scholarly journals Chemical Decomposition of the TFSI Anion Under Aqueous Basic Conditions

Author(s):  
Arthur France-Lanord ◽  
Fabio Pietrucci ◽  
A. Marco Saitta ◽  
Jean-Marie Tarascon ◽  
Alexis Grimaud ◽  
...  

Understanding the interfacial reactivity of aqueous electrolytes is crucial for their use in future batteries. We investigate the reactivity of the bis(trifluoromethane)sulfonimide (TFSI) anion when exposed to a strong alkaline medium, by means of ab initio molecular dynamics and enhanced sampling techniques. In particular, we study the nucleophilic attack by the hydroxide anion, which was proposed as a mechanism for the formation of the solid electrolyte interphase at the negative electrode with water-in-salt electrolytes. While in the gas phase we recover a stable gaseous product, namely fluoroform, we observe the formation of trifluoromethanol in strong basic conditions, which then rapidly deprotonates to form CF3O-. This anion was suggested recently as a key compound leading to the formation of a solid electrolyte interphase on an Si-C anode. Such an approach could be leveraged to discover convenient additives leading to the formation of a stable interphase.

2006 ◽  
Vol 161 (2) ◽  
pp. 1275-1280 ◽  
Author(s):  
Liwei Zhao ◽  
Izumi Watanabe ◽  
Takayuki Doi ◽  
Shigeto Okada ◽  
Jun-ichi Yamaki

2020 ◽  
Author(s):  
Samuel Blau ◽  
Hetal Patel ◽  
Evan Spotte-Smith ◽  
Xiaowei Xie ◽  
Shyam Dwaraknath ◽  
...  

Modeling reactivity with chemical reaction networks could yield fundamental mechanistic understanding that would expedite the development of processes and technologies for energy storage, medicine, catalysis, and more. Thus far, reaction networks have been limited in size by chemically inconsistent graph representations of multi-reactant reactions (e.g. A + B reacts to C) that cannot enforce stoichiometric constraints, precluding the use of optimized shortest-path algorithms. Here, we report a chemically consistent graph architecture that overcomes these limitations using a novel multi-reactant representation and iterative cost-solving procedure. Our approach enables the identification of all low-cost pathways to desired products in massive reaction networks containing reactions of any stoichiometry, allowing for the investigation of vastly more complex systems than previously possible. Leveraging our architecture, we construct the first ever electrochemical reaction network from first-principles thermodynamic calculations to describe the formation of the Li-ion solid electrolyte interphase (SEI), which is critical for passivation of the negative electrode. Using this network comprised of nearly 6,000 species and 4.5 million reactions, we interrogate the formation of a key SEI component, lithium ethylene dicarbonate. We automatically identify previously proposed mechanisms as well as multiple novel pathways containing counter-intuitive reactions that have not, to our knowledge, been reported in the literature. We envision that our framework and data-driven methodology will facilitate efforts to engineer the composition-related properties of the SEI - or of any complex chemical process - through selective control of reactivity.


2013 ◽  
Vol 160 (9) ◽  
pp. A1539-A1543 ◽  
Author(s):  
Hosang Park ◽  
Taeho Yoon ◽  
Junyoung Mun ◽  
Ji Heon Ryu ◽  
Jae Jeong Kim ◽  
...  

2020 ◽  
Author(s):  
Samuel Blau ◽  
Hetal Patel ◽  
Evan Spotte-Smith ◽  
Xiaowei Xie ◽  
Shyam Dwaraknath ◽  
...  

Modeling reactivity with chemical reaction networks could yield fundamental mechanistic understanding that would expedite the development of processes and technologies for energy storage, medicine, catalysis, and more. Thus far, reaction networks have been limited in size by chemically inconsistent graph representations of multi-reactant reactions (e.g. A + B reacts to C) that cannot enforce stoichiometric constraints, precluding the use of optimized shortest-path algorithms. Here, we report a chemically consistent graph architecture that overcomes these limitations using a novel multi-reactant representation and iterative cost-solving procedure. Our approach enables the identification of all low-cost pathways to desired products in massive reaction networks containing reactions of any stoichiometry, allowing for the investigation of vastly more complex systems than previously possible. Leveraging our architecture, we construct the first ever electrochemical reaction network from first-principles thermodynamic calculations to describe the formation of the Li-ion solid electrolyte interphase (SEI), which is critical for passivation of the negative electrode. Using this network comprised of nearly 6,000 species and 4.5 million reactions, we interrogate the formation of a key SEI component, lithium ethylene dicarbonate. We automatically identify previously proposed mechanisms as well as multiple novel pathways containing counter-intuitive reactions that have not, to our knowledge, been reported in the literature. We envision that our framework and data-driven methodology will facilitate efforts to engineer the composition-related properties of the SEI - or of any complex chemical process - through selective control of reactivity.


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