Li2O2 as a cathode additive for the initial anode irreversibility compensation in lithium-ion batteries

2017 ◽  
Vol 53 (59) ◽  
pp. 8324-8327 ◽  
Author(s):  
Yitian Bie ◽  
Jun Yang ◽  
Jiulin Wang ◽  
Jingjing Zhou ◽  
Yanna Nuli
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Li Ion Batteries ◽  
Li Ion ◽  
Cathode Additive

Li2O2 is proposed as a promising cathode additive to compensate the first cycle Li loss in Li-ion batteries.

Self-sacrificial organic lithium salt enhanced initial Coulombic efficiency for safer and greener lithium-ion batteries

2019 ◽  
Vol 55 (72) ◽  
pp. 10737-10739 ◽  
Author(s):  
Dapeng Wang ◽  
Zhian Zhang ◽  
Bo Hong ◽  
Yanqing Lai
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Salt ◽  
Coulombic Efficiency ◽  
Lithium Ion ◽  
Li Ion Batteries ◽  
Li Ion ◽  
Cathode Additive ◽  
Initial Coulombic Efficiency

Li2DHBA is proposed as a cathode additive that leaves no residue to compensate for first cycle Li loss in Li-ion batteries.

Overcharge protection of lithium-ion batteries with phenothiazine redox shuttles

2021 ◽  
Author(s):  
Susan A. Odom
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Li Ion Batteries ◽  
Phenothiazine Derivatives ◽  
Redox Shuttles ◽  
Li Ion ◽  
Overcharge Protection

Overcharge protection of Li-ion batteries with a variety of phenothiazine derivatives.

scholarly journals Parameter optimization and yield prediction of cathode coating separation process for direct recycling of end-of-life lithium-ion batteries

RSC Advances ◽  
2021 ◽  
Vol 11 (39) ◽  
pp. 24132-24136
Author(s):  
Liurui Li ◽  
Tairan Yang ◽  
Zheng Li
Keyword(s):  
Lithium Ion Batteries ◽  
End Of Life ◽  
Lithium Ion ◽  
Separation Process ◽  
Yield Prediction ◽  
Li Ion Batteries ◽  
Treatment Efficiency ◽  
Control Factors ◽  
Li Ion ◽  
Pre Treatment

The pre-treatment efficiency of the direct recycling strategy in recovering end-of-life Li-ion batteries is predicted with levels of control factors.

Metal–organic nanofibers as anodes for lithium-ion batteries

RSC Advances ◽  
2015 ◽  
Vol 5 (26) ◽  
pp. 20386-20389 ◽  
Author(s):  
Chongchong Zhao ◽  
Cai Shen ◽  
Weiqiang Han
Keyword(s):  
Amino Acid ◽  
Lithium Ion Batteries ◽  
Anode Materials ◽  
Lithium Ion ◽  
Copper Nitrate ◽  
Li Ion Batteries ◽  
Metal Organic ◽  
Li Ion

Metal organic nanofibers (MONFs) synthesized from precursors of amino acid and copper nitrate were applied as anode materials for Li-ion batteries.

Alternative Anodes for Low Temperature Lithium-Ion Batteries

2021 ◽  
Author(s):  
Gearoid A Collins ◽  
Hugh Geaney ◽  
Kevin Michael Ryan
Keyword(s):  
Low Temperature ◽  
Lithium Ion Batteries ◽  
Electric Vehicles ◽  
Lithium Ion ◽  
Li Ion Batteries ◽  
Li Ion ◽  
Critical Components

Li-ion batteries (LIBs) have become critical components in the manufacture of electric vehicles (EV) as they offer the best all-round performance compared to competing battery chemistries. However, LIB performance at...

