Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Responsive polymer materials can adapt to surrounding environments, regulate transport of ions and molecules, change wettability and adhesion of different species on external stimuli, or convert chemical and biochemical signals into optical, electrical, thermal and mechanical signals, and vice versa. These materials are playing an increasingly important part in a diverse range of applications, such as drug delivery, diagnostics, tissue engineering and 'smart' optical systems, as well as biosensors, microelectromechanical systems, coatings and textiles. We review recent advances and challenges in the developments towards applications of stimuli-responsive polymeric materials that are self-assembled from nanostructured building blocks. We also provide a critical outline of emerging developments.

Emerging applications of stimuli-responsive polymer materials

http://experimentationlab.berkeley.edu/sites/default/files/AFMImages/butt_AFM.pdf

Force measurements with the atomic force microscope: Technique, interpretation and applications

Coinage metals, such as Au, Ag, and Cu, have been important materials throughout history.1 While in ancient cultures they were admired primarily for their ability to reflect light, their applications have become far more sophisticated with our increased understanding and control of the atomic world. Today, these metals are widely used in electronics, catalysis, and as structural materials, but when they are fashioned into structures with nanometer-sized dimensions, they also become enablers for a completely different set of applications that involve light. These new applications go far beyond merely reflecting light, and have renewed our interest in maneuvering the interactions between metals and light in a field known as plasmonics.2–6

In plasmonics, the metal nanostructures can serve as antennas to convert light into localized electric fields (E-fields) or as waveguides to route light to desired locations with nanometer precision. These applications are made possible through a strong interaction between incident light and free electrons in the nanostructures. With a tight control over the nanostructures in terms of size and shape, light can be effectively manipulated and controlled with unprecedented accuracy.3,7 While many new technologies stand to be realized from plasmonics, with notable examples including superlenses,8 invisible cloaks,9 and quantum computing,10,11 conventional technologies like microprocessors and photovoltaic devices could also be made significantly faster and more efficient with the integration of plasmonic nanostructures.12–15 Of the metals, Ag has probably played the most important role in the development of plasmonics, and its unique properties make it well-suited for most of the next-generation plasmonic technologies.16–18

1.1. What is Plasmonics?
Plasmonics is related to the localization, guiding, and manipulation of electromagnetic waves beyond the diffraction limit and down to the nanometer length scale.4,6 The key component of plasmonics is a metal, because it supports surface plasmon polariton modes (indicated as surface plasmons or SPs throughout this review), which are electromagnetic waves coupled to the collective oscillations of free electrons in the metal.

While there are a rich variety of plasmonic metal nanostructures, they can be differentiated based on the plasmonic modes they support: localized surface plasmons (LSPs) or propagating surface plasmons (PSPs).5,19 In LSPs, the time-varying electric field associated with the light (Eo) exerts a force on the gas of negatively charged electrons in the conduction band of the metal and drives them to oscillate collectively. At a certain excitation frequency (w), this oscillation will be in resonance with the incident light, resulting in a strong oscillation of the surface electrons, commonly known as a localized surface plasmon resonance (LSPR) mode.20 This phenomenon is illustrated in Figure 1A. Structures that support LSPRs experience a uniform Eo when excited by light as their dimensions are much smaller than the wavelength of the light.



Figure 1

Schematic illustration of the two types of plasmonic nanostructures discussed in this article as excited by the electric field (Eo) of incident light with wavevector (k). In (A) the nanostructure is smaller than the wavelength of light and the free electrons ...



In contrast, PSPs are supported by structures that have at least one dimension that approaches the excitation wavelength, as shown in Figure 1B.4 In this case, the Eo is not uniform across the structure and other effects must be considered. In such a structure, like a nanowire for example, SPs propagate back and forth between the ends of the structure. This can be described as a Fabry-Perot resonator with resonance condition l=nλsp, where l is the length of the nanowire, n is an integer, and λsp is the wavelength of the PSP mode.21,22 Reflection from the ends of the structure must also be considered, which can change the phase and resonant length. Propagation lengths can be in the tens of micrometers (for nanowires) and the PSP waves can be manipulated by controlling the geometrical parameters of the structure.23

/pdf/controlling-the-synthesis-and-assembly-of-silver-1ktlgomyt6.pdf

Controlling the synthesis and assembly of silver nanostructures for plasmonic applications

Polymerization, Nanopatterning and Characterization of Surface‐Confined, Stimulus‐Responsive Polymer Brushes

Microphase Separation of Resilin-like and Elastin-like Diblock Copolypeptides in Concentrated Solutions.

Understanding of how to integrate DNA molecules with graphene materials is important for the development of biosensors and biomolecular logic circuits. For some of these applications, controlling DNA structural conformation on the graphene substrate is critically important and can be achieved through the use of self-assembled monolayers. Here, we performed all-atom molecular dynamics simulations to understand how various 1-octadecylamine (ODA) coatings of the graphene surface affect the conformation of double-stranded DNA (dsDNA) on the surface. The simulation results demonstrated that dsDNA structures become more stable as ODA concentration increases due to the formation of DNA-ODA hydrogen bonds and reduction of DNA-surface interactions, which aid in retaining internal DNA interactions. Specifically, the interaction of ODA molecules with DNA prevents nucleobases from forming π-π stacking interactions with the surface. Some dsDNA conformations, such as sharp kinks or unwinding, can occur more frequently in DNA with A-T sequences due to weaker pairing interactions than with G-C sequences. Furthermore, our results conclude that both DNA sequence and ODA concentration play an essential role in experimentally observed conformational changes of DNA on the graphene surface.

Effect of Octadecylamine Surfactant on DNA Interactions with Graphene Surfaces.

Colloidal probe microscopy was employed to study normal forces and sliding friction between model cellulose surfaces in aqueous solutions. Hydrodynamic interactions must be accounted for in data analysis. Longrange interactions are governed by double layer forces, and once surfaces contact, by osmotic repulsive forces and visco-elasticity. Increasing the ionic strength decreases surface potentials and increases adhesive forces. Polyelectrolytes cause strong steric repulsion at high surface coverage, where interactions are sensitive to probe velocity. Polymer bridging occurs at low coverage.

Surface Forces and Friction between Cellulose Surfaces in Aqueous Media

The triggered control of interfacial properties on the nanometer scale holds significant promise for actuation in bio-nanotechnology applications where polymeric actuators may manipulate the transport, separation, and detection of biomolecules. To fabricate patterned, stimulus-responsive polymer brushes we have developed several methods that combine surface initiated polymerization (SIP) with dip-pen nanolithography (DPN). Surface-confined, stimulus-responsive polymer brush nanopatterns were fabricated by amplification of DPN patterned, self-assembled monolayers of 16-mercaptohexadecanoic acid on gold surfaces by SIP of N-isopropylacrylamide (NIPAAm). While free radical polymerization yielded only short polymer brushes (DP<50), atom transfer free radical polymerization (ATRP) produced thick, uniform polymer brushes. For free radical polymerization the thickness of the polymer brush layer is a function of the lateral feature size and the initiator density and is maximal at pattern boundaries.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S1946427400144021

Stefan Zauscher

Papers

Polymerization, Nanopatterning and Characterization of Surface‐Confined, Stimulus‐Responsive Polymer Brushes

Microphase Separation of Resilin-like and Elastin-like Diblock Copolypeptides in Concentrated Solutions.

Effect of Octadecylamine Surfactant on DNA Interactions with Graphene Surfaces.

Surface Forces and Friction between Cellulose Surfaces in Aqueous Media

Fabrication of Stimulus-Responsive Polymeric Nanostructures by Proximal Probes