Young member - Taiyo Maeda

Taiyo Maeda
Trainee, High-Reliability Heat-Resistant Materials Group, Materials Manufacturing Field, Research Center for Structural Materials

C.V. (As of September 2024）
Bachelor, Mechanical Engineering Program, Department of Mechanical Engineering, Materials Science, and Ocean Engineering, College of Engineering Science, Yokohama National University, 2021.
Master, Mechanical Engineering Program, Department of Mechanical Engineering, Materials Science, and Ocean Engineering, Graduate School of Engineering Science, Yokohama National University, 2023.
For Doctor, Mechanical Engineering Program, Department of Mechanical Engineering, Materials Science, and Ocean Engineering, Graduate School of Engineering Science, Yokohama National University, April 2023 - present.

NIMS
Trainee, High Temperature Materials Group, Design and Producing Field, Research Center for Structural Materials, NIMS, October 2021 - March 2023

Internship, October - November 2021, August - September 2022 and August - September 2023
NIMS Joint Research Hub Program Use, June 2023 - March 2024

Trainee, High-Reliability Heat-Resistant Materials Group, Materials Manufacturing Field, Research Center for Structural Materials, NIMS, April 2024 - present

NIMS Joint Research Hub Program Use, June 2024 - present

Q＆A

Q：How did you come to know about NIMS?
A：The first time I learned of NIMS was when I was assigned to a laboratory in my fourth year at university. There was a research theme on self-healing ceramics. While researching oxidation-induced self-healing ceramics, I found that crack healing occurs through a process similar to that in human bone and that a NIMS researcher has elucidated the healing mechanism. I chose that research theme because I was strongly attracted to the fact that ceramics, non-living things, can repair a flaw (microcrack) by themselves.

Q：How did you get involved in materials research?
A：I was interested in it because the microstructure is an important factor in strength properties. Understanding the microstructure through observation greatly helps predict the strength properties. Conversely, observation of the fracture surface with a high-performance microscope can provide conclusive evidence to explain the cause when unexpected results are derived in a strength test.

Q：What is the attraction of NIMS?
A：The most attractive point is the numerous pieces of experimental equipment that are difficult to manage in a university laboratory, in terms of both budget and environment. The creep-testing machine, which holds the world's longest record, is a perfect example. In my internship, I conducted microstructural observation using a high-resolution scanning electron microscope (SEM) and acoustic emission analysis to identify crack initiation.
The strong connection among researchers is also an attractive feature. In university, I mostly discussed my work with my supervisor. However, in the NIMS internship, I had many opportunities to discuss my work with not only host researchers but also researchers inside and outside of my research group.

Q：What is your research topic, and what attracts you to it?
A：I am currently conducting research on the prediction of strength distribution in ceramic components. The strength of ceramic components is more susceptible to defects than that of metal components, and the location and shape of defects vary from time to time, resulting in scatter. This is a serious problem in strength design. To solve this problem, we are developing a numerical analysis method that can predict the strength distribution (lower limit and scatter) of ceramic components by inputting the defect distribution obtained from microstructural observation. It has been confirmed that the method is applicable to some types of ceramics and sized specimens. In actual testing, it takes a huge amount of time and cost to conduct strength tests on a large number of specimens, such as N = 1k, 10k. On the other hand, it takes only one hour to predict strength distributions with the proposed method. I am attracted to the fact that even tests that are difficult to conduct due to test environment and cost can be predicted by using numerical simulation technologies.