Evidence map›Paper›PMID 35863904›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2022

Operando Decoding of Surface Strain in Anode-Free Lithium Metal Batteries via Optical Fiber Sensor.

Yanpeng Li, Yi Zhang, Zhen Li, Zhijun Yan, Xiangpeng Xiao, Xueting Liu, Jie Chen, Yue Shen, Qizhen Sun, Yunhui Huang

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Review
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  6. National science review · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yanpeng LiSchool of Optical and Electronic Information, National Engineering Research Center of Next Generation Internet Access-system, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
Yi ZhangState Key Laboratory of Material Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
Zhen LiState Key Laboratory of Material Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
Zhijun YanSchool of Optical and Electronic Information, National Engineering Research Center of Next Generation Internet Access-system, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
Xiangpeng XiaoSchool of Optical and Electronic Information, National Engineering Research Center of Next Generation Internet Access-system, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
Xueting LiuState Key Laboratory of Material Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
Jie ChenState Key Laboratory of Material Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
Yue ShenState Key Laboratory of Material Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
Qizhen SunSchool of Optical and Electronic Information, National Engineering Research Center of Next Generation Internet Access-system, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
Yunhui HuangState Key Laboratory of Material Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.ORCID https://orcid.org/0000-0003-1687-1938

Funding

Innovation Fund of Wuhan National Laboratory for Optoelectronics (WNLO)National Natural Science Foundation of China 51972131National Natural Science Foundation of China 5202780089National Natural Science Foundation of China 61775072National Natural Science Foundation of China 61922033State Key Laboratory of Materials Processing and Die & Mould Technology
6 · The paper itself

Abstract

With zero excess lithium, anode-free lithium metal batteries (AFLMBs) can deliver much higher energy density than that of traditional lithium metal batteries. However, AFLMBs are prone to suffer from rapid capacity loss and short life. Monitoring and analyzing the capacity decay of AFLMBs are of great importance for their future applications. It is known that the capacity fade mainly comes from the formation of solid electrolyte interphase species and dead lithium, which leads to irreversible volume expansion. Therefore, monitoring and distinguishing the irreversible volume expansion or reversible volume expansion are the key points to analyze the capacity fade of AFLMBs. Herein, an applicable technique based on optical fiber sensors to characterize and quantize the volume change of AFLMBs is developed. By attaching fiber Bragg grating (FBG) sensors onto the surface of the multilayered anode-free pouch cells, the strain evolution of the cells is successfully monitored and correlated with their electrochemical properties. It is found that the decline of surface strain fluctuation amplitude caused by the loss of active lithium is the leading indicator of battery failure. The proposed sensing technique has excellent multiplexing capability that can be considered as an elementary unit for capacity fade analysis in next-generation battery management system.

Indexed as

anode-free lithium metal batteriesfiber Bragg gratingin situ strain monitor

Identifiers

PMID35863904
PMCPMC9475526

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.