Optimization of bioethanol production from glycerol by Escherichia coli SS1

Bioethanol is a promising biofuel and has a lot of great prospective and could become an alternative to fossil fuels. Ethanol fermentation using glycerol as carbon source was carried out by local isolate, ethanologenic bacterium Escherichia coli SS1 in a close system. Factors affecting bioethanol production from pure glycerol were optimized via response surface methodology (RSM) with central composite design (CCD). Four significant variables were found to influence bioethanol yield; initial pH of fermentation medium, substrate concentration, salt content and organic nitrogen concentration with statistically significant effect (p ≤ 0.05) on bioethanol production. The significant factor was then analyzed using central composite design (CCD). The optimum conditions for bioethanol production were substrate concentration at 34.5 g/L, pH 7.61, and organic nitrogen concentration at 6.42 g/L in which giving ethanol yield approximately 1.00 mol/mol. In addition, batch ethanol fermentation in a 2 L bioreactor was performed at the glycerol concentration of 20 g/L, 35 g/L and 45 g/L, respectively. The ethanol yields obtained from all tested glycerol concentrations were approaching theoretical yield when the batch fermentation was performed at optimized conditions.     

Process simulation of hydrogen production by steam reforming of diluted bioethanol solutions: Effect of operating parameters on electrical and thermal cogeneration by using fuel cells

The possibility to exploit diluted bioethanol streams is discussed for hydrogen production by steam reforming. An integrated unit constituted by a steam reformer, a hydrogen purification section with high- and low-temperature water gas shift, a methanator reactor and a fuel cell were simulated to achieve residential size cogeneration of 5 kW electrical power + 5 kW thermal power as target output.Process simulation allowed to investigate the effect of the reformer temperature, of bioethanol concentration and of catalyst loading on the temperature and concentration profiles in the steam reformer. The net power output was also calculated on the basis of 27 different operating conditions.P_electrical output ranging from 3.3 to 6.0 kW were obtained, whereas the total heat output P_{thermal, total} ranged from 3.9 to 7.2 kW. The highest overall energy output corresponded to P_electrical = 4.8 kW, P_{Thermal, FC} = 3.1 kW, P_{heat recovery} = 4.1 kW, for a total 12 kW energy output. This was achieved by feeding a mixture with water/ethanol ratio = 11 (mol/mol), irrespectively of the catalyst mass, and setting the ref split temperature so to have an average temperature of 635 °C in the ESR reactor.     

Catalytic valorization of bioethanol over Cu-Mg-Al mixed oxide catalysts

The conversion of ethanol into 1-butanol and 1,1-diethoxyethane was studied over Cu-Mg-Al mixed oxide catalysts obtained from LDH precursors. The optimum yields are obtained for Cu loadings comprised between 5 and 10 at.%. A reaction scheme accounting for the main and secondary reaction products is proposed. The influences of the reaction temperature and of the reaction time on the catalytic performances have also been investigated. The negative effect of water, a by-product of the reaction, on this transformation was evidenced.     

A simple rule for bioenergy conversion plant size optimisation: Bioethanol from sugar cane and sweet sorghum

Fuel ethanol from agricultural crops, “bioethanol”, is more expensive than petrol. Here we consider ways to reduce ethanol costs, by using mixed crops to extend the processing season and by optimising plant capacity. We derive a simple model of general applicability by balancing crop transport costs (which increase with plant size) against the (decreasing) production costs. We show that at the optimum, the cost of transporting crop, per unit quantity of alcohol, must be a predictable proportion of the unit cost of production, generally in the range 0.4–0.6. Under current Australian conditions, cane sugar and cane plus sweet sorghum bioethanol plants have optimum capacities around 245,000 and 175,000 kl/year, respectively. the model is equally applicable to any other bioenergy conversion plant which requires biomass to be transported from surrounding areas. The model also shows quantitatively how more efficient transport allows larger scale production, while lower production costs make smaller plants more economic.     

Economics of bioethanol production from wheat in the UK

The cost of bioethanol production from wheat was found to be very sensitive to the price of wheat. When wheat is purchased at a typical current UK price of £115/tonne, the net cost of ethanol was calculated to be 38.3p per litre, but growing wheat on set aside at £45/tonne could result in a net ethanol cost of 21p/litre.     

