메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
Jinwoong Hwang (Pusan National University) Ji-Eun Lee (Pusan National University) Minhee Kang (Pusan National University) Byeong-Gyu Park (Pohang University of Science and Technology) Jonathan Denlinger (Lawrence Berkeley National Laboratory) Sung-Kwan Mo (Lawrence Berkeley National Laboratory) Choongyu Hwang (Pusan National University)
저널정보
한국진공학회(ASCT) Applied Science and Convergence Technology Applied Science and Convergence Technology Vol.27 No.5
발행연도
2018.9
수록면
90 - 94 (5page)
DOI
10.5757/ASCT.2018.27.5.90

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
The electron band structure of manganese-adsorbed graphene on an SiC(0001) substrate has been studied using angleresolved photoemission spectroscopy. Upon introducing manganese atoms, the conduction band of graphene, that is observed in pristine graphene indicating intrinsic electron-doping by the substrate, completely disappears and the valence band maximum is observed at 0.4 eV below Fermi energy. At the same time, the slope of the valence band decreases by the presence of manganese atoms, approaching the electron band structure calculated using the local density approximation method. The former provides experimental evidence of the formation of nearly free-standing graphene on an SiC substrate, concomitant with a metal-to-insulator transition. The latter suggests that its electronic correlations are efficiently screened, suggesting that the dielectric property of the substrate is modified by manganese atoms and indicating that electronic correlations in grpahene can also be tuned by foreign atoms. These results pave the way for promising device application using graphene that is semiconducting and charge neutral.

목차

Abstract
Ⅰ. Introduction
Ⅱ. Experimental details
Ⅲ. Results
Ⅳ. Discussion
Ⅴ. Conclusions
References

참고문헌 (34)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2019-420-001277071