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Related Concept Videos

Polymers: Molecular Weight Distribution01:10

Polymers: Molecular Weight Distribution

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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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Polymers02:34

Polymers

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Molecular Models02:00

Molecular Models

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Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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Polymers: Defining Molecular Weight01:01

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Unlike small molecules with definite molecular weights, polymers are a mixture of individual polymer chains of varying lengths, each with a unique molecular weight.  So, the molecular weight of a polymer is expressed as an average value based on the average size of the polymer chains. The two most common forms of averages used for polymers are the number average molecular weight and weight average molecular weight.
The number average molecular weight (Mn) is the summation of the number...
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Step-Growth Polymerization: Overview01:03

Step-Growth Polymerization: Overview

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Step-growth or condensation polymerization is a stepwise reaction of bi or multifunctional monomers to form long-chain polymers. As all the monomers are reactive, most of the monomers are consumed at the early stages of the reaction to form small chains of reactive oligomers, which then combine to form long polymer chains in the late stages. Hence, the reaction has to proceed for a long time to achieve high molecular weight polymers.
Many natural and synthetic polymers are produced by...
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Molecular Weight of Step-Growth Polymers01:08

Molecular Weight of Step-Growth Polymers

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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.
As the step-growth polymerization involves step-wise condensation of monomers, the molecular weight also builds up eventually. Consequently, high molecular weight polymers are obtained at the late stages of the polymerization, where 99% of monomers have been consumed.
The extent of the...
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Modeling an Enzyme Active Site using Molecular Visualization Freeware
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Modular Software for Generating and Modeling Diverse Polymer Databases.

Alejandro Santana-Bonilla1, Raquel López-Ríos de Castro2,3, Peike Sun3

  • 1Department of Physics, King's College London, London WC2R 2LS, United Kingdom.

Journal of Chemical Information and Modeling
|June 8, 2023
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Summary
This summary is machine-generated.

Researchers developed PySoftK, a Python package automating polymer library creation for materials discovery. This accelerates the design of novel functional materials by simplifying database generation and ensuring data integrity.

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Area of Science:

  • Computational chemistry
  • Materials science
  • Polymer science

Background:

  • Machine learning (ML) accelerates materials discovery but requires large, diverse molecular databases.
  • Creating these databases computationally is challenging and time-consuming.
  • Automated workflows are crucial for efficient and reproducible data generation.

Purpose of the Study:

  • To develop a flexible and automated software package for creating, modeling, and curating polymer libraries.
  • To minimize user intervention in computational chemistry workflows.
  • To support data-driven discovery of new functional materials.

Main Methods:

  • Developed PySoftK (Python Soft Matter at King's College London), a Python package for automated polymer library generation.
  • Implemented flexible and automated computational workflows.
  • Included features for generating diverse polymer topologies and parallelized library creation.

Main Results:

  • PySoftK enables automated creation, modeling, and curation of polymer libraries with minimal user input.
  • The software supports a wide range of polymer topologies.
  • Library generation is fully parallelized for efficiency.

Conclusions:

  • PySoftK provides a versatile tool for generating large polymer databases essential for ML-driven materials discovery.
  • The package addresses concerns regarding data provenance and reproducibility.
  • It is expected to advance functional materials discovery in nanotechnology and biotechnology.