scholarly journals Effects of Coated Separator Surface Morphology on Electrolyte Interfacial Wettability and Corresponding Li–Ion Battery Performance

Polymers ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 117 ◽  
Author(s):  
Ruijie Xu ◽  
Henghui Huang ◽  
Ziqin Tian ◽  
Jiayi Xie ◽  
Caihong Lei
Keyword(s):  
Free Energy ◽  
Polyvinylidene Fluoride ◽  
Rate Capability ◽  
Lithium Ion ◽  
Cell Performance ◽  
Li Ion Battery ◽  
Particle Accumulation ◽  
Li Ion ◽  
Coated Separator ◽  
Better Than

In order to study the effect of interfacial wettability of separator on electrochemical properties for lithium–ion batteries, two different kinds of polyvinylidene fluoride-hexafluoropropylene (PVDF–HFP) solution are prepared and used to coat onto a polypropylene (PP) microporous membrane. It is found that the cell performance of a coated separator using aqueous slurry (WPS) is better than that of the coated separator using acetone (APS) as the solvent. The separator with flat and pyknotic surface (PP and APS) has a strong polar action with the electrolyte, where the polar part is more than 80%. To the contrary, the WPS has a roughness surface and when the PVDF–HFP particles accumulate loose, it makes the apolar part plays a dominate role in surface free energy; the dispersive energy reaches to 40.17 mJ m−2. The WPS has the lowest immersion free energy, 31.9 mJ m−2 with the electrolyte, and this will accelerate electrolyte infiltration to the separator. The loose particle accumulation also increases the electrolyte weight uptake and interfacial wettability velocity, which plays a crucial role in improving the cell performance such as the ionic conductivity, discharge capacity and the C-rate capability.

Crumpled N-doped carbon nanotubes encapsulated with peapod-like Ge nanoparticles for high-rate and long-life Li-ion battery anodes

2016 ◽  
Vol 4 (20) ◽  
pp. 7585-7590 ◽  
Author(s):  
Kaifu Huo ◽  
Lei Wang ◽  
Changjian Peng ◽  
Xiang Peng ◽  
Yuanyuan Li ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Lithium Ion Batteries ◽  
High Performance ◽  
High Capacity ◽  
Rate Capability ◽  
Lithium Ion ◽  
High Rate ◽  
Li Ion Battery ◽  
Li Ion ◽  
Long Life

Peapod-like Ge/CNx is designed as a high-performance anode for lithium-ion batteries, which boasts high capacity, excellent cyclability and rate capability.

scholarly journals A Commercial Carbonaceous Anode with a-Si Layers by Plasma Enhanced Chemical Vapor Deposition for Lithium Ion Batteries

2020 ◽  
Vol 4 (2) ◽  
pp. 72
Author(s):  
Chao-Yu Lee ◽  
Fa-Hsing Yeh ◽  
Ing-Song Yu
Keyword(s):  
Chemical Vapor Deposition ◽  
Vapor Deposition ◽  
Coulombic Efficiency ◽  
Low Cost ◽  
Specific Capacity ◽  
Rate Capability ◽  
Lithium Ion ◽  
Chemical Vapor ◽  
Li Ion Battery ◽  
Li Ion

In this study, we propose a mass production-able and low-cost method to fabricate the anodes of Li-ion battery. Carbonaceous anodes, integrated with thin amorphous silicon layers by plasma enhanced chemical vapor deposition, can improve the performance of specific capacity and coulombic efficiency for Li-ion battery. Three different thicknesses of a-Si layers (320, 640, and 960 nm), less than 0.1 wt% of anode electrode, were deposited on carbonaceous electrodes at low temperature 200 °C. Around 30 mg of a-Si by plasma enhanced chemical vapor deposition (PECVD) can improve the specific capacity ~42%, and keep coulombic efficiency of the half Li-ion cells higher than 85% after first cycle charge-discharge test. For the thirty cyclic performance and rate capability, capacitance retention can maintain above 96%. The thicker a-Si layers on carbon anodes, the better electrochemical performance of anodes with silicon-carbon composites we get. The traditional carbonaceous electrodes can be deposited a-Si layers easily by plasma enhanced chemical vapor deposition, which is a method with high potential for industrialization.

