scholarly journals Mechanical properties of Li–Sn alloys for Li-ion battery anodes: A first-principles perspective

AIP Advances ◽  
2016 ◽  
Vol 6 (1) ◽  
pp. 015107 ◽  
Author(s):  
Panpan Zhang ◽  
Zengsheng Ma ◽  
Wenjuan Jiang ◽  
Yan Wang ◽  
Yong Pan ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
First Principles ◽  
Li Ion Battery ◽  
Li Ion

MoS2/Graphene Heterostructure Anode for Li-Ion Battery Application: A First-Principles Study

2021 ◽  
Vol 896 ◽  
pp. 53-59
Author(s):  
Yi Yang Shen
Keyword(s):  
Density Of States ◽  
First Principles ◽  
Open Circuit Voltage ◽  
Discharge Rate ◽  
Open Circuit ◽  
Crystal Formation ◽  
Li Ion Battery ◽  
Li Ion ◽  
Battery Anode ◽  
Charge Discharge

The development of next generation Li ion battery has attracted many attentions of researchers due to the rapidly increasing demands to portable energy storage devices. General Li metal/alloy anodes are confronted with challenges of dendritic crystal formation and slow charge/discharge rate. Recently, the prosperity of two-dimensional materials opens a new window for the design of battery anode. In the present study, MoS2/graphene heterostructure is investigate for the anode application of Li ion battery using first-principles calculations. The Li binding energy, open-circuit voltage, and electronic band structures are acquired for various Li concentrations. We found the open-circuit voltage decreases from ~2.28 to ~0.4 V for concentration from 0 to 1. Density of states show the electrical conductivity of the intercalated heterostructures can be significantly enhanced. The charge density differences are used to explain the variations of voltage and density of states. Last, ~0.43 eV diffusion energy barrier of Li implies the possible fast charge/discharge rate. Our study indicate MoS2/graphene heterostructure is promising material as Li ion battery anode.

First-Principles Study of EMIM-FAFSA Molecule Adsorption on a Li(100) Surface as a Model for Li-Ion Battery Electrodes

2012 ◽  
Vol 116 (15) ◽  
pp. 8493-8509 ◽  
Author(s):  
Hubert Valencia ◽  
Masanori Kohyama ◽  
Shingo Tanaka ◽  
Hajime Matsumoto
Keyword(s):  
First Principles ◽  
Li Ion Battery ◽  
First Principles Study ◽  
Molecule Adsorption ◽  
Li Ion

scholarly journals Identification of Li-ion battery models through monotonic echo serial networks for coarse data

2020 ◽  
Vol 28 (1) ◽  
pp. 109-120
Author(s):  
Antonio Álvarez-Caballero ◽  
Cecilio Blanco ◽  
Inés Couso ◽  
Luciano Sánchez
Keyword(s):  
First Principles ◽  
Experimental Validation ◽  
Expert Knowledge ◽  
Rechargeable Batteries ◽  
Li Ion Battery ◽  
Monotone Transformation ◽  
Battery Model ◽  
Inaccurate Data ◽  
Li Ion ◽  
Better Than

Abstract Monotone transformation models are extended to inaccurate data and are combined with recurrent neural networks in a new battery model that is able to ascertain the health of rechargeable batteries for automotive applications. The presented method exploits the information contained in the vehicle’s operational records better than other cutting-edge models and uses a minimum amount of human expert knowledge. The experimental validation of the technique includes a comparative analysis of batteries in different health conditions, comprising first-principles models and different machine learning procedures.

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