A major factor in determining solar cell efficiency is the size and distribution of iron particles within the silicon - even though the silicon used in solar cells has been purified to the 99.9999 percent level, the tiny remaining amount of iron forms obstacles that can block the flow of electrons. But it’s not just the overall amount that matters; it’s the exact distribution and size of the iron particles, which is hard to predict and measure.
A team led by assistant professor of mechanical engineering Tonio Buonassisi, graduate students David Fenning and Douglas Powell, and collaborators from the Solar Energy Institute at Spain's Technical University of Madrid, found a way to use basic physics and a detailed computer simulation to predict exactly how iron atoms and particles will behave during the wafer-manufacturing process. They then used a highly specialized measurement tool — an X-ray beam from a synchrotron at Argonne National Laboratory — to confirm their simulations by revealing the actual distribution of the particles in the wafers.
“High-temperature processing redistributes the metals,” Buonassisi explains. Using that sophisticated equipment, the team took measurements of the distribution of iron in the wafer, both initially and again after processing, and compared that with the predictions from their computer simulation.
Already, Powell says, I2E has been used by “research centers from around the world.”
Watch a video on I2E below.
Transcript
00:00:00 Hi I'm Dr. Jasmine Hofstetter. I'm a member of the MIT PV Lab. And I'm working on improving silicon materials to make solar energy more cost effective. Defects in the silicon wafer, including iron impurities, as represented by the red dots in this sketch, have the potential to reduce solar cell efficiency. However, it is possible to engineer the distribution and concentration of defects during solar cell processing
00:00:28 to reduce the negative impact. Together with colleagues from MIT's PV Lab and from the Polytechnical University of Madrid, where I did my PhD, we have created a predictive simulation tool-- the Impurity to Efficiency Simulator, or I2E for short. I2E helps us to identify the optimal way to process our solar cells. Predictions from the I2E model have been validated by comparison to experimental data.
00:00:52 The inputs to I2E are the initial iron concentration and distribution, the time temperature profile you want to test, and the architecture of your solar cell. I2E outputs the characteristics of a simulated solar cell, including the final phosphorus emitter profile, iron distribution, charge carrier lifetimes, and device efficiency. The I2E simulation tool enables easy and fast process design to increase solar cell efficiency,
00:01:17 even on low-cost silicon materials. We are already significantly reducing costs and increasing throughput of solar cells in collaboration with industrial partners. The I2E simulator is freely accessible online from our group's website. Please visit us online at pv.mit.edu and thank you for watching.
