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Record W4402070899 · doi:10.1002/aenm.202402967

Unraveling the Trade‐Off Between Oxygen Vacancy Concentration and Ordering of Perovskite Oxides for Efficient Lattice Oxygen Evolution

2024· article· en· W4402070899 on OpenAlexaff
Lin‐Bo Liu, Yu‐Feng Tang, Shuo Liu, Mulin Yu, Yifei Sun, Xian‐Zhu Fu, Jing‐Li Luo, Subiao Liu

Bibliographic record

VenueAdvanced Energy Materials · 2024
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Alberta
FundersNatural Science Foundation of Hunan ProvinceNational Natural Science Foundation of China
KeywordsMaterials scienceOxygenLattice (music)Perovskite (structure)Vacancy defectOxygen evolutionCondensed matter physicsChemical physicsCrystallographyPhysical chemistryOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

Abstract Oxygen evolution reaction (OER) over perovskite oxides, upon undergoing a lattice oxygen oxidation mechanism, is strongly oxygen vacancy‐correlated as determined by the oxygen ion diffusivity. Despite substantial efforts having been devoted to tuning the oxygen vacancy concentration in perovskite oxides, the impact of the concomitant altering of oxygen vacancy ordering is often underestimated. In particular, the underlying mechanism of how the ordering and the concentration of oxygen vacancy affect the lattice OER, and how to well balance them still remain inadequately understood. Herein, a series of Sr 1− x Ca x Co 0.5 Fe 0.5 O 3− δ with gradually increased oxygen vacancy concentration and ordering are synthesized. Theoretical calculations indicated that a higher oxygen vacancy concentration promoted the lattice oxygen migration, whereas a higher oxygen vacancy ordering impeded it. Particularly, Sr 0.5 Ca 0.5 Co 0.5 Fe 0.5 O 3− δ with a relatively higher oxygen vacancy concentration and a lower ordering displayed the maximum oxygen diffusion rate and the optimal OER activity, affording a current density of 10 mA cm −2 at a quite low overpotential of 310.2 mV, together with a small Tafel slope of 55.87 mV dec −1 . This study sheds light on the critical influence of oxygen vacancy configuration on the lattice OER, and paves a compromised avenue to screen and design advanced electrocatalysts for various electrochemical devices.

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 score0.109
Threshold uncertainty score0.818

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 head0.009
GPT teacher head0.238
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 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

Citations50
Published2024
Admission routes1
Has abstractyes

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