MétaCan
Menu
Back to cohort
Record W4306631542 · doi:10.1002/cjce.24723

Ultrathin <i> Ti <sub>3</sub> C <sub>2</sub> T <sub>x</sub> </i> nanosheets modified separators for lithium–sulphur batteries

2022· article· en· W4306631542 on OpenAlexvenueno aff
Dong Chen, Yangyang Mao, Yongan Cao, Wenju Wang

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2022
Typearticle
Languageen
FieldMaterials Science
TopicMXene and MAX Phase Materials
Canadian institutionsnot available
FundersFundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of China
KeywordsSeparator (oil production)Materials scienceLithium (medication)Energy storageChemical engineeringBattery (electricity)

Abstract

fetched live from OpenAlex

Abstract Currently, among the various emerging energy storage systems, the lithium–sulphur (Li‐S) battery is expected to be one of the next‐generation lithium secondary batteries with high efficiency. However, the practical application of Li‐S batteries still faces many obstacles. To solve the shuttle effect of lithium polysulphides, ultrathin Ti 3 C 2 T x nanosheets were prepared through the in‐situ acid etching method and applied to separator modification to suppress the shuttle effect of lithium polysulphides. Ultrathin Ti 3 C 2 T x nanosheets with enlarged interlayer spacing accelerated the migration of Li + . The abundant termination groups on the surface of Ti 3 C 2 T x played the role of the lithium polysulphide capture centre. When the mass loading of separator modification materials was set as 0.025 mg cm −2 , the as‐prepared battery exhibited a reversible specific capacity as high as 780 mAh g −1 after 200 cycles at 0.2 C, and the single‐cycle capacity decay rate was only 0.09%.

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 score0.001
Threshold uncertainty score0.003

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.201
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

Citations3
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicMXene and MAX Phase MaterialsFrench-language works237,207