Hierarchically porous nitrogen-rich carbon derived from wheat straw as an ultra-high-rate anode for lithium ion batteries

2014 ◽  
Vol 2 (25) ◽  
pp. 9684-9690 ◽  
Author(s):  
Li Chen ◽  
Yongzhi Zhang ◽  
Chaohong Lin ◽  
Wen Yang ◽  
Yan Meng ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Wheat Straw ◽  
Specific Capacity ◽  
Rate Capability ◽  
Lithium Ion ◽  
High Rate ◽  
Li Ion Battery ◽  
Hierarchically Porous ◽  
Li Ion ◽  
Battery Anode

Hierarchically porous nitrogen-rich carbon derived from wheat straw presents an impressive specific capacity and ultrahigh rate capability as a Li-ion battery anode.

Study of LiFePO4 Electrode Morphology for Li-Ion Battery Performance

2018 ◽  
Vol 69 (3) ◽  
pp. 549-552
Author(s):  
Mihaela Buga ◽  
Alexandru Rizoiu ◽  
Constantin Bubulinca ◽  
Silviu Badea ◽  
Mihai Balan ◽  
...  
Keyword(s):  
Polyvinylidene Fluoride ◽  
Lithium Iron Phosphate ◽  
Lithium Ion ◽  
Iron Phosphate ◽  
Li Ion Battery ◽  
X Ray Diffraction ◽  
Industry Standard ◽  
Lithium Ion Cells ◽  
Eds Analysis ◽  
Li Ion

The paper focuses on the development of lithium-ion battery cathode based on lithium iron phosphate (LiFePO4). Li-ion battery cathodes were manufactured using the new Battery R&D Production Line from ROM-EST Centre, the first and only facility in Romania, capable of fabricating the industry standard 18650 lithium-ion cells, customized pouch cells and CR2032 cells. The cathode configuration contains acetylene black (AB), LiFePO4, polyvinylidene fluoride (PVdF) as binder and N-Methyl-2-pyrrolidone (NMP) as solvent. X-ray diffraction measurements and SEM-EDS analysis were conducted to obtain structural and morphological information for the as-prepared electrodes.

Enhancing Co/Co2VO4 Li-ion Battery Anode Performances via 2D-2D Heterostructure Engineering

Nanoscale ◽  
2021 ◽  
Author(s):  
Kun Wang ◽  
Yongyuan Hu ◽  
Jian Pei ◽  
Fengyang Jing ◽  
Zhongzheng Qin ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Anode Material ◽  
Output Voltage ◽  
High Capacity ◽  
Lithium Ion ◽  
Li Ion Battery ◽  
Li Ion ◽  
Battery Anode

High capacity Co2VO4 becomes a potential anode material for lithium ion batteries (LIBs) benefiting from its lower output voltage during cycling than other cobalt vanadates. However, the application of this...

Real-Time Estimation of Lithium-Ion Concentration in Both Electrodes of a Lithium-Ion Battery Cell Utilizing Electrochemical–Thermal Coupling

2017 ◽  
Vol 139 (3) ◽  
Author(s):  
Satadru Dey ◽  
Beshah Ayalew
Keyword(s):  
Real Time ◽  
Unscented Kalman Filter ◽  
Lithium Ion ◽  
Time Estimation ◽  
Li Ion Battery ◽  
Battery Cell ◽  
Thermal Dynamics ◽  
Estimation Scheme ◽  
Real Time Estimation ◽  
Li Ion

