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

3.7K
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.
3.7K
Step-Growth Polymerization: Overview01:03

Step-Growth Polymerization: Overview

3.6K
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...
3.6K
Olefin Metathesis Polymerization: Ring-Opening Metathesis Polymerization (ROMP)01:16

Olefin Metathesis Polymerization: Ring-Opening Metathesis Polymerization (ROMP)

2.7K
Ring-opening metathesis polymerization or ROMP involves strained cycloalkenes as starting materials. The mechanism of ROMP proceeds by reacting cycloalkene with Grubbs catalyst to give metallacyclobutane intermediate which undergoes a ring-opening reaction to form new carbene. The new carbene reacts with another molecule of cycloalkene. Repetition of these steps leads to the formation of an unsaturated open-chain polymer product. All these steps are reversible, however, relieving the ring...
2.7K
Molecular Weight of Step-Growth Polymers01:08

Molecular Weight of Step-Growth Polymers

2.3K
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...
2.3K
Olefin Metathesis Polymerization: Overview01:13

Olefin Metathesis Polymerization: Overview

2.2K
Recently, the development of olefin metathesis polymerization advanced the field of polymer synthesis. Simply put, the reorganization of substituents on their double bonds between two olefins in the presence of a catalyst is known as the olefin metathesis reaction. The use of metathesis reaction for polymer synthesis is called olefin metathesis polymerization.
Ruthenium-based Grubbs catalyst is the most commonly used catalyst for olefin metathesis polymerization. Grubbs catalyst consists...
2.2K
Polymer Classification: Stereospecificity01:26

Polymer Classification: Stereospecificity

2.6K
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...
2.6K

You might also read

Related Articles

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

Sort by
Same author

Pathway-Aware Template-Based Retrosynthesis.

Journal of chemical information and modeling·2026
Same author

Quantifying the failure modes of current one-step retrosynthesis models.

Chemical science·2026
Same author

Multimerization interactions between protein-inspired single-chain random heteropolymers.

PloS one·2026
Same author

A machine learning-based workflow for transaminase selection.

Chemical science·2026
Same author

An overview of reaction outcome prediction with physics-based and data-driven methods.

Chemical Society reviews·2026
Same author

Hydrolysis Reaction Rate Prediction Using Machine Learning: WaterDRoP.

Environmental science & technology·2026

Related Experiment Video

Updated: Sep 9, 2025

Self-assembling Morphologies Obtained from Helical Polycarbodiimide Copolymers and Their Triazole Derivatives
09:22

Self-assembling Morphologies Obtained from Helical Polycarbodiimide Copolymers and Their Triazole Derivatives

Published on: February 7, 2017

7.9K

Autonomous Discovery of Functional Random Heteropolymer Blends through Evolutionary Formulation Optimization.

Guangqi Wu1,2,3, Tianyi Jin1,4, Alfredo Alexander-Katz4

  • 1Department of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, 02139, MA, USA.

Matter
|August 29, 2025
PubMed
Summary

Developing new functional polymers is accelerated by an autonomous platform that rapidly explores polymer blends. This system discovers novel random heteropolymer blends (RHPs) with enhanced properties, outperforming individual components.

Keywords:
autonomous discoveryoptimizationpolymer blendsrandom heteropolymers

More Related Videos

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

10.5K
Depolymerizable Olefinic Polymers Based on Fused-Ring Cyclooctene Monomers
08:12

Depolymerizable Olefinic Polymers Based on Fused-Ring Cyclooctene Monomers

Published on: December 16, 2022

3.4K

Related Experiment Videos

Last Updated: Sep 9, 2025

Self-assembling Morphologies Obtained from Helical Polycarbodiimide Copolymers and Their Triazole Derivatives
09:22

Self-assembling Morphologies Obtained from Helical Polycarbodiimide Copolymers and Their Triazole Derivatives

Published on: February 7, 2017

7.9K
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

10.5K
Depolymerizable Olefinic Polymers Based on Fused-Ring Cyclooctene Monomers
08:12

Depolymerizable Olefinic Polymers Based on Fused-Ring Cyclooctene Monomers

Published on: December 16, 2022

3.4K

Area of Science:

  • Materials Science
  • Polymer Chemistry
  • Chemical Engineering

Background:

  • Developing novel polymers traditionally takes years, but blending existing polymers offers a faster, cost-effective route to new materials.
  • Optimizing functional polymer blends is complex due to vast design spaces, non-additive properties, and limited predictive understanding.
  • Random heteropolymers (RHPs) represent a promising class of materials, but their blending (RHPBs) requires efficient exploration strategies.

Purpose of the Study:

  • To develop an autonomous platform for rapid discovery of functional polymer blends.
  • To explore the complex blending space of random heteropolymers (RHPs) efficiently.
  • To identify RHP blends (RHPBs) with emergent properties exceeding those of their constituents.

Main Methods:

  • Integration of high-throughput blending, real-time data acquisition, and evolutionary algorithms for automated composition optimization.
  • Utilizing an autonomous platform to navigate the combinatorial blending space of random heteropolymers (RHPs).
  • Employing enzyme thermal stability as a model objective function to guide the discovery process.

Main Results:

  • The autonomous platform successfully discovered random heteropolymer blends (RHPBs) that exhibited superior performance compared to all individual polymer components.
  • Rapid exploration of the RHP blending space was achieved, demonstrating the platform's efficiency.
  • Retrospective analysis identified segment-level interactions as key factors correlating with the enhanced performance of the discovered RHPBs.

Conclusions:

  • Autonomous discovery platforms can significantly accelerate the identification of polymers with emergent properties.
  • The random heteropolymer (RHP) and random heteropolymer blend (RHPB) space offers substantial opportunities for novel material development.
  • Understanding segment-level interactions is crucial for optimizing polymer blend performance and guiding future material design.