Solar energy sources are almost endless, but the cost of transforming them into electricity through Crystalline Silicon solar cells is extremely expensive, almost ten times the cost of coal power generation. Organic solar cells (polymer solar cells) are expected to become a solution. However, the electrical properties of polymers are not ideal, and the design of organic solar cells is still defective.
At present, researchers at Northwestern University in the United States are developing new designs for organic solar cells that can make solar power more efficient and less costly.
The researchers sought to design the geometric pattern of the scattering layer to maximize the amount of light stored in the cell and did not intend to achieve this by changing the thickness of the solar cell polymer layer.
Using mathematical search algorithms for natural evolution, researchers have precisely designed specific geometric models to capture sunlight and store it in thin organic solar cells.
This final design is three times more efficient than the thermodynamic limit Yablonovitch Limit developed in the 1980s.
In this type of new organic solar cell, the light first enters a 100 nm thick “scattering layer†(a geometrical pattern that can maximally transmit light to the cell's dielectric layer), which is then transported to the active layer where it is converted into electricity.
McCormick researchers design geometrically patterned light scattering layers to make solar cells more efficient and less expensive
Cheng Sun, co-author of the assistant professor of the Northwestern University's McCormick School of Engineering and Applied Science, said: "We need to determine the geometry of the scattering layer to ensure that it performs at its best."
“However, given the high likelihood, where to start is still tricky. Therefore, we seek natural selection rules to guide us.â€
Professor Wei Chen of the School of Engineering and Applied Science at McCormick explained: “The researchers chose genetic algorithms for R&D. This is a random search and optimization method based on natural selection and genetic mechanisms of biology.â€
Chen said: "Given the highly nonlinear and irregular behavior of the system, you must use an intelligent solution to find the best solution. Our research program is based on the survival of the fittest in the process of biological evolution."
The researchers started with dozens of random design elements, "paired" them, and then analyzed their "offspring" to determine the light trapping performance. This process will be over 20 generations.
This model will be manufactured by the partner Argonne National Laboratory. (Translator: Krystal)
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