Preparation of composite high-efficiency dust suppressant and relevant molecular dynamics simulation for wetting coal surface

Abstract An anionic surfactant, sodium dodecyl sulfate (SDS) was used to modify the coal structure. This was done to improve the compactness of the coal structure, promote the damage of coal structure, improve the efficiency of gas drainage, and prevent shock pressure disasters. The mercury intrusion experiment and uniaxial compression experiments were used to determine the changes in the pore structure and mechanical properties of coal after modified by surfactant. This work established six groups of water / surfactant / coal simulation systems with different concentrations. Based on the energy behavior and dynamics characteristics ( interaction energy, relative concentration distribution, radial distribution function, mean square displacement) of each system, the effects of surfactants with different concentrations on the structural damage of coal were analyzed by molecular dynamics simulation, and the mechanism of coal structural damage was revealed. The results show that the SDS solution can significantly reduce the mechanical strength of the coal. When the solution concentration is 0.6%, the degree of damage to the coal structure is the maximum. SDS molecules can be detected at the water / coal interface. SDS molecules are adsorbed to the coal surface through intermolecular interactions, and -SO3 groups are preferentially adsorbed to the oxygen-containing functional groups on the coal surface. The difference in SDS adsorption on the coal surface is caused by the difference in the number and spatial distribution of alkyl chains in the SDS molecule. The main modification mechanisms of surfactants on coal are that when SDS is adsorbed on the coal surface, a large number of secondary pores and cracks are generated on the surface and inside of the coal, and cracks are formed under the action of tensile stress. The cracks continue to expand, extend, which ultimately promotes damage to the coal structure. The results are expected to provide a theoretical basis for the structure damage of coal modified by surfactant, and provide a new method for the prevention of rockburst disasters and gas outburst control.

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De novo protein structure prediction using ultra-fast molecular dynamics simulation

10.1101/262188 ◽

2018 ◽

Cited By ~ 1

Author(s):

Ngaam J. Cheung ◽

Wookyung Yu

Keyword(s):

Molecular Dynamics ◽

Protein Structure ◽

Molecular Dynamics Simulation ◽

Protein Structure Prediction ◽

Structure Prediction ◽

High Efficiency ◽

Tertiary Structure ◽

De Novo ◽

Protein Structures ◽

Dynamics Simulation

ABSTRACTModern genomics sequencing techniques have provided a massive amount of protein sequences, but experimental endeavor in determining protein structures is largely lagging far behind the vast and unexplored sequences. Apparently, computational biology is playing a more important role in protein structure prediction than ever. Here, we present a system of de novo predictor, termed NiDelta, building on a deep convolutional neural network and statistical potential enabling molecular dynamics simulation for modeling protein tertiary structure. Combining with evolutionary-based residue-contacts, the presented predictor can predict the tertiary structures of a number of target proteins with remarkable accuracy. The proposed approach is demonstrated by calculations on a set of eighteen large proteins from different fold classes. The results show that the ultra-fast molecular dynamics simulation could dramatically reduce the gap between the sequence and its structure at atom level, and it could also present high efficiency in protein structure determination if sparse experimental data is available.

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