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

You might also read

Related Articles

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

Sort by
Same author

Phase diagrams of conformationally asymmetric pentablock copolymer melts: a theory and simulation study.

Soft matter·2026
Same author

Tutorial: Machine-Learning-Based CREASE-2D Analysis of 2D SAXS Profiles to Characterize Anisotropic Nanostructures in Soft Materials.

ACS measurement science au·2026
Same author

PMSE Centennial: Celebration of Success and New Frontiers in Polymer Materials Science and Engineering.

ACS macro letters·2025
Same author

Inverse Design of Block Polymer Materials with Desired Nanoscale Structure and Macroscale Properties.

JACS Au·2025
Same author

Random field reconstruction of three-phase polymer structures with anisotropy from 2D-small-angle scattering data.

Soft matter·2024
Same author

A computational method for rapid analysis polymer structure and inverse design strategy (RAPSIDY).

Soft matter·2024

Related Experiment Video

Updated: Aug 8, 2025

Measurement of Scattering Nonlinearities from a Single Plasmonic Nanoparticle
15:06

Measurement of Scattering Nonlinearities from a Single Plasmonic Nanoparticle

Published on: January 3, 2016

12.9K

Computational Reverse-Engineering Analysis for Scattering Experiments of Assembled Binary Mixture of Nanoparticles.

Christian M Heil1, Arthi Jayaraman1,2

  • 1Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy Street, Newark, Delaware 19716, United States.

ACS Materials Au
|March 1, 2023
PubMed
Summary

We developed a computational method, CREASE, to analyze nanoparticle structures within supraparticles using scattering data. This tool accurately reveals nanoparticle arrangement, mixing, and domain sizes from scattering profiles.

More Related Videos

Assembly and Characterization of Polyelectrolyte Complex Micelles
08:44

Assembly and Characterization of Polyelectrolyte Complex Micelles

Published on: March 2, 2020

10.9K
Ligand-Mediated Nucleation and Growth of Palladium Metal Nanoparticles
11:54

Ligand-Mediated Nucleation and Growth of Palladium Metal Nanoparticles

Published on: June 25, 2018

10.4K

Related Experiment Videos

Last Updated: Aug 8, 2025

Measurement of Scattering Nonlinearities from a Single Plasmonic Nanoparticle
15:06

Measurement of Scattering Nonlinearities from a Single Plasmonic Nanoparticle

Published on: January 3, 2016

12.9K
Assembly and Characterization of Polyelectrolyte Complex Micelles
08:44

Assembly and Characterization of Polyelectrolyte Complex Micelles

Published on: March 2, 2020

10.9K
Ligand-Mediated Nucleation and Growth of Palladium Metal Nanoparticles
11:54

Ligand-Mediated Nucleation and Growth of Palladium Metal Nanoparticles

Published on: June 25, 2018

10.4K

Area of Science:

  • Materials Science
  • Computational Chemistry
  • Nanotechnology

Background:

  • Supraparticles assembled from nanoparticle mixtures present complex structures.
  • Analyzing these structures using scattering experiments requires sophisticated computational tools.

Purpose of the Study:

  • To introduce a computational method, CREASE, for analyzing scattering data from supraparticles.
  • To determine the internal structure of assembled nanoparticles, including mixing and domain sizes.

Main Methods:

  • Developed CREASE, a computational approach utilizing genetic algorithms.
  • Input: scattering intensity profiles, nanoparticle composition, and size distributions.
  • Validated using in silico scattering data from molecular simulations of binary nanoparticle mixtures.

Main Results:

  • CREASE accurately reproduces nanoparticle structures from simulations.
  • The method effectively analyzes limited wavevector (q) range scattering data.
  • Provides pairwise radial distribution functions and quantifies nanoparticle mixing/segregation.

Conclusions:

  • CREASE is a powerful tool for elucidating nanoparticle assembly within supraparticles.
  • The method offers detailed structural insights from scattering experiments.
  • Applicable to complex geometries and varying degrees of nanoparticle mixing.