Evidence map›Paper›PMID 35495224›Full record

ArticleRSC advances2020

Atomistic structure generation of covalent triazine-based polymers by molecular simulation.

Ce Song, Fangyuan Hu, Zhaoliang Meng, Shengming Li, Wenlong Shao, Tianpeng Zhang, Siyang Liu, Xigao Jian

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in RSC advances, 2020. 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

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

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

8 authors.

Ce SongSchool of Mathematical Sciences, Dalian University of Technology Dalian 116024 China jian4616@dlut.edu.cn.
Fangyuan HuSchool of Materials Science and Engineering, State Key Laboratory of Fine Chemicals, Dalian University of Technology Dalian 116024 China hufangyuan@dlut.edu.cn.ORCID https://orcid.org/0000-0002-1611-7372
Zhaoliang MengSchool of Mathematical Sciences, Dalian University of Technology Dalian 116024 China jian4616@dlut.edu.cn.
Shengming LiSchool of Innovation and Entrepreneurship, Dalian University of Technology Dalian 116024 China.
Wenlong ShaoState Key Laboratory of Fine Chemicals, Liaoning Province Engineering Research Centre of High Performance Resins, Dalian University of Technology Dalian 116024 China.
Tianpeng ZhangSchool of Materials Science and Engineering, State Key Laboratory of Fine Chemicals, Dalian University of Technology Dalian 116024 China hufangyuan@dlut.edu.cn.
Siyang LiuSchool of Materials Science and Engineering, State Key Laboratory of Fine Chemicals, Dalian University of Technology Dalian 116024 China hufangyuan@dlut.edu.cn.
Xigao JianSchool of Mathematical Sciences, Dalian University of Technology Dalian 116024 China jian4616@dlut.edu.cn.ORCID https://orcid.org/0000-0002-2061-2907

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The structures of amorphous materials are generally difficult to characterize and comprehend due to their unordered nature and indirect measurement techniques. However, molecular simulation has been considered as an alternative method that can provide molecular-level information supplementary to experimental techniques. In this work, a new approach for modelling the atomistic structures of amorphous covalent triazine-based polymers is proposed and employed on two experimentally synthesized covalent triazine-based polymers. To examine the proposed modelling approach, the properties of the established models, such as surface areas, pore volumes, structure factors and N

Identifiers

PMID35495224
PMCPMC9049061

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.