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Title: Prediction of binary nanoparticle superlattices from soft potentials

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:
 [1] ;  [2]
  1. Iowa State Univ., Ames, IA (United States)
  2. Ames Lab., Ames, IA (United States); Iowa State Univ., Ames, IA (United States)
Publication Date:
Report Number(s):
IS-J-8896
Journal ID: ISSN 0021-9606; JCPSA6
Grant/Contract Number:
AC02-07CH11358; BES DE-AC02-07CH11358
Type:
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)
Research Org:
Ames Laboratory (AMES), Ames, IA (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
77 NANOSCIENCE AND NANOTECHNOLOGY; free energy; DNA; nanoparticles; self assembly; Eigenvalues
OSTI Identifier:
1235588
Alternate Identifier(s):
OSTI ID: 1234147

Horst, Nathan, and Travesset, Alex. Prediction of binary nanoparticle superlattices from soft potentials. United States: N. p., Web. doi:10.1063/1.4939238.
Horst, Nathan, & Travesset, Alex. Prediction of binary nanoparticle superlattices from soft potentials. United States. doi:10.1063/1.4939238.
Horst, Nathan, and Travesset, Alex. 2016. "Prediction of binary nanoparticle superlattices from soft potentials". United States. doi: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},
journal = {Journal of Chemical Physics},
number = 1,
volume = 144,
place = {United States},
year = {2016},
month = {1}
}