Frontier explorations in nanodopant analysis

2017 Fiscal Year Final Research Report

• Project Area: Exploration of nanostructure-property relationships for materials innovation
• Project/Area Number: 25106003
• Research Category: Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)
• Allocation Type: Single-year Grants
• Review Section: Science and Engineering
• Research Institution: The University of Tokyo
• Principal Investigator: Shibata Naoya 東京大学, 大学院工学系研究科(工学部), 教授 (10376501)
• Co-Investigator(Kenkyū-buntansha): 藤平 哲也 大阪大学, 基礎工学研究科, 准教授 (00463878) ; 石川 亮 東京大学, 大学院工学系研究科(工学部), 助教 (20734156) ; 栃木 栄太 東京大学, 大学院工学系研究科(工学部), 助教 (50709483) ; 溝口 照康 東京大学, 生産技術研究所, 准教授 (70422334) ; 佐藤 幸生 九州大学, 工学(系)研究科(研究院), 准教授 (80581991)
• Co-Investigator(Renkei-kenkyūsha): IKUHARA YUICHI 東京大学, 大学院工学系研究科, 教授 (70192474)
• Project Period (FY): 2013-06-28 – 2018-03-31
• Keywords: 機能元素 / STEM / 界面、粒界、表面、転位 / その場観察

Outline of Final Research Achievements

In this project, we explored new frontiers of nano-dopant analysis using atomic-resolution scanning transmission electron microscopy (STEM). By developing new STEM techniques and applying them to the characterization of nano-dopant structures on surfaces, grain boundaries, dislocations and point defects of oxides and nitrides, we have succeeded in obtaining new structural information of nano-dopants at atomic dimensions. These results are shared with other groups and used for understanding structure-property relationships of nano-dopants inside materials. In addition, we developed a new technique called “grain boundary informatics,” which can predict stable grain boundary structures very efficiently using machine learning techniques.

Free Research Field

電子顕微鏡材料学