Evidence map›Paper›PMID 26997415›Full record

ArticleScientific reports2016

Potential of mean force between like-charged nanoparticles: Many-body effect.

Xi Zhang, Jin-Si Zhang, Ya-Zhou Shi, Xiao-Long Zhu, Zhi-Jie Tan

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Competitive Binding of MgBiophysical journal · 2018
    Article
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  7. 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

5 authors.

Xi ZhangCenter for Theoretical Physics and Key Laboratory of Artificial Micro &Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China.
Jin-Si ZhangCenter for Theoretical Physics and Key Laboratory of Artificial Micro &Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China.
Ya-Zhou ShiCenter for Theoretical Physics and Key Laboratory of Artificial Micro &Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China.
Xiao-Long ZhuDepartment of Physics, School of Physics &Information Engineering, Jianghan University, Wuhan 430056, China.
Zhi-Jie TanCenter for Theoretical Physics and Key Laboratory of Artificial Micro &Nano-structures of Ministry of Education, School of Physics and Technology, Wuhan University, Wuhan 430072, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ion-mediated interaction is important for the properties of polyelectrolytes such as colloids and nucleic acids. The effective pair interactions between two polyelectrolytes have been investigated extensively, but the many-body effect for multiple polyelectrolytes still remains elusive. In this work, the many-body effect in potential of mean force (PMF) between like-charged nanoparticles in various salt solutions has been comprehensively examined by Monte Carlo simulation and the nonlinear Poisson-Boltzmann theory. Our calculations show that, at high 1:1 salt, the PMF is weakly repulsive and appears additive, while at low 1:1 salt, the additive assumption overestimates the repulsive many-body PMF. At low 2:2 salt, the pair PMF appears weakly repulsive while the many-body PMF can become attractive. In contrast, at high 2:2 salt, the pair PMF is apparently attractive while the many-body effect can cause a weaker attractive PMF than that from the additive assumption. Our microscopic analyses suggest that the elusive many-body effect is attributed to ion-binding which is sensitive to ion concentration, ion valence, number of nanoparticles and charges on nanoparticles.

Identifiers

PMID26997415
PMCPMC4800448

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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.