Evidence map›Paper›PMID 37112051›Full record

ReviewPolymers2023

Recent Trends in Continuum Modeling of Liquid Crystal Networks: A Mini-Review.

Sanghyeon Park, Youngtaek Oh, Jeseung Moon, Hayoung Chung

Abstract readReview
In one paragraph

Review in Polymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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

4 authors.

Sanghyeon ParkDepartment of Mechanical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea.ORCID 0009-0003-9746-7095
Youngtaek OhDepartment of Mechanical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea.
Jeseung MoonDepartment of Mechanical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea.ORCID 0009-0003-5119-5418
Hayoung ChungDepartment of Mechanical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea.

Funding

National Research Foundation of Korea NRF-2020R1C1C1005741National Research Foundation of Korea NRF-2021R1A4A1033224
6 · The paper itself

Abstract

This work aims to provide a comprehensive review of the continuum models of the phase behaviors of liquid crystal networks (LCNs), novel materials with various engineering applications thanks to their unique composition of polymer and liquid crystal. Two distinct behaviors are primarily considered: soft elasticity and spontaneous deformation found in the material. First, we revisit these characteristic phase behaviors, followed by an introduction of various constitutive models with diverse techniques and fidelities in describing the phase behaviors. We also present finite element models that predict these behaviors, emphasizing the importance of such models in predicting the material's behavior. By disseminating various models essential to understanding the underlying physics of the behavior, we hope to help researchers and engineers harness the material's full potential. Finally, we discuss future research directions necessary to advance our understanding of LCNs further and enable more sophisticated and precise control of their properties. Overall, this review provides a comprehensive understanding of the state-of-the-art techniques and models used to analyze the behavior of LCNs and their potential for various engineering applications.

Indexed as

liquid crystal networkphase behaviorphase transitionsoft elasticityspontaneous behavior

Identifiers

PMID37112051
PMCPMC10142630

What OpenQuestion holds

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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.