Viscosities and Densities of Binary and Ternary Mixtures of Aliphatic and Polyaromatic Hydrocarbons: Pyrene +1-Methylnaphthalene + Dodecane at T = (293.15 to 343.15) K. Experiment and Modeling.

This work presents new experimental viscosity and density data for aromatic and polyaromatic compounds in binary and ternary pyrene, 1-methylnaphthalene, and dodecane mixtures. The lack of experimental viscosity data for these mixtures requires the development of a new database, which is vital for understanding the behavior of mixtures in more complex systems, such as asphaltenes and fuels. The mixtures proposed in this work have been measured over a temperature range of (293.15 to 343.15) K at atmospheric pressure. Several mixture compositions have been studied at these conditions: 1.0, 2.5, 5.0, 7.5, 10.0, 12.5, and 15.0% pyrene mass fraction. The concentration of pyrene correlates with an increase in the viscosity and density values. At the lowest temperature in binary mixtures, the corresponding values reach 4.4217 mPa·s for viscosity and 1.0447 × 103 kg·m-3 for density, respectively. In ternary mixtures, the introduction of dodecane leads to the lowest maximum values of 3.5555 mPa·s for viscosity and 1.0112 × 103 kg·m-3 for density at the same temperature. The experimental data have been employed for the specific modification of viscosity models. These modifications could facilitate the prediction of the viscosity of mixtures that are more complex than those presented in this work. Various viscosity models have been employed, such as Linear, Ratcliff and Khan, modified UNIFAC-Visco, and Krieger-Dougherty. The settings in the models used reliably reproduce the experiment reliably. However, the Ratcliff model agrees excellently with the experiment, having a low standard deviation (2.0%) compared to other models. Furthermore, a model based on the equation of state of Guo is proposed to predict the viscosity values by modifying the specific parameters and adjusting them to the mixtures proposed in this work. The results from this study are compared to previous work, where pyrene, toluene, and heptane mixtures were analyzed. In this case, we find that the decrease of aggregation grade in the present systems is predicted by the model fixed in this work.

Fast and simplified determination of PCA and aromatic carbon content of treated distilled aromatic extract (TDAE) by NMR.

Aromatic oils obtained during lubricant production (DAE) have high value as rubber extenders in tire manufacturing, but they have high carcinogenic potential due to the content of polycyclic aromatic compounds (PCAs). Legislation on PCA content requires additional treatment to reach treated oils (TDAE) with a PCA content lower than 3% according to the IP 346 method. IP 346 is a highly time-consuming and high uncertainty method, and several proposals have tried to replace it, but nowadays, there is no standard alternative. In this work, an extensive collection of samples covering a broad PCA content were obtained and characterized by physical properties, NMR, and aromatic and PCA content. Several correlations were tested to establish an optimum procedure to estimate the aromatic and the PCA content according to the requirement of high accuracy and low time and effort. The combination of several properties does not improve the accuracy of the correlation, and simpler equations were preferred. Integrated spectra appear as an acceptable characterization method as NMR percent of the total aromatic proton and polycyclic aromatic proton correlates satisfactory with the number of aromatic carbons and PCA content, respectively. The refractive index yields the best results for the correlation to PCA content. Obtained deviations compare favorably with methods previously described in the literature and with the uncertainty involved in the experimental method. They can be considered adequate methods to analyze such magnitudes routinely.

Broadening of polymer chromatographic signals: Analysis, quantification and correction through effective diffusion coefficients.

Average molecular weights and polydispersity indexes are some of the most important parameters considered in the polymer characterization. Usually, gel permeation chromatography (GPC) and multi angle light scattering (MALS) are used for this determination, but GPC values are overestimated due to the dispersion introduced by the column separation. Several procedures were proposed to correct such effect usually involving more complex calibration processes. In this work, a new method of calculation has been considered including diffusion effects. An equation for the concentration profile due to diffusion effects along the GPC column was considered to be a Fickian function and polystyrene narrow standards were used to determine effective diffusion coefficients. The molecular weight distribution function of mono and poly disperse polymers was interpreted as a sum of several Fickian functions representing a sample formed by only few kind of polymer chains with specific molecular weight and diffusion coefficient. Proposed model accurately fit the concentration profile along the whole elution time range as checked by the computed standard deviation. Molecular weights obtained by this new method are similar to those obtained by MALS or traditional GPC while polydispersity index values are intermediate between those obtained by the traditional GPC combined to Universal Calibration method and the MALS method. Values for Pearson and Lin coefficients shows improvement in the correlation of polydispersity index values determined by GPC and MALS methods when diffusion coefficients and new methods are used.