Phase-Field Simulation and Machine Learning Study of the Effects of Elastic and Plastic Properties of Electrodes and Solid Polymer Electrolytes on the Suppression of Li Dendrite Growth

枝晶(数学) 材料科学 电解质 弹性模量 电极 复合材料 相(物质) 快离子导体 化学工程 纳米技术 几何学 化学 物理化学 有机化学 数学 工程类
作者
Yao Ren,Kena Zhang,Yue Zhou,Ye Cao
出处
期刊:ACS Applied Materials & Interfaces [American Chemical Society]
卷期号:14 (27): 30658-30671 被引量:30
标识
DOI:10.1021/acsami.2c03000
摘要

Lithium (Li) dendrite growth in Li batteries is a long-standing problem, which causes critical safety concerns and severely limits the advancement of rechargeable Li batteries. Replacing a conventional liquid electrolyte with a solid electrolyte of high mechanical strength and rigidity has become a potential approach to inhibiting the Li dendrite growth. However, there still lacks an accurate understanding of the role of the mechanical properties of the metal electrode and the solid electrolyte in the Li dendrite growth. In this work, we develop a phase-field model coupled with the elastoplastic deformation to investigate the Li dendrite growth and its inhibition in the cell. Different mechanical properties, including the elastic modulus and the initial yield strength of both the metal electrode and the solid electrolyte, are explored to understand their independent roles in the inhibition of Li dendrite growth. High-throughput phase-field simulations are performed to establish a database of relationships between the aforementioned mechanical properties and the Li dendrite morphology, based on which a compressed-sensing machine learning model is trained to derive interpretable analytical correlations between the key material parameters and the dendrite morphology, as described by the dendrite length and area ratio. It is revealed that the Li dendrite can be effectively inhibited by electrolytes of high elastic moduli and initial yield strengths. Meanwhile, the role of the yield strength of the Li metal is also critical when the yield strength of the electrolyte becomes low. This work provides a fundamental understanding of the dendrite inhibition by mechanical suppression and demonstrates a computational data-driven methodology to potentially guide the electrode and electrolyte material selection for better inhibition of the dendrite growth.
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
PDF的下载单位、IP信息已删除 (2025-6-4)

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
科研通AI6应助虚拟的画板采纳,获得10
1秒前
2秒前
Flex完成签到,获得积分10
3秒前
科研通AI5应助马到成功采纳,获得10
3秒前
sy发布了新的文献求助10
4秒前
4秒前
5秒前
浮游应助朴素的SCI缔造者采纳,获得10
6秒前
6秒前
溟夔蝶魅完成签到,获得积分20
6秒前
科研小白完成签到,获得积分10
6秒前
7秒前
柴子完成签到,获得积分10
8秒前
心木完成签到 ,获得积分10
8秒前
9秒前
共享精神应助serendipity采纳,获得10
9秒前
John完成签到 ,获得积分10
11秒前
TANG完成签到,获得积分10
11秒前
13223456发布了新的文献求助10
11秒前
kdf发布了新的文献求助10
12秒前
量子星尘发布了新的文献求助10
13秒前
852应助科研通管家采纳,获得10
13秒前
星辰大海应助科研通管家采纳,获得10
13秒前
科研通AI2S应助科研通管家采纳,获得10
13秒前
科研通AI6应助科研通管家采纳,获得10
13秒前
科研通AI5应助科研通管家采纳,获得50
14秒前
爆米花应助科研通管家采纳,获得10
14秒前
丘比特应助科研通管家采纳,获得10
14秒前
浮游应助科研通管家采纳,获得10
14秒前
完美世界应助科研通管家采纳,获得10
14秒前
GPTea应助科研通管家采纳,获得150
14秒前
bkagyin应助科研通管家采纳,获得10
14秒前
加菲丰丰应助科研通管家采纳,获得30
14秒前
科研通AI6应助科研通管家采纳,获得10
14秒前
Orange应助科研通管家采纳,获得10
14秒前
乐乐应助科研通管家采纳,获得10
14秒前
丘比特应助科研通管家采纳,获得10
14秒前
14秒前
sxkoala应助科研通管家采纳,获得30
14秒前
加菲丰丰应助科研通管家采纳,获得30
14秒前
高分求助中
Comprehensive Toxicology Fourth Edition 24000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
LRZ Gitlab附件(3D Matching of TerraSAR-X Derived Ground Control Points to Mobile Mapping Data 附件) 2000
Pipeline and riser loss of containment 2001 - 2020 (PARLOC 2020) 1000
World Nuclear Fuel Report: Global Scenarios for Demand and Supply Availability 2025-2040 800
Handbook of Social and Emotional Learning 800
Risankizumab Versus Ustekinumab For Patients with Moderate to Severe Crohn's Disease: Results from the Phase 3B SEQUENCE Study 600
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 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 5133576
求助须知:如何正确求助?哪些是违规求助? 4334702
关于积分的说明 13504381
捐赠科研通 4171698
什么是DOI,文献DOI怎么找? 2287273
邀请新用户注册赠送积分活动 1288197
关于科研通互助平台的介绍 1229045