skip to main content

SciTech ConnectSciTech Connect

This content will become publicly available on January 7, 2017

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.
 [1] ;  [2] ;  [3]
  1. Iowa State Univ., Ames, IA (United States)
  2. Ames Lab., Ames, IA (United States)
  3. (United States)
Publication Date:
OSTI Identifier:
Report Number(s):
Journal ID: ISSN 0021-9606; JCPSA6
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Journal of Chemical Physics
Additional Journal Information:
Journal Volume: 144; Journal Issue: 1; Journal ID: ISSN 0021-9606
American Institute of Physics (AIP)
Research Org:
Ames Laboratory (AMES), Ames, IA (United States)
Sponsoring Org:
Country of Publication:
United States
free energy; DNA; nanoparticles; self assembly; Eigenvalues