MIT and Google together to develop new solar cells

In the race to develop ever-better materials and configurations for solar cells, there are many variables that can be adjusted to try and improve performance, including material type, thickness, and geometric arrangement. The development of new solar cells has generally been a process of making small changes to one of these parameters at a time. Computational simulators have made it possible to evaluate such changes without actually having to build each new variation for the test, but the process remains slow.

Now, researchers from MIT and Google Brain have developed a system that allows not only to evaluate one proposed project at a time, but to provide information on which changes will provide the desired improvements. This could greatly increase the speed for identifying new improved configurations.

Traditional solar cell simulators take the details of a solar cell configuration and output an expected efficiency, i.e. as a percentage of the energy from incoming sunlight is actually converted into an electric current. But this new simulator predicts efficiency and shows how much the output is affected by any of the input parameters.

Furthermore, as explained by the team, “our tool can identify a unique set of material parameters that have been neglected so far because it is very complex to perform that type of simulation”. While traditional approaches essentially use a random search for possible variations, the research team argues that, with their tool, it is possible to “follow a trajectory of change because the simulator tells you in which direction you are changing your device. This makes the process much faster because instead of exploring the entire space of opportunity, you can simply follow a single path "which leads directly to better performance.



Since advanced solar cells are often composed of multiple layers intertwined with conductive materials to carry electrical 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. 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 the insulating layers, or the bandgap, a measure of the energy levels of the 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. The simulator is based only on a one-dimensional version of the solar cell, so the next step will be to expand its capabilities to include two-dimensional and three-dimensional configurations. But Romano explained that even this 1D version “can cover most of the cells that are currently in production”. Some variants, such as so-called tandem cells that use different materials, cannot yet be simulated directly by this instrument, but according to the researchers there are ways to approximate a tandem solar cell by simulating each of the individual cells.