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An
online tool called "Impurities to Efficiency" (known as I2E) allows companies
or researchers exploring alternative manufacturing strategies to plug in
descriptions of their planned materials and processing steps. |
|
To
make a silicon solar cell, you start with a slice of highly purified silicon
crystal, and then process it through several stages involving gradual heating
and cooling. But figuring out the tradeoffs involved in selecting the purity
level of the starting silicon wafer—and then exactly how much to heat it, how
fast, for how long, and so on through each of several steps—has largely been a
matter of trial and error, guided by intuition and experience.
Now,
Massachusetts Institute of Technology (MIT) researchers think they have found a
better way.
An
online tool called "Impurities to Efficiency" (known as I2E) allows companies
or researchers exploring alternative manufacturing strategies to plug in
descriptions of their planned materials and processing steps. After about one
minute of simulation, I2E gives an indication of exactly how efficient the
resulting solar cell would be in converting sunlight to electricity.
One
crucial 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% 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, something that is both hard to predict and hard to
measure.
Graduate
student David Fenning, part of the MIT team behind I2E, compares the effect of
iron atoms on the flow of electrons in a solar cell to a group of protesters in
a city: If they gather together in one intersection, they may block traffic at
that point, but cars can still find ways around and there is little disruption. "But if there's one person in the middle of every intersection, the whole city
could shut down," he says, even though it's the same number of people.
A
team led by assistant professor of mechanical engineering Tonio Buonassisi,
including Fenning, fellow graduate student 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.
Free
of charge, the I2E Website has been online since July, and users have already
carried out approximately 2,000 simulations. The details of how the system
works and examples of industrial impact will be reported soon in a paper in Photovoltaics
International.
Already,
Powell says, I2E has been used by "research centers from around the world."
By
using the tool, a company called Varian Semiconductor Equipment Associates
(recently acquired by Applied Materials), which makes equipment for producing
solar cells, was able to fine-tune one of the furnaces they sell. The changes
enabled the equipment to produce silicon wafers for solar cells five times
faster than it originally did, even while slightly improving the overall efficiency
of the resulting cells.
The
company "started with a process that was fairly long," Buonassisi says. They
initially found a way to speed it up, but with too much of a sacrifice in
performance. Ultimately, he says, using I2E, "we came up with a process that
was about five times faster than the original, while performing just as well."
Without
the tool, there are simply too many possible variations to test, so people end
up selecting the best from a small number of choices. But with I2E, Buonassisi
says, "you can look for the global optimum"—that is, the best possible solution
for a given set of requirements. "We can really speed up the innovation
process," he says.
Russel
Low, who was a manager at Varian while they were collaborating with MIT on the
project but has no connection with the team, says "I would consider the
work being carried out at MIT to be leading edge—combining computation physics
with high-resolution experimentation. Given that silicon is still the major
cost component of producing a solar cell, any technique that is capable of
making use of lower quality silicon starting materials (i.e. cheaper materials)
... is a significant achievement."
Fenning
says that companies generally "can't afford to do these large experiments"
needed to figure out the best process for a given application. The physics of
what goes on inside the wafer during the processing is complex, he says: "There
are a number of competing mechanisms that cloud the picture of exactly what is
going on," which is why developing the simulation was a long and complex
process.
Now that the simulation tool is available, Fenning says, it helps
manufacturers balance product quality against production time. Because there
are so many variations in the supplies of starting material, he says, "it's a
constantly evolving problem. That’s what makes it interesting."
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