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Record W3121091342 · doi:10.1002/anie.202011493

Strain Engineering of a MXene/CNT Hierarchical Porous Hollow Microsphere Electrocatalyst for a High‐Efficiency Lithium Polysulfide Conversion Process

2021· article· en· W3121091342 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAngewandte Chemie International Edition · 2021
Typearticle
Languageen
FieldMaterials Science
TopicMXene and MAX Phase Materials
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPolysulfideMaterials scienceElectrocatalystChemical engineeringPorosityComposite numberNanotechnologyCatalysisNanosheetElectrochemistryElectrodeComposite materialChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Tensile‐strained Mxene/carbon nanotube (CNT) porous microspheres were developed as an electrocatalyst for the lithium polysulfide (LiPS) redox reaction. The internal stress on the surface results in lattice distortion with expanding Ti−Ti bonds, endowing the Mxene nanosheet with abundant active sites and regulating the d‐band center of Ti atoms upshifted closer to the Fermi level, leading to strengthened LiPS adsorbability and accelerated catalytic conversion. The macroporous framework offers uniformed sulfur distribution, potent sulfur immobilization, and large surface area. The composite interwoven by CNT tentacle enhances conductivity and prevents the restacking of Mxene sheets. This combination of tensile strain effect and hierarchical architecture design results in smooth and favorable trapping–diffusion–conversion of LiPS on the interface. The Li‐S battery exhibits an initial capacity of 1451 mAh g −1 at 0.2 C, rate capability up to 8 C, and prolonged cycle life.

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.

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 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 score0.025
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

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 head0.009
GPT teacher head0.248
Teacher spread0.239 · 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