Equilibrium clusters in suspensions of colloids interacting via potentials with a local minimum

In simple colloidal suspensions, clusters are various multimers that result from colloid self-association and exist in equilibrium with monomers.There are two types of potentials that are known to produce clusters: a) potentials that result from the competition between short-range attraction and long-range repulsion and are characterized by a global minimum and a repulsive tail and b) purely repulsive potentials which have a soft shoulder. Using computer simulations, we demonstrate in this work that potentials with a local minimum and a repulsive tail, not belonging to either of the known types, are also capable of generating clusters. A detailed comparative analysis shows that the new type of cluster-forming potential serves as a bridge between the other two. The new clusters are expanded in shape and their assembly is driven by entropy, like in the purely repulsive systems but only at low density. At high density, clusters are collapsed and stabilized by energy, in common with the systems with competing attractive and repulsive interactions.Comment: 12 pages, 7 figure

Viscoelastic model for the dynamic structure of binary systems

This paper presents the viscoelastic model for the Ashcroft-Langreth dynamic structure factors of liquid binary mixtures. We also provide expressions for the Bhatia-Thornton dynamic structure factors and, within these expressions, show how the model reproduces both the dynamic and the self-dynamic structure factors corresponding to a one-component system in the appropriate limits (pseudobinary system or zero concentration of one component). In particular we analyze the behavior of the concentration-concentration dynamic structure factor and longitudinal current, and their corresponding counterparts in the one-component limit, namely, the self dynamic structure factor and self longitudinal current. The results for several lithium alloys with different ordering tendencies are compared with computer simulations data, leading to a good qualitative agreement, and showing the natural appearance in the model of the fast sound phenomenon.Comment: 20 pages, 19 figures, submitted to PR

Bridge function for liquid Na

Bridge function B(r) for liquid Na is calculated in the referense hypernetted chain approximation from the pair distribution function obtained by means of MD simulations. A comparison with the bridge function obtained in a Mori-Hoshino-Watabe scheme is made. The influence of the cut-off radius and the MD sample size on the structure factor is investigated.Елементарні діаграми B(r) для рідкого Na розраховані в базисному гіперланцюговому наближенні з парних функцій розподілу отриманих методом МД. Проведено порівняння з B(r) в наближенні Морі-Хошіно-Ватабе. Досліджено залежність статичного структурного фактора від радіуса обрізання базисної парної функції розподілу

Finite-size dependence of the bridge function extracted from molecular dynamics simulations

金沢大学理学部The bridge function for liquid sodium at T5373 K is obtained by using the mean spherical approximation to extrapolate the pair distribution function ~PDF!, calculated in molecular dynamics ~MD! simulations, beyond the half simulation box length for two sizes of the MD system. The bridge function is found to strongly depend on the total number of particles used in the simulation cell. This dependency leads to a spurious maximum of the static structure factor at long wavelengths, obtained from the reference hypernetted-chain approximation ~RHNC! with the MD system used as a reference system ~RHNC-MD!. A simple self-consistent procedure, proposed to account for the finite-size effects in the bridge function, allows one to efficiently correct the RHNC-MD static structure factor for all unphysical manifestations

Glass transition in an off-lattice protein model studied by molecular dynamics simulations.

金沢大学理学部In this paper we report the results of a numerical investigation of the glass transition phenomenon in a minimalist protein model. The inherent structure theory of Stillinger and Weber was applied to an off-lattice protein model with a native state b-sheet motif. By using molecular dynamics simulations and the steepest descent method, sets of local potential energy minima were generated for the model over a range of temperatures. The mean potential energy of the inherent structures allowed to make rough estimates of the glasstransition temperature TK . More accurately TK was computed by direct evaluations of the total and vibrational entropies. It is found that for the present model the thermodynamic ratio of the folding and glass-transition temperatures is 1.7 which is in good agreement with experimental observations

Molecular Dynamics Simulation of Semiflexible Polyampholyte Brushes - The Effect of Charged Monomers Sequence

Planar brushes formed by end-grafted semiflexible polyampholyte chains, each chain containing equal number of positively and negatively charged monomers is studied using molecular dynamics simulations. Keeping the length of the chains fixed, dependence of the average brush thickness and equilibrium statistics of the brush conformations on the grafting density and the salt concentration are obtained with various sequences of charged monomers. When similarly charged monomers of the chains are arranged in longer blocks, the average brush thickness is smaller and dependence of brush properties on the grafting density and the salt concentration is stronger. With such long blocks of similarly charged monomers, the anchored chains bond to each other in the vicinity of the grafting surface at low grafting densities and buckle toward the grafting surface at high grafting densities.Comment: 8 pages,7 figure

A Condensation-Ordering Mechanism in Nanoparticle-Catalyzed Peptide Aggregation

Nanoparticles introduced in living cells are capable of strongly promoting the aggregation of peptides and proteins. We use here molecular dynamics simulations to characterise in detail the process by which nanoparticle surfaces catalyse the self- assembly of peptides into fibrillar structures. The simulation of a system of hundreds of peptides over the millisecond timescale enables us to show that the mechanism of aggregation involves a first phase in which small structurally disordered oligomers assemble onto the nanoparticle and a second phase in which they evolve into highly ordered beta-sheets as their size increases

Why are MD simulated protein folding times wrong?

The question of significant deviations of protein folding times simulated using molecular dynamics from experimental values is investigated. It is shown that in the framework of Markov State Model (MSM) describing the conformational dynamics of peptides and proteins, the folding time is very sensitive to the simulation model parameters, such as forcefield and temperature. Using two peptides as examples, we show that the deviations in the folding times can reach an order of magnitude for modest variations of the molecular model. We, therefore, conclude that the folding rate values obtained in molecular dynamics simulations have to be treated with care

Finite Size Effects in Simulations of Protein Aggregation

It is becoming increasingly clear that the soluble protofibrillar species that proceed amyloid fibril formation are associated with a range of neurodegenerative disorders such as Alzheimer's and Parkinson diseases. Computer simulations of the processes that lead to the formation of these oligomeric species are starting to make significant contributions to our understanding of the determinants of protein aggregation. We simulate different systems at constant concentration but with a different number of peptides and we study the how the finite number of proteins affects the underlying free energy of the system and therefore the relative stability of the species involved in the process. If not taken into account, this finite size effect can undermine the validity of theoretical predictions regarding the relative stability of the species involved and the rates of conversion from one to the other. We discuss the reasons that give rise to this finite size effect form both a probabilistic and energy fluctuations point of view and also how this problem can be dealt by a finite size scaling analysis