Simulation of Organic Liquid Products Deoxygenation by Multistage Countercurrent Absorber/Stripping Using CO2 as Solvent with Aspen-HYSYS: Thermodynamic Data Basis and EOS Modeling

In this work, the thermodynamic data basis and equation of state (EOS) modeling necessary to simulate the fractionation of organic liquid products (OLP), a liquid reaction product obtained by thermal catalytic cracking of palm oil at 450 °C, 1.0 atmosphere, with 10% (wt.) Na2CO3 as catalyst, in multistage countercurrent absorber/stripping columns using supercritical carbon dioxide (SC-CO2) as solvent, with Aspen-HYSYS was systematically investigated. The chemical composition of OLP was used to predict the density (ρ), boiling temperature (Tb), critical temperature (Tc), critical pressure (Pc), critical volume (Vc), and acentric factor (ω) of all the compounds present in OLP by applying the group contribution methods of Marrero-Gani, Han-Peng, Marrero-Pardillo, Constantinou-Gani, Joback and Reid, and Vetere. The RK-Aspen EOS used as thermodynamic fluid package, applied to correlate the experimental phase equilibrium data of binary systems OLP-i/CO2 available in the literature. The group contribution methods selected based on the lowest relative average deviation by computing Tb, Tc, Pc, Vc, and ω. For n-alkanes, the method of Marrero-Gani selected for the prediction of Tc, Pc and Vc, and that of Han-Peng for ω. For alkenes, the method of Marrero-Gani selected for the prediction of Tb and Tc, Marrero-Pardillo for Pc and Vc, and Han-Peng for ω. For unsubstituted cyclic hydrocarbons, the method of Constantinou-Gani selected for the prediction of Tb, Marrero-Gani for Tc, Joback for Pc and Vc, and the undirected method of Vetere for ω. For substituted cyclic hydrocarbons, the method of Constantinou-Gani selected for the prediction of Tb and Pc, Marrero-Gani for Tc and Vc, and the undirected method of Vetere for ω. For aromatic hydrocarbon, the method of Joback selected for the prediction of Tb, Constantinou-Gani for Tc and Vc, Marrero-Gani for Pc, and the undirected method of Vetere for ω. The regressions show that RK-Aspen EOS was able to describe the experimental phase equilibrium data for all the binary pairs undecane-CO2, tetradecane-CO2, pentadecane-CO2, hexadecane-CO2, octadecane-CO2, palmitic acid-CO2, and oleic acid-CO2, showing average absolute deviation for the liquid phase (AADx) between 0.8% and 1.25% and average absolute deviation for the gaseous phase (AADy) between 0.01% to 0.66%.

Prediction of the Miscibility of PBAT/PLA Blends

Designing polymer structures and polymer blends opens opportunities to improve the performance of plastics. Blending poly(butylene adipate-co-terephthalate) (PBAT) and polylactide (PLA) is a cost-effective approach to achieve a new sustainable material with complementary properties. This study aimed to predict the theoretical miscibility of PBAT/PLA blends at the molecular level. First, the basic properties and the structure of PBAT and PLA are introduced, respectively. Second, using the group contribution methods of van Krevelen and Hoy, the Hansen and Hildebrand solubility parameters of PBAT and PLA were calculated, and the effect of the molar ratio of the monomers in PBAT on the miscibility with PLA was predicted. Third, the dependence of the molecular weight on the blend miscibility was simulated using the solubility parameters and Flory–Huggins theory. Next, the glass transition temperature of miscible PBAT/PLA blends, estimated using the Fox equation, is shown graphically. According to the prediction and simulation, the blends with a number-average molecular weight of 30 kg/mol for each component were thermodynamically miscible at 296 K and 463 K with the possibility of spinodal decomposition at 296 K and 30% volume fraction of PBAT. This study contributes to the strategic synthesis of PBAT and the development of miscible PBAT/PLA blends.

Polymer genome–based prediction of gas permeabilities in polymers

Predicting gas permeabilities of polymers a priori is a long-standing challenge within the membrane research community that has important applications for membrane process design and ultimately widespread adoption of membrane technology. From early attempts based on free volume and cohesive energy to more recent group contribution methods, the ability to predict membrane permeability has improved in terms of accuracy. However, these models usually stay “within the paper”, i.e. limited model details are provided to the wider community such that adoption of these predictive platforms is limited. In this work, we combined an advanced polymer chemical structure fingerprinting method with a large experimental database of gas permeabilities to provide unprecedented prediction precision over a large range of polymer classes. No prior knowledge of the polymer is needed for the prediction other than the repeating unit chemical formula. In addition, we have incorporated this model into the existing Polymer Genome project to make it open to the membrane research community.

Property Data Estimation for Hemiformals, Methylene Glycols and Polyoxymethylene Dimethyl Ethers and Process Optimization in Formaldehyde Synthesis

Polyoxymethylene dimethyl ethers (OMEn) are frequently discussed as alternative diesel fuels, with various synthesis routes considered. OME3–5 syntheses demand significant amounts of thermal energy due to the complex separation processes that they entail. Therefore, innovative process designs are needed. An important tool for the development of new processes is process simulation software. To ensure sound process simulations, reliable physico-chemical models and component property data are necessary. Herein we present the implementation of a state-of-the-art thermodynamic model to describe the component systems of formaldehyde-water and formaldehyde-methanol using Microsoft® Excel (2010, Microsoft Corp, Redmond, WA, USA) and Aspen Plus®, (V8.8, Aspen Tech, Bedford, MA, USA) determine the deviation between the calculated results and experimental literature data, and minimize the deviation by means of parameter fitting. To improve the accuracy of the estimation of the missing property data of hemiformals and methylene glycols formed from formaldehyde using group contribution methods, the normal boiling points were estimated based on molecular analogies. The boiling points of OME6-10 are determined through parameter regression in accordance with the vapor pressure equation. As an application example, an optimization of the product separation of the state-of-the-art formaldehyde synthesis is presented that helps decrease the losses of methanol and formaldehyde in flue gas and wastewater.

A Global Model for the Estimation of Speeds of Sound in Deep Eutectic Solvents

Deep eutectic solvents (DESs) are newly introduced green solvents that have attracted much attention regarding fundamentals and applications. Of the problems along the way of replacing a common solvent by a DES, is the lack of information on the thermophysical properties of DESs. This is even more accentuated by considering the dramatically growing number of DESs, being made by the combination of vast numbers of the constituting substances, and at their various molar ratios. The speed of sound is among the properties that can be used to estimate other important thermodynamic properties. In this work, a global and accurate model is proposed and used to estimate the speed of sound in 39 different DESs. This is the first general speed of sound model for DESs. The model does not require any thermodynamic properties other than the critical properties of the DESs, which are themselves calculated by group contribution methods, and in doing so, make the proposed method entirely independent of any experimental data as input. The results indicated that the average absolute relative deviation percentages (AARD%) of this model for 420 experimental data is only 5.4%. Accordingly, based on the achieved results, the proposed model can be used to predict the speeds of sound of DESs.