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Multi-scale framework for the accelerated design of high-efficiency organic photovoltaic cells

Multi-scale framework for the accelerated design of high-efficiency organic photovoltaic cells . Ismael Dondasse. Mentor: Dr. Baskar Ganapathysubramanian Post-doc mentor: Dr. Olga Wodo. Introduction .

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Multi-scale framework for the accelerated design of high-efficiency organic photovoltaic cells

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  1. Multi-scale framework for the accelerated design of high-efficiency organic photovoltaic cells IsmaelDondasse Mentor: Dr. BaskarGanapathysubramanian Post-doc mentor: Dr. Olga Wodo

  2. Introduction Alternatives energy such as solar energy and wind energy are in the rise to supplement, see replace fossil fuel energy. Inorganic solar cells have been the most used. But, organic solar cells are right the stars in the solar energy research. However, organic solar cells have a low power conversion efficiency (about 5%).

  3. background • Organic solar cells are mostly made of an bulk-heterojunction of polymer and fullerene. • Low power conversion. • Importance of morphology.

  4. Background • Absorption of light and generation of excitons . • Diffusion of the excitons • Dissociation of the excitons with generation of charge • Charge transport and charge collection

  5. Motivations and objectives Motivation Objectives Automation of shape recognition in 2D and 3D • Improvement of organic solar cells efficiency • Acceleration of the design process

  6. Approach • Isoperimetric problem in 2D: for a given area, find the shortest length that can enclose the area. • Solution: circle • Isoperimetric problem in 3D: for a given volume, find the minimum surface area that can enclosed the volume. • Solution: sphere, cylinder, plane, Lawson’s and Schwartz’s surfaces. • The understanding of isoperimetric problem is a key to the study of phase space in the solar cell.

  7. A quarter of a cylinder whose axis is one of the edges of R An octant of a sphere centered at one vertex of R • A piece of a plane parallel to some of the faces of R

  8. Approach Many tests were run on the framework for different values of ɸ (0.2 to 1 with a step of 0.8). From the results of the tests, 2 shapes were observed: a stripe and a circle.

  9. Methods to automate • All pictures in a folder. • Use of Matlab. • Loop the folder and treat each image. for a=1:numel(pngfiles) source= pngfiles(a).name; I=imread(pngfiles(a).name);

  10. Make image black and white. • Graph only the phase space. • Make a curve fit to obtain an equation. • Derive the curvature. • Compare the curvature to a treshold.

  11. syms t; n=p(1)*t.^2+p(2)*t+p(3); m=diff(n,2); r=double(m); if (abs(r)>1e-6) b=1; else b=2; end

  12. Planned work • Tests with the framework in 3D. • Automatic recognition in 3D.

  13. END

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