56 research outputs found
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 C<sub>6</sub> 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
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
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 Surfactants’ Properties using Multiscale Molecular Modeling Tools: A Review
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
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