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Parallel Two-Electron Reduced Density Matrix Based Electronic Structure Software for Highly Correlated Molecules and Materials

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911NF-14-P-0048
Agency Tracking Number: A14A-013-0043
Amount: $150,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: A14A-T013
Solicitation Number: 2014.A
Solicitation Year: 2014
Award Year: 2014
Award Start Date (Proposal Award Date): 2014-09-29
Award End Date (Contract End Date): 2015-03-21
Small Business Information
5050 S. Lake Shore Dr. 3601, Chicago, IL, -
DUNS: 079463468
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 David Mazziotti
 Principal Investigator
 (773) 834-1762
Business Contact
 Mark Mazziotti
Title: Executive/Financial Officer
Phone: (973) 423-0364
Research Institution
 University of Chicago
 Andre Walker
 6030 S. Ellis Avenue
Room ED-114
Chicago, IL, 60637-
 (773) 702-3466
 Nonprofit college or university
Two-electron reduced-density-matrix (2-RDM) methods represent all of the electrons in any molecule or material with only two electrons by replacing the wave function by the 2-RDM as the basic variable for quantum many-electron theory. The 2-RDM methods, developed by David Mazziotti at The University of Chicago with support from the Army Research Office, have polynomial scaling with system size, allowing for the computation of strongly correlated molecules and materials that were previously inaccessible. They are capable of providing chemists, physicists, and materials scientists with the ability to predict and design novel molecules and materials with properties optimized for serving as power sources and energy storage and transfer media. We aim to transition previous 2-RDM method development into a user-friendly, parallel software platform RDMChem that can be utilized by a wide variety of scientists both within and outside of DoD for solving current problems in energy transport, storage, and release. The software RDMChem will be constructed upon three proven 2-RDM-based methods, developed by Professor Mazziotti and his research group, through a partnership between RDMChem LLC and The University of Chicago. It will include fast algorithms for large-scale semidefinite programming (SDP) with significant additional applications to medical and military imaging.

* Information listed above is at the time of submission. *

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