다성분계 물성을 예측하기 위한 BaTiO3기반 계산과학 플랫폼 구축open accessEstablishment of a BaTiO3-based Computational Science Platform to Predict Multi-component Properties
- Other Titles
- Establishment of a BaTiO3-based Computational Science Platform to Predict Multi-component Properties
- Authors
- 이동건; 이한욱; 임원빈; 고현석; 조성범
- Issue Date
- Sep-2022
- Publisher
- 한국센서학회
- Keywords
- Multilayer ceramic capacitors; BaTiO3 material; Special quasirandom structures; The first-principles calculations
- Citation
- 센서학회지, v.31, no.5, pp.318 - 323
- Indexed
- KCI
OTHER
- Journal Title
- 센서학회지
- Volume
- 31
- Number
- 5
- Start Page
- 318
- End Page
- 323
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/173067
- DOI
- 10.46670/JSST.2022.31.5.318
- ISSN
- 1225-5475
- Abstract
- Barium titanate (BaTiO3) is considered to be a beneficial ceramic material for multilayer ceramic capacitor (MLCC) applications because of its high dielectric constant and low dielectric loss. Numerous attempts have been made to improve the physical properties of BaTiO3 in response to recent market trends by employing multicomponent alloying strategies. However, owing to its significantnumber of atomic combinations and unpredictable physical properties, finding a traditional experimental approach to develop multicomponent systems is difficult; the development of such systems is also time-consuming. In this study, 168 new structures were fabricated using special quasi-random structures (SQSs) of Ba1-xCaxTi1-yZryO3, and 1680 physical properties were extracted from first-principles calculations. In addition, we built an integrated database to manage the computational results, and will provide big data solutions by performing data analysis combined with AI modeling. We believe that our research will enable the global materials market to realize digital transformation through datalization and intelligence of the material development process.
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