To create a solar cell that can make the most of every inch of sunlight, researchers rely on computer modeling tools that allow researchers to assess the impact of subtle adjustments to parameters such as device structure, material use and thickness of different material layers on the final power output.
Some solar cell simulators are now available for free. But these tools are still slow and do not allow researchers to optimize different design parameters simultaneously. A team of researchers from MIT and Google Brain has developed new software that simplifies the improvement and discovery of solar cells.
Conventional calculation tools take the variables of a particular solar cell design as inputs and then output the final power rating.
But with the help of the new software, "we can not only provide output data, but also show the effect of any change in input parameters on efficiency." "You can keep changing the input parameters and see the gradient of the output data as it changes," said Giuseppe Romano, a research scientist at MIT's Soldier Nanotechnology Institute.
This reduces the number of times developers have to run these time-consuming and computationally intensive simulations. "You just run a simulation and automatically get all the information you need," he says. That's the beauty of this approach."
The photoelectric efficiency of commercial solar cells lags behind the theoretical maximum of the device. Solar cell simulators allow researchers to understand how physical factors such as material defects affect the ultimate performance of solar cells. Simulators have helped improve common photovoltaic technologies such as cadmium-based thin film cells and perovskite cells.
The new tool could help the development of solar cells in two ways. The first is optimisation, says Giuseppe Romano: "Let's say someone in the industry wants to make a high-performance solar cell but doesn't know the impact of light-absorbing materials on overall efficiency." This material layer usually has an optimal thickness and can use the absorbed light to produce the most carriers. The software will help determine the best parameters to maximize efficiency.
The software can also be used to evaluate optimal values for other variables, such as the amount of doping in the material layer, the band gap, or the dielectric constant of the insulating layer.
Another function of the tool is to reverse engineer existing solar cells. In this case, researchers can measure the solar cell's I-V curve (a function of voltage and current) and pair these experimental measurements using simulators.
From this data, the software can help calculate unknown values for specific material parameters.
Romano said that similar solar cell simulators may have been developed, but "this is the first open source simulator that can simulate such nuances." The package has been posted on GitHub and can be used and improved by anyone, he said.
Developers can apply their own optimization algorithms or machine learning systems to the simulator. Accelerate the development of more efficient solar cells by rapidly evaluating a wide range of materials and device structures.