Modeling natural organic matter: A stochastic approach

GEOC 33

Gabriela Chilom, gabriela.chilom@sdstate.edu, Department of Chemistry & Biochemistry, South Dakota State University, Shepard Hall, Brookings, SD 57007, Ras B. Pandey, Department of Physics and Astronomy, University of Southern Mississippi, Box 5046, Hattiesburg, MS 39406, and James A Rice, james_rice@sdstate.edu, Chemistry & Biochemistry, South Dakota State University, 121 Shepard Hall, Box 2202, Brookings, SD 57007.
The high degree of heterogeneity of natural organic matter (NOM) limits the application of the conventional structural determination approach. If the defining chemical characteristic of NOM is, in fact that it is a mixture, then what is left to explore are the tertiary and quaternary structures which result from molecule-molecule, aggregate-molecule, and aggregate-aggregate interactions. In this study we present the development and application of a stochastic modelling approach to simulate the organization of the components of NOM. The hypothesis underlying our work is that NOM is fundamentally mixture whose higher-level structure can be modeled using bulk chemical characteristics input into stochastic simulations. The stochastic modeling of the organization of NOM was performed with a computer program that combines thermal Monte Carlo (MC), kinetic MC, and direct simulation (i.e., rule-based cellular automata) methods. The independent parameters in these simulations are concentrations of hydrophilic components, hydrophobic components, amount of mineral matrix, relative interaction strengths and temperature. The present simulation, even at this early stage in its development, demonstrates that it can be used to predict behavior that can be verified experimentally.
 

General Poster Session
7:00 PM-9:00 PM, Sunday, 10 September 2006 Moscone Center -- Hall D, Poster

Division of Geochemistry

The 232nd ACS National Meeting, San Francisco, CA, September 10-14, 2006