Sequential surface modification of au nanoparticles: from surface-bound Ag(I) complexes to Ag(0) doping.

Gold nanoparticles (Au NPs) with tailor-made structures and properties are highly desirable for applications in catalysis and sensing. In this context, surface modifications of Au NPs are of particular relevance. Herein, we present a sequential surface modification of Au NPs with Ag(I) coordination complexes, which can be converted into Ag(0)-doped Au NPs by simple ligand-exchange reaction. The key innovative element of this surface modification is a multifunctional bioxazoline-based ligand that brings coordinated Ag(I) into close proximity to the particle surface.

Benchmarking Electron Densities and Electrostatic Potentials of Proteins from the Three-Partition Frozen Density Embedding Method.

The fragment-based Three-Partition Frozen Density Embedding (3-FDE) approach [ Jacob, C. R.; Visscher, L. J. Chem. Phys. 2008 , 128 , 155102 ] is used to generate protein densities and electrostatic potentials, which are critically assessed in comparison to supermolecular Kohn-Sham Density Functional Theory (DFT) results obtained with sophisticated exchange-correlation functionals. The influence of several parameters and user choices is explored with respect to accuracy and reliability. In addition, a recently implemented combination of the 3-FDE scheme with hybrid functionals is applied in production calculations for the first time. We demonstrate that the 3-FDE method not only closely reproduces results from corresponding supermolecular calculations for routine situations (peptides/proteins in solution) but can even surpass conventional Kohn-Sham DFT in accuracy for difficult cases, such as zwitterionic structures in vacuo. This is due to the fact that the fragmentation inherently limits the overdelocalization caused by the self-interaction error in common DFT approximations. The method is thus not only able to reduce the computational effort for the description of large biological entities but also can strongly reduce the artifacts brought about by the SIE.

A Local Variant of the Conductor-Like Screening Model for Fragment-Based Electronic-Structure Methods.

Due to steadily rising computational power and sophisticated modeling approaches, increasingly larger molecular systems can be modeled with ab initio methods. An especially promising approach is subsystem methods, where the total system is broken down into smaller subunits that can be treated individually. If an implicit solvent environment such as the conductor-like screening model (COSMO) is included in the description, then additional environmental effects can be incorporated at relatively low cost. For very large systems described with subsystem methods, however, the solution of the COSMO equations can actually become the bottleneck of the calculation. A prominent example in this area is biomolecular systems such as proteins, which can, for instance, be described with frozen density embedding (FDE), especially the related 3-FDE approach. In this article, we present an alternative COSMO variant, which exploits the subsystem nature of the underlying electronic description and has been implemented in a development version of the Amsterdam Density Functional program suite (Adf). We show that the computational cost for the solvent model can be reduced dramatically while retaining the accuracy of the regular description. We compare several schemes for density and surface charge updates and assess the effect of the single tuning parameter.

Parametrization and Benchmark of DFTB3 for Organic Molecules.

DFTB3 is a recent extension of the self-consistent-charge density-functional tight-binding method (SCC-DFTB) and derived from a third order expansion of the density functional theory (DFT) total energy around a given reference density. Being applied in combination with the parametrization of its predecessor (MIO), DFTB3 improves for hydrogen binding energies, proton affinities, and hydrogen transfer barriers. In the present study, parameters especially designed for DFTB3 are presented, and its performance is evaluated for small organic molecules focusing on thermochemistry, geometries, and vibrational frequencies from our own and several databases from literature. The new parameters remove significant overbinding errors, reduce errors for geometries of noncovalent interactions, and improve the overall performance.