Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Polymers: Molecular Weight Distribution01:10

Polymers: Molecular Weight Distribution

3.2K
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.
3.2K
Polymers02:34

Polymers

34.6K
The word polymer is derived from the Greek words “poly” which means “many” and “mer” which means “parts”. Polymers are long chains of molecules composed of repeating units of smaller molecules, known as monomers. They either occur naturally, such as DNA and proteins, or can be constructed synthetically, like plastics. They have varied structural characteristics, such as linear chains, branched chains, or complex networks, that contribute to the...
34.6K
Molecular Weight of Step-Growth Polymers01:08

Molecular Weight of Step-Growth Polymers

2.1K
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...
2.1K
Step-Growth Polymerization: Overview01:03

Step-Growth Polymerization: Overview

3.4K
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...
3.4K
Polymers: Defining Molecular Weight01:01

Polymers: Defining Molecular Weight

2.8K
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...
2.8K
Polymer Classification: Architecture01:14

Polymer Classification: Architecture

2.6K
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...
2.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

ForestSAR-YOLO: real-time detection of small human targets in UAV imagery.

Scientific reports·2026
Same author

Data-Driven Optimization of Discontinuous and Continuous Fiber Composite Processes Using Machine Learning: A Review.

Polymers·2025
Same author

Machine Learning in Polymeric Technical Textiles: A Review.

Polymers·2025
Same author

Physics-Informed Neural Networks in Polymers: A Review.

Polymers·2025
Same author

Support Vector Machines in Polymer Science: A Review.

Polymers·2025
Same author

Machine Learning-Based Process Optimization in Biopolymer Manufacturing: A Review.

Polymers·2024

Related Experiment Video

Updated: May 25, 2025

Polymer Microarrays for High Throughput Discovery of Biomaterials
13:37

Polymer Microarrays for High Throughput Discovery of Biomaterials

Published on: January 25, 2012

14.5K

Boosting-Based Machine Learning Applications in Polymer Science: A Review.

Ivan Malashin1, Vadim Tynchenko1, Andrei Gantimurov1

  • 1Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia.

Polymers
|February 26, 2025
PubMed
Summary
This summary is machine-generated.

Machine learning boosting methods are revolutionizing polymer science by enhancing data analysis and material design. These powerful algorithms accelerate the discovery and optimization of advanced polymer materials.

Keywords:
AdaBoostCatBoostGradient BoostingLightGBMXGBoostboosting methodsmachine learningpolymer science

More Related Videos

Characterization of Synthetic Polymers via Matrix Assisted Laser Desorption Ionization Time of Flight MALDI-TOF Mass Spectrometry
06:56

Characterization of Synthetic Polymers via Matrix Assisted Laser Desorption Ionization Time of Flight MALDI-TOF Mass Spectrometry

Published on: June 10, 2018

24.9K
Combinatorial Synthesis of and High-throughput Protein Release from Polymer Film and Nanoparticle Libraries
10:58

Combinatorial Synthesis of and High-throughput Protein Release from Polymer Film and Nanoparticle Libraries

Published on: September 6, 2012

10.3K

Related Experiment Videos

Last Updated: May 25, 2025

Polymer Microarrays for High Throughput Discovery of Biomaterials
13:37

Polymer Microarrays for High Throughput Discovery of Biomaterials

Published on: January 25, 2012

14.5K
Characterization of Synthetic Polymers via Matrix Assisted Laser Desorption Ionization Time of Flight MALDI-TOF Mass Spectrometry
06:56

Characterization of Synthetic Polymers via Matrix Assisted Laser Desorption Ionization Time of Flight MALDI-TOF Mass Spectrometry

Published on: June 10, 2018

24.9K
Combinatorial Synthesis of and High-throughput Protein Release from Polymer Film and Nanoparticle Libraries
10:58

Combinatorial Synthesis of and High-throughput Protein Release from Polymer Film and Nanoparticle Libraries

Published on: September 6, 2012

10.3K

Area of Science:

  • Polymer Science
  • Materials Science
  • Computational Chemistry

Background:

  • Increasing complexity in polymer systems necessitates advanced analytical tools.
  • Machine learning (ML) offers powerful solutions for data analysis, material design, and predictive modeling in polymer science.
  • Boosting methods are particularly effective for high-dimensional and complex polymer-related problems.

Purpose of the Study:

  • To provide a comprehensive overview of boosting methods applications in polymer science.
  • To highlight the contributions of boosting techniques to structure-property relationships, polymer synthesis, and performance prediction.
  • To showcase the potential of boosting methods for advancing polymer material design, characterization, and optimization.

Main Methods:

  • Review of existing literature and case studies on boosting methods in polymer science.
  • Analysis of applications including AdaBoost, Gradient Boosting, XGBoost, CatBoost, and LightGBM.
  • Focus on areas such as structure-property relationships, synthesis, performance prediction, and characterization.

Main Results:

  • Boosting methods demonstrate significant utility in analyzing complex polymer data.
  • These techniques have been successfully applied to predict polymer properties and guide synthesis.
  • Case studies illustrate the effectiveness of boosting in material characterization and performance evaluation.

Conclusions:

  • Boosting methods are pivotal for addressing challenges in modern polymer science.
  • Their application facilitates efficient data analysis and accelerates the design of novel polymer materials.
  • This review underscores the transformative potential of boosting techniques for the future of polymer research and development.