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Record W4308909138 · doi:10.1002/aenm.202270176

Creating Edge Sites within the 2D Metal‐Organic Framework Boosts Redox Kinetics in Lithium–Sulfur Batteries (Adv. Energy Mater. 42/2022)

2022· article· en· W4308909138 on OpenAlexaff
Xingbo Wang, Chunrong Zhao, Bingxue Liu, Shangqian Zhao, Yongguang Zhang, Lanting Qian, Zhongjun Chen, Jiantao Wang, Xin Wang, Zhongwei Chen

Bibliographic record

VenueAdvanced Energy Materials · 2022
Typearticle
Languageen
FieldMaterials Science
TopicPolyoxometalates: Synthesis and Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceLithium (medication)SulfurCathodeEnhanced Data Rates for GSM EvolutionAdsorptionRedoxCatalysisNanotechnologyMetalMetal-organic frameworkInorganic chemistryChemical engineeringOrganic chemistryChemistryComputer scienceMetallurgyEngineeringPhysical chemistry

Abstract

fetched live from OpenAlex

Metal-Organic Frameworks In article number 2201960, Jiantao Wang, Xin Wang, Zhongwei Chen, and co-workers adopted a simple method to design a material that can create edge sites and defects on two-dimensional metal-organic frameworks as the cathode for lithium sulfur batteries, which can be used to catalyze the conversion of polysulfides. The creation of edge active sites provides a new strategic perspective for the adsorption and catalysis of polysulfides and has great prospects for promoting the future development of lithium sulfur batteries.

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 score0.005

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 head0.010
GPT teacher head0.240
Teacher spread0.229 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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