H
Hiroyuki Sasabe
Researcher at Chitose Institute of Science and Technology
Publications - 341
Citations - 10091
Hiroyuki Sasabe is an academic researcher from Chitose Institute of Science and Technology. The author has contributed to research in topics: Carbazole & Monolayer. The author has an hindex of 50, co-authored 341 publications receiving 9796 citations. Previous affiliations of Hiroyuki Sasabe include University of Toyama & Rohm.
Papers
More filters
Journal ArticleDOI
Molecular Interaction of Phthalocyanine Studied by Electroabsorption in Near IR
Shuichi Yanagi,Akira Sakamoto,Tatsuo Wada,Jason P. Sokoloff,Minquan Tian,Keisuke Sasaki,Hiroyuki Sasabe +6 more
TL;DR: In this article, the linear and nonlinear optical properties of soluble phthalocyanines in the condensed states were investigated by the absorption and the electroabsorption spectra, and it was shown that the wavelength of the maximum refractive index changes is located at around 980 nm for the casted polymer film doped with binuclear PHTHC.
Journal ArticleDOI
Preparation of Pentacene Organic Field Effect Transistors by a Wet Process and their Carrier Mobilities
TL;DR: In this paper, bottom contact field effect transistors with fibers that were oriented perpendicular to the source and drain electrodes showed carrier mobilities as high as 0.04 cm2/Vs.
Journal ArticleDOI
Preparation of polythiophene copolymer for third order nonlinear optics
Journal ArticleDOI
Interpretation for STM Imaging of One-Dimensional Organic Conductors
TL;DR: In this article, a new interpretation for TTF-TCNQ images from the viewpoint of the relative phase difference of the molecular orbital in each organic molecule is presented, based on the interference effect on tunneling because of the short tip-sample distance.
Journal ArticleDOI
Vibrational Spectroscopy Using Infrared Raman Microscope for Cytoscreening
TL;DR: In this article, the authors performed cycloscreening of normal and cancer cells using an infrared Raman spectroscopy together with data analysis software, using principal component analysis and discriminant analysis.