Paper Citation Record · LEDGER

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study

As of 19 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2506.11199.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.11199 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:18:00.461393Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

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External citation measurements

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Outbound references

Observation 858667f5-1fd4-4ff4-8d29-5f67a1e7c08f · outbound

This paper cites an unresolved cited work.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Unresolved cited work

Reference 1

Resolution: verified exact; doi, observed 2026-08-07T04:18:00.670022Z

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Observation 8b02abe0-7ffa-492a-8aa9-c7e438fcd682 · outbound

This paper cites an unresolved cited work.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Unresolved cited work

Reference 2

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Observation 19bb3913-164e-46c2-9b50-d117bddd7cd1 · outbound

This paper cites Kamaya, K.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Kamaya, K

Reference 3

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This paper cites Adeli, J.D.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Adeli, J.D

Reference 4

Resolution: verified exact; doi, observed 2026-08-07T04:18:00.655111Z

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This paper cites an unresolved cited work.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Unresolved cited work

Reference 5

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This paper cites Liang, Y.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Liang, Y

Reference 6

Resolution: verified exact; doi, observed 2026-08-07T04:18:00.640182Z

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Observation 019e35a0-b6aa-4b3f-92f9-8fd5671a56bd · outbound

This paper cites an unresolved cited work.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Unresolved cited work

Reference 7

Resolution: verified exact; doi, observed 2026-08-07T04:18:00.632059Z

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Observation 844a02dd-e56d-4c9c-bbb4-5f5ecf3efefa · outbound

This paper cites an unresolved cited work.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Unresolved cited work

Reference 8

Resolution: verified exact; doi, observed 2026-08-07T04:18:00.623762Z

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This paper cites Kızılaslan, R.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Kızılaslan, R

Reference 9

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This paper cites an unresolved cited work.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Unresolved cited work

Reference 10

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Observation eeee294f-96ce-478b-b469-d842a9cc6cb6 · outbound

This paper cites an unresolved cited work.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Unresolved cited work

Reference 11

Resolution: verified exact; doi, observed 2026-08-07T04:18:00.606817Z

Source-reported events for the cited work

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Observation a241426f-200a-4660-ae0a-be6dcfa1dab9 · outbound

This paper cites Conlin, H.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Conlin, H

Reference 12

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Observation c9c89254-f085-4bc0-97b6-6aa41f8a4060 · outbound

This paper cites an unresolved cited work.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Unresolved cited work

Reference 13

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Observation 6e01b28d-d706-45a9-8e21-e4b61bbb3864 · outbound

This paper cites Selvaraj, V.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Selvaraj, V

Reference 14

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Observation 4301d97d-5f11-4daf-9e29-2bf3f235a7a8 · outbound

This paper cites Chandrasekaran, P.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Chandrasekaran, P

Reference 15

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Observation a333afb4-81cb-4964-8308-d2c90076af30 · outbound

This paper cites Chandrasekaran, M.R.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Chandrasekaran, M.R

Reference 16

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Observation cedc1f01-9d4e-4412-81e2-b634f2c0d6d6 · outbound

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Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Unresolved cited work

Reference 17

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This paper cites Zhang, L.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Zhang, L

Reference 18

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Observation b660c3a3-e953-4fdd-9c1d-01e70f215171 · outbound

This paper cites Hirel, Atomsk: A tool for manipulating and converting atomic data files.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Hirel, Atomsk: A tool for manipulating and converting atomic data files

Reference 19

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Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Unresolved cited work

Reference 20

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Observation 39447a89-31e6-496b-aa17-becbf559da7e · outbound

This paper cites Kresse, J.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Kresse, J

Reference 21

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Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Kresse, J

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Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Bl¨ ochl, Projector augmented-wave method

Reference 23

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Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Perdew, K

Reference 24

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This paper cites Burke, J.P.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Burke, J.P

Reference 25

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Observation 0651813c-ac48-44af-882b-2b11eed9efda · outbound

This paper cites DeePMD-kit v2: A software package for Deep Potential models.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study DeePMD-kit v2: A software package for Deep Potential models

Reference 26

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Observation 9ef14a1c-95b6-4201-8a85-69b94edc7d69 · outbound

This paper cites Abadi, A.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Abadi, A

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Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Zhang, J

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Observation 16d5e21b-a463-4e69-8316-33b40c8fca6d · outbound

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Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Thompson, H.M

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Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Unresolved cited work

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Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Unresolved cited work

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Observation 7f18cc9f-f2c8-429f-81d2-76280ea83183 · outbound

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Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Momma, F

Reference 33

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Observation d34f63c4-48dc-416a-84c0-17758b6fc7e4 · outbound

This paper cites Stukowski, Visualization and analysis of atomistic simulation data with ovito–the open visu- alization tool.

Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study Stukowski, Visualization and analysis of atomistic simulation data with ovito–the open visu- alization tool

Reference 34

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Observation 764ed7aa-b43f-45d7-b4a3-0c914732b57e · outbound

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Mechanisms and Stability of Li Dynamics in Amorphous Li-Ti-P-S-Based Mixed Ionic-Electronic Conductors: A Machine Learning Molecular Dynamics Study EV ANS, G.P

Reference 35

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Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.