Evidence map›Paper›PMID 35605974›Full record

ArticleThe journal of physical chemistry. B2022

Full-Atomistic Optimized Potentials for Liquid Simulations and Polymer Consistent Force Field Models for Biocompatible Shape-Memory Poly(ε-caprolactone).

Irena Yungerman, Ilya Starodumov, Ailifeire Fulati, Koichiro Uto, Mitsuhiro Ebara, Yevgeny Moskovitz

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Article in The journal of physical chemistry. B, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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.

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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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.

Irena YungermanDepartment of Chemical Engineering, Technion-Israel Institute of Technology, Haifa 32000, Israel.
Ilya StarodumovDepartment of Theoretical and Mathematical Physics, Laboratory of Multi-Scale Mathematical Modeling, Ural Federal University, Ekaterinburg 620000, Russian Federation.
Ailifeire FulatiResearch Center for Functional Materials, National Institute for Materials Science (NIMS), 1-1Namiki, Tsukuba, Ibaraki 305-0044, Japan.
Koichiro UtoResearch Center for Functional Materials, National Institute for Materials Science (NIMS), 1-1Namiki, Tsukuba, Ibaraki 305-0044, Japan.
Mitsuhiro EbaraResearch Center for Functional Materials, National Institute for Materials Science (NIMS), 1-1Namiki, Tsukuba, Ibaraki 305-0044, Japan.ORCID 0000-0002-7906-0350
Yevgeny MoskovitzDepartment of Chemical Engineering, Technion-Israel Institute of Technology, Haifa 32000, Israel.ORCID 0000-0001-9133-1961

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thermally induced shape memory poly(ε-caprolactone) (PCL)-based polymers are one of the most extensively researched families of biocompatible materials. They are degradable under physiological conditions and have high applicability in general biomedical engineering, with cross-linked PCL networks being particularly useful for tissue engineering. In this study, we used the optimized potentials for liquid simulations (OPLS) force field, which is well suited for describing intermolecular interactions in biomolecules, and the class II polymer consistent force field (PCFF) to investigate the properties of telechelic PCL with diacrylates as reactive functionalities on its end groups. PCFF has been specifically parameterized for simulating synthetic polymeric materials. We compare the findings of all-atom molecular dynamics simulations with known experimental data and theoretical assumptions to verify the applicability of both these force fields. We estimated the melt density, volume, transition temperatures, and mechanical characteristics of two-branched PCL diacrylates with a molecular weight of 2481 Da. Our findings point to the utility of the aforementioned force fields in predicting the properties of PCL-based polymers. It also opens avenues for developing PCL cross-linked polymer models and employing OPLS to investigate the interactions of synthetic polymers with biomolecules.

Indexed as

PolyestersPolymersBiocompatible MaterialsTissue EngineeringBiocompatible MaterialspolycaprolactonePolyestersPolymers

Identifiers

PMID35605974
PMCPMC9169671

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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.