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Record W4414922246 · doi:10.1007/s00340-026-08633-0

In situ measurement of the specific surface area of reduced graphene oxide using time-resolved laser induced incandescence

2025· article· en· W4414922246 on OpenAlexafffund
Horace I. Looi, Sarah Jahnkani, Michael A. Pope, Kyle J. Daun

Bibliographic record

VenueApplied Physics B · 2025
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Waterloo
KeywordsGrapheneOxideIncandescenceGraphene oxide paperGraphiteIn situAdsorptionQuenching (fluorescence)

Abstract

fetched live from OpenAlex

<title>Abstract</title> Reduced graphene oxide (rGO) produced by the rapid thermal expansion of graphite oxide is a promising alternative to graphene for applications requiring large volumes and some chemical functionality on the graphene, since this approach offers potentially high yields and throughput. However, the surface area and single layer dispersibility of the resulting rGO powder depends heavily on precursor moisture content, chemistry and morphology, as well as and process parameters that include residence time and quenching rates. While large-scale commercial deployments have been demonstrated, there are currently no real-time diagnostics capable of assessing inline material quality. In this study, we propose time-resolved laser-induced incandescence (TiRe-LII) as a means to derive the real-time relative specific surface area (SSA) of rGO particles which is expected to be a strong indicator of single sheet dispersibility. The TiRe-LII derived SSA were found to be consistent in both magnitude and trend to those found through batch gas adsorption measurements analyzed by fitting the Brunauer-Emmett-Teller (BET) isotherm.

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)0.000
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 score0.005
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.046
GPT teacher head0.273
Teacher spread0.227 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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