MétaCan
Menu
Back to cohort
Record W4210834172 · doi:10.1002/adma.202107954

Tuning Two‐Electron Oxygen‐Reduction Pathways for H<sub>2</sub>O<sub>2</sub> Electrosynthesis via Engineering Atomically Dispersed Single Metal Site Catalysts

2022· review· en· W4210834172 on OpenAlexaff
Xiaoxuan Yang, Yachao Zeng, Wajdi Alnoush, Yang Hou, Drew Higgins, Gang Wu

Bibliographic record

VenueAdvanced Materials · 2022
Typereview
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsMcMaster University
FundersNatural Science Foundation of Zhejiang ProvinceDivision of Chemical, Bioengineering, Environmental, and Transport SystemsNational Natural Science Foundation of ChinaFundamental Research Funds for the Central UniversitiesNational Science Foundation
KeywordsCatalysisElectrosynthesisMaterials scienceElectrochemistryRational designPlatinumNanotechnologyElectrolysisChemical engineeringElectrodeChemistryElectrolyteOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The hydrogen peroxide (H 2 O 2 ) generation via the electrochemical oxygen reduction reaction (ORR) under ambient conditions is emerging as an alternative and green strategy to the traditional energy‐intensive anthraquinone process and unsafe direct synthesis using H 2 and O 2 . It enables on‐site and decentralized H 2 O 2 production using air and renewable electricity for various applications. Currently, atomically dispersed single metal site catalysts have emerged as the most promising platinum group metal (PGM)‐free electrocatalysts for the ORR. Further tuning their central metal sites, coordination environments, and local structures can be highly active and selective for H 2 O 2 production via the 2e − ORR. Herein, recent methodologies and achievements on developing single metal site catalysts for selective O 2 to H 2 O 2 reduction are summarized. Combined with theoretical computation and advanced characterization, a structure–property correlation to guide rational catalyst design with a favorable 2e − ORR process is aimed to provide. Due to the oxidative nature of H 2 O 2 and the derived free radicals, catalyst stability and effective solutions to improve catalyst tolerance to H 2 O 2 are emphasized. Transferring intrinsic catalyst properties to electrode performance for viable applications always remains a grand challenge. The key performance metrics and knowledge during the electrolyzer development are, therefore, highlighted.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.234
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.015
GPT teacher head0.234
Teacher spread0.219 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreReview

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

Citations222
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueAdvanced MaterialsSame topicElectrocatalysts for Energy ConversionFrench-language works237,207