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We demonstrate single-walled carbon nanotube (SWCNT)/P3HT polymer bulk heterojunction solar cells with an AM1.5 efficiency of 0.72%, significantly higher than previously reported (0.05%). A key step in achieving high efficiency is the utilization of semiconducting SWCNTs coated with an ordered P3HT layer to enhance the charge separation and transport in the device active layer. Electrical characteristics of devices with SWCNT concentrations up to 40 wt % were measured and are shown to be strongly dependent on the SWCNT loading. A maximum open circuit voltage was measured for SWCNT concentration of 3 wt % with a value of 1.04 V, higher than expected based on the interface band alignment. Modeling of the open-circuit voltage suggests that despite the large carrier mobility in SWCNTs device power conversion efficiency is governed by carrier recombination. Optical characterization shows that only SWCNT with diameter of 1.3–1.4 nm can contribute to the photocurrent with internal quantum efficiency up to 26%. Our results advance the fundamental understanding and improve the design of efficient polymer/SWCNTs solar cells. [ABSTRACT FROM AUTHOR]

In this work we present a low cost and scalable technique, via ambient pressure chemical vapor deposition (CVD) on polycrystalline Ni films, to fabricate large area (∼cm2) films of single- to few-layer graphene and to transfer the films to nonspecific substrates. These films consist of regions of 1 to ∼12 graphene layers. Single- or bilayer regions can be up to 20 μm in lateral size. The films are continuous over the entire area and can be patterned lithographically or by prepatterning the underlying Ni film. The transparency, conductivity, and ambipolar transfer characteristics of the films suggest their potential as another materials candidate for electronics and opto-electronic applications. [ABSTRACT FROM AUTHOR]

A parallel deterministic global optimization algorithm for thin-film multilayer optical coatings is developed. This algorithm enables locating a global solution to an optimization problem in this class to within a user-specified tolerance. More specifically, the algorithm is a parallel branch-and-bound method with applicable bounds on the merit function computed using Taylor models. This study is the first one, to the best of our knowledge, to attempt guaranteed global optimization of this important class of problems, thereby providing an overview and an assessment of the current state of such techniques in this domain. As a proof of concept on a small scale, the method is illustrated numerically and experimentally in the context of antireflection coatings for silicon solar cells—we design and fabricate a three-layer dielectric stack on silicon that exhibits an average reflectance of (2.53 ± 0.10)%, weighted over a broad range of incident angles and the solar spectrum. The practicality of our approach is assessed by comparing its computational cost relative to traditional stochastic global optimization techniques which provide no guarantees on their solutions. While our method is observed to be significantly more computationally expensive, we demonstrate via our proof of concept that it is already feasible to optimize sufficiently simple practical problems at a reasonable cost, given the current accessibility of cloud computing resources. Ongoing advances in distributed computing are likely to bring more design problems within the reach of deterministic global optimization methods, yielding rigorous guaranteed solutions in the presence of practical manufacturing constraints. [ABSTRACT FROM AUTHOR]