Evidence map›Paper›PMID 36246548›Full record

ArticleLimnology and oceanography, methods2022

A method for tracking the Brownian motion to estimate the size distribution of submicron particles in seawater.

Yuanheng Xiong, Xiaodong Zhang, Lianbo Hu

Open access · greenAbstract read
In one paragraph

Article in Limnology and oceanography, methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
2.0field-weighted citation impact, top 15% of its field
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

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. Nanoparticle Skin Penetration: Depths and Routes Modeled In-Silico.Small (Weinheim an der Bergstrasse, Germany) · 2025
    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

3 authors at 3 institutions in 2 countries.

Yuanheng XiongDepartment of Earth System Science and Policy University of North Dakota Grand Forks North Dakota USA.ORCID https://orcid.org/0000-0001-5263-576X
Xiaodong ZhangDivision of Marine Science School of Ocean Science and Engineering, The University of Southern Mississippi, Stennis Space Center Mississippi USA.
Lianbo HuOcean Remote Sensing Institute Ocean University of China Qingdao China.
Ocean University of China · CNStennis Space Center · USUniversity of North Dakota · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Because the diffusivity of particles undergoing the Brownian motion is inversely proportional to their sizes, the size distribution of submicron particles can be estimated by tracking their movement. This particle tracking analysis (PTA) has been applied in various fields, but mainly focused on resolving monodispersed particle populations and is rarely used for measuring oceanic particles that are naturally polydispersed. We demonstrated using Monte Carlo simulation that, in principle, PTA can be used to size natural, oceanic particles. We conducted a series of lab experiments using microbeads of NIST-traceable sizes to evaluate the performance of ViewSizer 3000, a PTA-based commercial instrument, and found two major uncertainties: (1) the sample volume varies with the size of particles and (2) the signal-to-noise ratio for particles of sizes < 200-250 nm was reduced and hence their concentration was underestimated with the presence of larger particles. After applying the volume correction, we found the instrument can resolve oceanic submicron particles of sizes greater than 250 nm with a mean absolute error of 3.9% in size and 38% in concentration.

Identifiers

PMID36246548
PMCPMC9543390
OpenAlexW4287850282

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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.