Analysis of the Distribution and Influencing Factors of Diffusion Coefficient Model Parameters Based on Molecular Dynamics Simulations.

The establishment of mathematical models to predict the diffusion coefficients of gas and liquid systems have important theoretical significance and practical value. In this work, based on the previously proposed diffusion coefficient model DLV, the distribution and influencing factors of the model parameters characteristic length (L) and diffusion velocity (V) were further investigated using molecular dynamics simulations. The statistical analysis of L and V for 10 gas systems and 10 liquid systems was presented in the paper. New distribution functions were established to describe the probability distributions of molecular motion L and V. The mean values of the correlation coefficients were 0.98 and 0.99, respectively. Meanwhile, the effects of molecular molar mass and system temperature on the molecular diffusion coefficients were discussed. The results show that the effect of molecular molar mass on the diffusion coefficient mainly affects the molecular motion L, and the effect of system temperature on the diffusion coefficient mainly affects V. For the gas system, the average relative deviation of DLV and DMSD is 10.73% and that of DLV and experimental value is 12.63%; for the solution system, the average relative deviation of DLV and DMSD is 12.93% and that of DLV and experimental value is 18.86%, which indicates the accuracy of the new model results. The new model reveals the potential mechanism of molecular motion and provides a theoretical basis for further study of the diffusion process.

New Model to Predict Infinite Dilution Activity Coefficients Based on (∂p/∂x) T,x → 0.

Accurate prediction of infinite dilution activity coefficient (γ∞) is essential for the calculation of phase equilibria, solubility, and related properties in molecular thermodynamics. Here, we propose a new model to accurately predict the value of γ∞. It is applicable to calculate γ∞ for compounds in aqueous solution at different temperatures. The model is based on the relationship of (∂p/∂x) T,x→0 with γ∞ and temperature at low pressure. First, we introduce the new idea of using the group contribution method to estimate (∂p/∂x) T,x→0 and then obtain the activity coefficient of a solute at infinite dilution in water based on the relationship between (∂p/∂x) T,x→0 and γ∞. The accuracy of this model is verified using experimental data from 46 systems and more than 450 data points. The result shows that the total average relative deviation of the predicted values from the experimental values for training data is 4.73%. Besides, we test the applicability of the model using solutes that are not part of the training data set. The result shows that the model is satisfactory for the prediction of testing data. Compared with other models, the results prove that the developed model outperforms the UNIFAC model, the modified UNIFAC model, and previous predictive models for aqueous systems. The final equation with only simple arithmetic is more easily applied in engineering practices.

Molecular Simulation for Guiding the Design and Optimization of Mixed Matrix Membranes (MMMs) in the Pervaporation Process.

Molecular simulation has been used extensively in the study of pervaporation membranes as a new economical and environmentally friendly research method. In this paper, A-SiO2/PDMS-PTFE mixed matrix membranes (MMMs) were prepared by molecular-simulation-guided experiments to achieve the separation of dimethyl carbonate/methanol (DMC/MeOH)) azeotropes. The interaction energy, X-ray diffraction pattern mean square displacement, and density field between PDMS and inorganic particles were analyzed by molecular dynamics simulations. The dissolution and diffusion processes of the DMC/MeOH azeotropes system in the MMM were simulated, and the surface-silylated silica (A-SiO2) with relatively better performance was screened. Based on the simulation results, A-SiO2/PDMS-PTFE MMMs were prepared by the coblending method, and the pervaporation separation performance of MMM membranes for DMC/MeOH azeotropes with different A-SiO2 loadings was investigated. When the A-SiO2 loading was 15 wt %, the separation factor of DMC/MeOH azeotropes at 50 °C was 4.74 and the flux was 1178 g m-2 h-1, which was consistent with the expected results of the simulation. The MMMs showed good stability in pervaporation over a period of up to 120 h. This study demonstrates that molecular simulations can provide a viable means for pretest screening and validation of experimental mechanisms, and to a certain extent, guide the design and optimization of pervaporation membranes.

Research of a Thermodynamic Function (∂p∂x)T, x→0: Temperature Dependence and Relation to Properties at Infinite Dilution

In this work, we propose the idea of considering (∂p∂x)T, x→0 as an infinite dilution thermodynamic function. Our research shows that (∂p∂x)T,x→0 as a thermodynamic function is closely related to temperature, with the relation being simply expressed as: ln(∂p∂x)T, x→0=AT+B. Then, we use this equation to correlate the isothermal vapor−liquid equilibrium (VLE) data for 40 systems. The result shows that the total average relative deviation is 0.15%, and the total average absolute deviation is 3.12%. It indicates that the model correlates well with the experimental data. Moreover, we start from the total pressure expression, and use the Gibbs−Duhem equation to re-derive the relationship between (∂p∂x)T,x→0 and the infinite dilution activity coefficient (γ∞) at low pressure. Based on the definition of partial molar volume, an equation for (∂p∂x)T,x→0 and gas solubility at high pressure is proposed in our work. Then, we use this equation to correlate the literature data on the solubility of nitrogen, hydrogen, methane, and carbon dioxide in water. These systems are reported at temperatures ranging from 273.15 K to 398.15 K and pressures up to 101.325 MPa. The total average relative deviation of the predicted values with respect to the experimental data is 0.08%, and the total average absolute deviation is 2.68%. Compared with the Krichevsky−Kasarnovsky equation, the developed model provides more reliable results.

