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Record W3084670703 · doi:10.1002/anie.202009991

Turning on Zn 4s Electrons in a N<sub>2</sub>‐Zn‐B<sub>2</sub> Configuration to Stimulate Remarkable ORR Performance

2020· article· en· W3084670703 on OpenAlexaff
Jing Wang, Hongguan Li, Shuhu Liu, Yongfeng Hu, Jing Zhang, Meirong Xia, Yanglong Hou, John S. Tse, Jiujun Zhang, Yufeng Zhao

Bibliographic record

VenueAngewandte Chemie International Edition · 2020
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of SaskatchewanCanadian Light Source (Canada)
FundersNational Natural Science Foundation of China
KeywordsDelocalized electronCatalysisTransition metalAtom (system on chip)ChemistryElectron configurationMetalZincElectrocatalystElectron transferCrystallographyMaterials scienceInorganic chemistryNanotechnologyPhysical chemistryIonElectrochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract A zinc‐based single‐atom catalyst has been recently explored with distinguished stability, of which the fully occupied Zn 2+ 3d 10 electronic configuration is Fenton‐reaction‐inactive, but the catalytic activity is thus inferior. Herein, we report an approach to manipulate the s‐band by constructing a B,N co‐coordinated Zn‐B/N‐C catalyst. We confirm both experimentally and theoretically that the unique N 2 ‐Zn‐B 2 configuration is crucial, in which Zn + (3d 10 4s 1 ) can hold enough delocalized electrons to generate suitable binding strength for key reaction intermediates and promote the charge transfer between catalytic surface and ORR reactants. This exclusive effect is not found in the other transition‐metal counterparts such as M‐B/N‐C (M=Mn, Fe, Co, Ni and Cu). Consequently, the as‐obtained catalyst demonstrates impressive ORR activity, along with remarkable long‐term stability in both alkaline and acid media. This work presents a new concept in the further design of electrocatalyst.

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)
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 score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.011
GPT teacher head0.224
Teacher spread0.213 · 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

Citations234
Published2020
Admission routes1
Has abstractyes

Explore more

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