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Computational Reverse Engineering Analysis for Scattering Experiments (CREASE) on Vesicles Assembled from Amphiphilic
Ziyu Ye1, Zijie Wu1, Arthi Jayaraman1,2
1Colburn Laboratory, Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy Street, Newark, Delaware 19716, United States.
JACS Au
|November 29, 2021
Summary
We developed the Computational Reverse-Engineering Analysis for Scattering Experiments (CREASE) method to analyze vesicle structures from scattering data. CREASE accurately determines vesicle dimensions and provides detailed structural insights beyond traditional methods.
Area of Science:
- Polymer Science and Engineering
- Materials Science
- Biomaterials
Background:
- Vesicle structures are formed by amphiphilic copolymers in solution.
- Analyzing these complex structures using scattering data is challenging.
- Existing methods may not capture detailed structural features or handle dispersity well.
Purpose of the Study:
- To develop and validate a novel computational method, CREASE, for analyzing scattering data from copolymer vesicles.
- To determine vesicle structural features across multiple length scales.
- To provide a more comprehensive analysis than traditional scattering methods.
Main Methods:
- The CREASE method employs a two-step approach using a genetic algorithm (GA).
- Step 1: GA identifies vesicle dimensions by matching computed scattering profiles to experimental data (I_exp(q)).
- Step 2: GA-determined dimensions are used for molecular reconstruction; validation performed using in silico and experimental-like data.
Main Results:
- CREASE was successfully validated using mathematically generated and dispersity-including scattering profiles.
- CREASE demonstrated comparable or superior performance to the traditional core-multishell model fitting in SASVIEW for vesicles with dispersity.
- CREASE provided advanced structural information, including monomer distribution and chain packing within vesicle layers.
Conclusions:
- CREASE is a robust and effective computational tool for analyzing scattering data from copolymer vesicles.
- The method offers detailed structural insights unattainable with conventional analytical models.
- CREASE advances the understanding of self-assembled polymer nanostructures.
