The DOI matches its Crossref record; 384 of the 384 references it cites were found in a registry or an index.
Modeling and Simulations of Polymers: A Roadmap
Open accessAbstract
Abstract Molecular modeling and simulations are invaluable tools for the polymer science and engineering community. These computational approaches enable predictions and provide explanations of experimentally observed macromolecular structure, dynamics, thermodynamics, and microscopic and macroscopic material properties. With recent advances in computing power, polymer simulations can synergistically inform, guide, and complement in vitro macromolecular materials design and discovery efforts. To ensure that this growing power of simulations is harnessed correctly, and meaningful results are achieved, care must be taken to ensure the validity and reproducibility of these simulations. With these considerations in mind, in this Perspective we discuss our philosophy for carefully developing or selecting appropriate models, performing, and analyzing polymer simulations. We highlight best practices, key challenges, and important advances in model development/selection, computational method choices, advanced sampling methods, and data analysis, with the goal of educating potential polymer simulators about ways to improve the validity, usefulness, and impact of their polymer computational research.
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Cites
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Cited by
Feng, Q.-K., Zhong, S.-L., Pei, J.-Y., Zhao, Y., Zhang, D.-L., Liu, D.-F., Zhang, Y.-X., & Dang, Z.-M. (2022) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00793 · Cited by 744
Molecular Characterization of Polymer Networks
Danielsen, S. P. O., Beech, H. K., Wang, S., El-Zaatari, B. M., Wang, X., Sapir, L., Ouchi, T., Wang, Z., Johnson, P. N., Hu, Y., et al. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.0c01304 · Cited by 336
Metadata
- Authors
- Gartner, T. E., & Jayaraman, A.
- Venue
- Macromolecules
- Publisher
- American Chemical Society (ACS)
- Published
- 2019-01-22
- Volume
- 52
- Issue
- 3
- Pages
- 755-786
- ISSN
- 0024-9297 (ISSN-L)
- 1520-5835
- OpenAlex
- W2912807874
- Cited by
- 548
- References
- 384
- FWCI
- 34.19
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
