Researchers Mimic Evolution to Boost Solar Cell Efficiency
January 28, 2013 12:00 PM
Genetic algorithm discovered unusual pattern was best at trapping light
A common problem in the design of
thin film solar cells
is how to develop optical materials and nanopatterns for those materials. The ultimate goal is to trap and capture as much solar energy as possible. The problem is far too challenging for naive searches based solely on human creativity. Thus artificial intelligence is increasingly being employed to search for the optimal cell materials and nanopatterns.
Professor Wei Chen
and her graduate student Cheng Sun have published a new paper on how
-- an artificial intelligence technique based on evolutionary biology -- can be used to develop high performance nano-patterns.
Much like evolution and genetic processes serve in the real world serve to select creatures giving rise to fit species
, genetic algorithms weed out bad candidates, while preserving and mixing elements of the fittest performers.
Starting with dozens of random designs, Prof. Chen's team "bred" the nanopatterns through 20 generations, employing genetic algorithm techniques like mutation and crossover.
The result was a strike nanopattern that outperformed other designs.
The "fittest" pattern [Image Source: Northwestern University]
The optimized 100-nanometer-thick organic dielectric "scattering layer" appears superb in simulations at trapping photons and transmitting them into the active layer. In fact, the simulation results predict that the layer will surpass three-fold the Yablonovitch Limit; a thermodynamic limit developed in the 1980s that statistically describes how long a photon can be trapped in a semiconductor.
Current organic solar cells
have traditional been, in a word, bad. While relatively cheap to produce compared to their rare-metal thin film counterparts, their low efficiencies make them a disappointing dead end. But the new design is intriguing as it may boost organic thin film cells into a regime in which they would actually be cost effective -- perhaps more so than rare-metal designs.
Comments Prof. Chen, "Due to the highly nonlinear and irregular behavior of the system, you must use an intelligent approach to find the optimal solution. Our approach is based on the biologically evolutionary process of survival of the fittest."
Northwestern Univ. is currently working with
Argonne National Laboratory
to produce a prototype of the nanopatterned cell, for real world testing.
In the mean time, the work has been
in the peer-reviewed journal
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