Computational prediction of L_{3} EXAFS spectra of gold nanoparticles from classical molecular dynamics simulations

We present a computational approach for the simulation of extended x-ray absorption fine structure (EXAFS) spectra of nanoparticles directly from molecular dynamics simulations without fitting any of the structural parameters of the nanoparticle to experimental data. The calculation consists of two stages. First, a molecular dynamics simulation of the nanoparticle is performed and then the EXAFS spectrum is computed from “snapshots” of structures extracted from the simulation. A probability distribution function approach calculated directly from the molecular dynamics simulations is used to ensure a balanced sampling of photoabsorbing atoms and their surrounding scattering atoms while keeping the number of EXAFS calculations that need to be performed to a manageable level. The average spectrum from all configurations and photoabsorbing atoms is computed as an Au L3-edge EXAFS spectrum with the FEFF 8.4 package, which includes the self-consistent calculation of atomic potentials. We validate and apply this approach in simulations of EXAFS spectra of gold nanoparticles with sizes between 20 and 60 Å. We investigate the effect of size, structural anisotropy, and thermal motion on the gold nanoparticle EXAFS spectra and we find that our simulations closely reproduce the experimentally determined spectra

Fitting EXAFS data using molecular dynamics outputs and a histogram approach

The estimation of metal nanoparticle diameter by analysis of extended x-ray absorption fine structure (EXAFS) data from coordination numbers is nontrivial, particularly for particles <5 nm in diameter, for which the undercoordination of surface atoms becomes an increasingly significant contribution to the average coordination number. These undercoordinated atoms have increased degrees of freedom over those within the core of the particle, which results in an increase in the degree of structural disorder with decreasing particle size. This increase in disorder, however, is not accounted for by the standard means of EXAFS analysis, where each coordination shell is fitted with a single bond length and disorder term. In addition, the surface atoms of nanoparticles have been observed to undergo a greater contraction than those in the core, further increasing the range of bond distances. Failure to account for this structural change results in an increased disorder being measured, and therefore, a lower apparent coordination number and corresponding particle size are found. Here, we employ molecular dynamics (MD) simulations for a range of nanoparticle sizes to determine each of the nearest neighbor bond lengths, which were then binned into a histogram to construct a radial distribution function (RDF). Each bin from the histogram was considered to be a single scattering path and subsequently used in fitting the EXAFS data obtained for a series of carbon-supported platinum nanoparticles. These MD-based fits are compared with those obtained using a standard fitting model using Artemis and the standard model with the inclusion of higher cumulants, which has previously been used to account for the non-Gaussian distribution of neighboring atoms around the absorber. The results from all three fitting methods were converted to particle sizes and compared with those obtained from transmission electron microscopy (TEM) and x-ray diffraction (XRD) measurements. We find that the use of molecular dynamics simulations resulted in an improved fit over both the standard and cumulant models, in terms of both quality of fit and correlation with the known average particle size

Atomistic simulations of semiconductor and metallic nanoparticles

Semiconductor and metallic nanoparticles have recently become an attractive area of intensive research due to their unique and diverse properties, that differ significantly from bulk materials. With a wide range of applications and potential uses in nanoelectronics, catalysis, medicine, chemistry or physics an important amount of experimental and theoretical investigations aim to facilitate deeper understating in their physical and chemical behaviour. Within this context, this thesis is focused on the theoretical investigation of silicon, gold and platinum nanoclusters and nanoalloys, in order to provide support for experimental data obtained from collaborating researchers and scientists. Modelled structures of the above nanoparticles were constructed and studied by using a variety of computational tools such as, classical force field MD (DL POLY [1]), tightbinding DFT (DFTB+ [2]), conventional DFT (CASTEP [3]) and linear-scaling DFT (ONETEP [4]). A brief introduction regarding some basic principles of quantum mechanics (QM) and of solid state physics is presented in the first chapter; followed by a general chapter about the classical molecular dynamics (MD) method and its utilisation within the DL POLY code [1]. The last part of the second chapter is devoted to the introduction, validation and implementation of a non-default force field in the source code of DL POLY. The third chapter contains a brief description of some important theorems and terms used in density functional theory (DFT), with some basic information about linear-scaling DFT, as developed in the ONETEP code [4], and tight-binding DFT, reported in the last sections. Chapter 4, includes the results of a series of DFT calculations performed on silicon nanorods, with diameters varying from 0.8 nm to 1.3 nm and about 5.0 nm long. While up to now, similar computational works were conducted on periodic nanowires, in our case, the calculations were performed on the entire nanorods without imposing any symmetry. The fifth chapter proposes a new methodology for calculating extended x-ray absorption fine structure (EXAFS) spectra from modelled geometries of gold nanoparticles by exploiting some of the capabilities of the FEFF code [5]. From several snap-shots of a classical MD simulation, a probability distribution function is calculated for sampling the photoabsorbing and the scattering atoms of the simulated system. The results are then compared with experimental EXAFS data showing a good agreement between the predicted and the measured structures. Finally, in the last two chapters, classical MD simulations on gold and platinum nanoparticles and nanoalloys are reported, which have been performed to support the structural characterisation and analysis of synthesised gold and platinum nanoparticles. Within this framework, DFT calculations have also been attempted on ultrasmall gold nanoparticles and on gold nanosurfaces with one or two thiols attached to them, as a preliminary stage towards the application of linear-scaling DFT in simulating the properties of large metallic systems, currently being studied with semi-empirical quantum approaches or empirical force field

Large-scale first principles and tight-binding density functional theory calculations on hydrogen-passivated silicon nanorods

We present a computational study by density functional theory (DFT) of entire silicon nanorods with up to 1648 atoms without any periodicity or symmetry imposed. The nanorods have been selected to have varying aspect ratios and levels of surface passivation with hydrogen. The structures of the nanorods have been optimized using a density functional tight-binding approach, while energies and electronic properties have been computed using linear-scaling DFT with plane-wave accuracy with the ONETEP (Skylaris et al 2005 J. Chem. Phys. 122 084119) program. The aspect ratio and surface passivation (1 × 1 and 2 × 1 reconstructions) along with the size of the nanorods which leads to quantum confinement along all three dimensions, significantly affect their electronic properties. The structures of the nanorods also show interesting behaviour as, depending on their characteristics, they can in certain areas retain the structure of bulk silicon while in other parts significantly deviate from it.<br/