Pressure-Induced Structural Transformation in Cristobalite Studied by Molecular Dynamic Simulations

1995 ◽  
Vol 398 ◽  
Author(s):  
Lucas Duffrene ◽  
John Kjeffer
Keyword(s):  
Phase Transformation ◽  
Correlation Function ◽  
Molecular Dynamic ◽  
Vibrational Spectra ◽  
Time Correlation ◽  
Time Correlation Function ◽  
Atomic Scale ◽  
Molecular Dynamic Simulations ◽  
Dynamic Simulations ◽  
Transformation Front

ABSTRACTThe phase transformation between the α- and β-cristobalite modifications of SiO2 were studied using molecular dynamic simulations. The transformation was induced isothermally by control of the pressure within the structure, either through an externally applied constant stress or by changing the simulation box volume. The atomic scale mechanisms of the transformation can best be observed by means of a time-correlation function describing the spatial orientation of the planes containing the Si-O-Si bonds. These planes rotate by 90° over the course of the transition. Both, the bulk modulus, calculated for static structures, as well as the vibrational spectra of the Si-O-Si planes, reflect the softening of acoustic modes in the midst of the transition, which is characteristic of displacive phase transformations. Although the aperiodic shift of atomic positions upon passage of the transformation front could be responsible for a momentary softening of the structure, this is not the only reason, since this behavior persists when maintaining the structure at intermediate densities, which corresponds neither to α-, nor to β- cristobalite.

Rate Constants, Reactive Flux

2018 ◽  
Author(s):  
Niels Engholm Henriksen ◽  
Flemming Yssing Hansen
Keyword(s):  
Correlation Function ◽  
Rate Constant ◽  
Cross Sections ◽  
Time Correlation ◽  
Time Correlation Function ◽  
Exact Expression ◽  
Reaction Cross ◽  
Dividing Surface ◽  
Definition Of ◽  
Reactive Flux

This chapter discusses a direct approach to the calculation of the rate constant k(T) that bypasses the detailed state-to-state reaction cross-sections. The method is based on the calculation of the reactive flux across a dividing surface on the potential energy surface. Versions based on classical as well as quantum mechanics are described. The classical version and its relation to Wigner’s variational theorem and recrossings of the dividing surface is discussed. Neglecting recrossings, an approximate result based on the calculation of the classical one-way flux from reactants to products is considered. Recrossings can subsequently be included via a transmission coefficient. An alternative exact expression is formulated based on a canonical average of the flux time-correlation function. It concludes with the quantum mechanical definition of the flux operator and the derivation of a relation between the rate constant and a flux correlation function.

scholarly journals Ranking the Efficiency of Gas Hydrate Anti-agglomerants through Molecular Dynamic Simulations

2021 ◽  
Vol 125 (5) ◽  
pp. 1487-1502
Author(s):  
Stephan Mohr ◽  
Felix Hoevelmann ◽  
Jonathan Wylde ◽  
Natascha Schelero ◽  
Juan Sarria ◽  
...  
Keyword(s):  
Molecular Dynamic ◽  
Gas Hydrate ◽  
Molecular Dynamic Simulations ◽  
Dynamic Simulations

scholarly journals Flow of long chain hydrocarbons through carbon nanotubes (CNTs)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pranay Asai ◽  
Palash Panja ◽  
Raul Velasco ◽  
Milind Deo
Keyword(s):  
Carbon Nanotubes ◽  
Molecular Dynamic ◽  
Continuum Models ◽  
Molecular Dynamic Simulations ◽  
Dynamic Simulations ◽  
Pharmaceutical Applications ◽  
Molecular Sizes ◽  
Hydrocarbon Molecules ◽  
Pressure Driven Flow ◽  
Long Chain

AbstractThe pressure-driven flow of long-chain hydrocarbons in nanosized pores is important in energy, environmental, biological, and pharmaceutical applications. This paper examines the flow of hexane, heptane, and decane in carbon nanotubes (CNTs) of pore diameters 1–8 nm using molecular dynamic simulations. Enhancement of water flow in CNTs in comparison to rates predicted by continuum models has been well established in the literature. Our work was intended to observe if molecular dynamic simulations of hydrocarbon flow in CNTs produced similar enhancements. We used the OPLS-AA force field to simulate the hydrocarbons and the CNTs. Our simulations predicted the bulk densities of the hydrocarbons to be within 3% of the literature values. Molecular sizes and shapes of the hydrocarbon molecules compared to the pore size create interesting density patterns for smaller sized CNTs. We observed moderate flow enhancements for all the hydrocarbons (1–100) flowing through small-sized CNTs. For very small CNTs the larger hydrocarbons were forced to flow in a cork-screw fashion. As a result of this flow orientation, the larger molecules flowed as effectively (similar enhancements) as the smaller hydrocarbons.

scholarly journals Exploring aromatic cage flexibility of the histone methyllysine reader protein Spindlin1 and its impact on binding mode prediction: an in silico study

2021 ◽  
Author(s):  
Chiara Luise ◽  
Dina Robaa ◽  
Wolfgang Sippl
Keyword(s):  
Molecular Dynamic ◽  
In Silico ◽  
Binding Pocket ◽  
Binding Mode ◽  
Molecular Dynamic Simulations ◽  
Flexible Docking ◽  
Dynamic Simulations ◽  
Binding Mode Prediction ◽  
Aromatic Cage ◽  
The Right

AbstractSome of the main challenges faced in drug discovery are pocket flexibility and binding mode prediction. In this work, we explored the aromatic cage flexibility of the histone methyllysine reader protein Spindlin1 and its impact on binding mode prediction by means of in silico approaches. We first investigated the Spindlin1 aromatic cage plasticity by analyzing the available crystal structures and through molecular dynamic simulations. Then we assessed the ability of rigid docking and flexible docking to rightly reproduce the binding mode of a known ligand into Spindlin1, as an example of a reader protein displaying flexibility in the binding pocket. The ability of induced fit docking was further probed to test if the right ligand binding mode could be obtained through flexible docking regardless of the initial protein conformation. Finally, the stability of generated docking poses was verified by molecular dynamic simulations. Accurate binding mode prediction was obtained showing that the herein reported approach is a highly promising combination of in silico methods able to rightly predict the binding mode of small molecule ligands in flexible binding pockets, such as those observed in some reader proteins.

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