Ceramics range from structural components to materials that support advanced technologies such as semiconductors, dielectrics, and ionic conductors. Conventional ceramic research has been conducted by experimentally preparing samples and evaluating their performance. However, relying solely on experiment makes it difficult to significantly accelerate the search for new materials. On the other hand, computational performance has been developing exponentially, and in recent years it has become possible to predict material properties without conducting experiments using calculations based on quantum mechanics. Under this circumstance, our group aims to significantly accelerate ceramic research and discover new ceramic materials useful to society by using advanced computation technique and machine learning and by collaborating closely with experimental groups. We also aim to construct universal principles by taking a bird's-eye view of materials based on large-scale computational data.
Materials Processing and Characterization Division
Multi-Functional Materials Science
Prof.Yu KUMAGAI
- Senior Assist. Prof. Shin KIYOHARA
- Assist. Prof. Soungmin BAE
- Assist. Prof. Thi Ngoc Huyen VU
- Specially Appointed Assist. Prof. Seonghoon JANG
New Ceramic Materials Research by Integration of Advanced Computational Technology and Informatics
computational material science, materials informatics, ceramic materials
(a) Distribution of vacancy formation energy at 1700 oxygen sites. (b) Comparison of first-principles calculations and machine learning predictions of oxygen vacancy formation energies. The blue dots indicate the results for the training set and the orange ones for the test set. (c) Main factors determining the vacancy formation energies.