scholarly journals Molecular Dynamic Simulation of Large Model of Silica Liquid

2018 ◽  
Vol 34 (4) ◽  
Author(s):  
Nguyen Thi Thanh Ha ◽  
Phan Quan ◽  
Tran Van Hong ◽  
Le Van Vinh
Keyword(s):  
Molecular Dynamics ◽  
Network Structure ◽  
Materials Science ◽  
Structural Characteristics ◽  
Diffusion Mechanism ◽  
Physical Review ◽  
Dynamics Simulation ◽  
Angle Distribution ◽  
Earth Planet ◽  
Wide Range

Abstract: We perform a molecular dynamics simulation to study the microstructure and dynamical properties in large silica model at liquid state. The models consisting of 19998 atoms were constructed under a wide range of pressure (0-20 GPa) and at 3500K temperature. Structural characteristics were clarified through the pair radial distribution function (PRDF), the distribution of SiOx coordination units and network structure. The result shows that these liquids consist of identical units SiO4, SiO5 and SiO6 and have common partial O―Si―O angle distribution. Furthermore, the major change in the diffusion mechanism under pressure is also considered and discussed.  Keywords: Molecular dynamics, structure, coordination units, diffusion, network structure. References [1] Gergely Molnár, Patrick Ganster, Anne Tanguy, Physical review E 95, 043001 (2017) [2] M. M. Smedskjaer,Frontier Mater, 1(23),1,(2014)[3] B. Hehlen and D. R. Neuville. J Phys Chem B. 119 (10), 4093,( 2015)[4] T. Kawasaki, H. Tanaka, J. Phys.: Condens. Matter 22, 232102 (2010).[5] G. Calas, L. Galoisy, L. Cormier, G. Ferlat, G. Lelong,Procedia Materials Science 7, 23 (2014)[6] J. Badro, D. M. Teter, R. T. Downs, P. Gillet, R. J. Hemley, and J.L. Barrat, Phys. Rev. B 56, 5797 (1997)[7] C. Weigel, L. Cormier, G. Calas, L. Galoisy, D.T. Bowron, Phys. Rev. B 78, 064202 (2008)[8] H. Jabraoui, Y.Vaills, A. Hasnaoui, M. Badawi and S. Ouaskit, J. Phys. Chem. B 120, 13193 (2016).[9] T. K. Bechgaard eltal., J. Non-Cryst. Solids 441, 49 (2016)[10] S. K. Baggain, D. B. Ghosh, B. B. Karki, Phys. Chem. Min. 42, 393 (2015).[11] A. W.Cooper, P. Harrowell, and H. Fynewever, Phys. Rev. Lett 93, 135701 (2004).[12] J.R. Allwardt, J.F. Stebbins, B.C. Schmidt, D.J. Frost, A.C. Withers, M.M. Hirschmann, Am. Mineral. 90, 1218 (2005)[13] M. Bauchy, M. Micoulaut, Physical review B 83, 184118 (2011)[14] H. Jabraoui, E.M. Achhal, A. Hasnaoui, J.-L. Garden,Y.Vaills, S. Ouaskit, J.Non-Cryst-Solid 448,16(2016)[15] S.K. Lee, G.D. Cody, Y. Fei, B.O. Mysen, Chem. Geol. 229,162 (2006).[16] I. Jackson, Phys. Earth Planet. Inter. 1, 218 (1976) [17] B.T. Poe etal., Science 276, 1245 (1997) [18] M. Scott Shell, G.D.Pablo , Z.P. Athanassios, Phys. Rev.E 66, 011202 (2002)[19] D.I. Grimley, A.C. Wright, R.N. Sinclair, J. Non-Cryst. Solids 119, 49 (1990).[20] Mozzi R L and Warren B E, J. Appl. Crystallogr. 2 164 (1969)[21] Bauchy M, J Chem Phys. 141, 024507 (2014)[22] T. Morishita, Phys. Rev. E 72, 021201 (2005)[23] P.K. Hung, N.T.T. Ha, N.V. Hong, J. Non-Cryst. Solids 358, 1649 (2012)

scholarly journals The Microstructural Transformation and Dynamical Properties in Sodium-silicate: Molecular Dynamics Simulation

2020 ◽  
Vol 36 (2) ◽  
Author(s):  
Nguyen Thi Thanh Ha ◽  
Tran Thuy Duong ◽  
Nguyen Hoai Anh
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Sodium Silicate ◽  
Diffusion Mechanism ◽  
Sodium Atom ◽  
Dynamics Simulation ◽  
Basic Unit ◽  
Angle Distribution ◽  
Microstructural Transformation ◽  
And Diffusion

Molecular dynamics simulation of sodium-silicate has been carried out to investigate the microstructural transformation and diffusion mechanism. The microstructure of sodium silicate is studied by the pair radial distribution function, distribution of SiOx (x=4,5,6), OSiy (y=2,3) basic unit, bond angle distribution. The simulation results show that the structure of sodium silicate occurs the transformation from a tetrahedral structure to an octahedral structure under pressure. The additional network-modifying cation oxide breaking up this network by the generation of non-bridging O atoms and it has a slight effect on the topology of SiOx and OSiy units. Moreover, the diffusion of network- former atom in sodium-silicate melt is anomaly and diffusion coefficient for sodium atom is much larger than for oxygen or silicon atom. The simulation proves two diffusion mechanisms of the network-former atoms and modifier atoms.

