Splitting the Fast and Slow Motions in Molecular Dynamics Simulations Based on the Change of Cold Potential Well Bottom

The atomic motion is coupled by the fast and slow components due to the high frequency vibration of atoms and the low frequency deformation of atomic lattice, respectively. A two-step approximate method was presented to determine the atomic slow motion. The first step is based on the change of the location of the cold potential well bottom and the second step is based on the average of the appropriate slow velocities of the surrounding atoms. The simple tensions of one-dimensional atoms and two-dimensional atoms were performed with the full molecular dynamics simulations. The conjugate gradient method was employed to determine the corresponding location of cold potential well bottom. Results show that our two-step approximate method is appropriate to determine the atomic slow motion under the low strain rate loading. This splitting method may be helpful to develop more efficient molecular modeling methods and simulations pertinent to realistic loading conditions of materials.

Experimental study of the high-voltage breakdown and simulations for the RFQ cooler and buncher RFQ1L

The RFQ cooler and buncher RFQ1L is one of the key parts of the being-built super-heavy nuclide research spectrometer. In order to understand the high-voltage breakdown phenomenon, the voltages between electrodes have been measured. In addition, more extensive simulations have been performed for better understanding and optimizing the RFQ1L work points.

Simulations to design an online motion compensation system for scanned particle beams

Respiration-induced target motion is a major problem in intensity-modulated radiation therapy. Beam segments are delivered serially to form the total dose distribution. In the presence of motion, the spatial relation between dose deposition from different segments will be lost. Usually, this results in over-and underdosage. Besides such interplay effects between target motion and dynamic beam delivery as known from photon therapy, changes in internal density have an impact on delivered dose for intensity-modulated charged particle therapy. In this study, we have analysed interplay effects between raster scanned carbon ion beams and target motion. Furthermore, the potential of an online motion strategy was assessed in several simulations. An extended version of the clinical treatment planning software was used to calculate dose distributions to moving targets with and without motion compensation. For motion compensation, each individual ion pencil beam tracked the planned target position in the lateral aswell as longitudinal direction. Target translations and rotations, including changes in internal density, were simulated. Target motion simulating breathing resulted in severe degradation of delivered dose distributions. For example, for motion amplitudes of +/- 15 mm, only 47% of the target volume received 80% of the planned dose. Unpredictability of resulting dose distributions was demonstrated by varying motion parameters. On the other hand, motion compensation allowed for dose distributions for moving targets comparable to those for static targets. Even limited compensation precision (standard deviation similar to 2 mm), introduced to simulate possible limitations of real-time target tracking, resulted in less than 3% loss in dose homogeneity.

Calculating the equation of state parameters and predicting the spinodal curve of isotactic polypropylene/poly(ethylene-co-octene) blend by molecular dynamics simulations combined with Sanchez-Lacombe lattice fluid theory

Molecular dynamics simulations are adopted to calculate the equation of state characteristic parameters P*, rho*, and T* of isotactic polypropylene (iPP) and poly(ethylene-co-octene) (PEOC), which can be further used in the Sanchez-Lacombe lattice fluid theory (SLLFT) to describe the respective physical properties. The calculated T* is a function of the temperature, which was also found in the literature. To solve this problem, we propose a Boltzmann fitting of the data and obtain T* at the high-temperature limit. With these characteristic parameters, the pressure-volume-temperature (PVT) data of iPP and PEOC are predicted by the SLLFT equation of state. To justify the correctness of our results, we also obtain the PVT data for iPP and PEOC by experiments. Good agreement is found between the two sets of data. By integrating the Euler-Lagrange equation and the Cahn-Hilliard relation, we predict the density profiles and the surface tensions for iPP and PEOC, respectively. Furthermore, a recursive method is proposed to obtain the characteristic interaction energy parameter between iPP and PEOC. This method, which does not require fitting to the experimental phase equilibrium data, suggests an alternative way to predict the phase diagrams that are not easily obtained in experiments.

Stress transfer and damage evolution simulations of fiber-reinforced polymer-matrix composites

The stress transfer from broken fibers to unbroken fibers in fiber-reinforced thermosetting polymer-matrix composites and thermoplastic polymer-matrix composites was studied using a detailed finite element model. In order to check the validity of this approach, an epoxy-matrix monolayer composite was used as thermosetting polymer-matrix composite and a polypropylene (PP)-matrix monolayer composite was used as thermoplastic polymer-matrix composite, respectively. It is found that the stress concentrations near the broken fiber element cause damage to the neighboring epoxy matrix prior to the breakage of other fibers, whereas in the case of PP-matrix composites the fibers nearest to the broken fiber break prior to the PP matrix damage, because the PP matrix around the broken fiber element yields. In order to simulate composite damage evolution, a Monte Carlo technique based on a finite element method has been developed in the paper. The finite element code coupled with statistical model of fiber strength specifically written for this problem was used to determine the stress redistribution. Five hundred samples of numerical simulation were carried out to obtain statistical deformation and failure process of composites with fixed fiber volume fraction.

Temperature dependence of the distribution of the first passage time: Results from discontinuous molecular dynamics simulations of an all-atom model of the second beta-hairpin fragment of protein G

More than 22 000 folding kinetic simulations were performed to study the temperature dependence of the distribution of first passage time (FPT) for the folding of an all-atom Go-like model of the second beta-hairpin fragment of protein G. We find that the mean FPT (MFPT) for folding has a U (or V)-shaped dependence on the temperature with a minimum at a characteristic optimal folding temperature T-opt*. The optimal folding temperature T-opt* is located between the thermodynamic folding transition temperature and the solidification temperature based on the Lindemann criterion for the solid. Both the T-opt* and the MFPT decrease when the energy bias gap against nonnative contacts increases. The high-order moments are nearly constant when the temperature is higher than T-opt* and start to diverge when the temperature is lower than T-opt*. The distribution of FPT is close to a log-normal-like distribution at T* greater than or equal to T-opt*. At even lower temperatures, the distribution starts to develop long power-law-like tails, indicating the non-self-averaging intermittent behavior of the folding dynamics. It is demonstrated that the distribution of FPT can also be calculated reliably from the derivative of the fraction not folded (or fraction folded), a measurable quantity by routine ensemble-averaged experimental techniques at dilute protein concentrations.

Consensus scoring for enriching near-native structures from protein-protein docking decoys

The identification of near native protein-protein complexes among a set of decoys remains highly challenging. A stategy for improving the success rate of near native detection is to enrich near native docking decoys in a small number of top ranked decoys. Recently, we found that a combination of three scoring functions (energy, conservation, and interface propensity) can predict the location of binding interface regions with reasonable accuracy. Here, these three scoring functions are modified and combined into a consensus scoring function called ENDES for enriching near native docking decoys. We found that all individual scores result in enrichment for the majority of 28 targets in ZDOCK2.3 decoy set and the 22 targets in Benchmark 2.0. Among the three scores, the interface propensity score yields the highest enrichment in both sets of protein complexes. When these scores are combined into the ENDES consensus score, a significant increase in enrichment of near-native structures is found. For example, when 2000 dock decoys are reduced to 200 decoys by ENDES, the fraction of near-native structures in docking decoys increases by a factor of about six in average. ENDES was implemented into a computer program that is available for download at http://sparks.informatics.iupui.edu.