Evidence map›Paper›PMID 36050051›Full record

ArticleThe Review of scientific instruments2022

Acceleration of imaging in atomic force microscopy working in sub-resonance tapping mode.

Piers Echols-Jones, William Messner, Igor Sokolov

Abstract read
In one paragraph

Article in The Review of scientific instruments, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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.

Piers Echols-JonesTufts University, Medford, Massachusetts 02155, USA.
William MessnerConsultant in Amesbury, Amesbury, Massachusetts 01913, USA.
Igor SokolovTufts University, Medford, Massachusetts 02155, USA.ORCID 0000-0001-6260-4326

Funding

Noninvasive bladder cancer diagnostics via machine learning analysis of nanoscale surface images of epithelial cells extracted from voided urine samplesR01CA262147 · NCI · TUFTS UNIVERSITY MEDFORD · PI DEMIDENKO, EUGENE, SOKOLOV, IGOR · 2021 to 2025
$3.1M
Ultra-bright fluorescent nanoparticles for colorectal adenoma detectionR21DK125911 · NIDDK · DUKE UNIVERSITY · PI ROPER, JATIN, SOKOLOV, IGOR · 2021 to 2022
$461k
NCI NIH HHS R01 CA262147NIDDK NIH HHS R21 DK125911
6 · The paper itself

Abstract

Sub-resonance tapping (SRT) mode of atomic force microscopy (AFM) enables researchers to image surfaces with well-controlled load forces and to collect maps of multiple physical properties of samples. The major bottleneck of this mode is a relatively low scan speed compared to other scanning modes. This paper presents a novel control algorithm that substantially improves the scanning speed over the standard SRT. We propose naming the new modality Trajectory Tracking SRT (TT-SRT). In contrast with the standard SRT control, TT-SRT uses the feedback within every single touch of the sample by the AFM probe. To demonstrate the advantage of TT-SRT, we conduct scans on a variety of samples with differing topologies, roughnesses, and mechanical properties. Each sample region is scanned with both standard SRT and TT-SRT at the same set of speeds. The control gains are tuned before each scan for maximum performance in each mode. Performance is evaluated by selecting a given level of image quality and finding the maximum speed that can be achieved by each algorithm. We find that with increased demand for data quality, the utility of TT-SRT becomes more apparent; for example, the speed of TT-SRT can be ten times faster or more than standard SRT for a reasonable expectation of data quality.

Indexed as

AlgorithmsVibrationAccelerationFeedbackMicroscopy, Atomic Force

Identifiers

PMID36050051
PMCPMC9410730

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.