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

Alginate: properties and biomedical applications

Microfabricated integrated circuits revolutionized computation by vastly reducing the space, labor, and time required for calculations. Microfluidic systems hold similar promise for the large-scale automation of chemistry and biology, suggesting the possibility of numerous experiments performed rapidly and in parallel, while consuming little reagent. While it is too early to tell whether such a vision will be realized, significant progress has been achieved, and various applications of significant scientific and practical interest have been developed. Here a review of the physics of small volumes (nanoliters) of fluids is presented, as parametrized by a series of dimensionless numbers expressing the relative importance of various physical phenomena. Specifically, this review explores the Reynolds number Re, addressing inertial effects; the Peclet number Pe, which concerns convective and diffusive transport; the capillary number Ca expressing the importance of interfacial tension; the Deborah, Weissenberg, and elasticity numbers De, Wi, and El, describing elastic effects due to deformable microstructural elements like polymers; the Grashof and Rayleigh numbers Gr and Ra, describing density-driven flows; and the Knudsen number, describing the importance of noncontinuum molecular effects. Furthermore, the long-range nature of viscous flows and the small device dimensions inherent in microfluidics mean that the influence of boundaries is typically significant. A variety of strategies have been developed to manipulate fluids by exploiting boundary effects; among these are electrokinetic effects, acoustic streaming, and fluid-structure interactions. The goal is to describe the physics behind the rich variety of fluid phenomena occurring on the nanoliter scale using simple scaling arguments, with the hopes of developing an intuitive sense for this occasionally counterintuitive world.

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Microfluidics: Fluid physics at the nanoliter scale

This review summarizes theoretical progress in the field of active matter, placing it in the context of recent experiments. This approach offers a unified framework for the mechanical and statistical properties of living matter: biofilaments and molecular motors in vitro or in vivo, collections of motile microorganisms, animal flocks, and chemical or mechanical imitations. A major goal of this review is to integrate several approaches proposed in the literature, from semimicroscopic to phenomenological. In particular, first considered are ``dry'' systems, defined as those where momentum is not conserved due to friction with a substrate or an embedding porous medium. The differences and similarities between two types of orientationally ordered states, the nematic and the polar, are clarified. Next, the active hydrodynamics of suspensions or ``wet'' systems is discussed and the relation with and difference from the dry case, as well as various large-scale instabilities of these nonequilibrium states of matter, are highlighted. Further highlighted are various large-scale instabilities of these nonequilibrium states of matter. Various semimicroscopic derivations of the continuum theory are discussed and connected, highlighting the unifying and generic nature of the continuum model. Throughout the review, the experimental relevance of these theories for describing bacterial swarms and suspensions, the cytoskeleton of living cells, and vibrated granular material is discussed. Promising extensions toward greater realism in specific contexts from cell biology to animal behavior are suggested, and remarks are given on some exotic active-matter analogs. Last, the outlook for a quantitative understanding of active matter, through the interplay of detailed theory with controlled experiments on simplified systems, with living or artificial constituents, is summarized.

