Award Abstract #0626111
CRIF:CRF Structure-Adaptive Materials Prediction (SAMP)

NSF Org:	CHE Division of Chemistry
Initial Amendment Date:	August 1, 2006
Latest Amendment Date:	August 21, 2009
Award Number:	0626111
Award Instrument:	Continuing grant
Program Manager:	Carlos A. Murillo CHE Division of Chemistry MPS Directorate for Mathematical & Physical Sciences
Start Date:	September 1, 2006
Expires:	August 31, 2010 (Estimated)
Awarded Amount to Date:	$670700
Investigator(s):	Iosif Vaisman ivaisman@gmu.edu (Principal Investigator) Estela Blaisten-Barojas (Former Principal Investigator) Iosif Vaisman (Former Co-Principal Investigator)
Sponsor:	George Mason University 4400 UNIVERSITY DR FAIRFAX, VA 22030 703/993-2295
NSF Program(s):	CHEMICAL INSTRUMENTATION
Field Application(s):
Program Reference Code(s):	OTHR, 7569, 7237, 0000
Program Element Code(s):	1938

ABSTRACT

Estela Blaisten-Barojas and Iosif Vaisman of George Mason University are supported by the NSF Division of Chemistry under the Cyberinfrastructure and Research Facilities Program. This project will develop intelligent data mining tools and materials design strategies using the National Institute for Standards and Technology crystallographic and materials property data sources as an initial testbed. This cyber-intelligent connection of well-validated experimental data will lead to correlations and patterns that can be fed back to the data source with the following objectives: 1) to develop a rational cyber-design for determining the nature and types of data equivalencies in the structural chemical information of inorganic materials; 2) to open a visual portal enhancing the use of intelligently organized correlations of structural chemical data for predicting new materials; 3) to develop a Web-based learning system for educational purposes; 4) to enhance and improve accessibility and query tools; and 5) to replace legacy point-to-point query systems in the chemical sciences by a system conveying global validated correlations across databases.

Several communities in the chemical sciences will benefit from this Web-based intelligent system to query databases: solid-state synthetic experimentalists, theoretical chemical modelers and simulators, chemical educators, and instrument builders. In addition, this cyber-system will be deployed and tested in several introductory chemistry courses. Additional educational activities will include: 1) a battery of projects to be developed by chemistry undergraduates and incorporated into the intelligent system in order to search and discover structural knowledge of inorganic materials; and 2) the organization of groups of graduate students presenting their graduate projects (containing pieces of the Web-based system) in courses of the two summer workshops for undergraduates.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

D. A. Carr, M. Lach-hab, I. Vaisman, E. Blaisten-Barojas. "Delaunay Tessellation of Zeolite Structures," Proceedings 234th National Meeting of the ACS, Boston, MA, August 19-23, 2007, 2007.

D. A. Carr, M. Lach-hab, S. Yang, I. Vaisman, and E. Blaisten-Barojas. "Machine learning approach for structure-based zeolite classification," Microporous and Mesoporous Materials, v.117, 2008, p. 339.

M. Lach-hab, S. Yang, I. Vaisman and E. Blaisten-Barojas. "Assignment of Framework Types to the Zeolite Crystals in the Inorganic Crystal Structure Database," arXiv:0904.2597, 2009.

S. Yang,M. Lach-hab, I. I. Vaisman, E. Blaisten-Barojas. "Machine Learning Approach for Classification of Zeolite Crystals," WorldCom'08 Proceedings DMIN'08, 2008, p. 70.

Yang, S.; Lach-hab, M.; Vaisman, I. I.; Blaisten-Barojas, E.. "A cheminformatics approach for zeolite framework determination," Lecture Notes in Computer Science, v.5545, 2009, p. 160.

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