Network structure of SiO<sub>2</sub> and MgSiO<sub>3</sub> in amorphous and liquid States

Lan, Mai Thi; Duong, Tran Thuy; Huy, Nguyen Viet; Hong, Nguyen Van

doi:10.1088/2053-1591/aa6600

Cited by 7 publications

(7 citation statements)

References 24 publications

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“…For the Si‐Mg pair, the first peak of the G Si–Mg (r) locates at 3.22 ± 0.01 Å. These data are consistent with the experimental data and calculated results …”

Section: Resultssupporting

confidence: 90%

“…Meanwhile, by using first‐principle MD simulations, Ghosh et al reported that the Mg CN is 4.6 with the average Mg‐O BL of 2.05 Å. The Si‐rich and Mg‐rich regions of the network structure were interpreted in recent MD simulations as the OSi y and OMg y clusters were determined . The distribution of corner‐ and edge‐sharing bonds in this MgSiO 3 model has been showed that the corner‐sharing bonds are major and the edge‐sharing bonds are a few ten of bonds.…”

Section: Introductionmentioning

confidence: 83%

“…This potential has also been used many times in the studies and can reproduce the structural properties of MgSiO 3 systems, see for instance in Refs. . The long‐range Coulomb interactions were calculated by using the Ewald summation technique .…”

Section: Computational Proceduresmentioning

confidence: 99%

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Molecular Dynamics Simulations of Structural and Mechanical Properties in MgSiO₃ Glass

Nguyen

Nguyen²,

Dinh

et al. 2019

Physica Status Solidi (b)

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Molecular dynamics simulations of MgSiO3 glass have been carried out to study the structural and mechanical properties under uniaxial tension. The network structure consists of SiOx and MgOy units which link to others by corner‐, edge‐, and face‐sharing bonds. The Si‐rich and Mg‐rich regions exist in MgSiO3 glass. The stress–strain curves exhibit the elastic and plastic characteristics at the various strain rates. The transformations of SiOx and MgOy units occur with increasing strain, at which the corner‐, edge‐ and face‐sharing bonds among SiOx and MgOy units change. The Si‐rich and Mg‐rich regions increase with increasing strain. Not only the Mg–O bond length is easier to stretch than the Si–O bond length but also the O–Mg–O bond angle of MgOy units is easier to vary than that of SiOx units with the strain. The porosity is analyzed via the voids. The voids gather into the clusters of voids. The radii of voids increase with increasing strain. The number of big Mg‐voids increases under the tension and these voids coalesce to form large pores. These large pores do not coalesce to cause the fractured free surfaces. The formation of shear band was observed at the strain of 0.82.

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“…For the Si‐Mg pair, the first peak of the G Si–Mg (r) locates at 3.22 ± 0.01 Å. These data are consistent with the experimental data and calculated results …”

Section: Resultssupporting

confidence: 90%

Section: Introductionmentioning

confidence: 83%

See 1 more Smart Citation

Molecular Dynamics Simulations of Structural and Mechanical Properties in MgSiO₃ Glass

Nguyen

Nguyen²,

Dinh

et al. 2019

Physica Status Solidi (b)

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“…The Si-O coordination number was fixed to 4.0 in the fit (Wilding et al 2008) ). These structural parameters are also consistent with previously reported values derived from both simulations (Lan et al 2017a;Kim et al 2019) and experimental studies (Funamori et al 2004;Wilding et al 2008) where the angled brackets denote an average over the Q-range of the data.…”

Section: Further Developmentsupporting

confidence: 91%

LiquidDiffract: software for liquid total scattering analysis

Heinen

Drewitt

2022

Phys Chem Minerals

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LiquidDiffract is an open source, Python-based graphical application for X-ray total scattering analysis of liquids and disordered solids. The software implements procedures to obtain information on macroscopic bulk properties and local atomic-scale structure of monatomic or polyatomic samples from X-ray total scattering data. LiquidDiffract provides an easy to use interface with tools to perform background subtraction; calculation, normalisation, and refinement of the reciprocal-space structure factor and real-space correlation functions; and the extraction of structural information such as bond lengths, coordination number, and bulk density. The software is well suited to investigations of amorphous materials at extreme conditions, such as studies of high-pressure melt structure, polyamorphic phase transitions, and liquid equations of state. The open-source distribution and graphical interface will be of particular benefit to researchers who are new to the field. In this article we describe the distribution, system requirements, and installation of LiquidDiffract, and detail the data processing workflow and underlying numerical methods.

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“…At ambient pressure the calculated density of the sample is 2.52 g/cm 3 that not much larger than the real density of silica liquid. The pair radial distribution functions (PRDF) as obtained from our simulation are similar to those reported in reference [26].…”

Section: Computational Proceduressupporting

confidence: 82%

Insight into microstructure and dynamics of network forming liquid from the analysis based on shell–core particles

et al. 2019

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Large models of silica melt have been produced at 3500 K and pressures of 0, 5, 10, 15, 20, 25, 30 and 45 GPa by molecular dynamics simulation. New topological analysis is performed based on shell-core particles. The simulation shows that although the fraction of different types of basic units varies strongly, the topology of those units remains almost constant under pressure. The O-particles contain from 2 to 14 O and Si-particles have 1 or 2 Si. The clusters of particles (CP) include Si-clusters and O-clusters which occupy micro-regions with pure compositions and contain up to 8 Si and 106 O, respectively. The densification is realized by two ways: (i) increasing density of atoms in shell and core of particles; (ii) increasing number of small O-particles in expense of large ones. The simulation also reveals particles and CP which are stable for long times. Strong chemical bonds between core and shell atoms prevent those particles and CP from breaking apart. During about one nanosecond the solid-like atoms are non-uniformly distributed in the space where they gather instead in rigid Si-O subnets, stable particles and clusters of stable particles. We find that the dynamics heterogeneity observed at low pressure is originated from the small rate of bond-breaking events and non-uniform spatial distribution of these events.

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Network structure of SiO₂ and MgSiO₃ in amorphous and liquid States

Cited by 7 publications

References 24 publications

Molecular Dynamics Simulations of Structural and Mechanical Properties in MgSiO₃ Glass

Molecular Dynamics Simulations of Structural and Mechanical Properties in MgSiO₃ Glass

LiquidDiffract: software for liquid total scattering analysis

Insight into microstructure and dynamics of network forming liquid from the analysis based on shell–core particles

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Network structure of SiO2 and MgSiO3 in amorphous and liquid States

Cited by 7 publications

References 24 publications

Molecular Dynamics Simulations of Structural and Mechanical Properties in MgSiO3 Glass

Molecular Dynamics Simulations of Structural and Mechanical Properties in MgSiO3 Glass

LiquidDiffract: software for liquid total scattering analysis

Insight into microstructure and dynamics of network forming liquid from the analysis based on shell–core particles

Contact Info

Product

Resources

About

Network structure of SiO₂ and MgSiO₃ in amorphous and liquid States

Molecular Dynamics Simulations of Structural and Mechanical Properties in MgSiO₃ Glass

Molecular Dynamics Simulations of Structural and Mechanical Properties in MgSiO₃ Glass