ERC Researchers Develop Reactor to Rapidly Produce Material Used in High-Efficiency Solar Cells

Achievement date: 

University of Delaware researchers affiliated with the NSF-funded Engineering Research Center (ERC) for Quantum Energy and Sustainable Solar Technologies (QESST), which is headquartered at Arizona State University, have designed, constructed, and deployed a research-scale reactor for the rapid production of copper indium gallium diselenide (CIGS). CIGS is used in high-efficiency, simple, thin-film solar cells.


The rapid thermal processing reactor developed in this work (see accompanying figure) can substantially reduce the time to produce CIGS-based solar cells. Further, the reactor will be used to develop swifter film-forming processes that can be transferred to lower-cost manufacturing. Reduced manufacturing costs and improved solar-cell performance will lower the cost of solar electricity.


CIGS use in solar cells has already been commercialized by several companies, but CIGS thin films are commonly manufactured by the selenization process for which a fundamental understanding has never been fully developed. Solar-cell efficiency depends on micro-scale properties of the CIGS, so enhanced understanding of film formation enables better control of film properties and production of higher-efficiency devices.

The key technical challenges that had to be addressed were understanding the heat-transfer processes and designing a control system to regulate temperature. Computer models were developed to describe heat transfer in the reactor, including conduction, convection, and radiation. The modeling efforts assisted in selection of quartz-halogen lamps to supply heat rapidly to the reactor. Although temperature control is important in nearly any process, it becomes especially challenging in a system with rapid heating and high temperatures. A pyrometer is used for temperature measurement in the system to provide feedback to control the heat lamp. Finally the control system is designed based on fundamental temperature models that are supplemented by experimental data.