Silicon oxycarbide ceramics as anodes for lithium ion batteries: influence of carbon content on lithium storage capacity

RSC Advances ◽  
2016 ◽  
Vol 6 (106) ◽  
pp. 104597-104607 ◽  
Author(s):  
Monika Wilamowska-Zawlocka ◽  
Paweł Puczkarski ◽  
Zofia Grabowska ◽  
Jan Kaspar ◽  
Magdalena Graczyk-Zajac ◽  
...  
Keyword(s):  
Carbon Content ◽  
Lithium Ion Batteries ◽  
Storage Capacity ◽  
Lithium Ion ◽  
Silicon Oxycarbide ◽  
Synthesis And Characterization ◽  
Li Ion Batteries ◽  
Lithium Storage ◽  
Li Ion

We report here on the synthesis and characterization of silicon oxycarbide (SiOC) in view of its application as a potential anode material for Li-ion batteries.

Capacity Loss Estimation For Li-Ion Batteries Based On A Semi-Empirical Model

2021 ◽  
Author(s):  
Mohammed Rabah ◽  
Eero Immonen ◽  
Sajad Shahsavari ◽  
Mohammad-Hashem Haghbayan ◽  
Kirill Murashko ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Empirical Model ◽  
Lithium Ion ◽  
Average Error ◽  
Li Ion Batteries ◽  
Capacity Loss ◽  
Capacity Degradation ◽  
Battery Capacity ◽  
Li Ion ◽  
Semi Empirical

Understanding battery capacity degradation is instrumental for designing modern electric vehicles. In this paper, a Semi-Empirical Model for predicting the Capacity Loss of Lithium-ion batteries during Cycling and Calendar Aging is developed. In order to redict the Capacity Loss with a high accuracy, battery operation data from different test conditions and different Lithium-ion batteries chemistries were obtained from literature for parameter optimization (fitting). The obtained models were then compared to experimental data for validation. Our results show that the average error between the estimated Capacity Loss and measured Capacity Loss is less than 1.5% during Cycling Aging, and less than 2% during Calendar Aging. An electric mining dumper, with simulated duty cycle data, is considered as an application example.

scholarly journals Lithium‐Ion Batteries: Cyclic Aminosilane‐Based Additive Ensuring Stable Electrode–Electrolyte Interfaces in Li‐Ion Batteries (Adv. Energy Mater. 15/2020)

2020 ◽  
Vol 10 (15) ◽  
pp. 2070069
Author(s):  
Koeun Kim ◽  
Daeyeon Hwang ◽  
Saehun Kim ◽  
Sung O Park ◽  
Hyungyeon Cha ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Li Ion Batteries ◽  
Li Ion ◽  
Energy Mater

Prospectives for the Use of Li-Ion Batteries in Hybrid Stand-Alone Power Sources

2019 ◽  
Vol 20 (2) ◽  
Author(s):  
Sergey Khantimerov ◽  
Ranis Fatykhov ◽  
Nail Suleimanov
Keyword(s):  
Comparative Analysis ◽  
Energy Density ◽  
Service Life ◽  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Li Ion Batteries ◽  
Power Sources ◽  
Specific Energy Density ◽  
Li Ion ◽  
And Performance

Abstract In this paper, the possibility of using lithium-ion batteries in hybrid stand-alone power sources is considered. The article gives a comparative analysis of the energy and performance characteristics, the service life of lead-acid and lithium-ion batteries. It is shown that the longer service life and the specific energy density, the absence of the need for constant monitoring of the main parameters and the ability to preserve the original capacity at increased discharge currents, open the possibility of using lithium-ion batteries in hybrid stand-alone power sources.

Diagnostics and Prognostics of Lithium-Ion Batteries

2015 ◽  
Author(s):  
Zhimin Xi ◽  
Rong Jing ◽  
Cheol Lee
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Remaining Useful Life ◽  
State Of Charge ◽  
Data Driven ◽  
State Of Health ◽  
Li Ion Batteries ◽  
Battery State Of Charge ◽  
Li Ion ◽  
Useful Life

This paper investigates recent research on battery diagnostics and prognostics especially for Lithium-ion (Li-ion) batteries. Battery diagnostics focuses on battery models and diagnosis algorithms for battery state of charge (SOC) and state of health (SOH) estimation. Battery prognostics elaborates data-driven prognosis algorithms for predicting the remaining useful life (RUL) of battery SOC and SOH. Readers will learn not only basics but also very recent research developments on battery diagnostics and prognostics.

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