Evidence map›Paper›PMID 39896093›Full record

ArticleSurface topography : metrology and properties2024

Evaluating scanning electron microscopy for the measurement of small-scale topography.

Vimanyu Chadha, Nathaniel C Miller, Ruikang Ding, Kurt E Beschorner, Tevis D B Jacobs

Abstract read
In one paragraph

Article in Surface topography : metrology and properties, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
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.

Vimanyu ChadhaDepartment of Mechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, PA 15261.
Nathaniel C MillerDepartment of Mechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, PA 15261.
Ruikang DingDepartment of Mechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, PA 15261.
Kurt E BeschornerDepartment of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15261.
Tevis D B JacobsDepartment of Mechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, PA 15261.

Funding

NIOSH CDC HHS R21 OH012126
6 · The paper itself

Abstract

For predicting surface performance, multiscale topography analysis consistently outperforms standard roughness metrics; however, surface-characterization tools limit the range of sizes that can be measured. Therefore, we evaluate the use of scanning electron microscopy (SEM) to systematically measure small-scale topography. While others have employed SEM for similar purposes, the novelty of this investigation lies in the development and validation of a simple, flexible procedure that can be applied to a wide range of materials and geometries. First, we established four different options that can be used for sample preparation, and we measured quantitative topography of each using the SEM. Then the power spectral density (PSD) was used to compare topography among the four preparations, and against other techniques. A statistical comparison of PSDs demonstrated that SEM topography measurements outperformed AFM measurements at scales below 100 nm and were statistically indistinguishable from (highly labor-intensive) TEM measurements down to 16 nm. The limitations of SEM-based topography were quantified and discussed. Overall, the results show a simple generalizable method for revealing small-scale topography. When combined with traditional stylus profilometry, this technique characterizes surface topography across almost seven orders of magnitude, from 1 cm down to 16 nm, facilitating the use of physical models to predict performance.

Identifiers

PMID39896093
PMCPMC11783955

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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.