Effect of Metamaterial Perfect Absorber on Device Performance of PCPDTBT:PC₇₁BM Solar Cell

Abstract

Light absorption and device performance of organic solar cells with metamaterial perfect absorbers are examined, and their correlation is elucidated. The solar cells exhibit enhanced light absorption as well as device performance in the longer wavelength range. In the shorter wavelength range, the absorption is increased; however, the device performance is deteriorated. Precise nanofabrication and numerical calculations reveal the correlation between the improved light absorption and the device performance, which can be explained by the positions of the field localizations. In the longer wavelength range, the metamaterial perfect absorber confines light into the active layer, whereas in the shorter wavelength range, the field is localized outside the active layer.

Synthesis and Photovoltaics of Novel 2,3,4,5-Tetrathienylthiophene-co-poly(3-hexylthiophene-2,5-diyl) Donor Polymer for Organic Solar Cell

“…Polythiophenes based polymers are mostly used as the electron donor materials for OSCs because of their properties such as thermally stable, environmentally friendly, easy to process and less expensive [14,15]. These polythiophenes based polymers are widely reported [14][15][16][17]. Katsumata et al [16] reported OSCs with maximum PCE of 2.03% using poly[2,6-(4,4-bis-(2-ethylhexyl)-4H-cyclopenta[2,1-b;3,4b']dithiophene)-alt-4,7(2,1,3-benzothiadiazole)] (PCPDTBT) as organic donor material.…”

“…These polythiophenes based polymers are widely reported [14][15][16][17]. Katsumata et al [16] reported OSCs with maximum PCE of 2.03% using poly[2,6-(4,4-bis-(2-ethylhexyl)-4H-cyclopenta[2,1-b;3,4b']dithiophene)-alt-4,7(2,1,3-benzothiadiazole)] (PCPDTBT) as organic donor material. Kesters et al [17] chemically modified PCPDTBT with 4,4-dialkyl-4H-cyclopenta [2,1-b;3,4b ]dithiophene derivative with ester and alcohol moieties to achieve PCE of 2.02% and 1.82% respectively.…”

Optimizing broadband metamaterial absorber using deep reinforcement learning

“…We focus on thermal radiation absorption, as the optimized metamaterial absorber is targeted at metamaterial thermoelectric conversion, which converts thermal energy gathered from the surrounding environment into electricity. [31][32][33] To the best of our knowledge, this is the first report to utilize deep reinforcement learning for the optimization of metamaterial structures designed to absorb thermal radiation. We simulated the device performance of metamaterial thermoelectric conversion loaded with a metamaterial absorber optimized using deep reinforcement learning and discussed the usefulness of deep reinforcement learning by comparing device performance with that of a device loaded with a conventional metamaterial absorber.…”