Prediction of binary nanoparticle superlattices from soft potentials
Abstract
Driven by the hypothesis that a sufficiently continuous short-ranged potential is able to account for shell flexibility and phonon modes and therefore provides a more realistic description of nanoparticle interactions than a hard sphere model, we compute the solid phase diagram of particles of different radii interacting with an inverse power law potential. From a pool of 24 candidate lattices, the free energy is optimized with respect to additional internal parameters and the p-exponent, determining the short-range properties of the potential, is varied between p = 12 and p = 6. The phase diagrams contain the phases found in ongoing self-assembly experiments, including DNA programmable self-assembly and nanoparticles with capping ligands assembled by evaporation from an organic solvent. Thus, the resulting phase diagrams can be mapped quantitatively to existing experiments as a function of only two parameters: Nanoparticle radius ratio (γ) and softness asymmetry.
- Authors:
-
- Iowa State Univ., Ames, IA (United States)
- Ames Lab., Ames, IA (United States); Iowa State Univ., Ames, IA (United States)
- Publication Date:
- Research Org.:
- Ames Laboratory (AMES), Ames, IA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1235588
- Alternate Identifier(s):
- OSTI ID: 1234147
- Report Number(s):
- IS-J-8896
Journal ID: ISSN 0021-9606; JCPSA6
- Grant/Contract Number:
- AC02-07CH11358; BES DE-AC02-07CH11358
- Resource Type:
- Journal Article: Accepted Manuscript
- Journal Name:
- Journal of Chemical Physics
- Additional Journal Information:
- Journal Volume: 144; Journal Issue: 1; Journal ID: ISSN 0021-9606
- Publisher:
- American Institute of Physics (AIP)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 77 NANOSCIENCE AND NANOTECHNOLOGY; free energy; DNA; nanoparticles; self assembly; Eigenvalues
Citation Formats
Horst, Nathan, and Travesset, Alex. Prediction of binary nanoparticle superlattices from soft potentials. United States: N. p., 2016.
Web. doi:10.1063/1.4939238.
Horst, Nathan, & Travesset, Alex. Prediction of binary nanoparticle superlattices from soft potentials. United States. https://doi.org/10.1063/1.4939238
Horst, Nathan, and Travesset, Alex. 2016.
"Prediction of binary nanoparticle superlattices from soft potentials". United States. https://doi.org/10.1063/1.4939238. https://www.osti.gov/servlets/purl/1235588.
@article{osti_1235588,
title = {Prediction of binary nanoparticle superlattices from soft potentials},
author = {Horst, Nathan and Travesset, Alex},
abstractNote = {Driven by the hypothesis that a sufficiently continuous short-ranged potential is able to account for shell flexibility and phonon modes and therefore provides a more realistic description of nanoparticle interactions than a hard sphere model, we compute the solid phase diagram of particles of different radii interacting with an inverse power law potential. From a pool of 24 candidate lattices, the free energy is optimized with respect to additional internal parameters and the p-exponent, determining the short-range properties of the potential, is varied between p = 12 and p = 6. The phase diagrams contain the phases found in ongoing self-assembly experiments, including DNA programmable self-assembly and nanoparticles with capping ligands assembled by evaporation from an organic solvent. Thus, the resulting phase diagrams can be mapped quantitatively to existing experiments as a function of only two parameters: Nanoparticle radius ratio (γ) and softness asymmetry.},
doi = {10.1063/1.4939238},
url = {https://www.osti.gov/biblio/1235588},
journal = {Journal of Chemical Physics},
issn = {0021-9606},
number = 1,
volume = 144,
place = {United States},
year = {Thu Jan 07 00:00:00 EST 2016},
month = {Thu Jan 07 00:00:00 EST 2016}
}
Web of Science
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