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Record W2606211085 · doi:10.1002/anie.201700949

Enhancing Light Absorption and Charge Transfer Efficiency in Carbon Dots through Graphitization and Core Nitrogen Doping

2017· article· en· W2606211085 on OpenAlexfundno aff
Benjamin Martindale, Georgina A. M. Hutton, Christine A. Caputo, Sebastian Prantl, Robert Godin, James R. Durrant, Erwin Reisner

Bibliographic record

VenueAngewandte Chemie International Edition · 2017
Typearticle
Languageen
FieldMaterials Science
TopicCarbon and Quantum Dots Applications
Canadian institutionsnot available
FundersH2020 European Research CouncilChristian Doppler ForschungsgesellschaftFonds de recherche du Québec – Nature et technologiesEuropean CommissionÖsterreichische Nationalstiftung für Forschung, Technologie und Entwicklung
KeywordsDopingAbsorption (acoustics)Carbon fibersMaterials sciencePhotocatalysisPhotochemistryNitrogenAmorphous carbonAbsorption spectroscopyUltrafast laser spectroscopyAnalytical Chemistry (journal)Amorphous solidSpectroscopyChemistryOptoelectronicsOpticsCrystallographyOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

Abstract Single‐source precursor syntheses have been devised for the preparation of structurally similar graphitic carbon dots (CDs), with (g‐N‐CD) and without (g‐CD) core nitrogen doping for artificial photosynthesis. An order of magnitude improvement has been realized in the rate of solar (AM1.5G) H2 evolution using g‐N‐CD (7950 μmolH2 (gCD)−1 h−1) compared to undoped CDs. All graphitized CDs show significantly enhanced light absorption compared to amorphous CDs (a‐CD) yet undoped g‐CD display limited photosensitizer ability due to low extraction of photogenerated charges. Transient absorption spectroscopy showed that nitrogen doping in g‐N‐CD increases the efficiency of hole scavenging by the electron donor and thereby significantly extends the lifetime of the photogenerated electrons. Thus, nitrogen doping allows the high absorption coefficient of graphitic CDs to be translated into high charge extraction for efficient photocatalysis.

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 score0.003

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 head0.021
GPT teacher head0.274
Teacher spread0.254 · 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

Citations272
Published2017
Admission routes1
Has abstractyes

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