Computational Design of Nanostructured Soft Interfaces: Focus on Shape Changes and Spreading of Cubic Nanogels

Abstract

Understanding the dynamics of gels at soft interfaces is vital for a range of applications, from biocatalysis and drug delivery to enhanced oil recovery applications. Herein, we use dissipative particle dynamics simulations to focus on the shape changes of a cubic nanogel as it adsorbs from the aqueous phase onto the oil–water interface, effectively acting as a compatibilizer. Upon adsorption at the interface, the hydrogel spreads over the interface, adopting various shapes depending on its size and cross-link density. We characterize these shapes by the shape anisotropy and an effective extent of spreading. We highlight the differences between these characteristics for cubic and spherical nanogels and show that the choice of the cubic shape over the spherical one results in a wider range of topographies that could be dynamically prescribed onto the soft interface due to the gels’ adsorption. We first validate our model parameters with respect to the known experimental values for polyacrylamide (PAAm) gels and focus on spreading and shape changes of PAAm nanogels onto the oil–water interfaces. We then probe the behavior of active gels by changing an affinity of the polymer matrix for the solvent, which can be caused by the application of an external stimulus (light, temperature, or change in the chemical composition of solvent). Furthermore, we focus on the interactions between multiple gels placed at the liquid–liquid interface. We show that controlling the shapes and the clustering of the gels at the interfaces via variations in solvent quality result in tailoring the dynamics and topography of soft nanostructured interfaces. Hence, our findings provide insights into the design of soft active nanostructured interfaces with topographies controlled externally via solvent quality.

Highly Oil-Repellent Thermoplastic Boundaries via Surface Delivery of CF3 Groups by Molecular Bottlebrush Additives

“…To quantitatively characterize the evolution of clusters spreading, we calculate the following characteristics: the number of backbone beads in contact with polymer matrix beads and with air beads in PMMA (black curves in Figure g) and in Nylon 6 (red curves in Figure g), respectively; the number of the side chain beads in contact with the air beads (SI: Figure S10); and the shape anisotropy κ 2 in Figure h, which allows us to characterize the transition from the spherical shape of the cluster to a flat layer covering the surface. Notably, shape anisotropy is often used to characterize shapes of various objects with complex geometries − since it scales between κ 2 = 0 for an object with high symmetry (such as spherical or cubic symmetry), κ 2 = 0.25 for a planar object, and κ 2 = 1 for the points on a line …”

Mesoscale Modeling of Agglomeration of Molecular Bottlebrushes: Focus on Conformations and Clustering Criteria

“…We use the dissipative particle dynamics (DPD) approach [72][73][74][75] to model the time evolution and self-assembly in bottlebrush-solvent systems. DPD is a computationally efficient mesoscale approach that has been utilized to model a broad variety of polymer systems [76][77][78][79][80][81][82][83][84][85][86][87][88][89][90][91][92][93][94], including studies of the effects of solvent quality on structural characteristics [95][96][97][98] and self-assembly in various polymer systems [23,79,89]. Herein, we briefly introduce the DPD approach, the details of this approach can be found in [72][73][74].…”

“…The reference parameters in our DPD simulations are chosen as following [74,99]: the beads number density is ρ = 3, the cutoff distance is r c = 1, the strengths of the dissipative and random forces are γ = 4.5 and σ = 3.0, respectively, and the temperature and bead mass are set to unity in reduced DPD units. For the bonded interactions, we set [87] K b = 10 3 and r b = 0.7; notably, high spring constant values were used in a number of recent DPD studies [102][103][104]. The parameters defining mSRP interactions are set as [101] b = 80 and d c = 0.8.…”

Stability and Diffusion Properties of Insulin in Dissolvable Microneedles: A Multiscale Simulation Study

“…Although the speed of protein calculation and simulation has been dramatically improved, the all-atom simulation is no longer applicable once the study subject possesses a μm-to-μs scale, so the mesoscopic DPD simulation has been created . DPD simulation has been extensively used in the simulation of multiple drug delivery fields, such as polymer self-assembly, − pH-responsive carriers, , nanogels, and cell membrane absorption. ,, In a previous work, our research group has prepared a series of hyaluronic acid (HA) MNs and polyvinyl alcohol (PVA) MNs for insulin delivery. ,,, HA and PVA are two kinds of FDA-approved materials with good biocompatibility, and we have also evaluated the safety of these dissolving MNs in animals and confirmed the potential of the prepared MNs in drug delivery. − In this study, the all-atom simulation method has been applied to characterize the interaction between insulin and two polymers, PVA and HA, while DPD simulation has been applied to study the diffusion properties of insulin in polymer solutions, revealing two different insulin diffusion mechanisms. This research will serve as a case of further combining the computer simulation and basic research on MNs and provide a theoretical basis and guidance for the preparation of MNs.…”

“…Although the speed of protein calculation and simulation has been dramatically improved, the all-atom simulation is no longer applicable once the study subject possesses a μm-to-μs scale, so the mesoscopic DPD simulation has been created. 30 DPD simulation has been extensively used in the simulation of multiple drug delivery fields, such as polymer self-assembly, 31−33 pH-responsive carriers, 34,35 nanogels, 36 and cell membrane absorption. 33,37,38 In a previous work, our research group has prepared a series of hyaluronic acid (HA) MNs and polyvinyl alcohol (PVA) MNs for insulin delivery.…”