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Ice Nucleation of Model Nanoplastics and Microplastics: A Novel Synthetic Protocol and the Influence of Particle Capping at Diverse Atmospheric Environments

2019· article· en· W2967529931 on OpenAlex
Mainak Ganguly, Parisa A. Ariya

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

VenueACS Earth and Space Chemistry · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesEnvironment CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsMicroplasticsNucleationIce nucleusChemical engineeringParticle (ecology)PhenanthreneNanoparticleParticle sizeChemistryMaterials scienceEnvironmental chemistryNanotechnologyOrganic chemistry

Abstract

fetched live from OpenAlex

Little is known about airborne atmospheric aerosols containing emerging contaminants such as nano- and microplastics. A novel, minimum energy usage, synthetic protocol of plastic micro/nanoparticles was herein developed. Stable plastic hydrosols were synthesized and characterized using three different types of plastics. The ice nucleation efficiency (INE) was investigated in both normal and synthetic seawater to mimic environmental ice nucleation. Among the three tested plastic precursors (low-density polyethylene, high-density polyethylene, and polypropylene), polypropylene produced the highest particle density with narrow particle size distribution. The change of size, shape, surface charge, and electronic behavior of the plastic nano- and microparticles accounted for the altered INE. The effects of environmental factors such as particle acidity and temperature on ice nucleation were also examined. An increase in pH increased INE due to an increased particle density (number of particles per unit volume), whereas increased temperature decreased INE significantly due to aggregation (attaching particles to produce a larger particle). Four types of capping were used on the surfaces of nano- and microplastics to investigate how the plastics act to nucleate ice when mixed with different particles. They include (a) ZnO as an emerging metal contaminant, (b) kaolin as a clay mineral, (c) HgCl2 as a toxic ionic water pollutant, and (d) phenanthrene as a polycyclic aromatic hydrocarbon. Capping by ZnO and HgCl2 decreased the INE of plastic nano- and microparticles, whereas kaolin and phenanthrene enhanced INE significantly. The association of contaminants to micro- and nanoplastics changes INE likely due to water affinity, surface buckling, and lattice mismatch energy of ice, affecting ice nuclei formation processes. The observed differential physicochemical behaviors of nano- and microplastics, with and without co-contaminant cappings, provide further insights to understand natural environmental ice nucleation and precipitation events. Our work shows that future emissions of nano- and microplastics may become important for cloud formation and thus anthropogenic climate change.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.493
Threshold uncertainty score0.350

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 head0.004
GPT teacher head0.175
Teacher spread0.170 · 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