Although a strong link between the molar mass of conjugated polymers and the performance of the resulting polymer:fullerene bulk heterojunction organic solar cells has been established on numerous occasions, a clear understanding of the origin of this connection is still lacking. Moreover, the usual description of molar mass and polydispersity does not include the shape of the polymer distribution, although this can have a significant effect on the device properties. In this work, the effect of molar mass distribution on photovoltaic performance is investigated using a combination of structural and electro-optical techniques for the state-of-the-art low bandgap copolymer PTB7. Some of the studied commercial PTB7 batches exhibit a bimodal distribution, of which the low molar mass fraction contains multiple homocoupled oligomer species, as identified by MALDI-TOF analysis. This combination of low molar mass and homocoupling drastically reduces device performance, from 7.0 to 2.7%. High molar mass batches show improved charge carrier transport and extraction with much lower apparent recombination orders, as well as a more homogeneous surface morphology. These results emphasize the important effect of molar mass distributions and homocoupling defects on the operation of conjugated polymers in photovoltaic devices.

We propose photonic reservoir computing as a new approach to optical signal processing in the context of large scale pattern recognition problems. Photonic reservoir computing is a photonic implementation of the recently proposed reservoir computing concept, where the dynamics of a network of nonlinear elements are exploited to perform general signal processing tasks. In our proposed photonic implementation, we employ a network of coupled Semiconductor Optical Amplifiers (SOA) as the basic building blocks for the reservoir. Although they differ in many key respects from traditional software-based hyperbolic tangent reservoirs, we show using simulations that such a photonic reservoir can outperform traditional reservoirs on a benchmark classification task. Moreover, a photonic implementation offers the promise of massively parallel information processing with low power and high speed.

No abstract

Graphene has potential for applications in solar cells. We show that the short circuit current density of P3HT (Poly(3-hexylthiophene-2,5-diyl):PCBM((6,6)-Phenyl C61 butyric acid methyl ester) solar cells is enhanced by 10% upon the addition of graphene, with a 15% increase in the photon to electric conversion efficiency. We discuss the performance enhancement by studying the crystallization of P3HT, as well as the electrical transport properties. We show that graphene improves the balance between electron and hole mobilities with respect to a standard P3HT:PCBM solar cell.