Flexible silicon solar cells with high power-to-weight ratios.

Silicon solar cells are a mainstay of commercialized photovoltaics, and further improving the power conversion efficiency of large-area and flexible cells remains an important research objective1,2. Here we report a combined approach to improving the power conversion efficiency of silicon heterojunction solar cells, while at the same time rendering them flexible. We use low-damage continuous-plasma chemical vapour deposition to prevent epitaxy, self-restoring nanocrystalline sowing and vertical growth to develop doped contacts, and contact-free laser transfer printing to deposit low-shading grid lines. High-performance cells of various thicknesses (55-130 µm) are fabricated, with certified efficiencies of 26.06% (57 µm), 26.19% (74 µm), 26.50% (84 µm), 26.56% (106 µm) and 26.81% (125 µm). The wafer thinning not only lowers the weight and cost, but also facilitates the charge migration and separation. It is found that the 57-µm flexible and thin solar cell shows the highest power-to-weight ratio (1.9 W g-1) and open-circuit voltage (761 mV) compared to the thick ones. All of the solar cells characterized have an area of 274.4 cm2, and the cell components ensure reliability in potential-induced degradation and light-induced degradation ageing tests. This technological progress provides a practical basis for the commercialization of flexible, lightweight, low-cost and highly efficient solar cells, and the ability to bend or roll up crystalline silicon solar cells for travel is anticipated.

GPU-accelerated image registration algorithm in ophthalmic optical coherence tomography.

Limited to the power of the light source in ophthalmic optical coherence tomography (OCT), the signal-to-noise ratio (SNR) of the reconstructed images is usually lower than OCT used in other fields. As a result, improvement of the SNR is required. The traditional method is averaging several images at the same lateral position. However, the image registration average costs too much time, which limits its real-time imaging application. In response to this problem, graphics processing unit (GPU)-side kernel functions are applied to accelerate the reconstruction of the OCT signals in this paper. The SNR of the images reconstructed from different numbers of A-scans and B-scans were compared. The results demonstrated that: 1) There is no need to realize the axial registration with every A-scan. The number of the A-scans used to realize axial registration is suitable to set as ∼25, when the A-line speed was set as ∼12.5kHz. 2) On the basis of ensuring the quality of the reconstructed images, the GPU can achieve 43× speedup compared with CPU.