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Related Concept Videos

Polymer Classification: Crystallinity01:21

Polymer Classification: Crystallinity

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Unlike ionic or small covalent molecules, polymers do not form crystalline solids due to the diffusion limitations of their long-chain structures. However, polymers contain microscopic crystalline domains separated by amorphous domains.
Crystalline domains are the regions where polymer chains are aligned in an orderly manner and held together in proximity by intermolecular forces. For example, chains in the crystalline domains of polyethylene and nylon are bound together by van der Waals...
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Polymer Classification: Stereospecificity01:26

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Polymerization generates chiral centers along the entire backbone of a polymer chain. Accordingly, the stereochemistry of the substituent group has a significant effect on polymer properties. Polymers formed from monosubstituted alkene monomers feature chiral carbons at every alternate position in the polymer backbone. Relative to the predominant orientation of substituents at the adjacent chiral carbons, the polymer can exist in three different configurations: isotactic, syndiotactic, and...
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For any given polymer, the weight average molecular weight (Mw) is higher than, if not equal to, the number average molecular weight (Mn). The only situation in which the weight average molecular weight and the number average molecular weight are equal is when a polymer consists only of chains with equal molecular weight. However, this never happens in a synthetic polymer, since it is difficult to control the polymerization process up to a molecular level with accuracy to a hundred percent.
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Step growth polymerization involves bi or multifunctional monomers. Bifunctional monomers react to form linear step growth polymers, whereas multifunctional monomers react to form non-linear or branched polymers.
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Polymer Classification: Architecture01:14

Polymer Classification: Architecture

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Polymers are classified as linear or branched on the basis of their chain architecture. The polymer chains in linear polymers have a long chain-like structure with minimal to no branching at all. Even if a polymer features large substituent groups on the monomer, which appear as branches to the skeleton, it is not considered a branched polymer. A branched polymer contains secondary polymer chains that arise from the main polymer chain. The branching occurs when the polymer growth shifts from...
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Related Experiment Video

Updated: Jan 18, 2026

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
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Directional Entropy Bands for Surface Characterization of Polymer Crystallization.

Elyar Tourani1, Brian J Edwards1, Bamin Khomami1

  • 1Materials Research and Innovation Laboratory, Department of Chemical and Biomolecular Engineering, University of Tennessee, Knoxville, TN 37996, USA.

Polymers
|September 13, 2025
PubMed
Summary

New directional entropy bands improve analysis of polymer crystallization from molecular dynamics simulations, offering better insights into nucleation and crystal growth. This method captures complex alignment and surface phenomena effectively.

Keywords:
directional entropy bandslocal order parametersmolecular dynamicsnucleationphase transitionspolymer crystallizationsurface detection

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Area of Science:

  • Materials Science
  • Computational Chemistry
  • Polymer Science

Background:

  • Molecular dynamics (MD) simulations offer atomistic detail for polymer nucleation and crystallization.
  • Interpreting complex spatiotemporal data from MD simulations is challenging.
  • Existing order parameters struggle with directional alignment and spatial resolution, limiting analysis of anisotropic and heterogeneous crystallization.

Purpose of the Study:

  • To introduce novel local order parameters, directional entropy bands, for enhanced analysis of polymer crystallization.
  • To overcome limitations of conventional metrics in capturing directional alignment and surface phenomena.
  • To provide a more accurate and interpretable framework for studying polymer crystallization kinetics.

Main Methods:

  • Development and application of directional entropy bands, extending scalar entropy descriptors with angular moments.
  • Comparison of directional entropy bands against conventional metrics like entropy, crystallinity index, and SOAP descriptors.
  • Utilizing MD simulations of polymer crystallization and UMAP embeddings for data visualization and classification.

Main Results:

  • Scalar entropy bands outperform SOAP descriptors in polymer phase separation analysis at single-snapshot resolution.
  • Directional extensions effectively identify the evolving crystal-melt interface, enabling earlier nucleation detection.
  • Quantitative surface profiling and identification of a continuous melt-surface-core manifold were achieved.

Conclusions:

  • Directional entropy bands provide a robust and efficient method for analyzing polymer crystallization.
  • The novel parameters offer superior spatial resolution and directional sensitivity compared to existing metrics.
  • This framework facilitates deeper understanding of polymer crystallization kinetics and surface growth phenomena.