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Fully Automated Quantum Cascade Laser Design Aided by Machine Learning
Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68936-20-C-0082
Agency Tracking Number: N20A-T003-0001
Amount:
$139,902.00
Phase:
Phase I
Program:
STTR
Solicitation Topic Code:
N20A-T003
Solicitation Number:
20.A
Timeline
Solicitation Year:
2020
Award Year:
2020
Award Start Date (Proposal Award Date):
2020-06-24
Award End Date (Contract End Date):
2020-12-28
Small Business Information
30 Spinelli Place Suite 101
Cambridge, MA
02138-1111
United States
DUNS:
969569131
HUBZone Owned:
No
Woman Owned:
No
Socially and Economically Disadvantaged:
No
Principal Investigator
Name: Christian Pfluegl
Phone: (857) 413-9339
Email: pfluegl@pendar.tech
Phone: (857) 413-9339
Email: pfluegl@pendar.tech
Business Contact
Name: Seamus Fogarty
Phone: (617) 909-5726
Email: sfogarty@pendar.com
Phone: (617) 909-5726
Email: sfogarty@pendar.com
Research Institution
Name: Texas A&M Engineering Experiment Station
Contact: Yong-Joe Kim
Address:
Phone: (979) 845-9779
Type: Nonprofit College or University
Contact: Yong-Joe Kim
Address:
7607 Eastmark Drive
College Station, TX
77840-4027
United States
Phone: (979) 845-9779
Type: Nonprofit College or University
Abstract
Pendar Technologies proposes to develop a QCL simulation tools that leverage machine learning to dramatically improve the speed of QCL device design. The innovative QCL design suite proposed will benefit from recent advances made by Pendar in bandstructure engineering, laser cavity design and thermal management at the chip and the package level.
* Information listed above is at the time of submission. *
