Evidence map›Paper›PMID 35116155›Full record

ArticleRoyal Society open science2022

A double-population chaotic self-adaptive evolutionary dynamics model for the prediction of supercritical carbon dioxide solubility in polymers.

Yan Wu, Hang Zhang, Meng-Shan Li, Sheng Sheng, Jun Wang, Fu-An Wu

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Article in Royal Society open science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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.

Yan WuSchool of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212018, People's Republic of China.ORCID 0000-0002-0488-6967
Hang ZhangCollege of Physics and Electronic Information, Gannan Normal University, Ganzhou Jiangxi 341000, People's Republic of China.
Meng-Shan LiCollege of Physics and Electronic Information, Gannan Normal University, Ganzhou Jiangxi 341000, People's Republic of China.ORCID 0000-0001-7832-4185
Sheng ShengSchool of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212018, People's Republic of China.
Jun WangSchool of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212018, People's Republic of China.
Fu-An WuSchool of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212018, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Solubility of gas in polymers is an important physico-chemical property of foam materials and widely used in the preparation and modification of new materials. Under the conditions of high temperature and high pressure, the dissolution process is a nonlinear, non-equilibrium and dynamic process, so it is difficult to establish an accurate solubility calculation model. Inspired by particle dynamics and evolutionary algorithm, this paper proposes a hybrid model based on chaotic self-adaptive particle dynamics evolutionary algorithm (CSA-PD-EA), which can use the iterative process of particles in evolutionary algorithms at the dynamic level to simulate the mutual diffusion process of molecules during dissolution. The predicted solubility of supercritical CO

Indexed as

computational modeldissolution behaviourevolutionary computationparticle dynamics

Identifiers

PMID35116155
PMCPMC8767190

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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.