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

BACKGROUND Synthetic membranes are used for desalination, dialysis, sterile filtration, food processing, dehydration of air and other industrial, medical, and environmental applications due to low energy requirements, compact design, and mechanical simplicity. New applications are emerging from the water-energy nexus, shale gas extraction, and environmental needs such as carbon capture. All membranes exhibit a trade-off between permeability—i.e., how fast molecules pass through a membrane material—and selectivity—i.e., to what extent the desired molecules are separated from the rest. However, biological membranes such as aquaporins and ion channels are both highly permeable and highly selective. Separation based on size difference is common, but there are other ways to either block one component or enhance transport of another through a membrane. Based on increasing molecular understanding of both biological and synthetic membranes, key design criteria for new membranes have emerged: (i) properly sized free-volume elements (or pores), (ii) narrow free-volume element (or pore size) distribution, (iii) a thin active layer, and (iv) highly tuned interactions between permeants of interest and the membrane. Here, we discuss the permeability/selectivity trade-off, highlight similarities and differences between synthetic and biological membranes, describe challenges for existing membranes, and identify fruitful areas of future research. ADVANCES Many organic, inorganic, and hybrid materials have emerged as potential membranes. In addition to polymers, used for most membranes today, materials such as carbon molecular sieves, ceramics, zeolites, various nanomaterials (e.g., graphene, graphene oxide, and metal organic frameworks), and their mixtures with polymers have been explored. Simultaneously, global challenges such as climate change and rapid population growth stimulate the search for efficient water purification and energy-generation technologies, many of which are membrane-based. Additional driving forces include wastewater reuse from shale gas extraction and improvement of chemical and petrochemical separation processes by increasing the use of light hydrocarbons for chemicals manufacturing. OUTLOOK Opportunities for advancing membranes include (i) more mechanically, chemically, and thermally robust materials; (ii) judiciously higher permeability and selectivity for applications where such improvements matter; and (iii) more emphasis on fundamental structure/property/processing relations. There is a pressing need for membranes with improved selectivity, rather than membranes with improved permeability, especially for water purification. Modeling at all length scales is needed to develop a coherent molecular understanding of membrane properties, provide insight for future materials design, and clarify the fundamental basis for trade-off behavior. Basic molecular-level understanding of thermodynamic and diffusion properties of water and ions in charged membranes for desalination and energy applications such as fuel cells is largely incomplete. Fundamental understanding of membrane structure optimization to control transport of minor species (e.g., trace-organic contaminants in desalination membranes, neutral compounds in charged membranes, and heavy hydrocarbons in membranes for natural gas separation) is needed. Laboratory evaluation of membranes is often conducted with highly idealized mixtures, so separation performance in real applications with complex mixtures is poorly understood. Lack of systematic understanding of methodologies to scale promising membranes from the few square centimeters needed for laboratory studies to the thousands of square meters needed for large applications stymies membrane deployment. Nevertheless, opportunities for membranes in both existing and emerging applications, together with an expanding set of membrane materials, hold great promise for membranes to effectively address separations needs.

http://science.sciencemag.org/content/sci/356/6343/eaab0530.full.pdf

Maximizing the right stuff: The trade-off between membrane permeability and selectivity

For several centuries fluid dynamics studies have relied upon the assumption that when a liquid flows over a solid surface, the liquid molecules adjacent to the solid are stationary relative to the solid. This no-slip boundary condition (BC) has been applied successfully to model many macroscopic experiments, but has no microscopic justification. In recent years there has been an increased interest in determining the appropriate BCs for the flow of Newtonian liquids in confined geometries, partly due to exciting developments in the fields of microfluidic and microelectromechanical devices and partly because new and more sophisticated measurement techniques are now available. An increasing number of research groups now dedicate great attention to the study of the flow of liquids at solid interfaces, and as a result a large number of experimental, computational and theoretical studies have appeared in the literature. We provide here a review of experimental studies regarding the phenomenon of slip of Newtonian liquids at solid interfaces. We dedicate particular attention to the effects that factors such as surface roughness, wettability and the presence of gaseous layers might have on the measured interfacial slip. We also discuss how future studies might improve our understanding of hydrodynamic BCs and enable us to actively control liquid slip.

https://iopscience.iop.org/article/10.1088/0034-4885/68/12/R05/pdf

Boundary slip in Newtonian liquids: a review of experimental studies

The Yen–Mullins model, also known as the modified Yen model, specifies the predominant molecular and colloidal structure of asphaltenes in crude oils and laboratory solvents and consists of the following: The most probable asphaltene molecular weight is ∼750 g/mol, with the island molecular architecture dominant. At sufficient concentration, asphaltene molecules form nanoaggregates with an aggregation number less than 10. At higher concentrations, nanoaggregates form clusters again with small aggregation numbers. The Yen–Mullins model is consistent with numerous molecular and colloidal studies employing a broad array of methodologies. Moreover, the Yen–Mullins model provides a foundation for the development of the first asphaltene equation of state for predicting asphaltene gradients in oil reservoirs, the Flory–Huggins–Zuo equation of state (FHZ EoS). In turn, the FHZ EoS has proven applicability in oil reservoirs containing condensates, black oils, and heavy oils. While the development of the Yen–Mullin...

