Olga Kuksenok

Tailoring the structure of polymer networks with iniferter-mediated photo-growth

Using dissipative particle dynamics (DPD), we developed a computational approach to capture the photo-controlled radical polymerization (“photo-growth”) of polymer gels containing trithiocarbonate (TTC) groups within the network strands. Using this model, we focused on a “primary gel” and illuminated the sample to activate the TTCs, which then interacted with monomer and cross-linker in the solution. At low TTC concentrations, gels composed of compatible monomers formed two distinct, spatially separated layers. Conversely, at high TTC concentration, gels formed from incompatible components displayed a well-intermixed structure. Hence, in the presence of light, variations in the TTC concentration provide a new approach for controllably tailoring the structure of polymer gels, and thereby tailoring the functionality of the network.

Controlling deformations of gel-based composites by electromagnetic signals within the GHz frequency range

Using theoretical and computational modeling, we focus on dynamics of gels filled with uniformly dispersed ferromagnetic nanoparticles subjected to electromagnetic (EM) irradiation within the GHz frequency range. As a polymer matrix, we choose poly(N-isopropylacrylamide) gel, which has a low critical solution temperature and shrinks upon heating. When these composites are irradiated with a frequency close to the Ferro-Magnetic Resonance (FMR) frequency, the heating rate increases dramatically. The energy dissipation of EM signals within the magnetic nanoparticles results in the heating of the gel matrix. We show that the EM signal causes volume phase transitions, leading to large deformations of the sample for a range of system parameters. We propose a model that accounts for the dynamic coupling between the elastodynamics of the polymer gel and the FMR heating of magnetic nanoparticles. This coupling is nonlinear: when the system is heated, the gel shrinks during the volume phase transition, and the particle concentration increases, which in turn results in an increase of the heating rates as long as the concentration of nanoparticles does not exceed a critical value. We show that the system exhibits high selectivity to the frequency of the incident EM signal and can result in a large mechanical feedback in response to a small change in the applied signal. These results suggest the design of a new class of soft active gel-based materials remotely controlled by low power EM signals within the GHz frequency range.

Designing Highly Thermostable Lysozyme–Copolymer Conjugates: Focus on Effect of Polymer Concentration

Designing biomaterials capable of functioning in harsh environments is vital for a range of applications. Using molecular dynamics simulations, we show that conjugating lysozymes with a copolymer [poly(GMA- stat-OEGMA)] comprising glycidyl methacrylate (GMA) and oligo(ethylene glycol) methyl ether methacrylate (OEGMA) results in a dramatic increase of stability of these enzymes at high temperatures provided that the concentration of the copolymer in the close vicinity of the enzyme exceeds a critical value. In our simulations, we use triads containing the same ratio of GMA to OEGMA units as in our recent experiments (N. S. Yadavalli et al., ACS Catalysis, 2017, 7, 8675). We focus on the dynamics of the conjugate at high temperatures and on its structural stability as a function of the copolymer/water content in the vicinity of the enzyme. We show that the dynamics of phase separation in the water-copolymer mixture surrounding the enzyme is critical for the structural stability of the enzyme. Specifically, restricting water access promotes the structural stability of the lysozyme at high temperatures. We identified critical water concentration below which we observe a robust stabilization; the phase separation is no longer observed at this low fraction of water so that the water domains promoting unfolding are no longer formed in the vicinity of the enzyme. This understanding provides a basis for future studies on designing a range of enzyme-copolymer conjugates with improved stability.

CHAPTER 4:Modeling the Interaction of Active Cilia with Species in Solution: From Chemical Reagents to Microscopic Particles

Biological cilia can sense minute chemical variations or the presence of particulates in their environment, transmit this information to their neighbors, and thereby produce a global response to a local change. Using computational modeling, we demonstrate two distinct examples of analogous sensing and communicating behavior performed by artificial cilia. In the first example, cilia formed from chemo‐responsive gels undergo the oscillatory Belousov–Zhabotinsky (BZ) reaction. The activator for the reaction, u, is generated within these BZ cilia and diffuses between the neighboring gels. By varying the spatial arrangement of the BZ cilia, we not only alter the directionality of the traveling waves within the array, but also uncover a distinctive form of chemotaxis, where the tethered gels bend towards higher concentrations of u and, hence, towards each other. We also show that the cilial oscillations can be controlled remotely and non‐invasively by light. In our second example, we model the transport of a microscopic particle via a regular array of beating elastic cilia, whose tips experience an adhesive interaction with the particle’s surface. By varying the cilia–particle adhesion strength and the cilia stiffness, we pinpoint the parameters where the particle can be ‘released’, ‘propelled’ or ‘trapped’ by the cilial layer.