scholarly journals In situ Diagnostics of Coupled Electrochemical-Mechanical Properties of Solid Electrolyte Interphases on Lithium Metal Rechargeable Batteries

2020 ◽  
Author(s):  
Xingcheng Xiao ◽  
Keyword(s):  
Mechanical Properties ◽  
Solid Electrolyte ◽  
Rechargeable Batteries ◽  
Lithium Metal ◽  
In Situ Diagnostics

scholarly journals Artificial dual solid-electrolyte interfaces based on in situ organothiol transformation in lithium sulfur battery

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Wei Guo ◽  
Wanying Zhang ◽  
Yubing Si ◽  
Donghai Wang ◽  
Yongzhu Fu ◽  
...  
Keyword(s):  
Solid Electrolyte ◽  
Interface Reaction ◽  
Interfacial Instability ◽  
Anode Surface ◽  
Commercial Application ◽  
Lithium Metal ◽  
Metal Anode ◽  
Lithium Metal Anode ◽  
Lithium Sulfur

AbstractThe interfacial instability of the lithium-metal anode and shuttling of lithium polysulfides in lithium-sulfur (Li-S) batteries hinder the commercial application. Herein, we report a bifunctional electrolyte additive, i.e., 1,3,5-benzenetrithiol (BTT), which is used to construct solid-electrolyte interfaces (SEIs) on both electrodes from in situ organothiol transformation. BTT reacts with lithium metal to form lithium 1,3,5-benzenetrithiolate depositing on the anode surface, enabling reversible lithium deposition/stripping. BTT also reacts with sulfur to form an oligomer/polymer SEI covering the cathode surface, reducing the dissolution and shuttling of lithium polysulfides. The Li–S cell with BTT delivers a specific discharge capacity of 1,239 mAh g−1 (based on sulfur), and high cycling stability of over 300 cycles at 1C rate. A Li–S pouch cell with BTT is also evaluated to prove the concept. This study constructs an ingenious interface reaction based on bond chemistry, aiming to solve the inherent problems of Li–S batteries.

In situ fluorinated solid electrolyte interphase towards long-life lithium metal anodes

Nano Research ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 430-436 ◽  
Author(s):  
Shan-Min Xu ◽  
Hui Duan ◽  
Ji-Lei Shi ◽  
Tong-Tong Zuo ◽  
Xin-Cheng Hu ◽  
...  
Keyword(s):  
Solid Electrolyte ◽  
Solid Electrolyte Interphase ◽  
Lithium Metal ◽  
Lithium Metal Anodes ◽  
Long Life ◽  
Metal Anodes

Synchrotron Imaging of Li Metal Anodes in Solid State Batteries Aided by Machine Learning

2020 ◽  
Author(s):  
Marm Dixit ◽  
Ankit Verma ◽  
Wahid Zaman ◽  
Xinlin Zhong ◽  
Peter Kenesei ◽  
...  
Keyword(s):  
Machine Learning ◽  
Mechanical Properties ◽  
Solid Electrolyte ◽  
Effective Properties ◽  
Local Stress ◽  
High Rate ◽  
Lithium Metal ◽  
Morphological Transformations ◽  
Physical And Chemical ◽  
Metal Anodes

Reversible lithium metal anodes that can achieve high rate capabilities are necessary for next generation energy storage systems. Solid electrolyte can act as a barrier for unwanted physical and chemical decomposition that lead to unstable electrodeposition (e.g. dendrite and filament growth). The formation and growth of filaments is tied to unique chemo-mechanical properties that exists at buried solid|solid interfaces. Herein,<i> in situ</i> tomography of Li|LLZO|Li cells is carried out to track morphological transformations in Li metal electrodes and buried solid|solid interfaces during stripping and plating processes. Optimized experimental parameters provide high resolution, high contrast reconstructions that enable lithium metal visualization. Machine learning and image processing tools are combined to quantify changes in lithium metal during stripping and plating. The analysis enables quantifying local current densities and pore size distribution in lithium metal during cycling experiments. Hotspots in lithium metal are correlated with microstructural anisotropy in the solid electrolyte. Modeling studies show large heterogeneity in transport and mechanical properties of electrolyte at the electrode|electrolyte interfaces. Regions with lower effective properties (transport and mechanical) are nuclei for failure. Failure is attributed to microstructural heterogeneities in the solid electrolyte that lead to high local stress and flux distributions.

Synchrotron Imaging of Li Metal Anodes in Solid State Batteries Aided by Machine Learning

2020 ◽  
Author(s):  
Marm Dixit ◽  
Ankit Verma ◽  
Wahid Zaman ◽  
Xinlin Zhong ◽  
Peter Kenesei ◽  
...  
Keyword(s):  
Machine Learning ◽  
Mechanical Properties ◽  
Solid Electrolyte ◽  
Effective Properties ◽  
Local Stress ◽  
High Rate ◽  
Lithium Metal ◽  
Morphological Transformations ◽  
Physical And Chemical ◽  
Metal Anodes

Reversible lithium metal anodes that can achieve high rate capabilities are necessary for next generation energy storage systems. Solid electrolyte can act as a barrier for unwanted physical and chemical decomposition that lead to unstable electrodeposition (e.g. dendrite and filament growth). The formation and growth of filaments is tied to unique chemo-mechanical properties that exists at buried solid|solid interfaces. Herein,<i> in situ</i> tomography of Li|LLZO|Li cells is carried out to track morphological transformations in Li metal electrodes and buried solid|solid interfaces during stripping and plating processes. Optimized experimental parameters provide high resolution, high contrast reconstructions that enable lithium metal visualization. Machine learning and image processing tools are combined to quantify changes in lithium metal during stripping and plating. The analysis enables quantifying local current densities and pore size distribution in lithium metal during cycling experiments. Hotspots in lithium metal are correlated with microstructural anisotropy in the solid electrolyte. Modeling studies show large heterogeneity in transport and mechanical properties of electrolyte at the electrode|electrolyte interfaces. Regions with lower effective properties (transport and mechanical) are nuclei for failure. Failure is attributed to microstructural heterogeneities in the solid electrolyte that lead to high local stress and flux distributions.

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