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International Journal for Uncertainty Quantification
Fator do impacto: 0.967 FI de cinco anos: 1.301 SJR: 0.531 SNIP: 0.8 CiteScore™: 1.52

ISSN Imprimir: 2152-5080
ISSN On-line: 2152-5099

Open Access

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2012003950
pages 157-169

UNCERTAINTY CLASSIFICATION AND VISUALIZATION OF MOLECULAR INTERFACES

Aaron Knoll
Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois 60439, USA
Maria K. Y. Chan
Center for Nanoscale Materials Argonne National Laboratory, Argonne, Illinois 60439, USA
Kah Chun Lau
Materials Science Division, Argonne National Laboratory, Argonne, Illinois 60439, USA
Bin Liu
Center for Nanoscale Materials Argonne National Laboratory, Argonne, Illinois 60439, USA
Jeffrey Greeley
Center for Nanoscale Materials Argonne National Laboratory, Argonne, Illinois 60439, USA
Larry Curtiss
Materials Science Division, Argonne National Laboratory, Argonne, Illinois 60439, USA
Mark Hereld
Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois 60439, USA
Michael E. Papka
Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois 60439, USA

RESUMO

Molecular surfaces at atomic and subatomic scales are inherently ill-defined. In many computational chemistry problems, boundaries are better represented as volumetric regions than as discrete surfaces. Molecular structure of a system at equilibrium is given by the self-consistent field, commonly interpreted as a scalar field of electron density. While experimental measurements such as chemical bond and van der Waals radii do not spatially define the interface, they can serve as useful indicators of chemical and inert interactions, respectively. Rather than using these radial values to directly determine surface geometry, we use them to map an uncertainty interval in the electron density distribution, which then guides classification of volume data. This results in a new strategy for representing, analyzing, and rendering molecular boundaries that is agnostic to the type of interaction.