Analysis of diffusion in solid state electrolytes through MD-simulations, improvement of the Li-ion conductivity in \beta-Li3PS4 as an example

December 19, 2017

Klerk Niek J. J. de, der Maas Eveline van, Marnix Wagemaker

Physics

Condensed Matter

Chemical Physics

Materials Science

Molecular dynamics simulations are a powerful tool to study diffusion processes in battery electrolyte and electrode materials. From a single molecular dynamics simulation many properties relevant to diffusion can be obtained, including the diffusion path, attempt frequency, activation energies, and collective diffusion processes. These detailed diffusion properties provide a thorough understanding of diffusion in solid electrolytes, and provides direction for the design of improved solid electrolyte materials. Here a thorough analysis methodology is developed, and applied to DFT MD simulations of Li-ion diffusion in \beta-Li3PS4. The methodology presented is generally applicable to crystalline materials and facilitates the analysis of molecular dynamics simulations. The code used for the analysis is freely available at: https://bitbucket.org/niekdeklerk/md-analysis-with-matlab. The results on \beta-Li3PS4 demonstrate that jumps between bc-planes limit the conductivity of this important class of solid electrolyte materials. The simulations indicate that by adding Li-interstitials or Li-vacancies the rate limiting jump process can be accelerated significantly, which induces three dimensional diffusion, resulting in an increased Li-ion diffusivity. Li-vacancies can be introduced through Br-doping, which is predicted to result in an order of magnitude larger Li-ion conductivity in \beta-Li3PS4. Furthermore, the present simulations rationalise the improved Li-ion diffusivity upon O-doping through the creation of local Li-interstitials.

Diffusion of Lithium Ions in Lithium-Argyrodite Solid-State Electrolytes from Equilibrium and Nonequilibrium Molecular Dynamics Simulations

December 6, 2019

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Ardeshir Baktash, James C. Reid, ... , Searles Debra J.

Materials Science

The use of solid-state electrolytes to provide safer, next-generation rechargeable batteries is becoming more feasible as new materials with greater stability and higher ionic diffusion coefficients are designed. However, accurate determination of diffusion coefficients in solids is problematic and reliable calculations are highly sought-after. In this paper we compare diffusion coefficients calculated using nonequilibrium and equilibrium ab initio molecular dynamics simulati...

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Robust and efficient calculation of activation energy by automated path search and density functional theory

April 16, 2021

89% Match

Koki Technology Innovation Division, Panasonic Corporation Ueno, Kazuhide Technology Innovation Division, Panasonic Corporation Ichikawa, Kosei Department of Engineering, Nagoya Institute of Technology Sato, Daisuke Department of Engineering, Nagoya Institute of Technology Sugita, ... , Takeuchi Ichiro Department of Engineering, Nagoya Institute of Technology

Materials Science

Because inorganic solid electrolytes are one of the key components for application to all-solid-state batteries, high-ionic-conductivity materials must be developed. Therefore, we propose a method of efficiently evaluating the activation energy of ionic diffusion by calculating a potential-energy surface (PES), searching for the optimal diffusion path by an algorithm developed using dynamic programming (DP), and calculating the corresponding activation energy by the nudged el...

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August 8, 2017

88% Match

Stefano D. Di, A. Miglio, K. Robeyns, Y. Filinchuk, M. Lechartier, A. Senyshyn, H. Ishida, S. Spannenberger, D. Prutsch, S. Lunghammer, D. Rettenwander, M. Wilkening, B. Roling, ... , Hautier G.

Materials Science

Classical Physics

Solid-state materials with high ionic conduction are necessary to many technologies including all-solid-state Li-ion batteries. Understanding how crystal structure dictates ionic diffusion is at the root of the development of fast ionic conductors. Here, we show that LiTi2(PS4)3 exhibits a Li-ion diffusion coefficient about an order of magnitude higher than current state-of-the-art lithium superionic conductors. We rationalize this observation by the unusual crystal structure...