Improved Heat Exchanger Network Synthesis without Stream Splits Based on Comprehensive Learning Particle Swarm Optimizer.

In this paper, an improved heat exchanger network (HEN) synthesis method based on the comprehensive learning particle swarm optimizer algorithm (CLPSO) is proposed to synthesize HENs without stream splits. Compared with the standard particle swarm algorithm, CLPSO employs a novel learning strategy that preserves the diversity of the swarm to discourage premature convergence. However, while the algorithm's global exploration capability is enhanced, the local search capability decreases and the convergence speed becomes slow. In addition, the solution quality of CLPSO is largely determined by the randomly generated particles' best previous position (pbest) during initialization. Hence, the solution may be unstable due to different pbest. For the abovementioned considerations, this paper proposes a new HEN initialization and renovation method to improve the quality of pbest, reduce the initial cost, and retain the obtained optimization results as much as possible in the optimization process to speed up the convergence of the algorithm. Four typical cases are simulated to verify the effectiveness of the proposed method. This method only needs a single-level optimization algorithm to obtain high-quality solutions, which will give it a bright prospect in research and application.

Experimental and Modeling of Conductivity for Electrolyte Solution Systems.

Studying the concentration and temperature dependence of the conductivity of electrolyte solution is of great significance for the evaluation and improvement of the performance of the electrochemical system. In this paper, based on the influence of the number of free ions and ion mobility on the conductivity, a semiempirical conductivity model with five parameters was proposed to correlate the conductivity, concentration and temperature data of electrolyte solutions at medium and high concentrations. The conductivities of NaCl and CaCl2 in propylene carbonate-H2O binary solvents were measured at temperatures varying from 283.15 to 333.15 K. The validity of the model was verified by the experimental data of this paper and the conductivity, concentration, and temperature data of 28 electrolyte solution systems in the literature. The electrolyte solutions investigated in this paper included binary organic solvent systems, pure organic solvent systems, and aqueous solution systems. The results showed that the proposed model can fit the experimental data well for both pure solvent and mixed solvents systems, which is of great value to practical engineering applications.

Study of a New Process for the Preparation of Butyl Levulinate from Cellulose.

Butyl levulinate (BL) is a versatile chemical utilized widely in food and chemical industries, the production of which by using cellulose in biomass resources is of great significance to its sustainable development. Traditional synthesis processes for n-butyl levulinate are confronted with various problems such as high cost of raw materials, difficulty in separating products, etc. In this paper, a novel process for the preparation of BL from cellulose is proposed. The process is composed of five main unit operations including fed-batch hydrolysis, decolorization, extraction, esterification and purification. A 171.63 g/L concentration of the intermediate levulinic acid was obtained at the fifth feeding through the fed-batch hydrolysis process. The resin-activated carbon secondary decolorization method was adopted to remove the soluble humin byproducts with an accumulative decolorization rate of 89%. In the extraction process, the product BL was chosen as the extractant to avoid the introduction of new impurities. After purification, the purity of the final product BL reaches up to 98 wt %. The proposed technique allows for cost-effective and eco-friendly production of BL from biomass resources.

Preparation of platinum nanoparticle catalyst for propane dehydrogenation.

Supported Pt nanoparticle catalysts were prepared by combing a chemical reduction method with an ultrasonic sonication loading method. Several techniques including transmission electron microscopy (TEM), nitrogen sorption technique and pyridine adsorption Fourier-transform infrared (Py-IR) were applied to characterize the physicochemical properties of these catalysts. The catalytic performance of catalysts was evaluated in the dehydrogenation of propane. The influence of the preparation method of Pt nanoparticles, the ratio of Polyvinyl Pyrrolidone (PVP) to Pt, loading method and different supports on the catalytic performance was investigated. PVP is useful for controlling the size of Pt nanoparticles and a PVP/Pt ratio of 15 is favorable to achieve a good catalytic performance. NaBH4 reduction is better than ethanol refluxing in preparing Pt nanoparticles. The ultrasonic sonication is effective to load the Pt nanoparticles onto the support channels. The mesoporous alumina proved to be a good catalyst support due to its high surface area and unique pore structure.

[Study of simultaneous quantitative analysis of overlapping UV spectra].

The simultaneous multi-component quantitative determination was proposed without any chemical separation procedure. The method uses optimum wavelength gather obtained after hierarchical clustering and additive validation to reduce correlation of the component spectra. Information of 30 wavelength points after hierarchical clustering analysis was taken and, with the information of optimum wavelength gather, the absorptivity coefficient and component concentration of solutions were treated as independent variables, and a constrained optimization model was set up. The concentration awaiting test can be obtained after one optimization calculation for the mixed solution in which the concentration of every component is close to each other. But for some solutions in which component concentration is not close to each other, iterative optimization is necessary. The final results obtained are satisfying with a good accuracy and precision only after about 4 times of iterations, and the relative error can be controlled in 3.63%. So this method can be used for quantitative analysis of overlapping UV spectra.