| Budget Amount *help |
¥145,860,000 (Direct Cost: ¥112,200,000、Indirect Cost: ¥33,660,000)
Fiscal Year 2017: ¥18,070,000 (Direct Cost: ¥13,900,000、Indirect Cost: ¥4,170,000)
Fiscal Year 2016: ¥32,630,000 (Direct Cost: ¥25,100,000、Indirect Cost: ¥7,530,000)
Fiscal Year 2015: ¥24,180,000 (Direct Cost: ¥18,600,000、Indirect Cost: ¥5,580,000)
Fiscal Year 2014: ¥34,580,000 (Direct Cost: ¥26,600,000、Indirect Cost: ¥7,980,000)
Fiscal Year 2013: ¥36,400,000 (Direct Cost: ¥28,000,000、Indirect Cost: ¥8,400,000)
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| Outline of Final Research Achievements |
This study aims to develop frameworks for materials design using nanostructure datasets including atomic configurations, electronic structures localized at surfaces, interfaces and point defects. We developed i) thermodynamics-based methods for generating nanostructure datasets from first principles such as machine-learning interatomic potential and ii) machine learning-based techniques for discovering new functional materials. These data-mining approaches based on exhaustive first-principles calculations are expected to be useful for exploring new materials and unknown structures.
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