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Record W4405826950 · doi:10.1016/j.esci.2024.100370

Unraveling the dipole field in ultrathin, porous, and defective carbon nitride nanosheets for record-high piezo-photocatalytic H2O2 production

2024· article· en· W4405826950 on OpenAlexaff
Zhaoqiang Wang, Guixiang Ding, Hongwei Huang, Juntao Zhang, Qi Lv, Shuai Li, Yonghao Ni, Guangfu Liao

Bibliographic record

VenueeScience · 2024
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversity of New Brunswick
FundersNatural Science Foundation of Fujian ProvinceNational Natural Science Foundation of ChinaChina Association for Science and Technology
KeywordsPhotocatalysisMaterials scienceCarbon nitrideGraphitic carbon nitrideNitrideDipolePorosityNanotechnologyField (mathematics)Production (economics)Chemical engineeringOptoelectronicsComposite materialChemistryCatalysisEngineeringLayer (electronics)Organic chemistry

Abstract

fetched live from OpenAlex

Piezo-photocatalysis is capable of concerting mechanical vibration into chemical energy, portraying a promising alternative technology for H 2 O 2 production. However, low mechanical energy conversion efficiency and constrained surface active sites hinder its practical application. Herein, ultrathin porous carbon nitride nanosheets with controlled carbon vacancies and oxygen doping (OCN-X, where X represents the calcination temperature) are synthesized by thermal oxidation etching to achieve unprecedented piezo-photocatalytic H 2 O 2 production. The carbon vacancies and oxygen doping cause the formation of asymmetric structure of triazine unit with a strong dipole field, which creates spontaneous polarization field to speed up directional electron transfer to the nitrogen active sites for effective piezo-photocatalysis. Meanwhile, the ultrathin and porous structure formed by hot-oxygen etching enhances the mechanical energy conversion efficiency and collaboratively induces adsorbed oxygen via indirect two-electron oxygen reduction reaction (ORR) transfer pathway to effectively produce H 2 O 2 . Consequently, without any co-catalysts, the as-prepared OCN-460 displays record-high piezo-photocatalytic H 2 O 2 production rate of 19.30 ​mmol ​g −1 ​h −1 , far outdistancing those previously reported for piezo-photocatalysts. Furthermore, it also still maintains a notable piezo-photocatalytic activity of 2.87 ​mmol ​g −1 ​h −1 in the pure water system. This work offers some new insights for the future design of an effective piezo-photocatalytic H 2 O 2 production system. • Ultrathin porous g-C 3 N 4 nanosheets with carbon vacancies and oxygen doping were prepared. • Record-high piezo-photocatalytic H 2 O 2 production was achieved. • Dipole field in ultrathin, porous, and defective g-C 3 N 4 nanosheets was revealed. • Piezo-photocatalytic mechanism was revealed by state-of-the-art characterizations.

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 score0.000
Threshold uncertainty score0.001

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)0.0000.000

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 head0.011
GPT teacher head0.267
Teacher spread0.257 · 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

Citations72
Published2024
Admission routes1
Has abstractyes

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