MD study of the mixed alkali effect in a lithium&amp;.zsbnd;potassium metasilicate glass

Habasaki, Junko; Okada, Isao; Hiwatari, Yasuaki

doi:10.1016/0022-3093(94)00529-x

Cited by 101 publications

(69 citation statements)

References 19 publications

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“…The term jump implies that the time scale it takes to cross the saddle is much shorter than the time scale the ions fluctuate within the individual sites. This conclusion is in qualitative agreement with previous simulations [15,24,40,41,42] and also agrees with the appearance of the trajectories in Fig.1. The first minimum of G s (r, t) around r min ≈ 1.5Å can be used to distinguish local vibrational dynamics (|∆r(t)| < 1.5Å) and long-range dynamics (|∆r(t)| > 1.5Å).…”

Section: Dynamicssupporting

confidence: 93%

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Characterization of the complex ion dynamics in lithium silicate glasses via computer simulations

Heuer¹,

Kunow²,

Vogel³

et al. 2002

Phys. Chem. Chem. Phys.

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We present results of molecular dynamics simulations on lithium metasilicate over a broad range of temperatures for which the silicate network is frozen in but the lithium ions can still be equilibrated. The lithium dynamics is studied via the analysis of different correlation functions. The activation energy for the lithium mobility agrees very well with experimental data. The correlation of the dynamics of adjacent ions is weak. At low temperatures the dynamics can be separated into local vibrational dynamics and hopping events between adjacent lithium sites. The derivative of the mean square displacement displays several characteristic time regimes. They can be directly mapped onto respective frequency regimes for the conductivity. In particular it is possible to identify time regimes dominated by localized dynamics and longrange dynamics, respectively. The question of time-temperature superposition is discussed for the mean square displacement and the incoherent scattering function.

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Section: Dynamicssupporting

confidence: 93%

“…The individual potential parameters are listed in our previous work [26]. They are based on the work of Habasaki et al [13,14,27,28,29] and have been obtained from ab-initio calculations. Effective charges q Si = 2.4, q Li = 0.87, and q O = 1.38 have been chosen.…”

Section: Simulationmentioning

confidence: 99%

Characterization of the complex ion dynamics in lithium silicate glasses via computer simulations

Heuer¹,

Kunow²,

Vogel³

et al. 2002

Phys. Chem. Chem. Phys.

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“…MD simulation has been performed in the same way as in previous studies: [1][2][3][4] the numbers of the particles in the basic cube being 144 for Li, 72 for Si, and 216 for O. The volume was fixed at that derived by the NPT ͑constant pressure and temperature͒ ensemble simulation.…”

Section: MD Simulationmentioning

confidence: 99%

Fracton excitation and Lévy flight dynamics in alkali silicate glasses

1997

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We have examined the relaxation behavior of alkali metal ions in lithium metasilicate glasses by means of molecular dynamics simulation. We have observed a change of slope of the mean squared displacement at ϳ300 ps. In shorter time regions, localized motion of lithium ions within neighboring sites is observed, which is caused by the small fracton dimension ͑fracton excitation͒. On the other hand, an accelerated motion of particles due to cooperative jumps is found, which characterizes the diffusion and conduction mechanisms of the alkali metal ions in longer time regions. The dynamics of accelerated motion is discussed in relation to Lévy flight dynamics. ͓S0163-1829͑97͒03510-8͔

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“…We use a pair potential developed by J. Habasaki [18]. Previous studies with this potential have shown good agreement with experimental results for static and dynamic quantities [19,20,21]. The molecular dynamics simulations are performed with a modified version of Moldy [22].…”

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confidence: 99%

Complete Identification of Alkali Sites in Ion Conducting Lithium Silicate Glasses: A Computer Study of Ion Dynamics

Lammert¹,

Kunow²,

Heuer³

2003

Phys. Rev. Lett.

113

112

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The available sites for ions in a typical disordered ionic conductor are determined. For this purpose we devised a straightforward algorithm which via cluster analysis identifies these sites from long time ionic trajectories below the glass transition. This is exemplified for a lithium silicate glass (Li2O) x (SiO2) (1−x) for x = 0.5 and x = 0.1. We find for both concentrations that the number of sites is only slightly bigger than the number of ions. This result suggests a theoretical description of the dynamics in terms of mobile vacancies as most appropriate. Furthermore identification of the ionic sites allows one to obtain detailed characteristics of the ionic motion, e.g. quantification of correlated forward-backward jumps.Ion conducting glasses have been investigated by various experimental methods, including EXAFS [1, 2], NMR [3,4,5], and conductivity spectroscopy [6,7]. Whereas quite detailed information about the local structure has become available the mechanism of dynamics is still under debate although consensus has been reached that ion dynamics can be described as jumps of the mobile ions [8,9,10]. Whereas some authors stress the relevance of the disordered energy landscape [9,11] supplied by the network, others relate the complexity of ion dynamics to the Coulomb interaction among mobile ions [6]. Furthermore it has been argued from structural considerations that the distribution of alkali ions is inhomogeneous [12].For a closer understanding of ion dynamics microscopic information as supplied by molecular dynamics (MD) simulations is highly welcome. Jund et al. [13] found preferential pathways as a dynamical phenomenon by counting the number of different alkali ions that passed through subvolumes of the simulation box. The resulting subvolumes visited by the largest number of different alkali ions may be interpreted as fast areas. They form a network of conduction paths. Oviedo and Sanz have argued on a qualitative basis that for alkali concentrations lower than 10% the alkali ions are always surrounded by non-bridging oxygens (NBOs) despite the overall small number of NBOs [14]. This implies that new NBOs are formed via breaking of Si-O bonds along the alkali trajectory. In contrast, for higher concentrations hopping dynamics between so-called micro-channels is proposed such that no formation of new NBOs would be necessary. Horbach [15] showed in simulations of (Na 2 O)2(SiO 2 ), that the coherent intermediate scattering function of sodium relaxes only on the same timescale as those of the network species, proving the existence of stable alkali sites below the glass transition. Cormack [16] et al. have recently investigated the mechanism of sodium migration in simulations of (Na 2 O) 0.25 (SiO 2 ) 0.75 glasses, observing a few sequences of jumps between selected sites. He interpreted the resulting dynamics as the motion of vacancies and pointed out that the identification of all sites in the glass, empty or populated at a given time, would be most useful for obtaining a deeper understanding of ...

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MD study of the mixed alkali effect in a lithium&.zsbnd;potassium metasilicate glass

Cited by 101 publications

References 19 publications

Characterization of the complex ion dynamics in lithium silicate glasses via computer simulations

Characterization of the complex ion dynamics in lithium silicate glasses via computer simulations

Fracton excitation and Lévy flight dynamics in alkali silicate glasses

Complete Identification of Alkali Sites in Ion Conducting Lithium Silicate Glasses: A Computer Study of Ion Dynamics

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