Evidence map›Paper›PMID 35365741›Full record

ArticleScientific reports2022

Extending conventional surface roughness ISO parameters using topological data analysis for shot peened surfaces.

Jan F Senge, Asghar Heydari Astaraee, Pawel Dłotko, Sara Bagherifard, Wolfram A Bosbach

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.8field-weighted citation impact, top 18% of its field
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

2 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. 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 at 3 institutions in 2 countries.

Jan F SengeDepartment of Mathematics and Computer Science, University of Bremen, 28334, Bremen, Germany.
Asghar Heydari AstaraeeDepartment of Mechanical Engineering, Politecnico di Milano, 20156, Milan, Italy.
Pawel DłotkoDioscuri Centre for Topological Data Analysis, IMPAN, 00-656, Warszawa, Poland.
Sara BagherifardDepartment of Mechanical Engineering, Politecnico di Milano, 20156, Milan, Italy.
Wolfram A BosbachDiagnostic and Interventional Radiology, University of Heidelberg, 69120, Heidelberg, Germany. wb248@cantab.net.
Politecnico di Milano · ITHeidelberg University · DEUniversity of Bremen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The roughness of material surfaces is of greatest relevance for applications. These include wear, friction, fatigue, cytocompatibility, or corrosion resistance. Today's descriptors of the International Organization for Standardization show varying performance in discriminating surface roughness patterns. We introduce here a set of surface parameters which are extracted from the appropriate persistence diagram with enhanced discrimination power. Using the finite element method implemented in Abaqus Explicit 2019, we modelled American Rolling Mill Company pure iron specimens (volume 1.5 × 1.5 × 1.0 mm

Indexed as

Data AnalysisCorrosionSurface Properties

Identifiers

PMID35365741
PMCPMC8976008
OpenAlexW4220838433

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.