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Record W2785357392 · doi:10.1021/acs.chemmater.7b05108

Correlation of Structure and Fast Ion Conductivity in the Solid Solution Series Li<sub>1+2<i>x</i></sub>Zn<sub>1–<i>x</i></sub>PS<sub>4</sub>

2018· article· en· W2785357392 on OpenAlexafffund
Kavish Kaup, Fabien Lalère, Ashfia Huq, Abhinandan Shyamsunder, Torben Adermann, Pascal Hartmann, Linda F. Nazar

Bibliographic record

VenueChemistry of Materials · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaBASF
KeywordsOak Ridge National LaboratoryCitationLibrary sciencePhysicsComputer scienceEngineering physicsNanotechnologyMaterials scienceNuclear physics

Abstract

fetched live from OpenAlex

Solid electrolytes are the foundation of all-solid-state batteries (ASSB) and have the potential to provide improved safety and higher energy density than existing liquid battery systems. In the important search for new lithium ion conductors with fast ionic conductivity and good mechanical properties, thiophosphates are a particularly promising class of materials. The first experimental elucidation of new lithium ion conductors in the Li<sub>1+2x</sub>Zn<sub>1-x</sub>PS<sub>4</sub> (LZPS) solid solution whose existence had been predicted by theory is reported in this paper. Using neutron and synchrotron x-ray powder diffraction together with electrical impedance, and Raman studies, we resolve their crystalline nature and correlate this with ionic conductivity upon increasing the lithium/zinc ratio. We demonstrate that the materials exhibit high experimental ionic conductivities - up to 8 × 10<sup>-4</sup> S·cm<sup>-1</sup> - and show the nature of likely pathways for lithium ion conduction.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.203
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations55
Published2018
Admission routes2
Has abstractyes

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