Using Dissipative Particle Dynamics to Model Effects of Chemical Reactions Occurring within Hydrogels

Abstract

Computational models that reveal the structural response of polymer gels to changing, dissolved reactive chemical species would provide useful information about dynamically evolving environments. However, it remains challenging to devise one computational approach that can capture all the interconnected chemical events and responsive structural changes involved in this multi-stage, multi-component process. Here, we augment the dissipative particle dynamics (DPD) method to simulate the reaction of a gel with diffusing, dissolved chemicals to form kinetically stable complexes, which in turn cause concentration-dependent deformation of the gel. Using this model, we also examine how the addition of new chemical stimuli and subsequent reactions cause the gel to exhibit additional concentration-dependent structural changes. Through these DPD simulations, we show that the gel forms multiple latent states (not just the “on/off”) that indicate changes in the chemical composition of the fluidic environment. Hence, the gel can actuate a range of motion within the system, not just movements corresponding to the equilibrated swollen or collapsed states. Moreover, the system can be used as a sensor, since the structure of the layer effectively indicates the presence of chemical stimuli.

Structure and Dynamic Evolution of Interfaces between Polymer Solutions and Gels and Polymer Interdiffusion: A Molecular Dynamics Study

“…Computer simulations can give molecular insights into the structure of such interfaces and the mechanisms of solvent diffusion into the gel. While there have been numerous theoretical − and simulation studies on polymer gels, − as well as computer models simulating various reaction methods to create microgels, − comparatively few studies have been dedicated to gel–liquid interfaces. − At the same time, we are not aware of any work on interfaces between polymer networks and polymer solutions.…”

Crosslinker energy landscape effects on dynamic mechanical properties of ideal polymer hydrogels

“…20 Several computational efforts to fundamentally understand similar relationships have also been conducted, with a few notable examples including analytical 21 or Monte-Carlo models 22 of the reaction kinetics of reversible bonds for self-healing polymer networks, theoretical models for isolating the properties of reversible crosslinks within a polymer network, 12 and hybrid computational models on the role of crosslinker strengths on the toughness of networks. [23][24][25][26] These models have enabled detailed molecular understandings on the role of crosslinker on network dynamic mechanical properties. Our previous work also sought to bridge these two approaches by using the calculated energy landscape of a few crosslinker chemistries to predict the experimental relaxation time of an ideal polymer network crosslinked by those chemistries.…”

Mesoscale modeling of random chain scission in polyethylene melts

“…Recent developments and applications of DPD can be found in recent reviews by Español and Warren [37] and Santo and Neimark [38]. In particular, DPD has been used to model a range of reactive polymer systems [39][40][41][42][43][44][45][46][47][48][49][50]. A modified segmental repulsive potential (mSRP) introduced by Sirk et al [51] effectively minimizes topological violations or unphysical crossing of polymer chains, addressing this well-known limitation of the standard DPD approach.…”