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New technology can significantly improve the efficiency of solar cells

Category:Industry dynamic  Date:2013-12-05  Views:1819   [back]
China science and technology network news according to physicist organization network recently reported, Canadian scientists have developed a new technique can significantly improve the solar cell efficiency, the technology can improve solar energy conversion efficiency of 35% in the near infrared spectral region, the overall conversion efficiency (full spectrum) the increase of 11%, so that the quantum dots become excellent candidates to replace the existing photovoltaic solar cell technology. Related papers published in the latest issue of nano letters "on".
Photovoltaic quantum dots can provide large area solar power, low cost, but the device in the solar spectrum infrared efficiency is not high, and the infrared occupy half of the solar energy reaching the earth. Canada University of Toronto engineering professor Ted Sargent and his team put forward, through the plasma nanoparticle solution, absorption spectrum tuning, the propagation of light and can provide the ability to control the hitherto unknown.
Colloidal quantum dots has two major advantages. The first is more cheap, because they reduce the cost per watt of power generation, but the main advantage is that, simply by changing the size of the quantum dots, you can change the absorption spectrum. Size can be easily changed and tunable properties of plasma material: by changing the plasma particle size, researchers will be able to absorption and scattering spectra of these two important nanoparticle overlap.
The Sargent team through the gold nanoshell directly embedded QDs absorption film improves the efficiency of solar cells, they are the next step would be to find the cheaper metal to achieve the same goal. California University America nanosystems institute director Paul Weiss think, the importance of the study is to show by adjusting the characteristics of nanoparticles in order to improve the efficiency of the solar cell potential. Feng Weidong.