scispace - formally typeset
Search or ask a question
Institution

Nagoya Institute of Technology

EducationNagoya, Japan
About: Nagoya Institute of Technology is a education organization based out in Nagoya, Japan. It is known for research contribution in the topics: Thin film & Catalysis. The organization has 10766 authors who have published 19140 publications receiving 255696 citations. The organization is also known as: Nagoya Kōgyō Daigaku & Nitech.


Papers
More filters
Journal ArticleDOI
TL;DR: In this article, a thermodynamic theory of gases with the energy transfer from molecular translational mode to internal modes as an extension of Meixner's theory was studied, focusing on the simplest case with only one dissipative process due to the dynamic pressure.

91 citations

Journal ArticleDOI
TL;DR: In this paper, the α-methylene-β-aminonitriles of type (III) can be readily obtained with high levels of enantioselectivity in the presence of complex (Ia).
Abstract: Various α-methylene-β-aminonitriles of type (III) can be readily obtained with high levels of enantioselectivity in the presence of complex (Ia).

91 citations

Journal ArticleDOI
TL;DR: In this paper, an elastoplastic model for sands is presented, which can describe stress-strain behavior dependent on mean effective stress level and void ratio, and another new state parameter is used to determine the peak strength and describe the critical state behaviour of sands during shearing.
Abstract: An elastoplastic model for sands is presented in this paper, which can describe stress–strain behaviour dependent on mean effective stress level and void ratio. The main features of the proposed model are: (a) a new state parameter, which is dependent on the initial void ratio and initial mean stress, is proposed and applied to the yield function in order to predict the plastic deformation for very loose sands; and (b) another new state parameter, which is used to determine the peak strength and describe the critical state behaviour of sands during shearing, is proposed in order to predict simply negative/positive dilatancy and the hardening/softening behaviour of medium or dense sands. In addition, the proposed model can also predict the stress–strain behaviour of sands under three-dimensional stress conditions by using a transformed stress tensor instead of ordinary stress tensor. Copyright © 2004 John Wiley & Sons, Ltd.

90 citations

Journal ArticleDOI
TL;DR: The reduced relaxation function obtained here will serve as a useful tool to predict mechanical behavior of brain tissue in compression with strain rate greater than 10 s-1 and could be analysed in time and strain domains separately.
Abstract: Mechanical properties of brain tissue in high strain region are indispensable for the analysis of brain damage during traffic accidents. However, accurate data on the mechanical behavior of brain tissue under impact loading condition are sparse. In this study, mechanical properties of porcine brain tissues were characterized in their cylindrical samples cored out from their surface. The samples were compressed in their axial direction at strain rates ranging from 1 to 50 s-1. Stress relaxation test was also conducted following rapid compression with a rise time of ∼30 ms to different strain levels (20-70%). Brain tissue exhibited stiffer responses under higher impact rates: initial elastic modulus was 5.7±1.6, 11.9±3.3, 23.8±10.5 kPa (mean±SD) for strain rate of 1, 10, 50 s-1, respectively. We found that stress relaxation K(t,e) could be analysed in time and strain domains separately. The relaxation response could be expressed as the product of two mutually independent functions of time and strain as: K(t,e)=G(t)σe(e), where σe(e) is an elastic response, i.e., the peak stress in response to a step input of strain e, and G(t) is a reduced relaxation function: G(t)=0.642e-t/0.0207+0.142e-t/0.482+0.216e-t/18.9, i.e., the time-dependent stress response normalized by the peak stress. The reduced relaxation function obtained here will serve as a useful tool to predict mechanical behavior of brain tissue in compression with strain rate greater than 10 s-1.

90 citations

Journal ArticleDOI
TL;DR: In this paper, a femtosecond laser is used for rendering aerial and volumetric graphics using femto-cond (FSL) laser sources, which can produce holograms using spatial light modulation technology and scanning of a laser beam by a galvano mirror.
Abstract: We present a method of rendering aerial and volumetric graphics using femtosecond lasers. A high-intensity laser excites physical matter to emit light at an arbitrary three-dimensional position. Popular applications can thus be explored, especially because plasma induced by a femtosecond laser is less harmful than that generated by a nanosecond laser. There are two methods of rendering graphics with a femtosecond laser in air: producing holograms using spatial light modulation technology and scanning of a laser beam by a galvano mirror. The holograms and workspace of the system proposed here occupy a volume of up to 1 cm3; however, this size is scalable depending on the optical devices and their setup. This article provides details of the principles, system setup, and experimental evaluation, and discusses the scalability, design space, and applications of this system. We tested two laser sources: an adjustable (30--100fs) laser that projects up to 1,000 pulses/s at an energy of up to 7mJ/pulse and a 269fs laser that projects up to 200,000 pulses/s at an energy of up to 50μJ/pulse. We confirmed that the spatiotemporal resolution of volumetric displays implemented using these laser sources is 4,000 and 200,000 dots/s, respectively. Although we focus on laser-induced plasma in air, the discussion presented here is also applicable to other rendering principles such as fluorescence and microbubbles in solid or liquid materials.

90 citations


Authors

Showing all 10804 results

NameH-indexPapersCitations
Luis M. Liz-Marzán13261661684
Hideo Hosono1281549100279
Shunichi Fukuzumi111125652764
Andrzej Cichocki9795241471
Kwok-Hung Chan9140644315
Kimoon Kim9041235394
Alex Martin8840636063
Manijeh Razeghi82104025574
Yuichi Ikuhara7597424224
Richard J. Cogdell7348023866
Masaaki Tanaka7186022443
Kiyotomi Kaneda6537813337
Yulin Deng6464116148
Motoo Shiro6472017786
Norio Shibata6357414469
Network Information
Related Institutions (5)
Tokyo Institute of Technology
101.6K papers, 2.3M citations

97% related

Waseda University
46.8K papers, 837.8K citations

94% related

Tokyo University of Science
24.1K papers, 438K citations

94% related

Tokyo Metropolitan University
25.8K papers, 724.2K citations

93% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202316
202272
2021631
2020718
2019701
2018764