Evidence map›Paper›PMID 32938963›Full record

ArticleScientific reports2020

Predicting the influence of particle size on the glass transition temperature and viscosity of secondary organic material.

Markus Petters, Sabin Kasparoglu

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Effect of Aerosol Size on Glass Transition Temperature.The journal of physical chemistry letters · 2024
    Article
  4. Toward a molecular understanding of the surface composition of atmospherically relevant organic particles.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Markus PettersDepartment of Marine, Earth, and Atmospheric Sciences, NC State University, Raleigh, 27695-8208, USA. mdpetter@ncsu.edu.
Sabin KasparogluDepartment of Marine, Earth, and Atmospheric Sciences, NC State University, Raleigh, 27695-8208, USA.

Funding

U.S. Department of Energy DE-SC0018265
6 · The paper itself

Abstract

Atmospheric aerosols can assume liquid, amorphous semi-solid or glassy, and crystalline phase states. Particle phase state plays a critical role in understanding and predicting aerosol impacts on human health, visibility, cloud formation, and climate. Melting point depression increases with decreasing particle diameter and is predicted by the Gibbs-Thompson relationship. This work reviews existing data on the melting point depression to constrain a simple parameterization of the process. The parameter [Formula: see text] describes the degree to which particle size lowers the melting point and is found to vary between 300 and 1800 K nm for a wide range of particle compositions. The parameterization is used together with existing frameworks for modeling the temperature and RH dependence of viscosity to predict the influence of particle size on the glass transition temperature and viscosity of secondary organic aerosol formed from the oxidation of [Formula: see text]-pinene. Literature data are broadly consistent with the predictions. The model predicts a sharp decrease in viscosity for particles less than 100 nm in diameter. It is computationally efficient and suitable for inclusion in models to evaluate the potential influence of the phase change on atmospheric processes. New experimental data of the size-dependence of particle viscosity for atmospheric aerosol mimics are needed to thoroughly validate the predictions.

Identifiers

PMID32938963
PMCPMC7495436

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.