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Record W4293686424 · doi:10.1002/eom2.12266

Elucidation and modulation of active sites in holey graphene electrocatalysts for <scp>H<sub>2</sub>O<sub>2</sub></scp> production

2022· article· en· W4293686424 on OpenAlexafffund
Ki Hwan Koh, Amir Hassan Bagherzadeh Mostaghimi, Qiaowan Chang, Yu Joong Kim, Samira Siahrostami, Tae Hee Han, Zheng Chen

Bibliographic record

VenueEcoMat · 2022
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Calgary
FundersUniversity of California, San DiegoAmerican Chemical Society Petroleum Research FundCanada First Research Excellence FundNational Research Foundation of KoreaNational Research Foundation
KeywordsOverpotentialGrapheneDensity functional theoryElectrochemistryChemistryOxygenOxygen evolutionActive siteChemical engineeringNanotechnologyMaterials scienceCatalysisElectrodePhysical chemistryComputational chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Selective electrochemical oxygen reduction (ORR) toward a two‐electron (2e−) pathway is an eco‐friendly alternative method for H2O2 synthesis to replace the energy‐intensive anthraquinone oxidation process. Carbon‐based electrocatalysts (CBEs) show great potential for practical H2O2 synthesis. However, their complex structures make it challenging to determine the nature of active sites and to precisely control them. Herein, we show that precise modulation of the chemistry and structures of holey graphene with edge sites enriched by oxygen‐containing functional groups can facilitate 2e− ORR. These combined functionalities could improve ORR performance under various pH conditions, for example, resulting in an average of 95% H2O2 selectivity, ~97% Faraday efficiency, high productivity of 2360 mol kgcat−1 h−1 in alkaline media. Density functional theory calculations on the oxygen functional groups at the edge sites revealed the most active site for 2e− ORR is a synergy between ether (COC) and carbonyl (CO) functional groups with nearly zero overpotential. image

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 score0.001
Threshold uncertainty score0.002

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)0.0010.000

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 head0.008
GPT teacher head0.207
Teacher spread0.199 · 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

Citations43
Published2022
Admission routes2
Has abstractyes

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