Design of graphene for tailored functionalities: a novel mathematical approach

Research Project

Project/Area Number	24K06797
Research Category	Grant-in-Aid for Scientific Research (C)
Allocation Type	Multi-year Fund
Section	一般
Review Section	Basic Section 12020:Mathematical analysis-related
Research Institution	Kyushu University
Principal Investigator	Cesana Pierluigi 九州大学, マス・フォア・インダストリ研究所, 准教授 (60771532)
Project Period (FY)	2024-04-01 – 2027-03-31
Project Status	Granted (Fiscal Year 2024)
Budget Amount *help	¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000) Fiscal Year 2026: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000) Fiscal Year 2025: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000) Fiscal Year 2024: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Keywords	Disclination / Dislocation / Variational Principle / Graphene / Shape-Memory Alloys
Outline of Research at the Start	We create new mathematical methods to design graphene structures for specific applications. We predict shape and mechanical properties of graphene flocks with defects. We use machine learning to combine large-scale and nano-scale information to optimize the pattern of defects.