Abstract
The structure and material properties of polymer networks can depend sensitively on changes in the environment. There is a great deal of progress in the development of stimuli-responsive hydrogels for applications like sensors, self-repairing materials or actuators. Biocompatible, smart hydrogels can be used for applications, such as controlled drug delivery and release, or for artificial muscles. Numerical studies have been performed on different length scales and levels of details. Macroscopic theories that describe the network systems with the help of continuous fields are suited to study effects like the stimuli-induced deformation of hydrogels on large scales. In this article, we discuss various macroscopic approaches and describe, in more detail, our phase field model, which allows the calculation of the hydrogel dynamics with the help of a free energy that considers physical and chemical impacts. On a mesoscopic level, polymer systems can be modeled with the help of the self-consistent field theory, which includes the interactions, connectivity, and the entropy of the polymer chains, and does not depend on constitutive equations. We present our recent extension of the method that allows the study of the formation of nano domains in reversibly crosslinked block copolymer networks. Molecular simulations of polymer networks allow the investigation of the behavior of specific systems on a microscopic scale. As an example for microscopic modeling of stimuli sensitive polymer networks, we present our Monte Carlo simulations of a filament network system with crosslinkers.
Highlights
If you put a gummy bear into a glass of water, the day you will find the same bear grown in volume by more than a factor of five. (The effect depends on the choice of Gummy bears.) This is a very simple example of a polymer network that is strongly responsive to the stimuli of the environment
Properties of polymer networks can be studied on a microscopic level with the help of Monte Carlo simulations and molecular dynamic simulations, in which molecular details of the system can be investigated explicitly
We have studied the system with the help of Monte Carlo simulations
Summary
If you put a gummy bear into a glass of water, the day you will find the same bear grown in volume by more than a factor of five. (The effect depends on the choice of Gummy bears.) This is a very simple example of a polymer network that is strongly responsive to the stimuli of the environment (in this case humidity). Different kinds of smart polymer networks are sensitive to different stimuli, such as temperature changes [1,2], illumination [3,4], or properties of the solvent, such as the pH value [1,5,6,7], the ion concentration [7,8], or the chemical composition [5,8,9,10]. The starting point of the self-consistent field theory is the exact statistically physical description of a polymer model system so that constitutive equations are not required. ]. we discuss molecular modeling techniques and present, as an example, a Monte Carlo study of a network formed by stiff polymers and physical crosslinkers that, depending on external parameters, parameters, can change its structural and topological properties [24,25]. We have developed a phase field model, which avoids the precise localization of the phase boundaries and can be coupled with other phase fields that may describe descri additional phases in the system
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