NEW DESCRIPTORS TO CHARACTERIZE POROUS MATERIALS

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Aspects of asphaltene aggregation obtained from coarse-grained molecular modeling

We have performed a molecular-simulation-based study to explore some of the underlying mechanisms of asphaltene aggregation. The daunting complexity of the crude oil + asphaltene system precludes any type of meaningful molecular simulation unless some assumptions are made with respect to the key physical and chemical properties that must be explicitly described. In the present work, we focus on molecular simulations of a coarse-grained model of asphaltene molecules in pure solvents, which are based on the assumption that the general size asymmetry and asphaltene morphology play a key role in the aggregation process. We use simple single isotropic Lennard-Jones sites to represent paraffinic and aromatic C₆ segments, which are used as building blocks for the description of continental asphaltene models and solvent moieties. The energy and size parameters for the intermolecular models (ε and σ) for solute and solvent molecules are chosen to reproduce the experimental density of the liquid phase for different mixtures. An explicit pure solvent is considered, and the relationship between the aggregation mechanism and the solvent nature is investigated through direct simulation of the aggregation process. The results reproduce accurately expected trends observed for more-complex models as well as experiments, for example, strong aggregation of asphaltene molecules in <i>n-</i>heptane and high solubility in toluene. Different asphaltene models based on different geometries reveal that even at this level of simplification the topology of the molecules (number and position of aliphatic branches) does affect the way molecules aggregate

NEW DESCRIPTORS TO CHARACTERIZE POROUS MATERIALS

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Prediction of Surfactants’ Properties using Multiscale Molecular Modeling Tools: A Review

During one of the existing Enhanced Oil Recovery (EOR) procedures, a mixture of Alkaline/Surfactant/Polymer (ASP) is injected into wells in order to move the trapped oil from the reservoir to the wellbores. The conception and/or the tuning of new ASP combinations, structures of surfactants and/or mixtures of surfactants is of primary interest to improve the efficiency of a such procedure. Molecular modeling tools can be used to understand microscopic effects, predict surfactants’ properties and finally to optimize structures and mixtures of surfactants. We propose in this article a review of the literature on the ability of molecular simulation techniques such as Molecular Dynamics (MD), Monte Carlo (MC) simulations, Dissipative Particle Dynamics (DPD) and upper scale modeling methods such as Quantitative Structure-Property Relationship (QSPR) approaches to predict thermo-physical and structural properties of surfactants

Prediction of Surfactants’ Properties using Multiscale Molecular Modeling Tools: A Review

During one of the existing Enhanced Oil Recovery (EOR) procedures, a mixture of Alkaline/Surfactant/Polymer (ASP) is injected into wells in order to move the trapped oil from the reservoir to the wellbores. The conception and/or the tuning of new ASP combinations, structures of surfactants and/or mixtures of surfactants is of primary interest to improve the efficiency of a such procedure. Molecular modeling tools can be used to understand microscopic effects, predict surfactants’ properties and finally to optimize structures and mixtures of surfactants. We propose in this article a review of the literature on the ability of molecular simulation techniques such as Molecular Dynamics (MD), Monte Carlo (MC) simulations, Dissipative Particle Dynamics (DPD) and upper scale modeling methods such as Quantitative Structure-Property Relationship (QSPR) approaches to predict thermo-physical and structural properties of surfactants. Une des voies possibles de récupération assistée du pétrole, l’EOR (Enhanced Oil Recovery), consiste en l’injection d’un fluide ASP (Alkaline/Surfactant/Polymer) dans le réservoir dans le but de déplacer le pétrole piégé vers le puits de production. La conception et/ou l’optimisation de mélanges ASP, de tensioactifs ou de mélanges de tensioactifs est donc d’un intérêt premier pour améliorer l’efficacité d’un tel procédé. Les codes de simulation moléculaire développés et largement validés durant ces dernières décennies apparaissent comme des outils incontournables pour la compréhension des effets microscopiques, la prédiction de propriétés de tensioactifs complexes ou encore l’optimisation des structures voire de la composition de mélanges de tensioactifs. Dans cet article, nous présentons une revue des travaux de la littérature sur le potentiel de diverses techniques de simulation moléculaire pour la prédiction de propriétés structurales ou thermophysiques des tensioactifs. Les techniques de simulation auxquelles nous nous sommes intéressés sont la dynamique moléculaire (MD), les simulations Monte Carlo (MC), la dissipative particle dynamics (DPD) ainsi que des approches statistiques faisant un lien direct entre structure et propriété (QSPR, pour Quantitative Structure-Property Relationship)

The role of molecular interactions in the change of sign of the Soret coefficient

The change of sign with composition in aqueous mixtures of associating fluids is analyzed by means of molecular-dynamics simulations. The results obtained are in quantitative agreement with the experimental data in water-ethanol and water-methanol solutions, which exhibit the mentioned change of sign. A subsequent theoretical analysis is addressed to establish a relationship between the dependence of the Soret coefficient with composition with the existence of large inter-species interactions. Although the change of sign of the Soret coefficient with composition is not only due to the so-called chemical contribution analyzed here, we discuss the role that these interactions play in such a change of sign

Prediction of critical micelle concentration for per- and polyfluoroalkyl substances

In this study, we focus on the development of Quantitative Structure-Property Relationship (QSPR) models to predict the critical micelle concentration (CMC) for per- and polyfluoroalkyl substances (PFASs). Experimental CMC values for both fluorinated and non-fluorinated compounds were meticulously compiled from existing literature sources. Our approach involved constructing two distinct types of models based on Support Vector Machine (SVM) algorithms applied to the dataset. Type (I) models were trained exclusively on CMC values for fluorinated compounds, while Type (II) models were developed utilizing the entire dataset, incorporating both fluorinated and non-fluorinated compounds. Comparative analyses were conducted against reference data, as well as between the two model types. Encouragingly, both types of models exhibited robust predictive capabilities and demonstrated high reliability. Subsequently, the model having the broadest applicability domain was selected to complement the existing experimental data, thereby enhancing our understanding of PFAS behaviour.</p

Guest-induced gate-opening of a zeolite imidazolate framework

3 Aguado, Sonia Bergeret, Gerard Titus, Marc Pera Moizan, Virginie Nieto-Draghi, Carlos Bats, Nicolas Farrusseng, DavidThe zinc benzimidazolate coordination polymer (ZIF-7) shows a reversible gate-opening effect upon variation of partial pressure of CO2 or temperature. This phenomenon, which is unique for a MOF with sodalite topology, arises from a phase-to-phase transformation upon guest adsorption-desorption