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Record W2465314652 · doi:10.1021/acsenergylett.6b00145

Layered TiS<sub>2</sub> Positive Electrode for Mg Batteries

2016· article· en· W2465314652 on OpenAlexaff
Xiaoqi Sun, Patrick Bonnick, Linda F. Nazar

Bibliographic record

VenueACS Energy Letters · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Waterloo
FundersBasic Energy Sciences
KeywordsElectrodeMaterials scienceNanotechnologyMetallurgyOptoelectronicsChemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Magnesium batteries are a good candidate for high energy storage systems, but the limited discovery of functional positive electrode materials beyond the seminal Chevrel phase (Mo 6 S 8 ) has slowed their development. Herein, we report on layered TiS 2 as a promising positive electrode intercalation material, providing 115 mAh g –1 stabilized capacity in a Mg full cell. Reversible Mg 2+ intercalation into the structure is proven by elemental analysis combined with X-ray diffraction studies that elucidate the phase behavior upon cycling. The voltage profiles reveal distinct Mg 2+ cation ordering, unlike the solid solution behavior exhibited by Li + . Our findings not only point to the important role of “soft” lattices to facilitate divalent solid-state cation mobility but also now provide an alternative sulfide to serve as a platform for the fundamental understanding of Mg 2+ intercalation in lattices.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.006
GPT teacher head0.194
Teacher spread0.189 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations374
Published2016
Admission routes1
Has abstractyes

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