Ion Transport in Na2M2TeO6: Insights from Molecular Dynamics Simulation

Sau, Kartik; Kumar, P. Padma

doi:10.1021/jp5094349

Cited by 39 publications

(40 citation statements)

References 50 publications

(72 reference statements)

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“…Thereafter Na–Na and Na–O potentials were fine‐tuned to reproduce the conductivity and overall structure–dynamic properties agreeing with experimental data. The initial studies showed that ion–ion correlation effects, indicating a cooperative conduction mechanism, and a strongly disordered sublattice for the Na ions were key to fast ion transport, similarly to what had previously been shown for both Nasicon as well as β‐alumina. This ion–ion correlation was later examined in more detail for Na 2 Ni 2 TeO 6 by systematically changing the Na‐occupancy in the conduction layers, resulting in a conduction variation by an order of magnitude, maximum at 20% Na deficiency.…”

Section: Ceramic Glassy and Solid‐state Ionic Materialssupporting

confidence: 60%

“…A novel class of Na + conductors is Na 2 M 2 TeO 6 , where M = Ni, Zn, Co, or Mg, built from edge‐sharing M–O and T–O octahedral layers, with Na + in the interlayer, result in conductivities similar to β‐alumina: 0.11 S cm −1 at 573 K . This was explored by classic MD simulations, using a FF constructed by fitting parameters in short‐range MD simulations until the crystallographic structure was reproduced. Thereafter Na–Na and Na–O potentials were fine‐tuned to reproduce the conductivity and overall structure–dynamic properties agreeing with experimental data.…”

Section: Ceramic Glassy and Solid‐state Ionic Materialsmentioning

confidence: 99%

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Sodium‐Ion Battery Electrolytes: Modeling and Simulations

Åvall

Mindemark

Brandell

et al. 2018

Advanced Energy Materials

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www.advancedsciencenews.comapplications in the battery-and these materials have also been more rigorously investigated using electronic structure methodology. Therefore, the latter family of compounds is also more straightforward subjected to meta-analysis, as we will see in this review.The overall purpose is to review the various SIB electrolyte concepts employed, the simulation methods used to study them, and the research questions targeted, with the greater aim to visualize how the field of SIB R&D in general has benefitted from and progressed by the simulations. We finish by some concluding remarks of what has not been done yet and areas uncovered, where we strongly feel SIB electrolyte simulation could contribute substantially. Liquid ElectrolytesLiquid electrolytes are the most common electrolytes for LIBs, and thus in focus also for SIBs. The components of these electrolytes mimic each other; the most common organic solvents are the same, in particular linear and cyclic carbonates are used, and the Na-salts are often just the Na-analogs of the Li salts. Hence there are also from a computational standpoint no methodological differences and many studies performed for LIBs be can reused or made in a (very) similar manner.Liquid electrolytes start from choosing several components and adding them together in a quite free manner, and this is also reflected in the way they are simulated. The anions/salts, solvents, and possibly additives, are most often modeled as separate entities-to, e.g., elucidate chemical and electrochemical stabilities, and with respect to very local interactions-to elucidate ion-ion and ion-solvent interactions, cation solvation, solvation shells, etc. Computationally these problems often can make use of the accuracy of ab initio and DFT methods as the sizes of the systems in general are small. Full liquid electrolytes, however, rapidly become very complex and large systems, and as the dynamics of the different species in solution and the ion transport, etc. are of main interest, these are most often studied by classic, nonquantum mechanics based, MD simulations, but more recently also by ab initio MD (AIMD).Starting with the choice of solvents for the SIB electrolyte most basic properties of the solvents themselves are of course possible to directly find in the LIB literature, such as the vast review by Xu. [9] Hence, these are not in need of specific SIB simulation efforts. A very important practical property which, however, needs specific simulations and where more or less all SIBs still are struggling, is the ability to create a stable solid electrolyte interphase (SEI), and this is most often made by reducing solvents or additives to SEI forming compounds. Liu et al. [10] used DFT to study the changes in energies, enthalpies, and free energies for all steps in a number of possible reduction reaction of common carbonate solvents: ethylene carbonate (EC), propylene carbonate (PC), and vinylene carbonate (VC)-the latter the most common additive since a long time for LIB electrolytes [11]...

