Evidence map›Paper›PMID 38496050›Full record

ArticleACS materials Au2024

Quantitative Structure-Permittivity Relationship Study of a Series of Polymers.

Yevhenii Zhuravskyi, Kweeni Iduoku, Meade E Erickson, Anas Karuth, Durbek Usmanov, Gerardo Casanola-Martin, Maqsud N Sayfiyev, Dilshod A Ziyaev, Zulayho Smanova, Alicja Mikolajczyk and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in ACS materials Au, 2024. 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
–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

2 citing papers in PubMed.

  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

11 authors.

Yevhenii ZhuravskyiDepartment of Technology of Organic Products, Lviv Polytechnic National University, Lviv 79013, Ukraine.
Kweeni IduokuDepartment of Coatings and Polymeric Materials, North Dakota State University, Fargo, North Dakota 58102, United States.
Meade E EricksonDepartment of Coatings and Polymeric Materials, North Dakota State University, Fargo, North Dakota 58102, United States.
Anas KaruthDepartment of Coatings and Polymeric Materials, North Dakota State University, Fargo, North Dakota 58102, United States.
Durbek UsmanovDepartment of Coatings and Polymeric Materials, North Dakota State University, Fargo, North Dakota 58102, United States.ORCID https://orcid.org/0000-0002-7349-377X
Gerardo Casanola-MartinDepartment of Coatings and Polymeric Materials, North Dakota State University, Fargo, North Dakota 58102, United States.ORCID https://orcid.org/0000-0003-0383-2032
Maqsud N SayfiyevDepartment of Chemistry, National University of Uzbekistan, Tashkent 100174, Uzbekistan.
Dilshod A ZiyaevDepartment of Chemistry, National University of Uzbekistan, Tashkent 100174, Uzbekistan.
Zulayho SmanovaDepartment of Chemistry, National University of Uzbekistan, Tashkent 100174, Uzbekistan.
Alicja MikolajczykLaboratory of Environmental Chemometrics, Institute for Environmental and Human Health Protection, Faculty of Chemistry, University of Gdansk, Gdansk 80-308, Poland.ORCID https://orcid.org/0000-0002-0019-8323
Bakhtiyor RasulevDepartment of Coatings and Polymeric Materials, North Dakota State University, Fargo, North Dakota 58102, United States.ORCID https://orcid.org/0000-0002-7845-4884

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dielectric constant is an important property which is widely utilized in many scientific fields and characterizes the degree of polarization of substances under the external electric field. In this work, a structure-property relationship of the dielectric constants (ε) for a diverse set of polymers was investigated. A transparent mechanistic model was developed with the application of a machine learning approach that combines genetic algorithm and multiple linear regression analysis, to obtain a mechanistically explainable and transparent model. Based on the evaluation conducted using various validation criteria, four- and eight-variable models were proposed. The best model showed a high predictive performance for training and test sets, with

Identifiers

PMID38496050
PMCPMC10941280

What OpenQuestion holds

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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.