Atomistic Polymer Modeling: Recent Advances and Challenges in Building and Parametrization Workflows Article Swipe
YOU?
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· 2025
· Open Access
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· DOI: https://doi.org/10.1021/acs.macromol.5c01166
Synthetic polymers are a broad and versatile class of soft materials covering a large chemical space. “Computational microscopy” approaches such as atomistic molecular dynamics (MD) simulations are an effective tool to validate and rationalize experimental data for structure–property characterization. The predictive quality of MD simulations and the properties derived from them are primarily driven by the accuracy and relevance of the force field used to represent the system. While biomolecular simulation (nucleic acids, proteins) workflows benefit from dedicated toolkits and domain-specific force fields, the modeling of synthetic polymers has not progressed to the same extent. This perspective will discuss recent efforts to improve system building and parametrization workflows for synthetic polymers, and the unique challenges differentiating them from biopolymers. We will outline shortcomings in established workflows, review best practices for FAIR polymer simulations, and highlight new tools/workflows leveraging cheminformatics, direct chemical perception, and neural networks.
Related Topics
- Type
- article
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- en
- Landing Page
- https://doi.org/10.1021/acs.macromol.5c01166
- OA Status
- hybrid
- References
- 166
- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4415615509Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1021/acs.macromol.5c01166Digital Object Identifier
- Title
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Atomistic Polymer Modeling: Recent Advances and Challenges in Building and Parametrization WorkflowsWork title
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-10-28Full publication date if available
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Hannah N. Turney, Micaela MattaList of authors in order
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https://doi.org/10.1021/acs.macromol.5c01166Publisher landing page
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1021/acs.macromol.5c01166Direct OA link when available
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0Total citation count in OpenAlex
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