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Section: Ceramic Glassy and Solid‐state Ionic Materialssupporting

confidence: 60%

Section: Ceramic Glassy and Solid‐state Ionic Materialsmentioning

confidence: 99%

Sodium‐Ion Battery Electrolytes: Modeling and Simulations

Åvall

Mindemark

Brandell

et al. 2018

Advanced Energy Materials

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“…In this context, modeling the potential parameter to perform CMD would play a major role in opening up various theoretical studies to understand fundamentals of ion-hopping mechanisms. The potential of CMD has already been proven in systems such as AgI [29], beta-alumina [30], Na 2 M 2 TeO 6 (M = Ni 2+ , Zn 2+ , Co 2+ , or Mg 2+ ) [31][32][33][34], Na 1+x Zr 2 Si x P 3−x O 12 [26], and some liquids [35], where it satisfactorily mimicked various experimental observations.…”

Section: Introductionmentioning

confidence: 54%

Reorientational motion and Li+ -ion transport in Li2B12H12 system: M

Ikeshoji

Kim

et al. 2019

Phys. Rev. Materials

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Li 2 B 12 H 12 and its derivatives are promising solid electrolytes for solid-state batteries. In this work, a potential model is proposed, and an extensive classical molecular dynamics study is performed to understand the origin of the fast ion conduction in Li 2 B 12 H 12 . The proposed potential model reveals structural and dynamical properties of Li 2 B 12 H 12 that are consistent with first-principles molecular dynamics simulation and experimental results. The mechanism of Li + -ion transport is studied systematically. The low-temperature α phase exhibits negligible diffusivity within a timescale of a few nanoseconds, whereas the high-temperature β phase with a similar crystal structure and larger lattice parameter exhibits entropy-driven high Li + -ion diffusion assisted by anionic reorientation. We explicitly demonstrate the role of closo-borane anionic reorientational motion in the Li + -ion diffusion and explain how the cell parameter facilitates the anionic reorientational motion. In addition, enhancing the degree of H freedom (by changing the B-B-H angular force parameters) results in significantly high cationic diffusivity at low temperature. Further insight into Li + -ion transport is obtained by constructing a three-dimensional density map and determining the free-energy barrier, and the factors affecting cationic diffusion are thoroughly investigated with high precision using long simulations (5 ns).

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“…Na2 is sandwiched between the triangular faces of the ZnO 6 octahedra, and Na3 is between the ZnO 6 octahedra and TeO 6 octahedra. Based on a molecular dynamics (MD) simulation of Na + ion transport in Na 2 Ni 2 TeO 6 (NNTO), Na + ions migrate from Na1 to Na2, but with less contribution from Na3 because the potential energy of Na1 and Na2 (−2.45 and −2.65 eV, respectively) is much lower than that of Na3 (−2.32 eV) . However, our bond valence sum (BVS) studies show that Na3 has nearly equal potential energy to Na1 and Na2 in Na 2 Zn 2 TeO 6 (NZTO) (see Figure S1, Supporting Information) because the repulsion of Na + with Zn 2+ of NZTO is much less than that of Na + with Te 6+ of NNTO.…”

Section: Figurementioning

confidence: 91%

A P2‐Type Layered Superionic Conductor Ga‐Doped Na₂Zn₂TeO₆ for All‐Solid‐State Sodium‐Ion Batteries

Deng

Peng

et al. 2018

Chemistry A European J

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Here, a P2-type layered Na Zn TeO (NZTO) is reported with a high Na ion conductivity ≈0.6×10 S cm at room temperature (RT), which is comparable to the currently best Na Zr Si P O NASICON structure. As small amounts of Ga substitutes for Zn , more Na vacancies are introduced in the interlayer gaps, which greatly reduces strong Na -Na coulomb interactions. Ga-substituted NZTO exhibits a superionic conductivity of ≈1.1×10 S cm at RT, and excellent phase and electrochemical stability. All solid-state batteries have been successfully assembled with a capacity of ≈70 mAh g over 10 cycles with a rate of 0.2 C at 80 °C. Na nuclear magnetic resonance (NMR) studies on powder samples show intra-grain (bulk) diffusion coefficients D on the order of 12.35×10 m s at 65 °C that corresponds to a conductivity σ of 8.16×10 S cm , assuming the Nernst-Einstein equation, which thus suggests a new perspective of fast Na ion conductor for advanced sodium ion batteries.

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Ion Transport in Na₂M₂TeO₆: Insights from Molecular Dynamics Simulation

Cited by 39 publications

References 50 publications

Sodium‐Ion Battery Electrolytes: Modeling and Simulations

Sodium‐Ion Battery Electrolytes: Modeling and Simulations

Reorientational motion and Li+ -ion transport in Li2B12H12 system: M

A P2‐Type Layered Superionic Conductor Ga‐Doped Na₂Zn₂TeO₆ for All‐Solid‐State Sodium‐Ion Batteries

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Ion Transport in Na2M2TeO6: Insights from Molecular Dynamics Simulation

Cited by 39 publications

References 50 publications

Sodium‐Ion Battery Electrolytes: Modeling and Simulations

Sodium‐Ion Battery Electrolytes: Modeling and Simulations

Reorientational motion and Li+ -ion transport in Li2B12H12 system: M

A P2‐Type Layered Superionic Conductor Ga‐Doped Na2Zn2TeO6 for All‐Solid‐State Sodium‐Ion Batteries

Contact Info

Product

Resources

About

Ion Transport in Na₂M₂TeO₆: Insights from Molecular Dynamics Simulation

A P2‐Type Layered Superionic Conductor Ga‐Doped Na₂Zn₂TeO₆ for All‐Solid‐State Sodium‐Ion Batteries