↓ Skip to main content

Mutable polyelectrolyte tube arrays: mesoscale modeling and lateral force microscopy

Overview of attention for article published in Soft Matter, January 2017
Altmetric Badge

Mentioned by

twitter
1 X user

Readers on

mendeley
13 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Article details
Title
Mutable polyelectrolyte tube arrays: mesoscale modeling and lateral force microscopy
Published in
Soft Matter, January 2017
DOI 10.1039/c7sm00864c
Pubmed ID
Authors
Abstract

In this study, the pH-dependent friction of layer-by-layer assemblies of poly(allylamine hydrochloride) and poly(acrylic acid) (PAH/PAA) are quantified for microtube array structures via experimental and simulated lateral force microscopy (LFM). A novel coarse-grain tube model is developed, utilizing a molecular dynamics (MD) framework with a Hertzian soft contact potential (such that F ∼ δ(3/2)) to allow the efficient dynamic simulation of 3D arrays consisting of hundreds of tubes at micrometer length scales. By quantitatively comparing experimental LFM and computational results, the coupling between geometry (tube spacing and swelling) and material properties (intrinsic stiffness) results in a transition from bending dominated deformation to bending combined with inter-tube contact, independent of material adhesion assumptions. Variation of tube spacing (and thus control of contact) can be used to exploit the normal and lateral resistance of the tube arrays as a function of pH (2.0/5.5), beyond the effect of areal tube density, with increased resistances (potential mutability) up to a factor of ∼60. This study provides a novel modeling platform to assess and design dynamic polyelectrolyte-based substrates/coatings with tailorable stimulus-responsive surface friction. Our results show that micro-geometry can be used alongside stimulus-responsive material changes to amplify and systematically tune mutability.

Login to access the Attention Digest and the Sentiment Analysis related to this output.

Timeline Attention over time Attention Score history
Login to access the full charts related to this output.
Activity
Login to access the full charts related to this output.
X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Login to view Mendeley reader trends over time.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 3 23%
Professor 2 15%
Researcher 2 15%
Librarian 1 8%
Student > Doctoral Student 1 8%
Other 0 0%
Unknown 4 31%
Readers by discipline
Readers by discipline Count As %
Materials Science 4 31%
Engineering 3 23%
Chemical Engineering 1 8%
Biochemistry, Genetics and Molecular Biology 1 8%
Physics and Astronomy 1 8%
Other 0 0%
Unknown 3 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 July 2017.
All research outputs
#27,205,565
of 32,950,213 outputs
Outputs from Soft Matter
#6,379
of 8,630 outputs
Outputs of similar age
#351,742
of 448,262 outputs
Outputs of similar age from Soft Matter
#379
of 603 outputs
Altmetric has tracked 32,950,213 research outputs across all sources so far. This one is in the 9th percentile – i.e., 9% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,630 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 15th percentile – i.e., 15% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 448,262 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 603 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.