scholarly journals Quantum chemical calculations of lithium-ion battery electrolyte and interphase species

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Evan Walter Clark Spotte-Smith ◽  
Samuel M. Blau ◽  
Xiaowei Xie ◽  
Hetal D. Patel ◽  
Mingjian Wen ◽  
...  

AbstractLithium-ion batteries (LIBs) represent the state of the art in high-density energy storage. To further advance LIB technology, a fundamental understanding of the underlying chemical processes is required. In particular, the decomposition of electrolyte species and associated formation of the solid electrolyte interphase (SEI) is critical for LIB performance. However, SEI formation is poorly understood, in part due to insufficient exploration of the vast reactive space. The Lithium-Ion Battery Electrolyte (LIBE) dataset reported here aims to provide accurate first-principles data to improve the understanding of SEI species and associated reactions. The dataset was generated by fragmenting a set of principal molecules, including solvents, salts, and SEI products, and then selectively recombining a subset of the fragments. All candidate molecules were analyzed at the ωB97X-V/def2-TZVPPD/SMD level of theory at various charges and spin multiplicities. In total, LIBE contains structural, thermodynamic, and vibrational information on over 17,000 unique species. In addition to studies of reactivity in LIBs, this dataset may prove useful for machine learning of molecular and reaction properties.

2021 ◽  
Author(s):  
Evan Walter Clark Spotte-Smith ◽  
Samuel Blau ◽  
Xiaowei Xie ◽  
Hetal Patel ◽  
Mingjian Wen ◽  
...  

Lithium-ion batteries (LIBs) represent the state of the art in high-density energy storage. To further advance LIB technology, a fundamental understanding of the underlying chemical processes is required. In particular, the decomposition of electrolyte species and associated formation of the solid electrolyte interphase (SEI) is critical for LIB performance. However, SEI formation is poorly understood, in part due to insufficient exploration of the vast reactive space. The Lithium-Ion Battery Electrolyte(LIBE) dataset reported here aims to provide accurate first-principles data to improve the understanding of SEI species and associated reactions. The dataset was generated by fragmenting a set of principal molecules, including solvents, salts, and SEI products, and then selectively recombining a subset of the fragments. All candidate molecules were analyzed at the ωB97X-V/def2-TZVPPD/SMD level of theory at various charges and spin multiplicities. In total, LIBE contains structural,thermodynamic, and vibrational information on over 17,000 unique species. In addition to studies of reactivity in LIBs, this dataset may prove useful for machine learning of molecular and reaction properties.


2021 ◽  
Author(s):  
Evan Walter Clark Spotte-Smith ◽  
Samuel Blau ◽  
Xiaowei Xie ◽  
Hetal Patel ◽  
Mingjian Wen ◽  
...  

Lithium-ion batteries (LIBs) represent the state of the art in high-density energy storage. To further advance LIB technology, a fundamental understanding of the underlying chemical processes is required. In particular, the decomposition of electrolyte species and associated formation of the solid electrolyte interphase (SEI) is critical for LIB performance. However, SEI formation is poorly understood, in part due to insufficient exploration of the vast reactive space. The Lithium-Ion Battery Electrolyte(LIBE) dataset reported here aims to provide accurate first-principles data to improve the understanding of SEI species and associated reactions. The dataset was generated by fragmenting a set of principal molecules, including solvents, salts, and SEI products, and then selectively recombining a subset of the fragments. All candidate molecules were analyzed at the ωB97X-V/def2-TZVPPD/SMD level of theory at various charges and spin multiplicities. In total, LIBE contains structural,thermodynamic, and vibrational information on over 17,000 unique species. In addition to studies of reactivity in LIBs, this dataset may prove useful for machine learning of molecular and reaction properties.


2021 ◽  
Author(s):  
Evan Walter Clark Spotte-Smith ◽  
Samuel Blau ◽  
Xiaowei Xie ◽  
Hetal Patel ◽  
Mingjian Wen ◽  
...  

Lithium-ion batteries (LIBs) represent the state of the art in high-density energy storage. To further advance LIB technology, a fundamental understanding of the underlying chemical processes is required. In particular, the decomposition of electrolyte species and associated formation of the solid electrolyte interphase (SEI) is critical for LIB performance. However, SEI formation is poorly understood, in part due to insufficient exploration of the vast reactive space. The Lithium-Ion Battery Electrolyte(LIBE) dataset reported here aims to provide accurate first-principles data to improve the understanding of SEI species and associated reactions. The dataset was generated by fragmenting a set of principal molecules, including solvents, salts, and SEI products, and then selectively recombining a subset of the fragments. All candidate molecules were analyzed at theωB97X-V/def2-TZVPPD/SMD level of theory at various charges and spin multiplicities. In total, LIBE contains structural,thermodynamic, and vibrational information on over 17,000 unique species. In addition to studies of reactivity in LIBs, this dataset may prove useful for machine learning of molecular and reaction properties.


2021 ◽  
Author(s):  
Evan Walter Clark Spotte-Smith ◽  
Samuel Blau ◽  
Xiaowei Xie ◽  
Hetal Patel ◽  
Mingjian Wen ◽  
...  

Lithium-ion batteries (LIBs) represent the state of the art in high-density energy storage. To further advance LIB technology, a fundamental understanding of the underlying chemical processes is required. In particular, the decomposition of electrolyte species and associated formation of the solid electrolyte interphase (SEI) is critical for LIB performance. However, SEI formation is poorly understood, in part due to insufficient exploration of the vast reactive space. The Lithium-Ion Battery Electrolyte(LIBE) dataset reported here aims to provide accurate first-principles data to improve the understanding of SEI species and associated reactions. The dataset was generated by fragmenting a set of principal molecules, including solvents, salts, and SEI products, and then selectively recombining a subset of the fragments. All candidate molecules were analyzed at theωB97X-V/def2-TZVPPD/SMD level of theory at various charges and spin multiplicities. In total, LIBE contains structural,thermodynamic, and vibrational information on over 17,000 unique species. In addition to studies of reactivity in LIBs, this dataset may prove useful for machine learning of molecular and reaction properties.


2020 ◽  
Vol 59 (15) ◽  
pp. 6128-6137 ◽  
Author(s):  
Jonas Henschel ◽  
Christoph Peschel ◽  
Sven Klein ◽  
Fabian Horsthemke ◽  
Martin Winter ◽  
...  

2015 ◽  
Vol 3 (36) ◽  
pp. 18657-18666 ◽  
Author(s):  
Yang Yang ◽  
Fangcai Zheng ◽  
Guoliang Xia ◽  
Zhengyan Lun ◽  
Qianwang Chen

The lithium adsorption abilities of various functional groups (NH2, NO2, SO3H, Cl, Br, I) are studied by first-principles quantum chemical calculations which are doped at the edge of graphene sheets. Among all the groups, the nitro-group shows the best properties.


2020 ◽  
Vol 132 (15) ◽  
pp. 6184-6193 ◽  
Author(s):  
Jonas Henschel ◽  
Christoph Peschel ◽  
Sven Klein ◽  
Fabian Horsthemke ◽  
Martin Winter ◽  
...  

2021 ◽  
Vol 23 (6) ◽  
pp. 4030-4038
Author(s):  
Xinghui Liu ◽  
Shiru Lin ◽  
Jian Gao ◽  
Hu Shi ◽  
Seong-Gon Kim ◽  
...  

Simple carbon (nitrogen) doped Mo2P as promoting lithium-ion battery anode materials with extremely low energy barrier and high capacity.


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