STTR PHASE I: In-situ Diagnostics and Process Control Based on Optical Emission Spectroscopy and Neural Networks for Manufacturing Thin Film Silicon Photovoltaic Materials

Award Information
Agency:
National Science Foundation
Branch
n/a
Amount:
$149,999.00
Award Year:
2008
Program:
STTR
Phase:
Phase I
Contract:
0740538
Agency Tracking Number:
0740538
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
Advanced Fuel Research, Inc.
87 Church Street, East Hartford, CT, 06108
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
021804661
Principal Investigator:
Joseph Cosgrove
BS
(860) 528-9806
cosgrove@afrinc.com
Business Contact:
Joseph Cosgrove
BS
(860) 528-9806
cosgrove@afrinc.com
Research Institution:
University of Delaware
Stuart Bowden
210 Hullihen Hall
Newark, DE, 19716 2553
(860) 528-9806
Nonprofit college or university
Abstract
The Small Business Technology Transfer Research (STTR) Phase I project will address the need for an advanced process control system for improved manufacturing of photovoltaic cells. Thin film silicon photovoltaic modules offer a potentially lower cost alternative to crystalline silicon modules through reduced materials utilization and lower processing temperatures if improvements in conversion efficiencies and/or lower production costs can be achieved. The objective of this program is to develop an intelligent sensor based on optical emission spectroscopy and artificial neural networks (ANNs), for process monitoring and control during manufacturing of thin film silicon solar cells. Phase I will demonstrate the sensor technology and develop the ANN model. The process control system resulting from this project will provide significant advantages in photovoltaic cell technology development and manufacturing, providing a competitive edge to U.S. manufacturers and helping to re-establish the previous U.S. global market dominance in photovoltaics. Worldwide, the benefits of solar power are numerous. Solar energy is non-polluting, producing no atmospheric emissions or greenhouse gases. It is an abundant, renewable source of energy and can be employed in remote areas of the world where other energy sources are inaccessible.

* information listed above is at the time of submission.

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