Evidence map›Paper›PMID 35208438›Full record

ArticleMicromachines2022

Prediction of Surface Roughness as a Function of Temperature for SiO

Muhammad Rizwan Amirzada, Yousuf Khan, Muhammad Khurram Ehsan, Atiq Ur Rehman, Abdul Aleem Jamali, Abdul Rafay Khatri

Open access · goldAbstract read
In one paragraph

Article in Micromachines, 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
1.5field-weighted citation impact, top 23% 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, 11 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

6 authors at 4 institutions in 1 country.

Muhammad Rizwan AmirzadaFaculty of Engineering and Computer Sciences, National University of Modern Languages, Islamabad 44000, Pakistan.ORCID 0000-0002-6760-8278
Yousuf KhanDepartment of Electronic Engineering, Balochistan University of Information Technology, Engineering and Management Sciences, Quetta 87300, Pakistan.ORCID 0000-0002-0415-6948
Muhammad Khurram EhsanFaculty of Engineering Sciences, Bahria University, Lahore Campus, 47-C, Civic Center, Johar Town, Lahore 54000, Pakistan.ORCID 0000-0002-1977-2022
Atiq Ur RehmanDepartment of Electronic Engineering, Balochistan University of Information Technology, Engineering and Management Sciences, Quetta 87300, Pakistan.ORCID 0000-0002-9510-6531
Abdul Aleem JamaliDepartment of Electronic Engineering, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah 67480, Pakistan.
Abdul Rafay KhatriDepartment of Electronic Engineering, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah 67480, Pakistan.
Balochistan University of Information Technology, Engineering and Management Sciences · PKQuaid-e-Awam University of Engineering, Science and Technology · PKBahria University · PKNational University of Modern Languages · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An analytical model to predict the surface roughness for the plasma-enhanced chemical vapor deposition (PECVD) process over a large range of temperature values is still nonexistent. By using an existing prediction model, the surface roughness can directly be calculated instead of repeating the experimental processes, which can largely save time and resources. This research work focuses on the investigation and analytical modeling of surface roughness of SiO

Indexed as

analytical predictionMEMSmicro-mirrorsPECVD processSiO2 thin-filmssurface roughness

Identifiers

PMID35208438
PMCPMC8877521
OpenAlexW4213273302

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.