Tunneling and delocalization in hydrogen bonded systems: a study in position and momentum space

Novel experimental and computational studies have uncovered the proton momentum distribution in hydrogen bonded systems. In this work, we utilize recently developed open path integral Car-Parrinello molecular dynamics methodology in order to study the momentum distribution in phases of high pressure ice. Some of these phases exhibit symmetric hydrogen bonds and quantum tunneling. We find that the symmetric hydrogen bonded phase possesses a narrowed momentum distribution as compared with a covalently bonded phase, in agreement with recent experimental findings. The signatures of tunneling that we observe are a narrowed distribution in the low-to-intermediate momentum region, with a tail that extends to match the result of the covalently bonded state. The transition to tunneling behavior shows similarity to features observed in recent experiments performed on confined water. We corroborate our ice simulations with a study of a particle in a model one-dimensional double well potential that mimics some of the effects observed in bulk simulations. The temperature dependence of the momentum distribution in the one-dimensional model allows for the differentiation between ground state and mixed state tunneling effects.Comment: 14 pages, 13 figure

Discrete molecular dynamics studies of the folding of a protein-like model

Background: Many attempts have been made to resolve in time the folding of model proteins in computer simulations. Different computational approaches have emerged. Some of these approaches suffer from the insensitivity to the geometrical properties of the proteins (lattice models), while others are computationally heavy (traditional MD). Results: We use a recently-proposed approach of Zhou and Karplus to study the folding of the protein model based on the discrete time molecular dynamics algorithm. We show that this algorithm resolves with respect to time the folding --- unfolding transition. In addition, we demonstrate the ability to study the coreof the model protein. Conclusion: The algorithm along with the model of inter-residue interactions can serve as a tool to study the thermodynamics and kinetics of protein models.Comment: 15 pages including 20 figures (Folding & Design in press

Numerical analysis of a planar wave propagation based micropropulsion system

Micropropulsion mechanisms differ from macro scale counterparts owing to the domination of viscous forces in microflows. In essence, propulsion mechanisms such as cilia and flagella of single celled organisms can be deemed as nature’s solution to a challenging problem, and taken as a basis for the design of an artificial micropropulsion system. In this paper we present numerical analysis of the flow due to oscillatory planar waves propagating on microstrips. The time-dependent three-dimensional flow due to moving boundaries of the strip is governed by incompressible Navier-Stokes equations in a moving coordinate system, which is modeled by means of an arbitrary Lagrangian-Eulerian formulation. The fluid medium surrounding the actuator boundaries is bounded by a channel, and neutral boundary conditions are used in the upstream and downstream. Effects of actuation parameters such as amplitude, excitation frequency, wavelength of the planar waves are demonstrated with numerical simulations that are carried out by third party software, COMSOL. Functional-dependencies with respect to the actuation parameters are obtained for the average velocity of the strip and the efficiency of the mechanism

An optimal control approach to cell tracking

Cell tracking is of vital importance in many biological studies, hence robust cell tracking algorithms are needed for inference of dynamic features from (static) in vivo and in vitro experimental imaging data of cells migrating. In recent years much attention has been focused on the modelling of cell motility from physical principles and the development of state-of-the art numerical methods for the simulation of the model equations. Despite this, the vast majority of cell tracking algorithms proposed to date focus solely on the imaging data itself and do not attempt to incorporate any physical knowledge on cell migration into the tracking procedure. In this study, we present a mathematical approach for cell tracking, in which we formulate the cell tracking problem as an inverse problem for fitting a mathematical model for cell motility to experimental imaging data. The novelty of this approach is that the physics underlying the model for cell migration is encoded in the tracking algorithm. To illustrate this we focus on an example of Zebrafish (Danio rerio's larvae) Neutrophil migration and contrast an ad-hoc approach to cell tracking based on interpolation with the model fitting approach we propose in this study