Generalized dipole correction for charged surfaces in the repeated-slab approach

First-principles calculations of surfaces or two-dimensional materials with a finite surface charge invariably include an implicit or explicit compensating countercharge. We show that an ideal constant-charge counterelectrode in the vacuum region can be introduced by means of a simple correction to the electrostatic potential in close analogy to the well-known dipole correction for charge-neutral asymmetric slabs. Our generalized dipole correction accounts simultaneously for the sheet-charge electrode and the huge voltage built up between the system of interest and the counterelectrode. We demonstrate its usefulness for two prototypical cases, namely, field evaporation in the presence of huge electric fields (20 V/nm) and the modeling of charged defects at an insulator surface. We also introduce algorithmic improvements to charge initialization and preconditioning in the density functional theory algorithm that proved crucial for ensuring rapid convergence in slab systems with high electric fields

Molecular modeling to study dendrimers for biomedical applications

© 2014 by the authors; licensee MDPI; Basel; Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/). Date of Acceptance: 17/11/2014Molecular modeling techniques provide a powerful tool to study the properties of molecules and their interactions at the molecular level. The use of computational techniques to predict interaction patterns and molecular properties can inform the design of drug delivery systems and therapeutic agents. Dendrimers are hyperbranched macromolecular structures that comprise repetitive building blocks and have defined architecture and functionality. Their unique structural features can be exploited to design novel carriers for both therapeutic and diagnostic agents. Many studies have been performed to iteratively optimise the properties of dendrimers in solution as well as their interaction with drugs, nucleic acids, proteins and lipid membranes. Key features including dendrimer size and surface have been revealed that can be modified to increase their performance as drug carriers. Computational studies have supported experimental work by providing valuable insights about dendrimer structure and possible molecular interactions at the molecular level. The progress in computational simulation techniques and models provides a basis to improve our ability to better predict and understand the biological activities and interactions of dendrimers. This review will focus on the use of molecular modeling tools for the study and design of dendrimers, with particular emphasis on the efforts that have been made to improve the efficacy of this class of molecules in biomedical applications.Peer reviewedFinal Published versio

Implementation of the LANS-alpha turbulence model in a primitive equation ocean model

This paper presents the first numerical implementation and tests of the Lagrangian-averaged Navier-Stokes-alpha (LANS-alpha) turbulence model in a primitive equation ocean model. The ocean model in which we work is the Los Alamos Parallel Ocean Program (POP); we refer to POP and our implementation of LANS-alpha as POP-alpha. Two versions of POP-alpha are presented: the full POP-alpha algorithm is derived from the LANS-alpha primitive equations, but requires a nested iteration that makes it too slow for practical simulations; a reduced POP-alpha algorithm is proposed, which lacks the nested iteration and is two to three times faster than the full algorithm. The reduced algorithm does not follow from a formal derivation of the LANS-alpha model equations. Despite this, simulations of the reduced algorithm are nearly identical to the full algorithm, as judged by globally averaged temperature and kinetic energy, and snapshots of temperature and velocity fields. Both POP-alpha algorithms can run stably with longer timesteps than standard POP. Comparison of implementations of full and reduced POP-alpha algorithms are made within an idealized test problem that captures some aspects of the Antarctic Circumpolar Current, a problem in which baroclinic instability is prominent. Both POP-alpha algorithms produce statistics that resemble higher-resolution simulations of standard POP. A linear stability analysis shows that both the full and reduced POP-alpha algorithms benefit from the way the LANS-alpha equations take into account the effects of the small scales on the large. Both algorithms (1) are stable; (2) make the Rossby Radius effectively larger; and (3) slow down Rossby and gravity waves.Comment: Submitted to J. Computational Physics March 21, 200

Formation control of nonholonomic mobile robots using implicit polynomials and elliptic Fourier descriptors

This paper presents a novel method for the formation control of a group of nonholonomic mobile robots using implicit and parametric descriptions of the desired formation shape. The formation control strategy employs implicit polynomial (IP) representations to generate potential fields for achieving the desired formation and the elliptical Fourier descriptors (EFD) to maintain the formation once achieved. Coordination of the robots is modeled by linear springs between each robot and its two nearest neighbors. Advantages of this new method are increased flexibility in the formation shape, scalability to different swarm sizes and easy implementation. The shape formation control is first developed for point particle robots and then extended to nonholonomic mobile robots. Several simulations with robot groups of different sizes are presented to validate our proposed approach

Formation control of multiple robots using parametric and implicit representations

A novel method is presented for formation control of a group of autonomous mobile robots using parametric and implicit descriptions of the desired formation. Shape formation is controlled by using potential fields generated from Implicit Polynomial (IP) representations and the control for keeping the desired shape is designed using Elliptical Fourier Descriptors (EFD). Coordination of the robots is modeled by linear springs between each robot and its nearest two neighbors. This approach offers more flexibility in the formation shape and scales well to different swarm sizes and to heterogeneous systems. The method is simulated on robot groups with different sizes to form various formation shapes