In-line LBIC

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-FG02-13ER90676
Agency Tracking Number: 76551
Amount: $225,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: 07b
Solicitation Number: DE-FOA-0000801
Timeline
Solicitation Year: 2013
Award Year: 2013
Award Start Date (Proposal Award Date): 2013-06-10
Award End Date (Contract End Date): N/A
Small Business Information
25 Old Homestead Rd, Westford, MA, 01886-2424
DUNS: 031064478
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Rob Janoch
 Dr.
 (508) 633-5413
 robjanoch@janochengineering.com
Business Contact
 Rob Janoch
Title: Mr.
Phone: (508) 633-5413
Email: robjanoch@janochengineering.com
Research Institution
 Stub
Abstract
Problem statement: For low cost manufacturing of high efficiency solar cells and solar modules, manufacturers are ever looking for effective tools to measure the problematic defects and performance variations in their critical processes. Approach to addressing the problem: The light, or laser, beam induced current (LBIC) technique has been used in the laboratory to produce detailed images of the opto-electronic performance of photovoltaic devices. These images locate defects, and with analysis of the signals, can provide measurements of properties such as diffusion length, shunt resistance, surface recombination, etc. An in-line instrument providing such measurements would be an extremely useful process control tool. We are proposing an In-line LBIC machine that would be capable of producing these types of process control measurements within solar cell and solar module manufacturing cycle times. By integrating four lasers into a compact optics head, and scanning it in discrete paths over a module or cell, a large number of well-distributed data points can be acquired. Analyzing and reducing these multiple wavelength data points into a few well-chosen figures of merit, in near real time, would provide the manufacturing line with essential measurements of process variability. Benefits: Near real-time measurements will reduce process variability and enable increased module efficiency and reduced manufacturing cost. In addition manufacturing lines will ramp up more quickly and R & amp;D can be more effective.

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

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