MétaCan
Menu
Back to cohort
Record W4393317344 · doi:10.1021/acs.nanolett.4c00808

Vacancy-Enhanced Sb–N<sub>4</sub> Sites for the Oxygen Reduction Reaction and Zn–Air Battery

2024· article· en· W4393317344 on OpenAlexafffund
Ying Zhang, Zhiwen Chen, Xu Liu, Zi Wen, Chandra Veer Singh, Chun Cheng Yang, Qing Jiang

Bibliographic record

VenueNano Letters · 2024
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Toronto
FundersJilin Scientific and Technological Development ProgramAlliance de recherche numérique du CanadaJilin UniversityUniversity of TorontoNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsDensity functional theoryVacancy defectCatalysisScanning transmission electron microscopyChemistryBattery (electricity)AdsorptionAbsorption (acoustics)OxygenCarbon fibersMoleculeMetalTransmission electron microscopyNanotechnologyMaterials sciencePhysical chemistryCrystallographyComputational chemistryPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

With the advantages of a Fenton-inactive characteristic and unique p electrons that can hybridize with O 2 molecules, p-block metal-based single-atom catalysts (SACs) for the oxygen reduction reaction (ORR) have tremendous potential. Nevertheless, their undesirable intrinsic activity caused by the closed d 10 electronic configuration remains a major challenge. Herein, an Sb-based SAC featuring carbon vacancy-enhanced Sb–N 4 active centers, corroborated by the results of high-angle annular dark-field scanning transmission electron microscopy and X-ray absorption fine structure, has been developed for an incredibly effective ORR. The obtained Sb SA –N–C demonstrates a positive half-wave potential of 0.905 V and excellent structural stability in alkaline environments. Density functional theory calculations reveal that the carbon vacancies weaken the adsorption between Sb atoms and the OH* intermediate, thus promoting the ORR performance. Practically, the Sb SA –N–C-based Zn–air batteries achieve impressive outcomes, such as a high power density of 181 mW cm –2, showing great potential in real-world applications.

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 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 score0.033
Threshold uncertainty score0.654

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)0.0000.000

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 head0.212
Teacher spread0.204 · 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.

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

Citations39
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueNano LettersSame topicElectrocatalysts for Energy ConversionFrench-language works237,207