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Record W3123999877 · doi:10.1002/ange.202016891

Innentitelbild: Strain Engineering of a MXene/CNT Hierarchical Porous Hollow Microsphere Electrocatalyst for a High‐Efficiency Lithium Polysulfide Conversion Process (Angew. Chem. 5/2021)

2021· article· en· W3123999877 on OpenAlexaff
Xin Wang, Dan Luo, Jiayi Wang, Zhenghao Sun, Guoliang Cui, Yuxuan Chen, Tong Wang, Lirong Zheng, Yan Zhao, Lingling Shui, Guofu Zhou, Krzysztof Kempa, Yongguang Zhang, Zhongwei Chen

Bibliographic record

VenueAngewandte Chemie · 2021
Typearticle
Languageen
FieldMaterials Science
TopicMXene and MAX Phase Materials
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMicrosphereLithium (medication)Materials scienceChemistryPolysulfidePorosityElectrocatalystChemical engineeringNanotechnologyElectrochemistryPhysical chemistryComposite materialElectrodeElectrolyteEngineering

Abstract

fetched live from OpenAlex

Poröse MXene/CNT-Mikrokugeln wurden von Xin Wang, Zhongwei Chen et al. in ihrem Forschungsartikel auf S. 2401 als Elektrokatalysator für hochleistungsfähige Lithium-Schwefel-Batterien entwickelt. Eine einzigartige O-Ti-C-Grenzfläche wurde auf der MXene-Oberfläche durch einen Sprühtrocknungsprozess und Wärmebehandlung konstruiert, um eine innere Spannung zu erzeugen, die eine Gitterverzerrung und eine Vergrößerung der Ti-Ti-Bindung induziert.

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), Insufficient payload (model declined to judge)
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 studies0.0000.000
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 head0.008
GPT teacher head0.237
Teacher spread0.228 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

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