Molecular dynamics study of the flagella inside the carbon torus

We propose a system that avoids the open ends of the nanotube, we used a device consisting of flagellum (FLA) inside a nanotorus (NT) formed by carbon atoms. The flagellum consists of a C20 nanosphere with fixed size of tail within the NT. The full system consists of a closed loop drive and static nanotubes and nanospheres not static with different sizes of flagella released inside the nanotube, with each simulation, allows the relaxation between (internal and external NT). The nanospheres result in a system that provides movement of Van der Waals. The simulations were done by well-known classic molecular dynamics with standard parameterization. We calculate thermodynamic properties of these devices as heat capacity and molar entropy variation. For this system were obtained properties such as: the speed of nanospheres plagued the efficiency of molecular motor versus time, the kinetic energy, potential energy and total energy in each of the simulations. In our calculations, this system has a number of carbon atoms ranging from (2721 until 2728) with up to almost 10 ps simulation. These facts can be useful for the construction of new molecular machines.     

分子动力学模拟噻吩/正庚烷在PEG膜中溶解-扩散行为

采用分子动力学方法模拟汽油组分在聚乙二醇(PEG)膜中的溶解-扩散行为。吸附动力学模拟结果表明,动力学平衡之后,噻吩与聚合物表面距离明显缩短。PEG对噻吩与正庚烷的吸附能分别为-52.17 kJ/mol和-38.00 kJ/mol。PEG对噻吩的吸附能小于正庚烷,因而PEG对噻吩具有吸附选择性。扩散动力学模拟结果表明,在不同温度下,噻吩的扩散系数均高于正庚烷,PEG对噻吩具有扩散选择性,与实验结果相符。     

The Topology Sampling of H2SO4·NH3 with Meta-Dynamics Method

The configurations of molecular clusters have significant impacts on their growth into fine particles in atmosphere. In this paper, we explore the topology space of the structure of H2SO4·NH3 dimer with a novel sampling technique of meta-dynamics (MTD) method and ab initio molecular dynamics simulations. The simulations are carried out at the temperatures of both 50 K and 242 K, which represent the typical high and low latitudes of troposphere. The results show that, compared with only traditional MD simulations, the structure samplings are significantly accelerated with MTD method. Therefore, more isomers of the dimer are discovered within the same simulation time scale. In addition, the results show that MTD is more efficient for circumstances with high temperature.     

Temporal and steric analysis of ionic permeation and binding in SERCA via molecular dynamic simulations

The availability of the crystal structure of the sarco(endo)plasmic reticulum calcium ATPase (SERCA) has allowed atomic-level molecular dynamic (MD) simulations of this membrane transport protein to be done. The biomedical and nanotechnological implications of this work are discussed as well as the methods of performing the simulations and analysis. We have performed nanosecond timescale simulations of SERCA for several of its known conformations in a lipid/water environment. One simulation contained Ca(2+) ions, while others without ions were analyzed by techniques such as steric pathway determination. We discuss details of the resulting putative cytoplasmic and lumenal pathways, along with experimental evidence from the literature to support our conclusions. Finally, we give a brief overview of future research directions, as they pertain to MD simulations and their analysis. The methodology used in this work shows that significant insight into the structure-function relationship of ion-motive transmembrane pumps can be derived by a combination of simulation tools and analysis techniques including MD trajectories, steric analysis and electrostatic potentials.     

Degradation of the blister agent sulfur mustard, bis(2-chloroethyl) sulfide, on concrete

The products formed from the degradation of the blister agent sulfur mustard [bis(2-chloroethyl) sulfide] on concrete were identified using gas chromatography with mass spectrometry detection (GC/MSD), (1)H NMR, 2D (1)H-(13)C NMR and (13)C solid state magic angle spinning (SSMAS) NMR. In situ and extraction experiments were performed. Sulfur mustard was detected in the in situ (13)C SSMAS samples for 12 weeks, whereas less than 5% of the sulfur mustard was detected in extracts from the concrete monoliths after 8 days. Sulfonium ions and (2-chloroethylthio)ethyl ether (T) were observed on the in situ samples after a period of 12 weeks, whereas vinyl species and bis(2-chloroethyl) sulfoxide were observed in the extracts of the concrete monoliths within 24h. The differences between the extraction and the SSMAS data indicated that the sulfur mustard existed in the concrete in a non-extractable form prior to its degradation. Extraction methods alone were not sufficient to identify the products; methods to identify the presence of non-extractable degradation products were also required.     

