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Record W3042365350 · doi:10.1002/ppsc.202000119

Toward Uniform Optical Properties of Carbon Dots

2020· article· en· W3042365350 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueParticle & Particle Systems Characterization · 2020
Typearticle
Languageen
FieldMaterials Science
TopicCarbon and Quantum Dots Applications
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaConcordia University
KeywordsQuantum dotNanotechnologyCarbon quantum dotsNanomaterialsFluorescenceMaterials scienceCarbon fibersUltrafiltration (renal)AbsorbanceChemical engineeringChemistryChromatography

Abstract

fetched live from OpenAlex

Abstract Carbon dots possess versatile optical properties that have prompted their investigation in applications including photocatalysis, photovoltaics, imaging, and drug delivery, among others. However, the preparation of these nanodots is accompanied by the formation of fluorophores and intermediates, which can be difficult to separate. In the absence of thorough purification protocols, the reported optical properties are often heterogeneous, which hinders understanding of their physicochemical and optical properties and concrete application development. Here, two hydrophilic carbon dot systems starting with citric acid and diethylenetriamine are prepared. The impact of purification, including dialysis, ultrafiltration, and organic washes, on the properties of the dots is demonstrated. It is shown that monitoring the purification endpoint using near‐infrared, fluorescence, and absorbance spectroscopies is possible. Moreover, it is demonstrated that fluorescence quantum yields can be a reliable tool to determine the purification endpoint. This work shows that even carbon dots derived from the same chemical precursors can have different purification profiles and purification requirements. However, the developed approach can be used to determine the proper purification procedure and endpoint for any carbon dot system regardless of the starting materials. Finally, it is envisioned that this work can be easily extended toward the purification of other hydrophilic nanomaterials.

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.

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)0.000
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 score0.114
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

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 head0.059
GPT teacher head0.241
Teacher spread0.183 · 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