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Record W4306412159 · doi:10.1002/cptc.202200166

On the Molecular Origin of the Red Emission in the Newly Synthesized Carbon‐Based Quantum Dots

2022· article· en· W4306412159 on OpenAlexafffund
Connor R. Bourgonje, Belinda Heyne, Max Anikovskiy

Bibliographic record

VenueChemPhotoChem · 2022
Typearticle
Languageen
FieldMaterials Science
TopicCarbon and Quantum Dots Applications
Canadian institutionsWilfrid Laurier UniversityUniversity of CalgaryUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Calgary
KeywordsFluorescenceQuantum dotNanomaterialsCarbon fibersSpectroscopyLuminescenceFormamideMaterials scienceAbsorption (acoustics)Fluorescence spectroscopyPhotochemistryNanoparticleAbsorption spectroscopyEmission spectrumNanotechnologyChemistryOptoelectronicsOrganic chemistrySpectral linePhysics

Abstract

fetched live from OpenAlex

Abstract Carbon‐based quantum dots (QDs) represent a new family of luminescent nanomaterials with intriguing emission properties. They are synthesized predominately with the emission in the blue and green region of the visible spectrum, with limited success in producing red emission. Furthermore, the current literature on the subject lacks consensus with respect to the morphology of QDs. Contrary to their semiconductor counterparts, the data on the structure of fluorescing centers is scarce. Herein, we describe a facile one‐pot synthesis of red emissive QDs using citric acid and formamide as precursors without addition of any other source of nitrogen. The photophysical properties of the synthesized species were investigated by steady state and transient absorption and fluorescence spectroscopy. Some structural peculiarities were revealed using fluorescence correlation spectroscopy. Our findings show that the newly synthesized carbon‐based QDs, at least their emissive centers, are not part of nanoparticles but rather resemble small organic fluorophores. Furthermore, we have not eliminated the possibility that multiple fluorophores with different emission properties may be embedded within a single molecular entity.

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)0.000
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 score0.008
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.020
GPT teacher head0.254
Teacher spread0.234 · 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

Citations1
Published2022
Admission routes2
Has abstractyes

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