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Record W2049676315 · doi:10.1021/es505298d

Chemical and Toxicological Evolution of Carbon Nanotubes During Atmospherically Relevant Aging Processes

2015· article· en· W2049676315 on OpenAlexafffund
Yongchun Liu, John Liggio, Shao‐Meng Li, Dalibor Breznan, Renaud Vincent, Errol M. Thomson, Premkumari Kumarathasan, Dharani Das, Jonathan P. D. Abbatt, María Antiñolo, Lynn M. Russell

Bibliographic record

VenueEnvironmental Science & Technology · 2015
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsHealth CanadaUniversity of TorontoEnvironment and Climate Change Canada
FundersChinese Academy of SciencesGovernment of Canada
KeywordsCarbon nanotubeOzoneSurface modificationEnvironmental chemistryAdsorptionChemistryCarbon fibersRedoxParticulatesAtmosphere (unit)Chemical engineeringOrganic chemistryMaterials scienceNanotechnology

Abstract

fetched live from OpenAlex

The toxicity of carbon nanotubes (CNTs) has received significant attention due to their usage in a wide range of commercial applications. While numerous studies exist on their impacts in water and soil ecosystems, there is a lack of information on the exposure to CNTs from the atmosphere. The transformation of CNTs in the atmosphere, resulting in their functionalization, may significantly alter their toxicity. In the current study, the chemical modification of single wall carbon nanotubes (SWCNTs) via ozone and OH radical oxidation is investigated through studies that simulate a range of expected tropospheric particulate matter (PM) lifetimes, in order to link their chemical evolution to toxicological changes. The results indicate that the oxidation favors carboxylic acid functionalization, but significantly less than other studies performed under nonatmospheric conditions. Despite evidence of functionalization, neither O3 nor OH radical oxidation resulted in a change in redox activity (potentially giving rise to oxidative stress) or in cytotoxic end points. Conversely, both the redox activity and cytotoxicity of SWCNTs significantly decreased when exposed to ambient urban air, likely due to the adsorption of organic carbon vapors. These results suggest that the effect of gas-particle partitioning of organics in the atmosphere on the toxicity of SWCNTs should be investigated further.

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 score0.008
Threshold uncertainty score0.798

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 studies0.0000.002
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 head0.008
GPT teacher head0.212
Teacher spread0.204 · 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

Citations44
Published2015
Admission routes2
Has abstractyes

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