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Hyeon Suk Shin

Researcher at Ulsan National Institute of Science and Technology

Publications -  173
Citations -  22852

Hyeon Suk Shin is an academic researcher from Ulsan National Institute of Science and Technology. The author has contributed to research in topics: Graphene & Chemical vapor deposition. The author has an hindex of 56, co-authored 158 publications receiving 18304 citations. Previous affiliations of Hyeon Suk Shin include Pohang University of Science and Technology.

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Construction of a gene expression profile of a human fetal liver by single-pass cDNA sequencing.

TL;DR: An overall gene expression profile of a human fetal liver is obtained by sequencing the 5′ ends of random cDNA clones from an unbiased cDNA library, and many novel genes that might be related to liver growth and hemopoiesis have been identified.
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Two-Dimensional Gradient Mapping Technique Useful for Detailed Spectral Analysis of Polymer Transition Temperatures

TL;DR: The potential of a two-dimensional gradient mapping technique that utilized the eigenvalue manipulating transformation (EMT) of the spectral data set to determine the transition temperatures, which are not readily detected in convention spectral analysis is demonstrated.
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Hydrogen-Bonding Networks of Dialkyl Disulfides Containing the Urea Moiety in Self-Assembled Monolayers

TL;DR: In this article, a self-assembled monolayers of two newly synthesized dialkyl disulfides containing the urea moiety, 4-(3-octadecylureido)phenyl disulfide (ODPD) and 3-(octadecyclureido)-ethanedisulfide(ODED), were prepared and studied by infrared spectroscopy.
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Sphere‐to‐Multipod Transmorphic Change of Nanoconfined Pt Electrocatalyst during Oxygen Reduction Reaction

TL;DR: The improved durability observed from Pt-loaded hCR-rGO originates from 1) dendritic pod structure of Pt exposing more active sites to reactants and 2) highly ORR-active Pt {110} planes dominant on the surface.
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Large Area Automated Characterisation of Chemical Vapour Deposition Grown Monolayer Transition Metal Dichalcogenides Through Photoluminescence Imaging

TL;DR: In this paper, photoluminescence imaging and computer vision techniques are applied to create an automated analysis for large area samples of semiconducting TMDs, measuring the properties of island size, density of islands, relative PL intensity and homogeneity, and orientation of triangular domains.