MIT develops tool to speed development of solar cells

14 Dec 2021

Simulator helps predict if changes to materials and design will improve photovoltaic performance.

Developing new solar cells can been a tedious process involving making small changes to permutations of parameters such as material type, thickness, and geometric arrangement. While computational simulators have made it possible to evaluate such changes without having to actually build each new variation for testing, the process remains slow.

Now, researchers at MIT and Google Brain have developed a system that makes it possible not just to evaluate one proposed design at a time, but to provide information about which changes will provide the desired improvements. They say that this could significantly increase the rate of discovery of new, improved configurations.

The new system, called a differentiable solar cell simulator, is described in a paper published in Computer Physics Communications, authored by MIT junior Sean Mann, research scientist Giuseppe Romano of MIT’s Institute for Soldier Nanotechnologies, and four others at MIT and at Google Brain.

Efficiency and parameters

Romano explained that traditional solar cell simulators take the details of a solar cell configuration and produce as their output a predicted efficiency — that is, what percentage of the energy of incoming sunlight actually gets converted to an electric current. But this new simulator both predicts the efficiency and shows how much that output is affected by any one of the input parameters.

“It tells you directly what happens to the efficiency if we make this layer a little bit thicker, or what happens to the efficiency if we for example change the property of the material,” he said. “We have developed a tool that will enable others to discover more quickly other higher performance devices. We are decreasing the number of times that we need to run a simulator to give quicker access to a wider space of optimized structures.”

Mann added, “With this tool, we can follow a trajectory of change because the simulator tells you what direction you want to be changing your device. That makes the process much faster because instead of exploring the entire space of opportunities, the user can just follow a single path that leads directly to improved performance.”

Multiple layers

Since advanced solar cells often are composed of multiple layers interlaced with conductive materials to carry electric charge from one to the other, this computational tool reveals how changing the relative thicknesses of these different layers will affect the device’s output.

“This is very important because the thickness is critical. There is a strong interplay between light propagation and the thickness of each layer and the absorption of each layer,” said Mann.

Other variables that can be evaluated include the amount of doping (the introduction of atoms of another element) that each layer receives, or the dielectric constant of insulating layers, or the bandgap, a measure of the energy levels of photons of light that can be captured by different materials used in the layers. This simulator is now available as an open-source tool that can be used immediately to help guide research in this field, said Romano. “It is ready, and can be taken up by industry experts.”

At this point, the simulator is based on just a one-dimensional version of the solar cell, so the next step will be to expand its capabilities to include two- and three-dimensional configurations. But even the 1D version “can cover the majority of cells that are currently under production,” said Romano. Certain variations, such as so-called tandem cells using different materials, cannot yet be simulated directly by this tool, but “there are ways to approximate a tandem solar cell by simulating each of the individual cells,” said Mann.

Moving forward, said Romano, because this device runs on an open-source code, “so once it's up there, the community can contribute to it. And that's why we are really excited.” Thus anybody working in the field can make their own enhancements and improvements to the code and introduce new capabilities.