A Reverse Monte-Carlo Modeling Study Of Amorphous Hydrogenated Carbon

Walters, J.K. and Rigden, Jane S. and Newport, Robert J. (1994) A Reverse Monte-Carlo Modeling Study Of Amorphous Hydrogenated Carbon. In: Euroconference 94 on Neutrons in Disordered Matter, 9-13 June 1994, Stockholm, Sweden. (Access to this publication is restricted)

PDF
Restricted to Repository staff only
Contact us about this Publication Download (9MB)
[img]
Official URL
http://dx.doi.org/10.1088/0031-8949/1995/T57/024

Abstract

The results of a Reverse Monte Carlo (RMC) modelling of amorphous hydrogenated carbon (a-C:H) are presented. The RMC method has been implemented with the introduction of maximum co-ordination number and ''triplet'' constraints, whilst fitting both neutron and X-ray diffraction data. The positions of 5000 ''atoms'' in a box, with full periodicity, are altered until the associated model structure factor, S(Q), and pair distribution function, G(r), agree with the analogous experimental data within the errors. Once the data has been fitted, it is possible to generate model partial pair distribution functions (i.e. those associated with C-C, C-H and H-H), bond angle distributions, co-ordination number distributions, etc. X-ray data is used to provide information on the carbon-carbon network, whilst neutrons are also sensitive to the cross-terms involving hydrogen. The fitting of both types of data simultaneously therefore provides sufficient information to generate a viable ''physical'' model for the structure of these materials. The effects of increasing the number density inside the box have also been investigated.

Item Type: Conference or workshop item (Paper)
Subjects: Q Science
Divisions: Faculties > Science Technology and Medical Studies > School of Physical Sciences > Functional Materials Group
Depositing User: J.M. Smith
Date Deposited: 07 May 2009 14:06
Last Modified: 17 Jul 2014 09:27
Resource URI: http://kar.kent.ac.uk/id/eprint/16001 (The current URI for this page, for reference purposes)
  • Depositors only (login required):

Downloads

Downloads per month over past year