Y
Yi Cui
Researcher at Stanford University
Publications - 1109
Citations - 245406
Yi Cui is an academic researcher from Stanford University. The author has contributed to research in topics: Anode & Lithium. The author has an hindex of 220, co-authored 1015 publications receiving 199725 citations. Previous affiliations of Yi Cui include KAIST & University of California, Berkeley.
Papers
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Robustness of amorphous silicon during the initial lithiation/delithiation cycle
TL;DR: In this article, the authors studied the fracture resistance of amorphous silicon micropillars (∼2.3mm tall) after electrochemical lithiation and delithiation.
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Nanoporous silicon networks as anodes for lithium ion batteries
TL;DR: Nanoporous silicon (Si) networks with controllable porosity and thickness are fabricated by a simple and scalable electrochemical process, and then released from Si wafers and transferred to flexible and conductive substrates to serve as high performance Li-ion battery electrodes.
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Functionalization of silicon nanowire surfaces with metal-organic frameworks
TL;DR: In this article, a polycrystalline metal-organic framework (MOF) was synthesized on surface modified silicon nanowires (SiNWs) by matching of the SiNW surface functional groups with the MOF organic linker coordinating groups.
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Microscopic model for fracture of crystalline Si nanopillars during lithiation
TL;DR: In this article, a microscopic model is presented to describe the size-dependent fracture of crystalline Si nanopillars (NPs) during lithiation, where the initial size and spacing of the nanovoids, together with the computed facture toughness, are chosen to conform to recent experiments which showed the critical diameter of Si NPs to be 300-400nm.
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Patch Ordering-Based SAR Image Despeckling Via Transform-Domain Filtering
TL;DR: Experimental results with both simulated images and real SAR images demonstrate that the proposed method achieves state-of-the-art despeckling performance in terms of peak signal-to-noise ratio (PSNR), structural similarity (SSIM) index, equivalent number of looks (ENLs), and ratio image.