Multiscale Modelling of Polymer Self-Assembly in Binary Solvent Mixtures

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Effect of different good solvents in flash nano-precipitation via multi-scale population balance modeling-CFD coupling approach

A computational and modeling approach is used to highlight the key factors that affect polymer nanoparticles (NP) formation in flash nano-precipitation (FNP), when the good solvent, e.g., acetone, is replaced by acetonitrile, tetrahydrofuran and tert-butanol. A population balance model is coupled with computational fluid dynamics to study the kinetics effects on FNP. The mean NP size is predicted in terms of mean radius of gyration via the Flory law of real polymers. The effect of different good solvents is modeled in terms of solute–solvent interactions, using the Flory–Huggins theory and Hansen solubility parameters. Promising results show how the proposed methodology is able to investigate the role played by different good solvents, analyzing single factors at the time. A deep insight into both the dynamics of mixing and the dynamics of aggregation is therefore reached and the main mechanisms involved are pointed out, showing a good agreement with experimental data

Molecules as building blocks for a CFD-PBE model to describe the effect of fluid dynamics on nanoparticle formation

Recently research efforts have focused on the effect of fluid dynamics on particle formation processes, by using special mixing devices, that allow to perform controlled experiments, and complex models, that allow to quantify its influence on the final particle size. The standard modelling approach consists in considering three different steps: nucleation, molecular growth and aggregation. This is usually done by simulating the process with a population balance equation (PBE) coupled with computational fluid dynamics (CFD), in which these three different steps are considered separately. The PBE is often written using as internal coordinate the actual particle size or volume; here, we propose a new modelling strategy that overcomes the concepts of nucleation and molecular growth, by using as internal coordinate the number of molecules which aggregate, or self-assemble, together forming a nanoparticle. The novel modelling approach is therefore defined as a purely-aggregative model

Nanoprobes to interrogate nonspecific interactions in lipid bilayers: from defect-mediated adhesion to membrane disruption

When a lipid membrane approaches a material/nanomaterial, nonspecific adhesion may occur. The interactions responsible for nonspecific adhesions can either preserve the membrane integrity or lead to its disruption. Despite the importance of the phenomenon, there is still a lack of clear understanding of how and why nonspecific adhesions may originate different resulting scenarios and how these interaction scenarios can be interrogated. This work aims at bridging this gap by investigating the interplay between cationic electrostatic and hydrophobic interactions in modulating the membrane stability during nonspecific adhesion phenomena. Here, the stability of the membrane has been studied employing anisotropic nanoprobes in zwitterionic lipid membranes with the support of coarse-grained molecular dynamics simulations to interpret the experimental observations. Lipid membrane electrical measurements and nanoscale visualization in combination with molecular dynamics simulations revealed the phenomena driving nonspecific adhesion. Any interaction with the lipidic bilayer is defect-mediated involving cationic electrostatically-driven lipid extractions and hydrophobicallydriven chains protrusion, whose interplay determines the existence of a thermodynamic optimum for the membrane structural integrity. These findings unlock unexplored routes to exploit nonspecific adhesion in lipid membranes. The proposed platform can act as a straightforward probing tool to locally interrogate interactions between synthetic materials and lipid membranes for the design of antibacterials, antivirals, and scaffolds for tissue engineering

Extended Charge-on-Particle Optimized Potentials for Liquid Simulation Acetone Model: The Case of Acetone-Water Mixtures

It is well-known that classical molecular dynamics simulations of acetone–water mixtures lead to a strong phase separation when using most of the standard all-atom force fields, despite the well-known experimental fact that acetone is miscible with water in any proportion at room temperature. We describe here the use of a charge-on-particle model for accounting for the induced polarization effect in acetone–water mixtures which can solve the demixing problem at all acetone molar fractions. The polarizability effect is introduced by means of a virtual site (VS) on the carbonyl group of the acetone molecule, which increases its dipole moment and leads to a better affinity with water molecules. The VS parameter is set by fitting the density of the mixture at different acetone molar fractions. The main novelty of the VS approach lies on the transferability and universality of the model because the polarizability can be controlled without modifying the force field adopted, like previous efforts did. The results are satisfactory also in terms of the transport properties, that is, diffusivity and viscosity coefficients of the mixture

A novel multiscale model for the simulation of polymer flash nano-precipitation

Numerous models describe the flash nano-precipitation (FNP) process to form polymer nanoparticles, however most of them are based on equilibrium approaches and are not capable of predicting kinetically stable configurations. Moreover, since FNP occurs through solvent-displacement, the way in which the solvent and anti-solvent are mixed plays an important role, which is often overlooked. Here we propose a multiscale approach, which combines molecular dynamics (MD), a Smoluchowski population balance equation (PBE) and computational fluid dynamics (CFD), to model the FNP process, from the atomistic-scale up to the macro-scale. The particle formation process is not described with the usual nucleation-and-growth approach, but as Brownian aggregation of the polymer molecules into nanoparticles. Being the final nanoparticles amorphous, no energy barrier to the aggregation process is considered, whereas the effects of both turbulent mixing and turbulent aggregation on the evolution of the nanoparticles are accounted for. The main novelty of this work is that the aggregation kernel appearing in the PBE, coupled in turn with CFD, is calculated from MD simulations, following the multiscale modeling paradigm. The model is tested on the FNP of poly-ε-caprolactone nanoparticles in acetone-water mixtures. Predictions for the final mean nanoparticle size are found in good agreement with experiments, especially at high initial polymer concentrations, where the hypothesis of no energy barrier is more realistic

Soft matter self-assembly in acetone-water mixtures: a multiscale modeling approach

This work focuses on macromolecule (poly-ε-caprolactone, PCL) self-assembly in acetone/water mixtures by a novel multiscale approach which combines molecular dynamics (MD), a Smoluchowski population balance model (PBM) and computational fluid dynamics (CFD), to model the self-assembly process from the atomistic to the macro-scale