The influence of pressure on the structural transformation and diffusion mechanism in lithium-silicate melt: Molecular dynamics simulation

2020 ◽  
Vol 34 (32) ◽  
pp. 2050312
Author(s):  
Nguyen Thi Thanh Ha
Keyword(s):  
Molecular Dynamics ◽  
Structural Transformation ◽  
Diffusion Mechanism ◽  
Bond Distance ◽  
Silicate Melt ◽  
Dynamics Simulation ◽  
Lithium Silicate ◽  
Angle Distribution ◽  
Bond Angle Distribution ◽  
And Diffusion

The structural transformation and diffusion mechanism of lithium-silicate melt is carried by molecular dynamics method. In order to investigate the nature of the pressure-induced structural transformations, the pair radial distribution function (PRDF), distribution of SiO[Formula: see text], OSi[Formula: see text] and LiO[Formula: see text] coordination units, bond angle distribution (BAD) and bond distance distribution (BDD) are analyzed. The investigation reveals that there is a structural transformation in the structure of lithium-silicate. The addition of alkali oxides results in the formation of nonbridging oxygens (NBOs) by disruption of the Si–O network and it has a slight effect on the topology of SiO[Formula: see text] and OSi[Formula: see text] units. Furthermore, we show that the diffusion of network-former atom in lithium-silicate melt is anomaly and Li atoms have significantly faster diffusion rate than those of oxygen or silicon atoms. Therefore, there is an existence of two diffusion mechanisms in lithium-silicate.

Molecular Dynamics Simulation Study of the Effect of Ni, Fe, Cu on Cryolite Molten Salt System 78% Na3AlF6-9.5%AlF3-5.0%CaF2-7.5%-Al2O3

2021 ◽  
Vol 1026 ◽  
pp. 39-48
Author(s):  
Han Bing He ◽  
Yu Si Wang ◽  
Ze Xiang Luo ◽  
Jing Zeng
Keyword(s):  
Molecular Dynamics ◽  
Diffusion Coefficient ◽  
Molten Salt ◽  
Diffusion Mechanism ◽  
Research Work ◽  
Dynamics Simulation ◽  
Salt System ◽  
Electrolyte System ◽  
Aluminum Composite ◽  
Molten Salt System

The effect of different additives Ni, Fe, Cu on the structure and properties of electrolyte system 78% Na3AlF6- -9.5%AlF3-5.0%CaF2-7.5%Al2O3 at 1200K and 1.01Mpa was studied by molecular dynamics method. The radial distribution function, coordination number, diffusion coefficient, conductivity, and viscosity of the system were discussed in detail. The results demonstrated that the order of the self-diffusion coefficient of ions in the electrolyte system is: Na+ > F- > O2- > Ca2+ >Al3+. The addition of Ni and Fe connected the free aluminum composite ion groups in the system through fluorine bridges, which enhanced the interaction between Al3+ and Al3+. The addition of Cu weakened the interaction between Al3 + and Al3+ and the F-. The interaction between Al3+ and Na+, [AlF7]4- ionic groups might appeared in the melt system. After adding NiO, Fe2O3, and Cu, the electrical conductivity of the system increased, and the viscosity decreased. The research work revealed the influence of Ni, Fe, Cu on the ion existence form, mobility, inter-ion interaction and diffusion mechanism of cryolite molten salt system, which has important guiding significance for aluminum electrolysis production.

scholarly journals A method to construct the dynamic landscape of a bio-membrane with experiment and simulation

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Albert A. Smith ◽  
Alexander Vogel ◽  
Oskar Engberg ◽  
Peter W. Hildebrand ◽  
Daniel Huster
Keyword(s):  
Molecular Dynamics ◽  
Nmr Relaxation ◽  
Dynamics Simulation ◽  
Comprehensive Description ◽  
Correlation Times ◽  
Wide Range ◽  
Dynamic Landscape ◽  
C Nmr ◽  
Analysis Of Motion

AbstractBiomolecular function is based on a complex hierarchy of molecular motions. While biophysical methods can reveal details of specific motions, a concept for the comprehensive description of molecular dynamics over a wide range of correlation times has been unattainable. Here, we report an approach to construct the dynamic landscape of biomolecules, which describes the aggregate influence of multiple motions acting on various timescales and on multiple positions in the molecule. To this end, we use 13C NMR relaxation and molecular dynamics simulation data for the characterization of fully hydrated palmitoyl-oleoyl-phosphatidylcholine bilayers. We combine dynamics detector methodology with a new frame analysis of motion that yields site-specific amplitudes of motion, separated both by type and timescale of motion. In this study, we show that this separation allows the detailed description of the dynamic landscape, which yields vast differences in motional amplitudes and correlation times depending on molecular position.

