Radial distribution function code RDF

Steinhauer and Gasteiger [30] developed a new 3D descriptor based on the idea of radial distribution functions (RDFs), which is well known in physics and physico-chemistry in general and in X-ray diffraction in particular [31], The radial distribution function code (RDF code) is closely related to the 3D-MoRSE code. The RDF code is calculated by Eq. (25), where/is a scaling factor, N is the number of atoms in the molecule, p/ and pj are properties of the atoms i and/ B is a smoothing parameter, and Tij is the distance between the atoms i and j g(r) is usually calculated at a number of discrete points within defined intervals [32, 33]. 

These descriptors are based on the distance distribution in the - geometrical representation of a molecule and constitute a radial distribution function code (RDF code) that shows certain characteristics in common with the - 3D-MoRSE code. 

Formally, the radial distribution function of an ensemble of A atoms can be interpreted as the probability distribution of finding an atom in a spherical volume of radius R. The general form of the radial distribution function code (RDF code) is represented by ... 

D MoRSE desaiptor, radial distribution function (RDF code), WHIM descriptors, GETAWAY descriptors,... 

The compounds were described by a set of 32 radial distribution function (RDF) code values [27] representing the 3D structure of a molecule and eight additional descriptors. The 3D coordinates were obtained using the 3D structure generator GORINA [33]. 

A slight modification of the general form of an RDF leads to a molecular descriptor, the radial distribution function (RDF) code, which includes atom properties that address characteristic atom features in the molecular environment. Fields of application for RDF codes are the simulation of infrared spectra and deriving molecular structure information from infrared spectra [40,41]. 

The potential parameters for the water molecule were empirically fitted to reproduce the experimental dipole moment, 0-H bond length and H-O-H angle of the water monomer and the structure of the water dimer and infra-red data. Molecular dynamics simulations were then used to calculate the self-diffusion coefficient, radial distribution functions (RDFs) and energy of evaporation of liquid water. The computer code DL POLY 2.6 code (Forester and Smith 1995) was employed. We simulated a box containing 256 water molecules at a temperature of 300 K where the conditions were initially set at the experimental density of p= 1.0 g/cm and run with an NPT ensemble. We chose a mass for the oxygen shell of 0.2 a.u., which is small compared to the mass of the hydrogen atom of 1.0 a.u. However, due to the small shell mass we needed to run the MD simulation with the small timestep of 0.2 fs in order to keep the system stable. With this timestep we obtained data at constant pressure and temperature for a period of 100 picoseconds. 

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