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Record W4402501812 · doi:10.11159/icepr24.131

Promotional Effects And Risks Of Multi-Walled Carbon Nanotubes On Phytoremediation Of Plastic Films

2024· article· en· W4402501812 on OpenAlexvenueno aff
Haoran Liu, Lena Ciric, Manni Bhatti

Bibliographic record

VenueProceedings of the World Congress on New Technologies · 2024
Typearticle
Languageen
FieldEngineering
TopicNanotechnology research and applications
Canadian institutionsnot available
Fundersnot available
KeywordsCarbon nanotubePhytoremediationMaterials scienceCarbon fibersNanotechnologyEnvironmental scienceComposite materialSoil science

Abstract

fetched live from OpenAlex

Alfalfa is a representative plant for remediating pollutants in soil, but its rate of plastic degradation rate remains low.Porous materials are often utilized as additives to improve pollutant degradation rates, yet the use of emerging nanomaterials (NMs) has not been tested.This study aims to combine alfalfa and carbon nanomaterials (CNMs) to research the degradation effect on double-layer polyethylene (PE) plastic films (PF) in soil.Meta-analysis was used to select multi-walled carbon nanotubes (MWCNTs) with low phytotoxicity from various NMs.In a 90-day dynamic experiment, the combination of 100 and 200 mg/kg MWCNTs and alfalfa significantly improved the PF degradation rate in both surface and bottom soil layers.In particular, the PF degradation rate of the surface layer, with the direct participation of alfalfa roots, reached a degradation of 11.081.34%.This suggests that a degradation system incorporating alfalfa and MWCNTs holds promising potential for plastic phytoremediation.

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)0.001
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 score0.061
Threshold uncertainty score0.391

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.022
GPT teacher head0.273
Teacher spread0.251 · 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
Published2024
Admission routes1
Has abstractyes

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