THE CORRELATION BETWEEN BOND ANGLE DISTRIBUTION AND THE COORDINATION OF SILICA LIQUID UNDER PRESSURE

2012 ◽  
Vol 26 (20) ◽  
pp. 1250117 ◽  
Author(s):  
L. T. VINH ◽  
N. V. HUY ◽  
P. K. HUNG
Keyword(s):  
Experimental Data ◽  
Molecular Dynamics ◽  
Bond Angle ◽  
Simple Expression ◽  
Dynamics Simulation ◽  
Angle Distribution ◽  
Bond Angle Distribution ◽  
Simulation Results ◽  
Substantial Change ◽  
Good Agreement

Molecular dynamics simulation is carried out for liquid SiO 2 at pressure ranged from zero to 30 GPa and by using BKS, Born–Mayer type and Morse–Stretch potentials. The constructed models reproduce well the experimental data in terms of mean coordination number, bond angle and pair radial distribution function. Furthermore, the density of all samples can be expressed by a linear function of fractions SiO x. It is found that the topology of units SiO x and linkages OSi y is unchanged upon compression although the liquid undergoes substantial change in its network structure. Consequently, the partial bond angle distribution for SiO x and OSi y is identical for all samples constructed by the same potential. This result allows to establishing a simple expression between total bond angle distribution (BAD) and fraction of SiO x and OSi y. The simulation shows a good agreement between the calculation and simulation results for both total O–Si–O and Si–O–Si BADs. This supports a technique to estimate amount of units SiO x and linkages OSi y on base of total Si–O–Si and O–Si–O BADs measured experimentally.

scholarly journals Optical Diagnostics of Supercritical CO2 and CO2-Ethanol Mixture in the Widom Delta

Molecules ◽  
2020 ◽  
Vol 25 (22) ◽  
pp. 5424
Author(s):  
Evgenii Mareev ◽  
Timur Semenov ◽  
Alexander Lazarev ◽  
Nikita Minaev ◽  
Alexander Sviridov ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Optical Properties ◽  
Supercritical Co2 ◽  
Cluster Formation ◽  
Mie Scattering ◽  
Density Fluctuations ◽  
Optical Measurements ◽  
Dynamics Simulation ◽  
Ethanol Mixture ◽  
Wide Range

The supercritical CO2 (scCO2) is widely used as solvent and transport media in different technologies. The technological aspects of scCO2 fluid applications strongly depend on spatial–temporal fluctuations of its thermodynamic parameters. The region of these parameters’ maximal fluctuations on the p-T (pressure-temperature) diagram is called Widom delta. It has significant practical and fundamental interest. We offer an approach that combines optical measurements and molecular dynamics simulation in a wide range of pressures and temperatures. We studied the microstructure of supercritical CO2 fluid and its binary mixture with ethanol in a wide range of temperatures and pressures using molecular dynamics (MD) simulation. MD is used to retrieve a set of optical characteristics such as Raman spectra, refractive indexes and molecular refraction and was verified by appropriate experimental measurements. We demonstrated that in the Widom delta the monotonic dependence of the optical properties on the CO2 density is violated. It is caused by the rapid increase of density fluctuations and medium-sized (20–30 molecules) cluster formation. We identified the correlation between cluster parameters and optical properties of the media; in particular, it is established that the clusters in the Widom delta acts as a seed for clustering in molecular jets. MD demonstrates that the cluster formation is stronger in the supercritical CO2-ethanol mixture, where the extended binary clusters are formed; that is, the nonlinear refractive index significantly increased. The influence of the supercritical state in the cell on the formation of supersonic cluster jets is studied using the Mie scattering technique.

Molecular Dynamics Simulation of Al2O3-SiC Interface

2011 ◽  
Vol 697-698 ◽  
pp. 192-197 ◽  
Author(s):  
Ting Ting Zhou ◽  
Chuan Zhen Huang ◽  
Han Lian Liu ◽  
Bin Zou ◽  
Hong Tao Zhu
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Interfacial Energy ◽  
Diffusion Coefficients ◽  
Diffusion Mechanism ◽  
Dynamics Simulation ◽  
Interface Model ◽  
Relationship Of ◽  
The Relationship ◽  
And Diffusion

The interfacial energy and diffusion phenomenon of the Al2O3(012)-SiC (011) interface model are studied based on molecular dynamics. The interfacial energy increases firstly until reaches its maximum 0.459J/m2at the temperature of 1500K and then decreases. The relationship of diffusion coefficients for each kind of atoms is C>Si>O>Al. Diffusion coefficients of atoms increase at first and then decrease as the temperature goes up. This indicates the diffusion mechanism has been changed during the temperature rising process.

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