Hydrodynamics of soft active matter

Part I: Fundamentals 1. Introduction to Complex Fluids 1.3 Rheological Measurements and Properties 1.4 Kinematics and Stress 1.5 Flow, Slip, and Yield 1.6 Structural Probes of Complex Fluids 1.7 Computational Methods 1.8 The Stress Tensor 1.9 Summary 2. Basic Forces 2.1 Intoduction 2.3 Van der Waals Interactions 2.4 Electrostatic Interactions 2.5 Hydrogen-Bonding, Hydrophobic, and Other Interactions 2.6 Summary Part II: Polymers, Glassy Liquids, and Polymer Gels 3. Polymers 3.1 Introduction 3.2 Equilibrium Properties 3.3 Intrinsic Viscosity and Overlap Concentration 3.4 Elementary Molecular Theories 3.5 Linear Viscoelasticity and Time-Temperature Superposition 3.6 The Rheology of Dilute Polymer Solutions 3.7 The Rheology of Entangled Polymers 3.8 Summary 4. Glassy Liquids 4.1 Introduction 4.2 Phenomenology of the Glass Transition 4.3 Free-Volume Theories 4.4 Entropy Theories 4.5 Nonlinear Relaxation and Aging 4.6 Mode-Coupling Theory and Colloidal Hard-Sphere Glasses 4.7 Analog Models 4.8 Rheology of Glassy Liquids 4.9 Summary 5. Polymer Gels 5.1 Introduction 5.2 Gelation Theoies 5.3 Rheology of Chemical Gels and Near-Gels 5.4 Rheology of Physical Gels 5.5 Summary Part III: Suspensions 6. Particulate Suspensions 6.1 Introduction 6.2 Hard, and Slightly Deformable Spheres 6.3 Nonspherical Particles 6.4 Electrically Charged Particles 6.5 Particles in Viscoelastic Liquids: "Filled Melts" 6.6 Summary 7. Particulate Gels 7.1 Introduction 7.2 Particle Interactions in Suspensions 7.3 Rheology of Particulate Gels 7.4 Summary 8. Electro- and Magneto-Responsive Suspensions 8.1 Introduction 8.2 Electrorheological Fluids 8.3 Magnetorheological Fluids 8.4 Ferrofluids 8.5 Summary 9. Foams, Emulsions, and Blends 9.1 Introduction 9.2 Emulsion Preparation 9.3 Rheology of Emulsions and Immiscible Blends 9.4 Structure and Coarsening of Foams 9.5 Rheology of Foams 9.6 Summary Part IV: Liquid Crystals and Self-Assembling Fluids 10. Liquid Crystals 10.1 Introduction 10.2 Nematics 10.3 Cholesterics: Chiral Nemantics 10.4 Smectics 10.5 Summary 11. Liquid Crystalline Polymers 11.1 Introduction 11.2 Molecular Characteristics of Liquid Crystalline Polymers 11.3 Flow Properties of Nematic LCP's 11.4 Molecular Dynamics of Polymeric Nematics 11.5 Molecular Theory for the Rheology of Polymeric Nematics 11.6 Summary 12. Surfactant Solutions 12.1 Introduction 12.2 Methods of Predicting Microstructures 12.3 Disordered Micellar Solutions 12.4 Surfactant Liquid Crystals 12.5 Summary 13. Block Copolymers 13.1 Introduction 13.2 Thermodynamics of Block Copolymers 13.3 Rheology and Shear-Aligning of Block Copolymers 13.4 Summary Appendix: Momentum-Balance Equations in the Absence of Inertia

The Structure and Rheology of Complex Fluids

Many biologically interesting phenomena occur on a time scale that is too long to be studied by atomistic simulations. These phenomena include the dynamics of large proteins and self-assembly of biological materials. Coarse-grained (CG) molecular modeling allows computer simulations to be run on length and time scales that are 2–3 orders of magnitude larger compared to atomistic simulations, providing a bridge between the atomistic and the mesoscopic scale. We developed a new CG model for proteins as an extension of the MARTINI force field. Here, we validate the model for its use in peptide-bilayer systems. In order to validate the model, we calculated the potential of mean force for each amino acid as a function of its distance from the center of a dioleoylphosphatidylcholine (DOPC) lipid bilayer. We then compared amino acid association constants, the partitioning of a series of model pentapeptides, the partitioning and orientation of WALP23 in DOPC lipid bilayers and a series of KALP peptides in dimyris...

The MARTINI Coarse-Grained Force Field: Extension to Proteins

We show here both experimentally and theoretically that the formation of “coffee-ring” deposits observed at the edge of drying water droplets requires not only a pinned contact line (Deegan et al. Nature 1997, 389, 827) but also suppression of Marangoni flow. For simple organic fluids, deposition actually occurs preferentially at the center of the droplet, due to a recirculatory flow driven by surface-tension gradients produced by the latent heat of evaporation. The manipulation of this Marangoni flow in a drying droplet should allow one in principle to control and redirect evaporation-driven deposition and assembly of colloids and other materials.

Marangoni effect reverses coffee-ring depositions.

The evaporation of a sessile droplet with a pinned contact line is investigated experimentally, by analytic theory and by computation using the finite element method (FEM). Because of the low value of R2/Dtf = cv(1 − H)/ρ = 1.4 × 10-5, where R is the contact-line radius, D is the water vapor diffusivity, cv is the saturated water vapor concentration, H is the relative humidity, and ρ is the liquid water density, the evaporation can be considered as a quasi-steady-state process. Hence, the vapor concentration distribution above the droplet satisfies the Laplace equation but with a time-varying droplet surface. It is found both theoretically and experimentally that the net evaporation rate from the droplet remains almost constant with time for a small initial contact angle (θ < 40°), even though the evaporation flux becomes more strongly singular at the edge of the droplet as the contact angle decreases during evaporation. We also measured the critical contact angle at which the contact line starts to reced...

Ronald G. Larson

Papers

The Structure and Rheology of Complex Fluids

The MARTINI Coarse-Grained Force Field: Extension to Proteins

Marangoni effect reverses coffee-ring depositions.

Evaporation of a Sessile Droplet on a Substrate

Constitutive equations for polymer melts and solutions