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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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A polymer dataset for accelerated property prediction and design.

Tran Doan Huan1, Arun Mannodi-Kanakkithodi1, Chiho Kim1

  • 1Institute of Materials Science, University of Connecticut, 97 North Eagleville Rd., Unit 3136, Storrs, Connecticut 06269, USA.

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Researchers created a new dataset of 1,073 polymers with calculated properties like dielectric constants. This data accelerates the discovery of novel materials with desired characteristics.

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Area of Science:

  • Materials Science, Computational Chemistry, Polymer Science

Background:

  • Computation- and data-driven methods are crucial for designing materials with specific properties.
  • Identifying structure-property relationships requires large, relevant material datasets.
  • Predictive modeling accelerates the materials design cycle.

Purpose of the Study:

  • To develop and release a comprehensive dataset of polymers and related materials.
  • To facilitate the rational design of high dielectric constant polymers.
  • To establish a foundation for future materials discovery and property prediction.

Main Methods:

  • Compiled a dataset of 1,073 polymers using first-principles calculations.
  • Structures were obtained from existing databases or through structure search methods.
  • Calculated optimized structures, atomization energies, band gaps, and dielectric constants.

Main Results:

  • A publicly available dataset (http://khazana.uconn.edu/) containing 1,073 polymers.
  • The dataset includes essential properties for materials design, focusing on dielectric constants.
  • Uniform data preparation ensures consistency and reliability for computational studies.

Conclusions:

  • The developed dataset significantly aids in the design of high dielectric constant polymers.
  • This resource accelerates materials discovery by enabling property prediction.
  • The dataset will be expanded with more materials and properties over time.