Development of Dissipative Particle Dynamics framework for modeling hydrogels with degradable bonds
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MRS Advances © 2020 Materials Research Society DOI: 10.1557/adv.2020.148
Development of Dissipative Particle Dynamics framework for modeling hydrogels with degradable bonds Vaibhav Palkar1, Chandan K. Choudhury1, Olga Kuksenok1* 1
Department of Materials Science and Engineering, Clemson University, Clemson, SC, 29634
*Email: [email protected]
ABSTRACT
Controlled degradation of hydrogels enables several applications of these materials, including controlled drug and cell release applications and directed growth of neural networks. These applications motivate the need of a simulation framework for modeling controlled degradation in hydrogels. We develop a Dissipative Particle Dynamics (DPD) framework for hydrogel degradation. As a model hydrogel, we prepare a network formed by end-linking tetra-arm polyethylene glycol precursors. We model bond breaking during degradation of this hydrogel as a stochastic process. The fraction of degradable bonds follows first order degradation kinetics. We characterize the rate of mass loss during degradation process.
INTRODUCTION Controlled degradation of the polymer network can be introduced in hydrogels enabling usage of these materials in a range of applications [1,2]. As an example of controlled degradation, gels with multiple degradation modes ranging between 10-2 – 10-5 s-1 have been synthesized [3] by incorporating multiple crosslinks in the polymer network. Similarly, hydrogels with multiple crosslinks which break in response to different wavelengths of light have been synthesized [4,5]. Such hydrogels can be used in selective drug [5] and cell [4] release applications. In degradation-based drug release applications, the rate of degradation reaction is essential in controlling drug release kinetics from the hydrogel [6]. This is in contrast to diffusion-based release platforms and swelling-based release platforms where the diffusion of encapsulated species and
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rates of hydrogel network swelling correspondingly determine release kinetics [6]. Hydrogel degradation and subsequent drug release can be triggered as a response to external stimuli [7] such as pH [8] or light [9]. Apart from drug release applications, controlled and directed hydrogel degradation using a 2-photon laser can be utilized to develop a platform for directed growth of neural networks [2]. Existence of these systems motivates the need of a numerical framework for simulating hydrogel degradation. Mass loss profiles from degrading hydrogels provide insights into the degradation mechanism. Bulk degradation, as opposed to surface erosion, demonstrates sudden fast mass loss due to reverse gelation of the hydrogel network [10]. Bulk degrading nanogel samples [11] and larger hydrogel samples of millimeter thickness [10] have previously been shown to exhibit fast mass
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