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Although its name conjurs connections with the dinosaur realm, fallen Roman (or Romulan) Empire heroes, or fabled half-human/half-horse creatures, Synopsys' Sentaurus has more in common with virtual reality than paleontology, ancient history, or Greek mythology. The system's "simulation environment," what the company's Ric Borges calls "the cockpit," funnels the company's TCAD tools (leveraged from years of experience and Giga-reams of data and code developed for the semiconductor industry) into one platform to model silicon and nonsilicon-based wafer and thin-film solar-cell process and device technologies.

"People have used TCAD (technology computer-aided design) for solar-cell development for awhile," Borges (who's no relation to the [in]famous labyrinthine Argentine writer, the late Jorge Luis Borges) told me during Intersolar North America/Semicon West week, "but now it's become much more active." And not just for modeling the active areas of the cells.

The system's ability to accurately model and learn more about the physics of cell operations, improve process recipes and optimize conversion efficiencies, and explore new cell designs appeals to a growing number of photovoltaic researchers and device designers.

Users of the software include teams at the US National Renewable Energy Laboratory, Germany's Fraunhofer Institute for Solar Energy Systems ISE in Freiburg, and other renowned institutions, according to the Synopsys senior product marketing manager. Dozens of papers have been published from the various research collaborations using the TCAD tool. Sentaurus also roams the virtual halls of at least three c-Si solar-cell companies and three compound semi (III-V and thin film) manufacturers, he said, with many more interested in the "virtual solar-cell" package.

For c-Si applications, Sentaurus can perform a variety of numerical simulations on the process itself, Borges explained. By inputting data and tweaking the parameters from process recipes (including specifics from diffusion, oxidation, implantation, deposition, and etch steps), geometries, and optical and electrical information, the tool can create accurate process, optical, and device models that point to ways to extend cell lifetimes and enhance cell efficiencies.

Borges described a study where gettering was simulated, and a link was established between optimization of that process (in this case, the dependency of the gettering time on external quantum efficiency) and improved cell performance. The impact of surface texturing on increased photon collection has been modeled using 2- and 3-D geometric "meshing engines." "Optical generation models" have been run across the spectrum to evaluate interference effects of different antireflective coatings.

In the area of device simulation, he explained how Sentarus can run a 2-D cell optimization. Using this approach, one selects the parameters to be investigated (front and back contact characteristics, substrate thickness, doping concentrations, recombination velocities, etc.), "parameterizes" (which I pointed out to Ric is not really a word...yet) the TCAD model, runs a host of simulations, and then "visualizes" (which is a word) the influence or impact of each of those process-variable parameters, displaying a variety of coordinate and scatter plots, IV and efficiency curves, and tabular data.

In an example that Borges showed, the range of screened parameter settings included a mean substrate thickness of 250 microns with a minimum/maximum variation of +/-50 microns, a mean back-contact width of 2.5 microns with a min/max of +/- 0.5 microns, a mean front-surface recombination velocity of 1800 cm/second with a minimum variation of 900 cm/sec and a maximum of 3600 cm/sec, and about several other parameters.

Another simulation cited how bulk doping, lifetime, and front-surface recombination all had a significant influence on cell response, while yet another "visualization" showed how the use of a process window with a "response surface model" revealed that efficiency and open circuit voltages were a function of bulk doping and substrate thickness.

"You can vary the parameters, see how to optimize them, as well as [determining] the areas that don't need to be optimized, then [establish] the proper process window and optimize the design," Borges said.

Sentaurus can also be used to optimize existing designs or validate novel ones for amorphous- and micromorph-silicon, III-V, CIGS, and CdTe PV applications. Borges admitted that because the modeling of these non-c-Si cells is tougher, with more material defects, dislocations, and the like to deal with, the focus has been more on the physics than the process, such as simulating--and tweaking--the epitaxial structures of high-efficiency multijunction devices. (Note that the company has a Webcast on thin-film solar-cell simulation coming up Aug. 20-21.)

Synopsys may be extending its reach deeper into the photovoltaic manufacturing ecosystem, according to Borges. The company's Saber "mechatronic" modeling tools for automotive and other industrial applications "could be used at the module level with something brought up and leveraged from solar-cell TCAD." The list of optimization possibilities includes improvements to overall solar power system efficiencies (including inverters) as well as reducing string-cell "weakness" and minimizing the "shade effect" of panel arrays.

Despite the challenges of educating the industry and the research community to the value of TCAD, training people in its use, and building the support infrastructure, "so far, the people who have adopted it, really like it," said Borges. The company has focused teams working on solar-cell TCAD and its applications in each of the main regions, including several PhD-level specialists.

With the push to properly implement best practices and further innovate and significantly reduce costs, not just in the device architecture and fabrication area but along the entire PV value chain--from raw material feedstock to grid integration--comprehensive simulation tools like Sentaurus can play an increasingly vital role in the solar optimization surge.