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Record W3105677887 · doi:10.1038/s41467-020-19709-6

d-Orbital steered active sites through ligand editing on heterometal imidazole frameworks for rechargeable zinc-air battery

2020· article· en· W3105677887 on OpenAlexafffund
Yi Jiang, Ya‐Ping Deng, Ruilin Liang, Jing Fu, Rui Gao, Dan Luo, Zhengyu Bai, Yongfeng Hu, Aiping Yu, Zhongwei Chen

Bibliographic record

VenueNature Communications · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsCanadian Light Source (Canada)University of SaskatchewanUniversity of Waterloo
FundersNational Research Council CanadaWestern Economic Diversification CanadaNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchUniversity of WaterlooGovernment of CanadaUniversity of SaskatchewanCanadian Light Source
KeywordsCobaltLigand (biochemistry)ZincImidazoleBattery (electricity)DeprotonationMaterials scienceElectrodeChemistryMetallurgyPhysical chemistryStereochemistryOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract The implementation of pristine metal-organic frameworks as air electrode may spark fresh vitality to rechargeable zinc-air batteries, but successful employment is rare due to the challenges in regulating their electronic states and structural porosity. Here we conquer these issues by incorporating ligand vacancies and hierarchical pores into cobalt-zinc heterometal imidazole frameworks. Systematic characterization and theoretical modeling disclose that the ligand editing eases surmountable energy barrier for *OH deprotonation by its efficacy to steer metal d -orbital electron occupancy. As a stride forward, the selected cobalt-zinc heterometallic alliance lifts the energy level of unsaturated d -orbitals and optimizes their adsorption/desorption process with oxygenated intermediates. With these merits, cobalt-zinc heterometal imidazole frameworks, as a conceptually unique electrode, empowers zinc-air battery with a discharge-charge voltage gap of 0.8 V and a cyclability of 1250 h at 15 mA cm –2 , outperforming the noble-metal benchmarks.

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 score0.005

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)0.0020.000

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 head0.047
GPT teacher head0.327
Teacher spread0.279 · 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

Citations176
Published2020
Admission routes2
Has abstractyes

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Same venueNature CommunicationsSame topicAdvanced battery technologies researchFrench-language works237,207