Interfaces often control the structure and properties of materials, particularly at the molecular and nanoscale. At the same time, heterogeneous interfaces, challenge many computational approaches due to their complexity and the high atomic density on both sides. In this talk, we (i) show by density-functional calculations that shape and assembly of nanocrystals can be controlled by ligand adsorption on the nanocrystal facets [1] and (ii) develop a new approach that describes the effects of solvent in diffusion Monte Carlo through a classical density-functional description of the liquid environment, dramatically increasing the utility of quantum Monte Carlo calculations for solvated systems [2].
The self-assembly of nanocrystals into mesoscale superlattices provides a path to the design of materials with tunable electronic, physical and chemical properties for various applications. The self-assembly is controlled by the nanocrystal shape and ligand-mediated interactions between them. To understand this, it is necessary to know the effect of the ligands on the surface energies (which tune the nanocrystal shape), as well as the relative coverage of the different facets (which control the interactions). We will discuss how calculations of ab-initio surface and ligand-binding energies for PbSe nanocrystals predict the equilibrium shape of the nanocrystals and a transition from octahedral to cubic when increasing the ligand concentration during synthesis [1]. Our results furthermore suggest that the experimentally observed transformation of the nanocrystal superlattice structure from fcc to bcc is caused by the preferential detachment of ligands from particular facets, leading to anisotropic ligand coverage [3].
Next, we present a new approach that describes the effects of solvent in diffusion Monte Carlo through a classical density-functional description of the liquid environment, dramatically increasing the utility of quantum Monte Carlo calculations for solvated systems. The method yields free energies and thermodynamic averages directly, while eliminating the need for explicit solvent electrons. We implemented this approach into diffusion Monte Carlo and tested it for the solvation energy of formaldehyde. The method is general and suitable for calculations using any form of trial wave function and is applicable to molecules, surfaces, and crystals [2].
[1] ACS Nano 6, 2118 (2012).
[2] Phys. Rev. B 85, 201102(R) (2012).
[3] J. Am. Chem. Soc. 133, 3131 (2011).
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