneous Alkaline Catalysismentioning

confidence: 93%

Advances in Biodiesel Production from Microalgae

et al. 2023

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Biofuels, as a renewable, eco-friendly, and cost-effective energy source, can reduce the dependence on fossil fuels. The researchers considered different approaches for obtaining high biodiesel yields from microalgae biomass. This work aims to present an overview of the feasibility of microalgae use in biodiesel production. Therefore, biodiesel production from microalgae oil via the transesterification process was explained in detail. The application of non-catalytic transesterification and catalytic transesterification was reviewed. The achievements in the application of homogenous catalysts, heterogeneous catalysts, and enzymatic catalysts for microalgae oil transesterification were discussed. The present technologies for biodiesel production from microalgae need more improvements to increase their efficiencies and reduce costs. Therefore, future research should focus on the development of effective catalysts for biodiesel production from microalgae biomass.

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Section: Heterogeneous Alkaline Catalysismentioning

confidence: 93%

Advances in Biodiesel Production from Microalgae

et al. 2023

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“…In addition, glycerol byproduct is hard to purify and refine. The practice of heterogeneous catalysts in biodiesel synthesis simplifies these disabilities [7,8]. The catalytic activities of metal oxides were investigated alone and with other metal oxide supports for biodiesel production [9].…”

Section: Introductionmentioning

confidence: 99%

“…The use of calcium oxide (CaO) has attracted special attention since it can be obtained natural and cheap sources. Recently, eggshell [10], waste mud crab shell [11], mollusk [12], oyster shell [13], and dolomite [8,[14][15][16] were studied as heterogeneous catalyst for biodiesel production. Solubility of CaO in alcohol makes it difficult to separate from reaction mixture.…”

Section: Introductionmentioning

confidence: 99%

Study on Kinetics and Reaction Parameters of Biodiesel Production from Sunflower Oil and Methanol Using Zinc Oxide Supported Calcium Oxide

İlgen

2022

Period. Polytech. Chem. Eng.

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This study investigated the effect of reaction parameter, reaction kinetics and mechanism of transesterification of sunflower oil with methanol by using CaO/ZnO heterogeneous catalyst. The influence of reaction time, molar ratio and catalyst amount and reaction temperature on fatty acid methyl esters (FAME) yield was investigated. The catalysts were prepared by incipient wetness impregnation and characterized by using X-ray diffraction (XRD) and Hammett indicator method. The FAME contents were analyzed by gas chromatography using the EN 14103 standard method. The highest FAME yield of 82% was obtained at 9/1 methanol/oil molar ratio, 3 wt.% catalyst amount and 3 hours of reaction time at 65 °C of reaction temperature by using 20% CaO/ZnO catalyst. The reaction could be considered pseudo first order with respect to triglyceride (TG). The reaction model based on Eley-Rideal mechanism was proposed where adsorbed methanol reacted with TG before desorption of glycerin. The results showed that experimental reaction rates exhibited good agreement with calculated reaction rates.

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“…Transesterification is one such methodology through which vegetable-based bio-oil is transformed into biodiesel through a series of reversible chemical chain reactions [3].…”

Section: Introductionmentioning

confidence: 99%

Optimized biodiesel production from C. innophyllum bio-oil using Kriging and Ann predicitive models

et al. 2022

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This work aimed at optimizing the two-stage transesterification efficiency of the production of Calophyllum inophyllum biodiesel using Artificial Neural Network and Kriging predictive models. Response Surface Methodology was used to develop the central rotatable composite design of twenty-seven trial experimental runs with variations in the input process parameters like methanol to oil molar ratio, potassium hydroxide catalyst loading, and reaction time. A multi-layered non-linear regressive Artificial Neural Network model with feed-forward propagation and a numerical surrogate Kriging model was used to predict the Calophyllum inophyllum biodiesel yield. The efficacy of the developed model was verified using Analysis of Variance by comparing its coefficient of determination and the mean relative percentage deviation values. The optimized Calophyllum inophyllum biodiesel as 98.1% is derived with 0.94 v/v of methanol to oil molar ratio, 0.98 wt % of potassium hydroxide catalyst loading, and 80 minutes reaction time with 70oC constant reaction temperature as predicted by Kriging model. The optimized parameters were also verified experimentally.

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Catalytic activity of CaO-based catalyst in transesterification of microalgae oil with methanol

Cited by 23 publications

References 34 publications

Advances in Biodiesel Production from Microalgae

Advances in Biodiesel Production from Microalgae

Study on Kinetics and Reaction Parameters of Biodiesel Production from Sunflower Oil and Methanol Using Zinc Oxide Supported Calcium Oxide

Optimized biodiesel production from C. innophyllum bio-oil using Kriging and Ann predicitive models

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