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Updated: Mar 27, 2026

Liquid-cell Transmission Electron Microscopy for Tracking Self-assembly of Nanoparticles

Liquid-cell Transmission Electron Microscopy for Tracking Self-assembly of Nanoparticles

Published on: October 16, 2017

Prediction of binary nanoparticle superlattices from soft potentials.

Nathan Horst¹, Alex Travesset²

¹Department of Materials Science and Engineering, Iowa State University, Ames, Iowa 50011, USA.

The Journal of Chemical Physics

|January 10, 2016

Summary

This study introduces a continuous short-ranged potential for modeling nanoparticle interactions, revealing phase diagrams that align with experimental self-assembly findings. The model accurately predicts nanoparticle assembly based on radius ratio and softness asymmetry.

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Last Updated: Mar 27, 2026

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Published on: May 9, 2014

Area of Science:

Materials Science
Condensed Matter Physics
Nanotechnology

Background:

Traditional hard sphere models inadequately describe nanoparticle interactions, failing to account for shell flexibility and phonon modes.
Continuous short-ranged potentials offer a more realistic approach to modeling nanoparticle behavior and self-assembly.
Existing self-assembly experiments utilize methods like DNA programmability and ligand-directed assembly.

Purpose of the Study:

To compute the solid phase diagram for nanoparticles interacting via an inverse power law potential.
To investigate the influence of potential short-range properties (p-exponent) on nanoparticle phase behavior.
To develop a model that quantitatively maps to experimental self-assembly results.

Main Methods:

Calculation of the solid phase diagram using an inverse power law potential.
Optimization of free energy across 24 candidate lattices and variation of the p-exponent (6-12).
Quantitative mapping of computed phase diagrams to experimental parameters: nanoparticle radius ratio (γ) and softness asymmetry.

Main Results:

The computed phase diagrams accurately predict phases observed in current nanoparticle self-assembly experiments.
The model demonstrates that a continuous short-ranged potential effectively captures shell flexibility and phonon modes.
Phase diagrams are quantitatively reproducible using only nanoparticle radius ratio and softness asymmetry.

Conclusions:

A continuous short-ranged potential provides a more accurate description of nanoparticle interactions than hard sphere models.
The developed model successfully predicts and explains experimental nanoparticle self-assembly phenomena.
Nanoparticle assembly behavior can be effectively controlled and predicted by tuning radius ratio and softness asymmetry.