Catalytic etherification of glycerol by tert-butyl alcohol to produce oxygenated additives for diesel fuel

Frusteri, F.; Arena, Francesco; Bonura, Giuseppe; Cannilla, C.; Spadaro, Lorenzo; Blasi, O. Di

doi:10.1016/j.apcata.2009.07.037

Cited by 191 publications

(154 citation statements)

References 30 publications

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“…Therefore, employing heterogeneous acid catalysts can contribute to overcome these drawbacks [1,11,[13][14][15][16]. Due to their stronger Brönsted acidity than conventional solid acids like mixed oxides and zeolites, Keggin type heteropolyacids (HPAs) can be employed instead of classical homogeneous acids [17][18][19][20][21][22][23][24][25][26][27][28][29]. Some drawbacks of bulk HPAs like low thermal stability, high solubility in water and polar media and low surface area (1-10 m 2 g −1 ) can be improved by functionalizing them into the framework of high surface area porous supports (silica, activated carbon, zirconia, polymers and acidic ionexchange resin) [11,18,19].…”

Section: Introductionmentioning

confidence: 99%

Zr-modified hierarchical mordenite as heterogeneous catalyst for glycerol esterification

Popova

Lazarova

Kalvachev

et al. 2017

Catalysis Communications

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Hierarchical mordenite catalysts were prepared by HF and NH4F etching. Materials' zirconia modification was performed by incipient wetness impregnation in order to vary surface acidity type and strength. XRD, N2 physisorption, solid-state NMR and UV-Vis spectroscopies were applied for characterization. Acidic properties of the obtained materials were investigated by TPD of adsorbed ammonia and FT-IR spectra of adsorbed pyridine. Catalytic performance was studied for the glycerol esterification with acetic acid. Zr increased reaction turnover activity compared to raw zeolite substrate due to abundant Brönsted and Lewis moiety presence. The demonstrated biomass valorization processes to bio-based platform chemicals are of interest, as they employ biodiesel production waste.11

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Section: Introductionmentioning

confidence: 99%

Zr-modified hierarchical mordenite as heterogeneous catalyst for glycerol esterification

Popova

Lazarova

Kalvachev

et al. 2017

Catalysis Communications

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“…An extractive distillation unit with 1,4-butanediol was also required to separate TBA from the alcohol/water azeotrope formed [129] along with the MTGEs recycle. Another preliminary approach was investigated by using zeolites to remove the water, but they required a regeneration step to be reused [130]. Also Ozbay et al studied water separation by sorption with a zeolite physically mixed with the catalyst and packed into a flow reactor which allowed an important increase in glycerol conversion and DTGEs selectivity to be achieved [131].…”

Section: Fuel Additivesmentioning

confidence: 99%

Potential of Pervaporation and Vapor Separation with Water Selective Membranes for an Optimized Production of Biofuels—A Review

2017

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Abstract:The development of processes based on the integration of new technologies is of growing interest to industrial catalysis. Recently, significant efforts have been focused on the design of catalytic membrane reactors to improve process performance. In particular, the use of membranes, that allow a selective permeation of water from the reaction mixture, positively affects the reaction evolution by improving conversion for all reactions thermodynamically or kinetically limited by the presence of water. In this paper, how pervaporation (PV) and vapor permeation (VP) technologies can improve the catalytic performance of reactions of industrial interest is considered. Specifically, technological approaches proposed in the literature are discussed with the aim of highlighting advantages and problems encountered in order to address research towards the optimization of membrane reactor configurations for liquid biofuel production in large scale.

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“…GTBE has a positive effect on quality of diesel fuel and provides reducing in carbon monoxide and particulate matter from incomplete combustion due to the presence of oxygen in its structure. (Frusteri et al, 2009) A number of study on prediction of biodiesel production using artificial neural network was published recently (Badday et al, 2014;Farobie et al, 2015f). However, there has been no study on this artificial neural network approach to estimate biodiesel yield conducted in supercritical MTBE.…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network Approach to Predict Biodiesel Production in Supercritical tert-Butyl Methyl Ether

Farobie

Hasanah

2016

IJOST

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In this study, for the first time artificial neural network was used to predict biodiesel yield in supercritical tert-butyl methyl ether (MTBE). The experimental data of biodiesel yield conducted by varying four input factors (i.e. temperature, pressure, oil-to-MTBE molar ratio, and reaction time) were used to elucidate artificial neural network model in order to predict biodiesel yield. The main goal of this study was to assess how accurately this artificial neural network model to predict biodiesel yield conducted under supercritical MTBE condition. The result shows that artificial neural network is a powerful tool for modeling and predicting biodiesel yield conducted under supercritical MTBE condition that was proven by a high value of coefficient of determination (R) of 0.9969, 0.9899, and 0.9658 for training, validation, and testing, respectively. Using this approach, the highest biodiesel yield was determined of 0.93 mol/mol (corresponding to the actual biodiesel yield of 0.94 mol/mol) that was achieved at 400 °C, under the reactor pressure of 10 MPa, oil-to-MTBE molar ratio of 1:40 within 15 min of reaction time.

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Catalytic etherification of glycerol by tert-butyl alcohol to produce oxygenated additives for diesel fuel

Cited by 191 publications

References 30 publications

Zr-modified hierarchical mordenite as heterogeneous catalyst for glycerol esterification

Zr-modified hierarchical mordenite as heterogeneous catalyst for glycerol esterification

Potential of Pervaporation and Vapor Separation with Water Selective Membranes for an Optimized Production of Biofuels—A Review

Artificial Neural Network Approach to Predict Biodiesel Production in Supercritical tert-Butyl Methyl Ether

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