Chenxi Lin

TL;DR: The transfer matrix method is used to calculate the optical absorptance of vertically-aligned silicon nanowire (SiNW) arrays and shows that an optimized SiNW array with lattice constant of 600 nm and wire diameter of 540 nm has a 72% higher ultimate efficiency than a Si thin film of equal thickness.

TL;DR: In this article, the authors use electromagnetic simulations to carry out a systematic study of broadband absorption in vertically-aligned semiconductor nanowire arrays for photovoltaic applications, and show that the ultimate efficiencies of optimized arrays exceed those of equal-height thin films for all six materials and over a wide range of heights.

TL;DR: A deep convolutional neural network that targets representative feature learning in lithography hotspot detection and achieves comparable or better performance on the ICCAD 2012 contest benchmark compared to state-of-the-art hotspot detectors based on deep or representative machine leaning.

TL;DR: A partially aperiodic, vertically-aligned silicon nanowire array that maximizes photovoltaic absorption is designed using a random walk algorithm with transfer matrix method based electromagnetic forward solver and it is found that randomly-selected, a periodic structures invariably outperform the periodic array.

TL;DR: Combining nanosphere lithography (NSL) and selected area metal-organic chemical vapor deposition (SA-MOCVD) for the first time for scalable synthesis of vertically aligned gallium arsenide nanowire arrays is reported, and it is shown that such nanowires arrays with patterning defects due to NSL can be as good as highly ordered nanowir arrays in terms of optical absorption and reflection.