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데이터 최적화 기법을 도입한 기계적 물성치 예측 모델과 새로운 2차원 소재의 발견
이인효(Inhyo Lee),김준철(Joonchul Kim),김태현(Taehyun Kim),민경민(Kyoungmin Min) 대한기계학회 2022 대한기계학회 춘추학술대회 Vol.2022 No.11
Two-dimensional (2D) materials are attractive materials. Many studies are being conducted because of their unique characteristics. However, there is lack of information about properties of 2D materials. Therefore, this study attempted to solve this problem by developing a machine learning (ML) model that predicts mechanical properties of 2D materials. In addition, a 2D materials generation framework was developed using a classification model and a deep learning-based generative model. ML model to predict mechanical properties is trained from existing 2D database and reduces the uncertainty of prediction through data optimization techniques. Potential 2D materials are discovered through screening processes such as measuring structure and atomic similarities. We believe that the developing of ML model and framework for finding new 2D materials could open a new chapter in material science
데이터 최적화 기법을 도입한 기계적 물성치 예측 모델과 새로운 2차원 소재의 발견
이인효(Inhyo Lee),김준철(Joonchul Kim),김태현(Taehyun Kim),민경민(Kyoungmin Min) 대한기계학회 2022 대한기계학회 춘추학술대회 Vol.2022 No.11
Two-dimensional (2D) materials are attractive materials. Many studies are being conducted because of their unique characteristics. However, there is lack of information about properties of 2D materials. Therefore, this study attempted to solve this problem by developing a machine learning (ML) model that predicts mechanical properties of 2D materials. In addition, a 2D materials generation framework was developed using a classification model and a deep learning-based generative model. ML model to predict mechanical properties is trained from existing 2D database and reduces the uncertainty of prediction through data optimization techniques. Potential 2D materials are discovered through screening processes such as measuring structure and atomic similarities. We believe that the developing of ML model and framework for finding new 2D materials could open a new chapter in material science
배정호 ( Jungho Bae ) 한국국방기술학회 2024 한국국방기술학회 논문지 Vol.6 No.1
2차원 평면에 결정구조를 갖는 2차원 소재는 2004년 처음 발견된 그래핀(Graphene)을 시작으로 2011년 발견된 맥신(MXene)에 이르기까지 나노기술 분야의 차세대 소재로 주목받고 있다. 2차원 소재 중 광범위하게 연구되고 있는 그래핀, 맥신, 육방정계 질화붕소, 전이금속 칼코게나이드의 특성을 소개하고 각 2차원 소재를 국방 분야에 적용할 수 있는 기술을 소개하여 차세대 무기체계 및 전력지원체계에 적용할 수 있는 방안을 제시하고자 한다. Two-dimensional materials, which have a crystal structure in a two-dimensional plane, are attracting attention as next-generation materials in nanotechnology, from Graphene, first discovered in 2004, to MXene, discovered in 2011. In this study, Among new 2D materials, we introduce the characteristics of Graphene, MXene, hexagonal boron nitride, and transition metal chalcogenide, which are being studied extensively, and introduce technologies that can be used to apply each 2D material to the defense field. We would like to present a method that can be applied to next-generation weapon systems and war-power support systems.