Attila Vrabecz | PubMed Health

PubMed2005

Pair potentials from diffraction data on liquids: a neural network solution.

The inverse theorem of liquids states a one to one correspondence between classical mechanical pair potentials and structural functions. Molecular-dynamics and Monte Carlo simulations provide exact structural functions for known pair interactions. There is no exact or widespread method in the opposite direction, where the pair interactions are to be determined from a priori known pair-correlation functions or structure factors. The methods based on the integral equation theories of liquids are approximate and the iterative refinements of pair potentials with simulations take a long time. We applied artificial neural networks to get pair interactions from known structure factors in this study. We performed molecular-dynamics simulations on one-component systems with different pair potentials and the structure factors were calculated. To optimize (train) the weights of neural networks 2000 pair interaction-structure factor pairs were used. The performance of the method was tested on further 200 data pairs. The method provided reasonable potentials for the majority of the systems opening a "quick and dirty" method to determine pair interactions.

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PubMed2004

Evaluation of small-angle x-ray scattering data of a Raney-type Ni catalyst with computer simulation.

A reverse Monte Carlo-type simulation method was developed for the evaluation of anomalous small-angle x-ray scattering data of a Raney-type Ni catalyst. Based on other experimental data the catalytic Ni particles were modeled as small crystalline cylinders dispersed in the matrix. The average size of the Ni particles and their pair-correlation function were determined. Despite the unknown density of the catalyst, it is shown that each particle has about 2 neighbors in the first neighboring shell independent of the modeling density, and the position of the first peak of the pair-correlation function does not depend on the modeling density. A method was elaborated to get reasonable performance of the Reverse Monte Carlo-type simulation. The scattered intensity was calculated on the basis of probe scattering atoms put inside the cylinders. The effects of the omission of the real number of the atoms, the unknown density, the lack of normalization and the uncertainties in the cross sections were unified in two constants that were determined during the simulation. The method can be used for nanoparticles with other shape, where analytic form factors are complicated, and it may be powerful in the investigation of the usually neglected or simplified inter-particle structure of these systems.

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