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Disorder-dependent Li diffusion in $\mathrm{Li_6PS_5Cl}$ investigated by machine learning potential

October 30, 2023

88% Match

Jiho Lee, Suyeon Ju, Seungwoo Hwang, Jinmu You, Jisu Jung, ... , Han Seungwu

Materials Science

Solid-state electrolytes with argyrodite structures, such as $\mathrm{Li_6PS_5Cl}$, have attracted considerable attention due to their superior safety compared to liquid electrolytes and higher ionic conductivity than other solid electrolytes. Although experimental efforts have been made to enhance conductivity by controlling the degree of disorder, the underlying diffusion mechanism is not yet fully understood. Moreover, existing theoretical analyses based on ab initio MD si...

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February 19, 2021

88% Match

Marcel Sadowski, Karsten Albe

Materials Science

We investigate the influence of Br$^-$/S$^{2-}$ site-exchange on lithium diffusion in the agyrodite-type solid electrolyte Li$_6$PS$_5$Br by ab-initio molecular dynamics simulations. Based on the calculated trajectories a new mechanism for the internal lithium reorganization within the Li-cages around the $4d$ sites is identified. This reorganization mechanism is highly concerted and cannot be described by one single rotation axis only. Simulations with Br$^-$/S$^{2-}$ defect...

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November 30, 2020

87% Match

Kiarash Gordiz, Sokseiha Muy, Wolfgang G. Zeier, ... , Henry Asegun

Materials Science

Computational Physics

Ion diffusion is important in a variety of applications, yet fundamental understanding of the diffusive process in solids is still missing, especially considering the interaction of lattice vibrations (phonons) and the mobile species. In this work, we introduce two formalisms that determine the individual contributions of normal modes of vibration (phonons) to the diffusion of ions through a solid, based on (i) Nudged Elastic Band (NEB) calculations and (ii) molecular dynamic...

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Mechanistic Insights into Temperature Effects for Ionic Conductivity in Li6PS5Cl

March 21, 2024

87% Match

Zicun Li, Jianxing Huang, Xinguo Ren, Jinbin Li, ... , Li Hong

Materials Science

Computational Physics

Ensuring solid-state lithium batteries perform well across a wide temperature range is crucial for their practical use. Molecular dynamics (MD) simulations can provide valuable insights into the temperature dependence of the battery materials, however, the high computational cost of ab initio MD poses challenges for simulating ion migration dynamics at low temperatures. To address this issue, accurate machine-learning interatomic potentials were trained, which enable efficien...

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October 24, 2023

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Lorenzo Gigli, Davide Tisi, ... , Ceriotti Michele

Materials Science

Lithium ortho-thiophosphate (Li$_3$PS$_4$) has emerged as a promising candidate for solid-state-electrolyte batteries, thanks to its highly conductive phases, cheap components, and large electrochemical stability range. Nonetheless, the microscopic mechanisms of Li-ion transport in Li$_3$PS$_4$ are far to be fully understood, the role of PS$_4$ dynamics in charge transport still being controversial. In this work, we build machine learning potentials targeting state-of-the-art...

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Enhanced ionic conductivity through crystallization of glass-Li$_3$PS$_4$ by machine learning molecular dynamics simulations

December 12, 2023

87% Match

Koji Shimizu, Parth Bahuguna, Shigeo Mori, ... , Watanabe Satoshi

Materials Science

Understanding the atomistic mechanism of ion conduction in solid electrolytes is critical for the advancement of all-solid-state batteries. Glass-ceramics, which undergo crystallization from a glass state, frequently exhibit unique properties including enhanced ionic conductivities compared to both the original crystalline and glass forms. Despite these distinctive features, specific details regarding the behavior of ion conduction in glass-ceramics, particularly concerning c...

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Simulating diffusion properties of solid-state electrolytes via a neural network potential: Performance and training scheme

October 22, 2019

87% Match

Aris Marcolongo, Tobias Binninger, ... , Laino Teodoro

Computational Physics

The recently published DeePMD model (https://github.com/deepmodeling/deepmd-kit), based on a deep neural network architecture, brings the hope of solving the time-scale issue which often prevents the application of first principle molecular dynamics to physical systems. With this contribution we assess the performance of the DeePMD potential on a real-life application and model diffusion of ions in solid-state electrolytes. We consider as test cases the well known Li10GeP2S12...

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