Advances in Asphaltene Science and the Yen–Mullins Model

Chemical compositions of improved model asphalt systems for molecular simulations

Metal–organic frameworks (MOFs) are porous crystals with the potential to improve many industrial gas separation processes Because there is a practically unlimited number of different MOFs, which vary in their pore geometry and chemical composition, it is challenging to find the best MOF for a given application Here, we applied high-throughput computational methods to rapidly explore thousands of possible MOFs, given a library of starting materials, in the context of Xe/Kr separation We generated over 137 000 structurally diverse hypothetical MOFs from a library of chemical building blocks and screened them for Xe/Kr separation For each MOF, we calculated geometric properties via Delaunay tessellation and predicted thermodynamic Xe/Kr adsorption behavior via multicomponent grand canonical Monte Carlo simulations Specifically, we calculated the pore limiting diameter, largest cavity diameter, accessible void volume, as well as xenon and krypton adsorption at 10, 50 and 10 bar at 273 K From these data we show that MOFs with pores just large enough to fit a single xenon atom, and having morphologies resembling tubes of uniform width, are ideal for Xe/Kr separation Finally, we compare our generated MOFs to several known structures (IRMOF-1, HKUST-1, ZIF-8, Pd-MOF, & MOF-505) and conclude that significantly improved materials remain to be synthesized All crystal structure files are freely available for download and browsing in an online database

Thermodynamic analysis of Xe/Kr selectivity in over 137000 hypothetical metal–organic frameworks

Molecular simulations have been used to estimate the properties of three-component mixtures whose constituents were chosen to represent the chemical families found in paving asphalts Naphthene aromatics and saturates were represented by 1,7-dimethylnaphthalene and n-C22, respectively Two different asphaltene model structures were considered The first has a large aromatic core with a few short side chains; the second contains a moderate size aromatic core with larger branches Both types have been proposed in the recent literature based on experimental characterizations of asphaltene fractions Properties calculated from atomistic molecular simulations of the mixtures include density and isothermal compressibility (inverse of bulk modulus) The thermodynamic properties suggest a high-frequency glass transition above 25 °C for both model mixtures The mixture based on the more aromatic asphaltene shows a more pronounced transition and has a higher bulk modulus For a polymer-modified model asphalt, the c

Analyzing properties of model asphalts using molecular simulation

Molecular dynamics simulation was used to calculate rotational relaxation time, diffusion coefficient, and zero-shear viscosity for a pure aromatic compound (naphthalene) and for aromatic and aliphatic components in model asphalt systems over a temperature range of 298–443 K. The model asphalt systems were chosen previously to represent real asphalt. Green–Kubo and Einstein methods were used to estimate viscosity at high temperature (443.15 K). Rotational relaxation times were calculated by nonlinear regression of orientation correlation functions to a modified Kohlrausch–Williams–Watts function. The Vogel–Fulcher–Tammann equation was used to analyze the temperature dependences of relaxation time, viscosity, and diffusion coefficient. The temperature dependences of viscosity and relaxation time were related using the Debye–Stokes–Einstein equation, enabling viscosity at low temperatures of two model asphalt systems to be estimated from high temperature (443.15 K) viscosity and temperature-dependent relaxa...

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Relaxation time, diffusion, and viscosity analysis of model asphalt systems using molecular simulation

The fatigue-cracking life of an asphalt mixture measured in the laboratory is generally a small fraction of the fatigue-cracking life observed in the field. One of the reasons for this large difference is the self-healing property of asphalt binders. Self-healing is a process that reverses the growth of fatigue cracks during rest periods between load applications. A thorough understanding of the healing mechanism is required to accurately model and predict the influence of healing on the fatigue-cracking life of asphalt mixtures. Previous studies have used experimental evidence to demonstrate a correlation between chemistry of asphalt functional groups, such as chain length and branching, and healing measured in asphalt binders. One of the mechanisms of healing is the self-diffusion of molecules across the crack interface. This paper demonstrates the use of molecular simulation techniques to investigate the correlation of chain length and chain branching to self-diffusivity of binder molecules. The findings reported in this paper are consistent with observations reported in previous studies and expand on the understanding of the relationship between molecular architecture, self-diffusivity, and self-healing properties of asphalt binders.

Michael L. Greenfield

Papers

Chemical compositions of improved model asphalt systems for molecular simulations

Thermodynamic analysis of Xe/Kr selectivity in over 137000 hypothetical metal–organic frameworks

Analyzing properties of model asphalts using molecular simulation

Relaxation time, diffusion, and viscosity analysis of model asphalt systems using molecular simulation

Use of Molecular Dynamics to Investigate Self-Healing Mechanisms in Asphalt Binders