Towards Practical Application of Li–S Battery with High Sulfur Loading and Lean Electrolyte: Will Carbon-Based Hosts Win This Race?

种族(生物学) 电池(电) 硫黄 碳纤维 电解质 锂硫电池 化学工程 材料科学 化学 工程类 功率(物理) 社会学 复合材料 物理 性别研究 电极 冶金 物理化学 复合数 量子力学
作者
Yi Gong,Jing Li,Kai Yang,Shaoyin Li,Ming Xu,Guangpeng Zhang,Yan Shi,Qiong Cai,Huanxin Li,Yunlong Zhao
出处
期刊:Nano-micro Letters [Springer Nature]
卷期号:15 (1) 被引量:40
标识
DOI:10.1007/s40820-023-01120-7
摘要

Abstract As the need for high-energy–density batteries continues to grow, lithium-sulfur (Li–S) batteries have become a highly promising next-generation energy solution due to their low cost and exceptional energy density compared to commercially available Li-ion batteries. Research into carbon-based sulfur hosts for Li–S batteries has been ongoing for over two decades, leading to a significant number of publications and patents. However, the commercialization of Li–S batteries has yet to be realized. This can be attributed, in part, to the instability of the Li metal anode. However, even when considering just the cathode side, there is still no consensus on whether carbon-based hosts will prove to be the best sulfur hosts for the industrialization of Li–S batteries. Recently, there has been controversy surrounding the use of carbon-based materials as the ideal sulfur hosts for practical applications of Li–S batteries under high sulfur loading and lean electrolyte conditions. To address this question, it is important to review the results of research into carbon-based hosts, assess their strengths and weaknesses, and provide a clear perspective. This review systematically evaluates the merits and mechanisms of various strategies for developing carbon-based host materials for high sulfur loading and lean electrolyte conditions. The review covers structural design and functional optimization strategies in detail, providing a comprehensive understanding of the development of sulfur hosts. The review also describes the use of efficient machine learning methods for investigating Li–S batteries. Finally, the outlook section lists and discusses current trends, challenges, and uncertainties surrounding carbon-based hosts, and concludes by presenting our standpoint and perspective on the subject.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
水冗发布了新的文献求助30
刚刚
1秒前
1秒前
迷你的心情完成签到,获得积分20
1秒前
紧张的背包完成签到,获得积分20
2秒前
kaikai发布了新的文献求助10
3秒前
共享精神应助xu采纳,获得10
3秒前
4秒前
manmanbuman发布了新的文献求助30
7秒前
充电宝应助踏实的白枫采纳,获得10
9秒前
9秒前
9秒前
CipherSage应助jackhlj采纳,获得30
9秒前
11秒前
kaikai完成签到,获得积分10
12秒前
zhang给zhang的求助进行了留言
14秒前
yinzenglinnn发布了新的文献求助10
15秒前
16秒前
18秒前
18秒前
留猪完成签到,获得积分10
19秒前
小花发布了新的文献求助10
20秒前
善学以致用应助泽佳采纳,获得10
20秒前
安静远航发布了新的文献求助10
21秒前
22秒前
Augenstern发布了新的文献求助10
24秒前
25秒前
25秒前
manmanbuman完成签到,获得积分10
27秒前
28秒前
28秒前
Owen应助冷酷芷雪采纳,获得10
28秒前
内秀发布了新的文献求助10
28秒前
28秒前
29秒前
顾矜应助kkk采纳,获得10
29秒前
英姑应助感动的曼容采纳,获得10
30秒前
00发布了新的文献求助10
32秒前
可爱君发布了新的文献求助10
32秒前
jackhlj完成签到,获得积分10
33秒前
高分求助中
Licensing Deals in Pharmaceuticals 2019-2024 3000
Cognitive Paradigms in Knowledge Organisation 2000
Effect of reactor temperature on FCC yield 2000
Introduction to Spectroscopic Ellipsometry of Thin Film Materials Instrumentation, Data Analysis, and Applications 1800
Natural History of Mantodea 螳螂的自然史 1000
A Photographic Guide to Mantis of China 常见螳螂野外识别手册 800
How Maoism Was Made: Reconstructing China, 1949-1965 800
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3313931
求助须知:如何正确求助?哪些是违规求助? 2946299
关于积分的说明 8529491
捐赠科研通 2621940
什么是DOI,文献DOI怎么找? 1434230
科研通“疑难数据库(出版商)”最低求助积分说明 665175
邀请新用户注册赠送积分活动 650738