模拟聚乙烯块体相变和导热的粗粒化模型和势场建立EI北大核心CSCD

建立适用于介观尺度聚乙烯块体相变和导热分子模拟的粗粒化模型及势场,并对其进行验证。基于全原子分子动力学模拟结果,采用多态-迭代玻尔兹曼变换法进行粗粒化分子动力学模拟来获得粗粒化势场。结果表明:粗粒化势场采用函数形式的势能描述,易于使用;对比全原子模拟结果,粗粒化势场能够较准确地模拟聚乙烯块体的静态结构性质;聚乙烯块体在300 K和500 K下密度的模拟值与实验值误差小于3%,玻璃化转变温度和熔化温度的模拟值与实验值相符较好;单链聚乙烯导热系数的粗粒化势场模拟值与全原子模拟值较一致,无序聚乙烯块体导热系数的模拟值与实验值吻合较好。研究结果为介观尺度聚乙烯的导热研究提供了一种更高效的模拟方法。     

Molecular simulation and electron paramagnetic resonance (EPR) studies of rapid bimolecular reactions in supercritical fluids

We present comparisons among Brownian dynamics simulations, molecular dynamics simulations, and electron paramagnetic resonance spectroscopic studies of the Heisenberg spin-exchange reaction between nitroxide free radicals at near-infinite dilution in near-critical and supercritical ethane. We discuss the effects of correlations in the solute-solute and solvent-solute radial distribution functions on the rate constants for collision and reaction. We find that the enhancements in the local density of solvents around solutes strongly affect the rate constant for solvent-solute encounters. This result holds implications for those reactions where collisional-energy transfer from solvent to solute is the rate-limiting step. While the rate of collisions between solutes is strongly affected by solute-solute correlations for all densities, the reaction rate constant is affected by such local density augmentations only for certain combinations of density and collision lenght scale. Rate constants estimated computationally and experimentally show the same qualitative trend as a function of density. Collision lifetimes estimated from the simulations show a strong density dependence. These lifetimes reflect the competing effects of the intermolecular force and the potential of mean force and are distinctly bimodal at the higher densities.     

The effect of loading on surface roughness at the atomistic level

One of the key points to better understand the origins of friction is to know how two surfaces in contact adhere to one another. In this paper we present molecular dynamics (MD) simulations of two aluminium bodies in contact, exposed to a range of normal loads. The contact surfaces of both aluminium bodies have a self-affine fractal roughness, but the exact roughness varies from simulation to simulation. Both bodies are allowed to have an adhesive interaction and are fully deformable. Tracking important contact parameters (such as contact area, number of contact clusters, and contact pressure) during a simulation is challenging. We propose an algorithm (embedded within a parallel MD code) which is capable of accessing these contact statistics. As expected, our results show that contact area is increasing in proportion with applied load, and that a higher roughness reduces contact area. Contact pressure distributions are compared to theoretical models, and we show that they are shifted into the tensile regime due to the inclusion of adhesion in our model.     

蒙脱土有机改性对丁基橡胶复合材料微观结构与性能的影响

采用季铵盐有机改性蒙脱土(OMMT)与丁基橡胶(IIR)机械共混和硫化制备成复合材料。研究了蒙脱土有机改性前后对复合材料的微观结构、力学和芥子气防护性能的影响。透射电镜(TEM)和X射线衍射(XRD)显示IIR/OMMT复合材料为插层型纳米复合材料,而IIR/MMT为未插层的微米复合材料。复合材料的微观结构和填料的界面活性对其力学性能影响重大,IIR/OMMT复合材料的力学性能明显优于IIR/MMT复合材料的力学性能。添加有机或无机蒙脱土都可使芥子气在丁基橡胶中的扩散系数显著降低。而芥子气在IIR/OMMT中的扩散系数更低,这显示出IIR/OMMT复合材料的芥子气防护性能更加优异。     

