↓ Skip to main content

Interpreting atomic force microscopy nanoindentation of hierarchical biological materials using multi-regime analysis

Overview of attention for article published in Soft Matter, January 2015
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 X users

Citations

dimensions_citation
38 Dimensions

Readers on

mendeley
81 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.
Title
Interpreting atomic force microscopy nanoindentation of hierarchical biological materials using multi-regime analysis
Published in
Soft Matter, January 2015
DOI 10.1039/c4sm02440k
Pubmed ID
Authors

M. R. Bonilla, J. R. Stokes, M. J. Gidley, G. E. Yakubov

Abstract

We present a novel Multi-Regime Analysis (MRA) routine for interpreting force indentation measurements of soft materials using atomic force microscopy. The MRA approach combines both well established and semi-empirical theories of contact mechanics within a single framework to deconvolute highly complex and non-linear force-indentation curves. The fundamental assumption in the present form of the model is that each structural contribution to the mechanical response acts in series with other 'mechanical resistors'. This simplification enables interpretation of the micromechanical properties of materials with hierarchical structures and it allows automated processing of large data sets, which is particularly indispensable for biological systems. We validate the algorithm by demonstrating for the first time that the elastic modulus of polydimethylsiloxane (PDMS) films is accurately predicted from both approach and retraction branches of force-indentation curves. For biological systems with complex hierarchical structures, we show the unique capability of MRA to map the micromechanics of live plant cells, revealing an intricate sequence of mechanical deformations resolved with precision that is unattainable using conventional methods of analysis. We recommend the routine use of MRA to interpret AFM force-indentation measurements for other complex soft materials including mammalian cells, bacteria and nanomaterials.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Ireland 2 2%
France 1 1%
Netherlands 1 1%
Italy 1 1%
United States 1 1%
Unknown 75 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 36%
Researcher 15 19%
Professor 7 9%
Professor > Associate Professor 7 9%
Student > Master 7 9%
Other 12 15%
Unknown 4 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 19%
Materials Science 14 17%
Engineering 13 16%
Physics and Astronomy 13 16%
Chemical Engineering 6 7%
Other 6 7%
Unknown 14 17%
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 28 December 2014.
All research outputs
#17,735,364
of 22,775,504 outputs
Outputs from Soft Matter
#4,611
of 8,099 outputs
Outputs of similar age
#241,700
of 352,928 outputs
Outputs of similar age from Soft Matter
#221
of 424 outputs
Altmetric has tracked 22,775,504 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,099 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 37th percentile – i.e., 37% 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 352,928 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 424 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.