High-Throughput Screening of Solid-State Li-Ion Conductors Using Lattice-Dynamics Descriptors
© 2019 The Authors Low lithium-ion migration barriers have recently been associated with low average vibrational frequencies or phonon band centers, further helping identify descriptors for superionic conduction. To further explore this correlation, here we present the computational screening of ∼14...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier BV
2021
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| Online Access: | https://hdl.handle.net/1721.1/134620 |
| _version_ | 1826217225810345984 |
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| author | Muy, Sokseiha Voss, Johannes Schlem, Roman Koerver, Raimund Sedlmaier, Stefan J Maglia, Filippo Lamp, Peter Zeier, Wolfgang G Shao-Horn, Yang |
| author_facet | Muy, Sokseiha Voss, Johannes Schlem, Roman Koerver, Raimund Sedlmaier, Stefan J Maglia, Filippo Lamp, Peter Zeier, Wolfgang G Shao-Horn, Yang |
| author_sort | Muy, Sokseiha |
| collection | MIT |
| description | © 2019 The Authors Low lithium-ion migration barriers have recently been associated with low average vibrational frequencies or phonon band centers, further helping identify descriptors for superionic conduction. To further explore this correlation, here we present the computational screening of ∼14,000 Li-containing compounds in the Materials Project database using a descriptor based on lattice dynamics reported recently to identify new promising Li-ion conductors. An efficient computational approach was optimized to compute the average vibrational frequency or phonon band center of ∼1,200 compounds obtained after pre-screening based on structural stability, band gap, and their composition. Combining a low computed Li phonon band center with large computed electrochemical stability window and structural stability, 18 compounds were predicted to be promising Li-ion conductors, one of which, Li3ErCl6, has been synthesized and exhibits a reasonably high room-temperature conductivity of 0.05–0.3 mS/cm, which shows the promise of Li-ion conductor discovery based on lattice dynamics. Computational Method in Materials Science; Energy Materials; Solid State Physics |
| first_indexed | 2024-09-23T17:00:19Z |
| format | Article |
| id | mit-1721.1/134620 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T17:00:19Z |
| publishDate | 2021 |
| publisher | Elsevier BV |
| record_format | dspace |
| spelling | mit-1721.1/1346202021-10-28T03:03:49Z High-Throughput Screening of Solid-State Li-Ion Conductors Using Lattice-Dynamics Descriptors Muy, Sokseiha Voss, Johannes Schlem, Roman Koerver, Raimund Sedlmaier, Stefan J Maglia, Filippo Lamp, Peter Zeier, Wolfgang G Shao-Horn, Yang © 2019 The Authors Low lithium-ion migration barriers have recently been associated with low average vibrational frequencies or phonon band centers, further helping identify descriptors for superionic conduction. To further explore this correlation, here we present the computational screening of ∼14,000 Li-containing compounds in the Materials Project database using a descriptor based on lattice dynamics reported recently to identify new promising Li-ion conductors. An efficient computational approach was optimized to compute the average vibrational frequency or phonon band center of ∼1,200 compounds obtained after pre-screening based on structural stability, band gap, and their composition. Combining a low computed Li phonon band center with large computed electrochemical stability window and structural stability, 18 compounds were predicted to be promising Li-ion conductors, one of which, Li3ErCl6, has been synthesized and exhibits a reasonably high room-temperature conductivity of 0.05–0.3 mS/cm, which shows the promise of Li-ion conductor discovery based on lattice dynamics. Computational Method in Materials Science; Energy Materials; Solid State Physics 2021-10-27T20:05:48Z 2021-10-27T20:05:48Z 2019 2020-08-06T13:47:36Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/134620 en 10.1016/J.ISCI.2019.05.036 iScience Creative Commons Attribution-NonCommercial-NoDerivs License http://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf Elsevier BV Elsevier |
| spellingShingle | Muy, Sokseiha Voss, Johannes Schlem, Roman Koerver, Raimund Sedlmaier, Stefan J Maglia, Filippo Lamp, Peter Zeier, Wolfgang G Shao-Horn, Yang High-Throughput Screening of Solid-State Li-Ion Conductors Using Lattice-Dynamics Descriptors |
| title | High-Throughput Screening of Solid-State Li-Ion Conductors Using Lattice-Dynamics Descriptors |
| title_full | High-Throughput Screening of Solid-State Li-Ion Conductors Using Lattice-Dynamics Descriptors |
| title_fullStr | High-Throughput Screening of Solid-State Li-Ion Conductors Using Lattice-Dynamics Descriptors |
| title_full_unstemmed | High-Throughput Screening of Solid-State Li-Ion Conductors Using Lattice-Dynamics Descriptors |
| title_short | High-Throughput Screening of Solid-State Li-Ion Conductors Using Lattice-Dynamics Descriptors |
| title_sort | high throughput screening of solid state li ion conductors using lattice dynamics descriptors |
| url | https://hdl.handle.net/1721.1/134620 |
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