The Role of Temperature and Lipid Charge on Intake/Uptake of Cationic Gold Nanoparticles into Lipid Bilayers

Understanding the molecular mechanisms governing nanoparticle–membrane interactions is of prime importance for drug delivery and biomedical applications. Neutron reflectometry (NR) experiments are combined with atomistic and coarse‐grained molecular dynamics (MD) simulations to study the interaction between cationic gold nanoparticles (AuNPs) and model lipid membranes composed of a mixture of zwitterionic di‐stearoyl‐phosphatidylcholine (DSPC) and anionic di‐stearoyl‐phosphatidylglycerol (DSPG). MD simulations show that the interaction between AuNPs and a pure DSPC lipid bilayer is modulated by a free energy barrier. This can be overcome by increasing temperature, which promotes an irreversible AuNP incorporation into the lipid bilayer. NR experiments confirm the encapsulation of the AuNPs within the lipid bilayer at temperatures around 55 °C. In contrast, the AuNP adsorption is weak and impaired by heating for a DSPC–DSPG (3:1) lipid bilayer. These results demonstrate that both the lipid charge and the temperature play pivotal roles in AuNP–membrane interactions. Furthermore, NR experiments indicate that the (negative) DSPG lipids are associated with lipid extraction upon AuNP adsorption, which is confirmed by coarse‐grained MD simulations as a lipid‐crawling effect driving further AuNP aggregation. Overall, the obtained detailed molecular view of the interaction mechanisms sheds light on AuNP incorporation and membrane destabilization.     

Diffusivity of solutes measured in glass capillaries using Taylor's analysis of dispersion and a commercial CE instrument

We present a strategy for the rapid, efficient, and accurate measurement of the coefficient of diffusion (D) of solutes using a commercial capillary electrophoresis (CE) instrument. This approach utilizes the classic analysis of Taylor of the dispersion of solutes pumped hydrostatically through glass capillaries. To obtain accurate values of D, we modified Taylor's analysis of dispersion to account for the finite time required to reach steady-state flow in the capillary when using a CE instrument. Neglecting this effect results in measured diffusivities of phenylalanine, a model solute, that are in error by as much as 60% when compared with published values. We provide an analysis of this effect and a simple strategy for avoiding these errors. Using this approach, we analyze profiles of concentration fronts and measured values of D for phenylalanine to within 5% of published values. We also analyze profiles of pulses of solute. To determine values of D accurately, measurements of dispersion first need to be made as a function of injection volume to correct for the finite width of the injection plug, before they are corrected for unsteady-state flow. This approach also yields values of D for phenylalanine to within 5% of published values. In contrast to other techniques used for the determination of D, this approach requires no fluorescent labeling and is applicable to solutes of any molecular weight.     

Computer simulation of the inclusion of hydrophobic nanoparticles into a lipid bilayer

Understanding influences of nanoparticle (NP) inclusions into a lipid membrane is important in a variety of areas including biological systems and pharmacology. However, the inhomogeneous nature of lipid bilayers on a nanometer length scale complicates experimental studies of membrane inclusion. Here, we have performed coarse-grained molecular dynamics simulations aimed at the influence of the hydrophobic NPs inclusion into the lipid bilayer (dipalmitoylphosphatidylcholine or DPPC bilayer). The immersion of a nanoparticle into the hydrophobic core of the membrane has been observed in the simulation. To gain more insight in the inclusion, we have obtained free energy, entropy, enthalpy, and heat capacity profiles based on umbrella sampling calculations. These results show the inclusion process is driven by the co-action of entropy and enthalpy, which is consistent with some experimental and theoretical observations. Those results could be applied in the design of specific nanoparticles for various biomedical applications.     

