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James Hone

Researcher at Columbia University

Publications -  702
Citations -  128248

James Hone is an academic researcher from Columbia University. The author has contributed to research in topics: Graphene & Monolayer. The author has an hindex of 127, co-authored 637 publications receiving 108193 citations. Previous affiliations of James Hone include DARPA & Santa Fe Institute.

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Lightly Fluorinated Graphene as a Protective Layer for n-Type Si(111) Photoanodes in Aqueous Electrolytes

TL;DR: The behavior of n-Si(111) photoanodes covered by monolayer sheets of fluorinated graphene (F-Gr) was investigated under a range of chemical and electrochemical conditions and showed that oxide formation at the Si surface was significantly inhibited for Si electrodes coated with F-Gr relative to bare Si electrodes exposed to the same conditions.
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Surface buckling of black phosphorus: Determination, origin, and influence on electronic structure

TL;DR: The surface structure of black phosphorus materials was determined using surface-sensitive dynamical microspot low energy electron diffraction (LEED) analysis using a high spatial resolution low-energy electron microscopy (LEEM) system as mentioned in this paper.
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Fabrication of hundreds of field effect transistors on a single carbon nanotube for basic studies and molecular devices

TL;DR: In this paper, a large number of carbon nanotube field effect transistors (CNTFETs) with uniform properties has been used to study the stability and uniformity of CNTFET properties, and two photolithography steps are used to pattern contacts and bonding pads, and next to define a mask to ‘burn away additional nanotubes by oxygen plasma etch.
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A Low-Power Edge Detection Image Sensor Based on Parallel Digital Pulse Computation

TL;DR: This work implements an all-digital parallel processing algorithm that detects differences between neighboring pixel pairs on chip, hence reducing the aforementioned power and cost overheads and a simple column-shared frequency comparator enables low-power operation by eliminating arithmetic computations with large memory requirement.