Liquid-liquid equilibrium experiment and mechanism analysis of menthol-based deep eutectic solvents extraction for separation of fuel additive tert-butanol.

Deep eutectic solvents (DESs) were synthesized using menthol as hydrogen bond acceptor (HBA) and different carbon chain carboxylic acids as hydrogen bond donors (HBD). The liquid equilibrium (LLE) experiment was used to determine the distribution coefficient (ß) and slectivity (S) at standard atmospheric pressure and temperature. The effect of DESs on the separation efficiency was discussed by changing the proportion. Non-random two fluid (NRTL) model was used to correlate the experimental data. The molecular dynamics (MD) simulation method was used to investigate the micro mechanism of the extraction process. The results show van der Waals force plays a leading role in the interaction between solvents and tert-butyl alcohol (TBA) and week force with water. Compared with experimental and simulation results, the interaction between DESs and TBA would also be affected by the change of the number of HBD carbon chains, and DESs with decanoic acid as HBD has the best separation effect, which verifies the feasibility of separating high alcohol compounds from water by DESs and then treating them by DESs.

Comparative analysis of life cycle water accounting of the Lurgi low-pressure methanol production process with biomass or coal as raw materials.

Water and energy are both essential for methanol production. This study focuses on the two processes of coal to methanol and biomass to methanol, and analyzes the water footprint of the methanol production process in the life cycle. The results indicate that the water footprint of biomass to methanol is 1707.54 L/MJ, and the dominant factor was the water consumption in the growth stage of biomass, accounting for over 95 % of the total water consumption. The water footprint of the coal to methanol process is 161.40 L/MJ. The main contributor to this process was the methanol stage, which accounted for 99.75 % of the total water footprint. However, the water consumption of the biomass to the methanol stage accounted for only 51.6 % of that of the coal to methanol stage. Based on the power situation of 30 provinces, the indirect water consumption caused by power generation in different regions was calculated, resulting in greater changes in the total water footprint of the biomass to methanol process. Through a sensitivity analysis, the effects of 24 influencing factors and main inputs on the total water consumption were investigated. This study provides the relevant water consumption of the two methanol production processes within the standard range, and the results emphasize the importance of biomass utilization and water conservation.

Comparative water footprint assessment of fuel cell electric vehicles and compressed natural gas vehicles.

Utilization of renewable energy has become a current energy development trend. In this study, the water footprints of a fuel cell electric vehicle (FCEV) and a compressed natural gas vehicle (CNG) under different fuel scenarios were evaluated. The FCEV exhibits a low water footprint of 27.2 L/100 km under steam methane reforming hydrogen production technology. Hydrogen production using steam methane reforming and water electrolysis via wind can enable the FCEV industry to save more water resources. The percentage difference between different metallic materials in automobiles was analyzed. The water consumption by steel accounted for 73.6% and 80.5%, respectively. The fluctuation law of the water footprint was analyzed based on different power structures and steel water consumption coefficients. It was found that for low steel water consumption coefficient, wind power generation is conducive to slowing down the water consumption during the entire life cycle. In addition, a sensitivity analysis was performed for the FCEV and CNG under different fuel scenarios. Fuel technology and material structure have a significant impact on the total water footprint. The results of this study can provide guidance for the layout of the automobile industry and for water-saving measures in the future.

Life cycle water footprint comparison of biomass-to-hydrogen and coal-to-hydrogen processes.

Water is essential for the industrial production of hydrogen. This study investigates the production of hydrogen from biomass and coal. To date, there are few studies focusing on the water footprint of biomass-to-hydrogen and coal-to-hydrogen processes. This research conducted a life cycle water use analysis on wheat straw biomass and coal to hydrogen via pyrolysis gasification processes. The results show that the water consumption of the entire biomass-to-hydrogen process was 76.77 L/MJ, of which biomass cultivation was the dominant contributor (99%). Conversely, the water consumption of the coal-to-hydrogen process was only 1.06 L/MJ, wherein the coal production stage accounted for only 4.15% for the total water consumption, which is far lower than that of the biomass-to-hydrogen process. The hydrogen production stage of biomass hydrogen production accounted for 76% of the total water consumption when excluding the water consumption of straw growth, whereas that of the coal hydrogen production stage was 96%. This research provides the associated water consumption, within a specified boundary, of both hydrogen production processes, and the influence of major factors on total water consumption was demonstrated using sensitivity analysis.

Phase Behavior and Thermodynamic Model Parameters in Simulations of Extractive Distillation for Azeotrope Separation.

Extractive distillation (ED) processes for separating ternary mixtures of benzene-cyclohexane-toluene with dimethyl formamide (DMF) and N-methyl-2-pyrrolidone (NMP) were studied using Aspen Plus and PRO/II simulators. The Aspen Plus built-in binary interaction parameters for the toluene-DMF, benzene-NMP and cyclohexane-NMP systems resulted in inaccurate phase behavior calculations. The vapor-liquid equilibrium (VLE) for the three binary systems was regressed to illustrate the importance of using accurate model parameters. The obtained binary interaction parameters described the phase behavior more accurately compared with the built-in binary interaction parameters in Aspen Plus. In this study, the effects of the regressed and built-in binary interaction parameters on the ED process design are presented. The total annual cost (TAC) was calculated to further illustrate the importance of the regressed binary interaction parameters. The results show that phase behavior and thermodynamic model parameters should receive more attention during the research and development of ED processes.