Stress in a stimuli-responsive polymer brush

The application of a polymer brush in sensing, actuation, self-folding, among others acutely depends on the tuneable bending of a brush-grafted substrate caused by the stress in the brush. However, the stress in a stimuli-responsive brush has not been investigated. In this work, we study the stress in the stimuli-responsive planar polymer brushes of neutral water-soluble polymers with low to very high graft densities using strong stretching theory (SST). First, SST with the Langevin force-extension relation for a polymer chain is extended to the study of stimuli-responsive brushes. Stress profile and other properties of a Poly(N-isopropylacrylamide) (PNIPAm) brush are then obtained using the extended SST and an empirical Flory-Huggins parameter. The model predicts that the stress in a PNIPAm brush is inhomogeneous and compressive at all temperatures and graft densities. The resultant stress is predicted to increase in magnitude with increasing graft density. Moreover, it decreases in magnitude with an increase in temperature before plateauing in low graft density brushes. In contrast, its magnitude increases weakly with increasing temperature in high density brushes. This contrasting behavior is traced to the minimum in interaction free energy density \emph{vs} polymer volume fraction curve for PNIPAm solution at a large volume fraction, and stiffening of chains due to finite extensibility. Furthermore, our results indicate that the ability to tune the resultant stress by changing temperature diminishes with increasing graft density

Wave propagation in two-dimensional periodic lattices

International audiencePlane wave propagation in infinite two-dimensional periodic lattices is investigated using Floquet-Bloch principles. Frequency bandgaps and spatial filtering phenomena are examined in four representative planar lattice topologies: hexagonal honeycomb, Kagomé lattice, triangular honeycomb, and the square honeycomb. These topologies exhibit dramatic differences in their long-wavelength deformation properties. Long-wavelength asymptotes to the dispersion curves based on homogenization theory are in good agreement with the numerical results for each of the four lattices. The slenderness ratio of the constituent beams of the lattice (or relative density) has a significant influence on the band structure. The techniques developed in this work can be used to design lattices with a desired band structure. The observed spatial filtering effects due to anisotropy at high frequencies (short wavelengths) of wave propagation are consistent with the lattice symmetries

Stress in a Stimuli-Responsive Polymer Brush

This work studies the stress in stimuli-responsive planar polymer brushes of neutral water-soluble polymers with low to very high graft densities using strong stretching theory (SST). SST with the Langevin force–extension relation for a polymer chain is extended to the study of stimuli-responsive brushes. The stress profile and other structural properties of a poly(N-isopropylacrylamide) (PNIPAm) brush are then obtained using the extended SST and an empirical Flory–Huggins parameter. The swelling ratio predicted by our model is in good qualitative agreement with experimental measurements from the literature. Our model predicts that the stress in a PNIPAm brush is inhomogeneous and compressive at all temperatures and graft densities. The resultant stress is predicted to increase in magnitude with increasing graft density. A temperature increase results in a decrease in the resultant stress magnitude in low graft density brushes but a mild increase in high density brushes. This contrasting behavior arises from the minimum in the interaction free energy density versus polymer volume fraction curve for a PNIPAm solution at a large volume fraction and the stiffening of chains due to finite extensibility. Our results indicate that the ability to tune the resultant stress by changing the temperature diminishes with increasing graft density

Tuning the thermal conductivity of silicon nanowires by surface passivation

Using large scale molecular dynamics simulations, we study the thermal conductivity of bare and surface passivated silicon nanowires (SiNWs). For the smaller cross-sectional widths $w$, SiNWs become unstable because of the surface amorphousization and even evaporation of a certain fraction of Si atoms when $w \leq 2$ nm. Our results suggest that the surface (in--)stability is related to a large excess energy $\Delta$ of the surface Si atoms with respect to the bulk Si. This is because the surface Si atoms being less coordinated and having dangling bonds. As a first step of our study, we propose a practically relevant method that uses $\Delta$ as a guiding tool to passivate these dangling bonds and thus stabilizes SiNWs. The surface stabilization is achieved by passivation of Si atoms by hydrogen or oxygen. These passivated SiNWs are then used for the calculation of the thermal conductivity coefficient $\kappa$. While the expected trend of $\kappa \propto w$ is observed for all SiNWs, surface passivation provides an added flexibility of tuning $\kappa$ with the surface coverage concentration $c$ of passivated atoms. Analyzing the phonon band structures via spectral energy density, we discuss separate contributions from the surface and the core to $\kappa$. The effect of passivation on SiNW stiffness is also discussed

A fast algorithm for exact sequence search in biological sequences using polyphase decomposition

Motivation: Exact sequence search allows a user to search for a specific DNA subsequence in a larger DNA sequence or database. It serves as a vital block in many areas such as Pharmacogenetics, Phylogenetics and Personal Genomics. As sequencing of genomic data becomes increasingly affordable, the amount of sequence data that must be processed will also increase exponentially. In this context, fast sequence search algorithms will play an important role in exploiting the information contained in the newly sequenced data. Many existing algorithms do not scale up well for large sequences or databases because of their high-computational costs. This article describes an efficient algorithm for performing fast searches on large DNA sequences. It makes use of hash tables of Q-grams that are constructed after downsampling the database, to enable efficient search and memory use. Time complexity for pattern search is reduced using beam pruning techniques. Theoretical complexity calculations and performance figures are presented to indicate the potential of the proposed algorithm