Related Experiment Video
Updated: Jul 26, 2025

08:45
Forming Giant-sized Polymersomes Using Gel-assisted Rehydration
Published on: May 26, 2016
9.4K
Bottom-Up Preparation of Phase-Separated Polymersomes
Safa Almadhi1, Joe Forth1, Laura Rodriguez-Arco1,2
1Department of Chemistry, University College London, London, WC1H 0AJ, UK.
Macromolecular Bioscience
|June 14, 2023
Summary
A novel bottom-up method creates uniform, patchy polymersomes for drug delivery. This self-assembly technique offers a high yield of nanoparticles with controlled size and surface properties.
Area of Science:
- Polymer chemistry
- Nanotechnology
- Materials science
Background:
- Polymersomes are versatile nanocarriers for drug delivery.
- Fabricating polymersomes with specific surface topology, like "patchy" designs, is challenging.
- Existing top-down methods for patchy polymersomes have limitations.
Purpose of the Study:
- To develop a bottom-up self-assembly approach for creating monodisperse, two-component polymersomes with phase-separated ("patchy") topology.
- To compare this new method with traditional top-down preparation techniques.
- To present an automated image processing algorithm for polymersome analysis.
Main Methods:
- Solvent-switch self-assembly of polymers.
- Characterization of polymersome size, morphology, and surface topology.
- Development and application of an image processing algorithm for transmission electron microscope (TEM) images.
Main Results:
- Successful fabrication of monodisperse, patchy polymersomes with a diameter of approximately 50 nm.
- High yield of nanoparticles with controlled size, morphology, and surface topology.
- Demonstration of a robust image processing algorithm for automated size distribution analysis from TEM images.
Conclusions:
- The bottom-up, solvent-switch self-assembly is an effective method for producing high-quality patchy polymersomes.
- This approach is suitable for drug delivery applications requiring precise nanoparticle characteristics.
- The automated image analysis tool enhances the characterization of nanoparticle populations.

