Relationship between crystallinity and device characteristics of In‐Sn‐Zn oxide

We have reported that the transistors having the c‐axis‐aligned crystalline (CAAC) In‐Ga‐Zn oxide (IGZO) show good performance. Recently, In‐Sn‐Zn Oxide (ITZO) has attracted much attention because of its high electron mobility, as well as IGZO. However, it has been reported that ITZO field effect transistors (FET) tend to have positive Vth (normally‐on characteristics) and poor reliability compared with IGZO‐FETs. We have reported that high‐performance and high‐reliability OS‐FETs can be fabricated by using CAAC‐IGZO, which has high crystallinity and has no clear grain boundaries, as an active layer. Therefore, we have fabricated CAAC‐ITZO thin films to improve performance of ITZO‐FETs by using CAAC‐ITZO as an active layer. In addition, FETs employing CAAC‐ITZO have better characteristics and reliability than FETs using nano‐crystal ITZO. Furthermore, constant photocurrent method (CPM) measurement was carried out in order to estimate density of deep‐level defect states caused by oxygen vacancies in oxide semiconductors. The results show that CAAC‐ITZO has lower density of deep‐level defect states than nano‐crystal ITZO. We attribute the improvement in reliability of ITZO‐FETs to a decrease in deep‐level defect states of an ITZO active layer, as is the case with IGZO.     

Data Center as a Key Player of a District Electric Power and Heat Network System： A Comparison in Urban and Suburb Regions

A DC （data center） demands air-conditioning power as large as the 1/3-1/2 of total electricity consumption. Thus, energy saving of cooling power of DC yields considerable effect on both economic and environmental views. PV （Photovoltaic） and absorption refrigerator with CGS （cogeneration systems） or gas boiler are possible power saving options. The waste warm air from DC would be utilized for greenhouse heating when DC and greenhouse locate near in the suburbs. In this study, the authors develop an energy network model to assess the potential contribution of DC as a major electric power and chilled air consumer as well as the warm air supplier in a district to the energy efficiency improvement. The evaporation heat of LNG （liquefied natural gas） utilization is also considered as well as PV, CGS. This model is applied to the cases of the urban area in Tokyo which involves athletic center, shops and hospital and the suburbs including greenhouse and then compared.     

KDDI：基于下一代网络的固定、移动和广电融合业务

在全球的CDMA运营商中,日本KDDI是非常突出的一家。KDDI于2002年4月推出了自己的3G业务,采用的是cdma20001x技术。与NTTDoCoMo的3G业务一开始缓慢发展相比,KDDI虽晚半年推出3G业务,但其3G业务一起步就进入了快速发展阶段,业务开展才84天,用户数就突破百万大关。到2004年10月,用户数突破1600万的KDDI。那么,到底是什么使KDDI后来居上的呢？本文试图从分析KDDI的业务人手,破解KDDI的成功密码.     

Observation of three-dimensional elemental distributions of a Si device using a 360 degrees -tilt FIB and the cold field-emission STEM system

A technique for preparation of a pillar-shaped specimen and its multidirectional observation using a combination of a scanning transmission electron microscope (STEM) and a focused ion beam (FIB) instrument has been developed. The system employs an FIB/STEM compatible holder with a specially designed tilt mechanism, which allows the specimen to be tilted through 360 degrees [T. Yaguchi, M. Konno, T. Kamino, T. Hashimoto, T. Ohnishi, K. Umemura, K. Asayama, Microsc. Microanal. 9 (Suppl. 2) (2003) 118; T. Yaguchi, M. Konno, T. Kamino, T. Hashimoto, T. Ohnishi, M. Watanabe, Microsc. Microanal. 10 (Suppl. 2) (2004) 1030]. This technique was applied to obtain the three-dimensional (3D) elemental distributions around a contact plug of a Si device used in a 90-nm technology. A specimen containing only one contact plug was prepared in the shape of a pillar with a diameter of 200nm and a length of 5mum. Elemental maps were obtained from the pillar specimen using a 200-kV cold-field emission gun (FEG) STEM model HD-2300C equipped with the EDAX genesis X-ray energy-dispersive spectrometry (XEDS) system through a spectrum imaging technique. In this study, elemental distributions of minor elements with weak signals were enhanced by applying principal component analysis (PCA), which is a superior technique to extract weak signals from a large dataset. The distributions of elements, especially the metallization component Ti and minor dopant As in this particular device, were successfully extracted by PCA. Finally, the 3D elemental distributions around the contact plug could be visualized by reconstruction from the tilt series of maps.     

TMN implementation strategy based on OSI management standards

In order to facilitate the implementations ofTMN interface protocols/services studied inITU-T, it is very important to define profiles for supportingTMN management service. This paper proposes a concrete method for achieving this based on osi management standards as a promisingTMN implementation method. It proposes an idea of structuring theTMN ISP’S based on the structure of the osi managementISP’S. The paper discusses aTMN based on the osi managementISP’S. Finally the implementation as software is discussed and a software architecture for efficient application development is proposed.     

High-rate Decoupled Water Electrolysis System Integrated with α-MoO3 as a Redox Mediator with Fast Anhydrous Proton Kinetics

Hydrogen is a promising alternative to fossil fuels that can reduce greenhouse gas emissions. Decoupled water electrolysis system using a reversible proton storage redox mediator, where the oxygen evolution reaction and hydrogen evolution reaction are separated in time and space, is an effective approach to producing hydrogen gas with high purity, high flexibility, and low cost. To realize fast hydrogen production in such a system, a redox mediator capable of releasing protons rapidly is required. Herein, α-MoO₃, with an ultrafast proton transfer property that can be explained by a dense hydrogen bond network in the lattice oxygen arrays of HxMoO₃, is examined as a high-rate redox mediator for fast hydrogen production in acidic electrolytes. The α-MoO₃ redox mediator shows both a large capacity of 204 mAh g⁻¹ and fast hydrogen production at a current rate of 10 A cm⁻²(≈153 A g⁻¹), outperforming most of the previously reported solid-state redox mediators.     

Development of an epileptic seizure prediction algorithm using R–R intervals with self-attentive autoencoder

Epilepsy is a neurological disorder that may affect the autonomic nervous system (ANS) from 15 to 20 min before seizure onset, and disturbances of ANS affect R–R intervals (RRI) on an electrocardiogram (ECG). This study aims to develop a machine learning algorithm for predicting focal epileptic seizures by monitoring R–R interval (RRI) data in real time. The developed algorithm adopts a self-attentive autoencoder (SA-AE), which is a neural network for time-series data. The results of applying the developed seizure prediction algorithm to clinical data demonstrated that it functioned well in most patients; however, false positives (FPs) occurred in specific participants. In a future work, we will investigate the causes of FPs and optimize the developing seizure prediction algorithm to further improve performance using newly added clinical data.