Hydrogen production from raw bioethanol over Rh/MgAl2O4 catalyst: Impact of impurities: Heavy alcohol, aldehyde, ester, acid and amine

The effect of various impurities added in a pure ethanol + water mixture was studied. The impurities chosen were acetic acid, diethylamine, butanol, butanal, ethyl acetate and diethylether. It was shown that the addition of diethylamine or butanal increases the ethanol conversion, compared to that obtained with a pure ethanol + water mixture, without changing the product selectivity. In the presence of the other impurities, butanol, ethylether and ethyl acetate, a strong deactivation of the catalyst with a decreased ethanol conversion was observed. Moreover, the selectivity in hydrogen was also strongly decreased, whereas an increase in intermediate products especially ethylene was observed. The deactivation was explained in terms of coke deposition at the catalyst surface. The poisoning effect induced by the presence of impurities can be classified in the following increasing order: diethylamine  butanal < no impurity < acetic acid < butanol < diethylether  ethyl acetate.     

Liquid–liquid equilibrium extraction of ethanol with mixed solvent for bioethanol concentration

The extraction of ethanol with the solvents of aldehydes mixed with m-xylene was studied for the bioethanol concentration process.Furfural and benzaldehyde were selected as extraction solvents,with which the solubility of water is small,expecting large distribution coefficient of ethanol.The liquid–liquid two-phase region was the largest with m-xylene solvent,followed by benzaldehyde and furfural.The region of two liquid–liquid phase became larger with the mixed solvent of m-xylene and furfural than that with furfural solvent.The NRTL model was applied to the ethanol–water–furfural–m-xylene system,and the model could well express the liquid–liquid equilibrium of the system.For any solvent used in this study,the separation selectivity of ethanol relative to water decreased as the distribution coefficient of ethanol increased.The separation selectivity with m-xylene was the largest among the employed solvents,but the distribution coefficient was the smallest.The solvent mixture of furfural and m-xylene showed relatively high distribution coefficient of ethanol and separation selectivity,even in the higher mass fraction of m-xylene in the solvent phase.The ethanol extraction with a countercurrent multistage extractor by a continuous operation was simulated to evaluate the extraction performance.The ethanol content could be concentrated in the extract phase with relatively small number of extraction stages but low yield of ethanol was obtained.     

Characterization,pretreatment and saccharification of spent seaweed biomass for bioethanol production using baker's yeast

Seaweeds are marine macroalgae found abundantly and viewed as potential source of phycocolloids to produce biofuel. In this study, seaweed spent biomass obtained from alginate production industry and biomass obtained after pigment extraction were found to contain a considerable amount of phycocolloids. These two spent biomasses were investigated for the production of ethanol. In this study, the red seaweed spent biomass of Gracilaria corticata var corticata showed higher content of polysaccharide (190.71 ± 30.67 mg g⁻¹ dry weight) than brown seaweed spent biomass (industrial) (136.28 ± 30.09 mg g⁻¹ dry weight). Hydrolysis of spent biomasses with different concentrations of sulfuric acid (0.1%, 0.5% and 1%) was also investigated. Brown seaweed spent biomass and red seaweed spent biomass exhibited high amount of sugar in 0.5% and 1% sulfuric acid treatment, respectively. Proximate and ultimate composition of seaweed spent biomasses were analysed for energy value. The FT-Raman spectra exhibited similar stretches for both acid hydrolysed spent biomasses with their respective standards. Ethanol produced through a fermentation process using spent hydrolysates with baker's yeast at pH 5.3 was found to be significant. The ethanol yield from brown seaweed spent biomass and red seaweed spent biomass was observed to be 0.011 g g⁻¹ and 0.02 ± 0.003 g g⁻¹ respectively, when compared with YPD (0.42 ± 0.03 g g⁻¹) and d-galactose (0.37 ± 0.04 g g⁻¹) as standard on day 4. The present study revealed the possibility of effective utilization of spent biomass from seaweed industry for ethanol production.     

Effect of doping pretreated corn stover conditions on yield of bioethanol in immobilized cell systems

The surface characteristics of immobilized yeast before and after adding CO₂-laser pretreated corn stover (LPCS) substrates were investigated using bioethanol production. Response surface methodology (RSM), based on the Box–Behnken design (BBD) for experiments, was used to optimize the doping condition. An optimum experimental condition was obtained at pH 4.5, 2.08% yeast concentration, and 0.20% LPCS substrates. Under this condition, doping LPCS increased the yield of bioethanol from 53% to 84%, which matched the predicted value. After doping LPCS, the results of inverted microscope (IM) and atomic force microscopy (AFM) illustrated that the immobilized gel beads changed from rod-like in shape with a smooth surface to a larger rod-like ultrastructure with a rougher surface. The yield was relatively stable within 28 d, with a downward trend subsequently appearing.