248 Li transport analysis in the charge-discharge process in 3D aggregation structures of Li-ion battery

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.

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Lithium-Rich Cobalt-Free Manganese-Based Layered Cathode Materials for Li-Ion Batteries: Suppressing the Voltage Fading

Energies ◽

10.3390/en13133487 ◽

2020 ◽

Vol 13 (13) ◽

pp. 3487

Author(s):

Ashraf Abdel-Ghany ◽

Ahmed M. Hashem ◽

Alain Mauger ◽

Christian M. Julien

Keyword(s):

Layered Structure ◽

Performance Enhancement ◽

Electrochemical Impedance ◽

Discharge Process ◽

High Porosity ◽

Li Ion Batteries ◽

Hydrothermal Route ◽

Li Ion ◽

Fading Rate ◽

Charge Discharge

Lithium-rich layered oxides are recognized as promising materials for Li-ion batteries, owing to higher capacity than the currently available commercialized cathode, for their lower cost. However, their voltage decay and cycling instability during the charge/discharge process are problems that need to be solved before their practical application can be envisioned. These problems are mainly associated with a phase transition of the surface layer from the layered structure to the spinel structure. In this paper, we report the AlF3-coating of the Li-rich Co-free layered Li1.2Ni0.2Mn0.6O2 (LLNMO) oxide as an effective strategy to solve these problems. The samples were synthesized via the hydrothermal route that insures a very good crystallization in the layered structure, probed by XRD, energy-dispersive X-ray (EDX) spectroscopy, and Raman spectroscopy. The hydrothermally synthesized samples before and after AlF3 coating are well crystallized in the layered structure with particle sizes of about 180 nm (crystallites of ~65 nm), with high porosity (pore size 5 nm) determined by Brunauer–Emmett–Teller (BET) specific surface area method. Subsequent improvements in discharge capacity are obtained with a ~5-nm thick coating layer. AlF3-coated Li1.2Ni0.2Mn0.6O2 delivers a capacity of 248 mAh g−1 stable over the 100 cycles, and it exhibits a voltage fading rate of 1.40 mV per cycle. According to the analysis from galvanostatic charge-discharge and electrochemical impedance spectroscopy, the electrochemical performance enhancement is discussed and compared with literature data. Post-mortem analysis confirms that the AlF3 coating is a very efficient surface modification to improve the stability of the layered phase of the Li-rich material, at the origin of the significant improvement of the electrochemical properties.

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Machine Learning Approaches for Designing Mesoscale Structure of Li-Ion Battery Electrodes

Batteries ◽

10.3390/batteries5030054 ◽

2019 ◽

Vol 5 (3) ◽

pp. 54 ◽

Cited By ~ 5

Author(s):

Yoichi Takagishi ◽

Takumi Yamanaka ◽

Tatsuya Yamaue

Keyword(s):

Machine Learning ◽

Process Parameters ◽

Volume Fraction ◽

Specific Resistance ◽

Active Material ◽

Li Ion Battery ◽

Battery Electrode ◽

Li Ion ◽

Simulation Results ◽

Charge Discharge

We have proposed a data-driven approach for designing the mesoscale porous structures of Li-ion battery electrodes, using three-dimensional virtual structures and machine learning techniques. Over 2000 artificial 3D structures, assuming a positive electrode composed of randomly packed spheres as the active material particles, are generated, and the charge/discharge specific resistance has been evaluated using a simplified physico-chemical model. The specific resistance from Li diffusion in the active material particles (diffusion resistance), the transfer specific resistance of Li+ in the electrolyte (electrolyte resistance), and the reaction resistance on the interface between the active material and electrolyte are simulated, based on the mass balance of Li, Ohm’s law, and the linearized Butler–Volmer equation, respectively. Using these simulation results, regression models, using an artificial neural network (ANN), have been created in order to predict the charge/discharge specific resistance from porous structure features. In this study, porosity, active material particle size and volume fraction, pressure in the compaction process, electrolyte conductivity, and binder/additives volume fraction are adopted, as features associated with controllable process parameters for manufacturing the battery electrode. As a result, the predicted electrode specific resistance by the ANN regression model is in good agreement with the simulated values. Furthermore, sensitivity analyses and an optimization of the process parameters have been carried out. Although the proposed approach is based only on the simulation results, it could serve as a reference for the determination of process parameters in battery electrode manufacturing.

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Influence of Heat Treatment on Charge/Discharge Characteristics of Sn-Ag Alloy Plating Films for Li-Ion Battery Anode

ECS Meeting Abstracts ◽

10.1149/ma2014-02/49/2185 ◽

2014 ◽

Keyword(s):

Heat Treatment ◽

Li Ion Battery ◽

Discharge Characteristics ◽

Li Ion ◽

Alloy Plating ◽

Battery Anode ◽

Charge Discharge

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(Invited) Operando Analysis for Charge/Discharge Reaction Mechanism of Graphite Anode of Li Ion Battery

ECS Meeting Abstracts ◽

10.1149/ma2019-02/5/266 ◽

2019 ◽

Keyword(s):

Reaction Mechanism ◽

Graphite Anode ◽

Li Ion Battery ◽

Li Ion ◽

Charge Discharge ◽

Discharge Reaction

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Effect of High Loading Glycine on Fe2O3 Nano Oval as Anode for Lithium-Ion Battery

Materials Science Forum ◽

10.4028/www.scientific.net/msf.964.215 ◽

2019 ◽

Vol 964 ◽

pp. 215-220

Author(s):

Lukman Noerochim ◽

Agny Muchamad Reza ◽

Budi Agung

Keyword(s):

Lithium Ion Battery ◽

Discharge Capacity ◽

Lithium Ion ◽

Nyquist Plot ◽

Discharge Process ◽

Promising Candidate ◽

Hydrothermal Temperature ◽

Specific Discharge ◽

Li Ion ◽

Charge Discharge

In this work, Fe2O3 nanooval is successfully synthesized with variation of glycine composition of 9, 12, and 15 mmol at hydrothermal temperature of 160 °C. The Fe2O3 nanooval is indexed by XRD as α-Fe2O3. SEM and TEM images show that the 12 mmol of glycine has the largest diameter with the perfect nanooval form. Nyquist plot shows that the 12 mmol of glycine sample has the best conductivity value of 8.26x10-5 S/m. The CV of sample 12 mmol delivers the best intercalate/de-intercalate with ΔV of 0.82 V. The 12 mmol sample shows the largest specific discharge capacity of 631.62 mAh/g. It is attributed to high conductivity and high kinetics reaction of Li ion during charge-discharge process. Therefore, Fe2O3 nanooval is a promising candidate as anode for lithium-ion battery.

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