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

논문 기본 정보

자료유형
학술저널
저자정보
Solomon Ansah (Hanbat National University) Namsoo Shin (Deep Solution Inc) Jong-Sook Lee (Chonnam National University) Hoon-Hwe Cho (Hanbat National University)
저널정보
대한금속·재료학회 Electronic Materials Letters Electronic Materials Letters Vol.17 No.6
발행연도
2021.11
수록면
532 - 542 (11page)

이용수

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

초록· 키워드

오류제보하기
Solid-state lithium-ion batteries (SSB) have been regarded over recent years as a promising candidate for next-generationenergy storage due to their increased energy density and safety compared to conventional lithium-ion batteries. However,some internal and design parameter eff ects are yet to be fully comprehended. Since numerical modeling gives the opportunityto explore easily the various parameters and their eff ect on the performance of the cell, herein, we present a numericalmodel to study some parameters to optimize the performance of the SSB. The model considers diff usion of lithium-ion inboth the electrode and electrolyte and electrochemical reactions within the SSB. The model prediction agrees with someexperimental discharge profi les, which therefore validates the model. The model is then used to understand the role of theelectrode and electrolyte thickness and maximum concentration of lithium in the solid phase on the performance of thecell. It was observed that increasing cathode thickness increases the cell capacity, whereas reducing electrolyte thicknessimproves the capacity of the cell. Moreover, a direct proportionality is established between the maximum concentration oflithium and the call capacity. Additionally, the role of transport parameter, diff usivity, on the capacity of the SSB at diff erentdischarging rates is also studied. The understanding garnered from the study will improve the cell electrode design tailoredto the desired applications of the SSB.

목차

등록된 정보가 없습니다.

참고문헌 (43)

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