Computational steering in Monte Carlo simulations of thin film polystyrene

High molecular weight polymer systems show very long relaxation times, of the order of milliseconds or more. This time-scale proves practically inaccessible for atomic-scale dynamical simulation such as molecular dynamics. Even with a Monte Carlo (MC) simulation, the generation of statistically independent configurations is non-trivial. Many moves have been proposed to enhance the efficiency of MC simulation of polymers. Each is described by a proposal density Q(x'; x): the probability of selecting the trial state x' given that the system is in the current state x. This proposal density must be parametrized for a particular chain length, chemistry and temperature. Choosing the correct set of parameters can greatly increase the rate at which the system explores its configuration space. Computational steering (CS) provides a new methodology for a systematic search to optimize the proposal densities for individual moves, and to combine groups of moves to greatly improve the equilibration of a model polymer system. We show that monitoring the correlation time of the system is an ideal single parameter for characterizing the efficiency of a proposal density function, and that this is best evaluated by a distributed network of replicas of the system, with the operator making decisions based on the averages generated over these replicas. We have developed an MC code for simulating an anisotropic atomistic bead model which implements the CS paradigm. We report simulations of thin film polystyrene.     

Sulfur mustard destruction using ozone, UV, hydrogen peroxide and their combination

Numerous methods are used for destruction of sulfur mustard. Oxidation is one of those methods. There have been only limited data concerning application of the advanced oxidation technologies (AOTs) for mustard destruction available before. In this study sulfur mustard oxidation rate depending on kind of the oxidative system and process parameters used was assessed using selected AOT. The following were selected for mustard oxidation: ozone (O(3)), UV light (UV), hydrogen peroxide (H(2)O(2)); double systems: UV/O(3), UV/H(2)O(2), and O(3)/H(2)O(2); a triple system: O(3)/H(2)O(2)/UV and Fenton reaction. Effectiveness of the selected AOT methods has been evaluated and the most suitable one for mustard destruction was chosen. Using ozone in various combinations with hydrogen peroxide and UV radiation mustard can be destroyed much quicker comparing to the classical oxidizers. Fast mustard oxidation (a few minutes) occurred in those systems where ozone alone was used, or in the following combinations: O(3)/H(2)O(2), O(3)/UV and O(3)/H(2)O(2)/UV. When those advanced oxidation technologies are used, mustard becomes destroyed mainly in course of the direct oxidation with ozone, and reactions of mustard with radicals formed due to ozone action play a secondary role. Rate of sulfur mustard oxidation in the above mentioned ozone-containing oxidative systems decreases with pH value increasing from 2 to 12. Only when pH value of reaction solutions is close to pH 5, mustard oxidation rate is minimal, probably due to "disappearance" of radicals participating in oxidation in this pH. Sulfur mustard can be most effectively destroyed using just ozone in pH 7. In that case mustard destruction rate is only slightly lower than the rate achieved in optimal conditions, and the system is the simplest.     

Probabilistic Analysis and Design of HCP Nanowires:An Efficient Surrogate Based Molecular Dynamics Simulation Approach

We investigate the dependency of strain rate,temperature and size on yield strength of hexagonal close packed(HCP) nanowires based on large-scale molecular dynamics(MD) simulation.A variance-based analysis has been proposed to quantify relative sensitivity of the three controlling factors on the yield strength of the material.One of the major drawbacks of conventional MD simulation based studies is that the simulations are computationally very intensive and economically expensive.Large scale molecular dynamics simulation needs supercomputing access and the larger the number of atoms,the longer it takes time and computational resources.For this reason it becomes practically impossible to perform a robust and comprehensive analysis that requires multiple simulations such as sensitivity analysis,uncertainty quantification and optimization.We propose a novel surrogate based molecular dynamics(SBMD)simulation approach that enables us to carry out thousands of virtual simulations for different combinations of the controlling factors in a computationally efficient way by performing only few MD simulations.Following the SBMD simulation approach an efficient optimum design scheme has been developed to predict optimized size of the nanowire to maximize the yield strength.Subsequently the effect of inevitable uncertainty associated with the controlling factors has been quantified using Monte Carlo simulation.Though we have confined our analyses in this article for Magnesium nanowires only,the proposed approach can be extended to other materials for computationally intensive nano-scale investigation involving multiple factors of influence.     

