Nagoya Institute of Technology

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.

Probe measurements and global model of inductively coupled Ar/CF4 discharges

Abstract: The electron energy distribution function (EEDF) is measured with a Langmuir probe in an inductively-coupled radio frequency (RF, 13.56 MHz) Ar/CF4 discharge over a pressure range 3-30 mTorr by changing the CF4 content from 0 to 20%, while keeping the power injected into the plasma at about 50 W. EEDFs measured at a pressure lower than 10 mTorr are bi-Maxwellian distributions over the measured CF4 content, while those at a pressure of 30 mTorr are Druyvesteyn ones in the presence of a small amount of CF4. The average electron energy slightly increases with CF4 content, while the electron density decreases. The decrease in the electron density with addition of CF4 is more prominent as the total pressure increases. Dependences of the electron density and the averaged electron energy on CF4 content are predicted in the global model.

Two conditions concerning common quadratic Lyapunov functions for linear systems

Abstract: Concerning a pair of linear systems, some triangle conditions for the existence of a common quadratic Lyapunov function are presented in this paper. These conditions are derived from a criterion for judging the semipositiveness of a linear map defined on symmetric matrices.

Continuous Stochastic Feature Mapping Based on Trajectory HMMs

Abstract: This paper proposes a technique of continuous stochastic feature mapping based on trajectory hidden Markov models (HMMs), which have been derived from HMMs by imposing explicit relationships between static and dynamic features. Although Gaussian mixture model (GMM)- or HMM-based feature-mapping techniques work effectively, their accuracy occasionally degrades due to inappropriate dynamic characteristics caused by frame-by-frame mapping. While the use of dynamic-feature constraints at the mapping stage can alleviate this problem, it also introduces inconsistencies between training and mapping. The technique we propose can eliminate these inconsistencies while retaining the benefits of using dynamic-feature constraints, and it offers entire sequence-level transformation rather than frame-by-frame mapping. The results obtained from speaker-conversion, acoustic-to-articulatory inversion-mapping, and noise-compensation experiments demonstrated that our new approach outperformed the conventional one.

High-temperature supercapacitor with a proton-conducting metal pyrophosphate electrolyte

Abstract: Expanding the range of supercapacitor operation to temperatures above 100°C is important because this would enable capacitors to operate under the severe conditions required for next-generation energy storage devices. In this study, we address this challenge by the fabrication of a solid-state supercapacitor with a proton-conducting Sn0.95Al0.05H0.05P2O7 (SAPO)-polytetrafluoroethylene (PTFE) composite electrolyte and a highly condensed H3PO4 electrode ionomer. At a temperature of 200°C, the SAPO-PTFE electrolyte exhibits a high proton conductivity of 0.02 S cm−1 and a wide withstanding voltage range of ±2 V. The H3PO4 ionomer also has good wettability with micropore-rich activated carbon, which realizes a capacitance of 210 F g−1 at 200°C. The resulting supercapacitor exhibits an energy density of 32 Wh kg−1 at 3 A g−1 and stable cyclability after 7000 cycles from room temperature to 150°C.