title: 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. 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.affiliation: Department of Materials Science and Engineering, Iowa State University, Ames, Iowa 50011, USA.
authors.forename: Nathan
authors.initials: N
authors.lastname: Horst
authors.affiliation: Department of Physics and Astronomy, Ames Laboratory and Iowa State University, Ames, Iowa 50011, USA.
authors.forename: Alex
authors.initials: A
authors.lastname: Travesset