This paper proposes and demonstrates an estimation scheme for Li-ion concentrations in both electrodes of a Li-ion battery cell. The well-known observability deficiencies in the two-electrode electrochemical models of Li-ion battery cells are first overcome by extending them with a thermal evolution model. Essentially, coupling of electrochemical–thermal dynamics emerging from the fact that the lithium concentrations contribute to the entropic heat generation is utilized to overcome the observability issue. Then, an estimation scheme comprised of a cascade of a sliding-mode observer and an unscented Kalman filter (UKF) is constructed that exploits the resulting structure of the coupled model. The approach gives new real-time estimation capabilities for two often-sought pieces of information about a battery cell: (1) estimation of cell-capacity and (2) tracking the capacity loss due to degradation mechanisms such as lithium plating. These capabilities are possible since the two-electrode model needs not be reduced further to a single-electrode model by adding Li conservation assumptions, which do not hold with long-term operation. Simulation studies are included for the validation of the proposed scheme. Effect of measurement noise and parametric uncertainties is also included in the simulation results to evaluate the performance of the proposed scheme.

Effects of SiO2 particles in copper current collector on diffusion induced stresses in layered Li-ion battery electrodes

2021 ◽  
pp. 095440622110036
Author(s):  
Roozbeh Pouyanmehr ◽  
Morteza Pakseresht ◽  
Reza Ansari ◽  
Mohammad Kazem Hassanzadeh-Aghdam
Keyword(s):  
Volume Fraction ◽  
Lithium Ion ◽  
Current Collector ◽  
Limiting Factors ◽  
Li Ion Battery ◽  
Current Collectors ◽  
Effect Of Particle Size ◽  
Li Ion ◽  
Induced Stresses ◽  
Copper Composite

One of the limiting factors in the life of lithium-ion batteries is the diffusion-induced stresses on their electrodes that cause cracking and consequently, failure. Therefore, improving the structure of these electrodes to be able to withstand these stresses is one of the ways that can extend the life of the batteries as well as improve their safety. In this study, the effects of adding graphene nanoplatelets and microparticles into the active plate and current collectors, respectively, on the diffusion induced stresses in both layered and bilayered electrodes are numerically investigated. The micromechanical models are employed to predict the mechanical properties of both graphene nanoplatelet-reinforced Sn-based nanocomposite active plate and silica microparticle-reinforced copper composite current collector. The effect of particle size and volume fraction in the current collector on diffusion induced stresses has been studied. The results show that in electrodes with a higher volume fraction of particles and smaller particle radii, decreased diffusion induced stresses in both the active plate and the current collector are observed. These additions will also result in a significant decrease in the bending of the electrode.

Online Estimation of Lithium-Ion Battery Capacity Using Deep Convolutional Neural Networks

2018 ◽  
Author(s):  
Sheng Shen ◽  
M. K. Sadoughi ◽  
Xiangyi Chen ◽  
Mingyi Hong ◽  
Chao Hu
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Convolutional Neural Networks ◽  
Lithium Ion ◽  
Relevance Vector Machine ◽  
Rechargeable Batteries ◽  
Li Ion Battery ◽  
Deep Convolutional Neural Networks ◽  
Battery Capacity ◽  
Li Ion

Over the past two decades, safety and reliability of lithium-ion (Li-ion) rechargeable batteries have been receiving a considerable amount of attention from both industry and academia. To guarantee safe and reliable operation of a Li-ion battery pack and build failure resilience in the pack, battery management systems (BMSs) should possess the capability to monitor, in real time, the state of health (SOH) of the individual cells in the pack. This paper presents a deep learning method, named deep convolutional neural networks, for cell-level SOH assessment based on the capacity, voltage, and current measurements during a charge cycle. The unique features of deep convolutional neural networks include the local connectivity and shared weights, which enable the model to estimate battery capacity accurately using the measurements during charge. To our knowledge, this is the first attempt to apply deep learning to online SOH assessment of Li-ion battery. 10-year daily cycling data from implantable Li-ion cells are used to verify the performance of the proposed method. Compared with traditional machine learning methods such as relevance vector machine and shallow neural networks, the proposed method is demonstrated to produce higher accuracy and robustness in capacity estimation.

Sign in / Sign up

Export Citation Format

Share Document