Evaluation of a grid based molecular dynamics approach for polypeptide simulations

Molecular dynamics is very important for biomedical research because it makes possible simulation of the behavior of a biological macromolecule in silico. However, molecular dynamics is computationally rather expensive: the simulation of some nanoseconds of dynamics for a large macromolecule such as a protein takes very long time, due to the high number of operations that are needed for solving the Newton's equations in the case of a system of thousands of atoms. In order to obtain biologically significant data, it is desirable to use high-performance computation resources to perform these simulations. Recently, a distributed computing approach based on replacing a single long simulation with many independent short trajectories has been introduced, which in many cases provides valuable results. This study concerns the development of an infrastructure to run molecular dynamics simulations on a grid platform in a distributed way. The implemented software allows the parallel submission of different simulations that are singularly short but together bring important biological information. Moreover, each simulation is divided into a chain of jobs to avoid data loss in case of system failure and to contain the dimension of each data transfer from the grid. The results confirm that the distributed approach on grid computing is particularly suitable for molecular dynamics simulations thanks to the elevated scalability.     

Self-decay-induced damage production and micro-structure evolution in fcc metals: An atomic-scale computer simulation approach

In this paper, we discuss the development and application of a hybrid molecular dynamics/kinetic Monte Carlo simulation to model defect production and microstructure evolution in irradiated fcc metals. The molecular dynamics results show that the primary damage state produced by high-energy 30 keV recoils in low melting point, high-Z fcc metals such as Pb and Au is dominated by populations of large vacancy and interstitial clusters, and only a small percentage of the damage is produced as isolated point defects. Kinetic Monte Carlo simulations were used to calculate the fraction of the defects produced by the 30 keV recoils that are able to avoid recombination within their nascent cascade and freely migrate through the lattice. We show that because of in-cascade clustering this fraction is different for vacancies and interstitials and depends strongly on temperature. The results are used to provide a qualitative explanation for the experimentally observed differences in void swelling between fcc and bcc metals. The kinetic Monte Carlo simulations were also used to model damage accumulation in Pb under 30 keV self-recoil irradiation as a function of dose rate and temperature. This revised version was published online in July 2006 with corrections to the Cover Date.     

Metal ion complexes of EDTA: a solute system for density gradient ultracentrifugation analysis of lipoproteins

In the study reported here, we apply some of the features of coordination chemistry to solve a long-standing problem in the separation and characterization of lipoprotein particles. Lipoproteins are circulating micelle-like particles responsible for lipid transport. They exist in three major classes: very-low-density lipoprotein, low-density lipoprotein, and high-density lipoprotein in well-defined density ranges using the density gradient ultracentrifugation (DGU) method. The analytical instrumentation of DGU has improved over the years in response to clinical evidence that certain lipoprotein species are linked to a high risk for developing cardiovascular disease. A long-standing problem has been a lack of appropriate gradient-forming solutes that can generate a useful gradient from a homogeneous solution. We have found that a new class of solutes based on metal ion complexes has the potential of providing a wide selection of compounds where the features can be modulated by choice of ligand, complexing metal ion, and counterion. In this study, we have chosen the cesium salt of BiEDTA (CsBiEDTA) and have investigated the dynamics of density gradient formation in the ultracentrifuge. We show that a useful density gradient can be formed within a few hours beginning with a homogeneous solution. We also present data on the migration behavior of lipoproteins under gradient-forming conditions and show that high-resolution density profiles can be obtained with good precision. The resolution of the CsBiEDTA profile is compared with those obtained using high molecular weight organic solutes.     

A simulation clock-based solution to the frequency domain experiment indexing problem

Frequency domain experiments (FDEs) were introduced to perform system sensitivity analysis for factor screening in complex simulations. Since then, FDEs have been used in simulation optimization, gradient estimation and several other research areas. Central to all FDEs is the Fourier analysis of a sampled data sequence. The choice of an appropriate oscillation index and associated sampling index for the sampled data sequence has been a much researched topic now known in the FDE literature as the indexing problem. In this paper we address the indexing problem by providing some general guidelines on the selection of the oscillation index and considering the implementation of two different indices: the continuous global simulation clock time and an inherently discrete index such as the job index in a simple queuing system. We show that the choice of a discrete oscillation index has to be made in an application-dependent manner and does not generalize well to different discrete-event simulation scenarios. In contrast, because the notion of time underlies all discrete-event simulations, the global simulation clock time is a natural choice for an FDE indexing scheme. Two different schemes for the global simulation clock time are presented. The results are illustrated via different scenarios commonly found in simulations of queuing networks and manufacturing systems.