Prelithiation Enhances Cycling Life of Lithium-Ion Batteries:A Mini Review

During the last decade,the rapid development of lithium-ion battery(LIB)energy storage systems has provided significant support for the efficient operation of renewable energy stations.In the coming years,the service life demand of energy storage systems will be further increased to 30 years from the current 20 years on the basis of the equivalent service life of renewable energy stations.However,the life of the present LIB is far from meeting such high demand.Therefore,research on the next-generation LIB with ultra-long service life is imminent.Prelithiation technology has been widely studied as an important means to compensate for the initial coulombic efficiency loss and improve the service life of LIBs.This review systematically summarized the different prelithiation methods from anode and cathode electrodes.Moreover,the large-scale industrialization challenge and the possibility of the existing prelithiation technology are analyzed,based on three key parameters:industry compatibility,prelithiation efficiency,and energy density.Finally,the future trends of improvement in LIB performance by other overlithiated cathode materials are presented,which gives a reference for subsequent research.

Tailoring Mg^(2+)Solvation Structure in a Facile All-Inorganic[Mg_(x)Li_(y)Cl2_(x+y)·nTHF]Complex Electrolyte for High Rate and Long Cycle-Life Mg Battery

A high-performance all-inorganic magnesium-lithium chloride complex(MLCC)electrolyte is synthesized by a simple room-temperature reaction of LiCl with MgCl_(2) in tetrahydrofuran(THF)solvent.Molecular dynamics simulation,density functional theory calculation,Raman spectroscopy,and nuclear magnetic resonance spectroscopy reveal that the formation of[Mg_(x)Li_(y)Cl_(2x+y)·nTHF]complex solvation structure significantly lowers the coordination number of THF in the first solvation sheath of Mg^(2+),which significantly enhances its de-solvation kinetics.The MLCC electrolyte presents a stable electrochemical window up to 3.1 V(vs Mg/Mg^(2+))and enables reversible cycling of Mg metal deposition/stripping with an outstanding Coulombic efficiency up to 99%at current densities as high as 10 mA cm^(-2).Utilizing the MLCC electrolyte,a Mg/Mo_(6)S_(8) full cell can be cycled for over 10000 cycles with a superior capacity retention of 85 mA h g^(-1) under an ultrahigh rate of 50 C(1 C=128.8 mA g^(-1)).The facile synthesis of highperformance MLCC electrolyte provides a promising solution for future practical magnesium batteries.

Zr-doping stabilizes spinel LiMn_(2)O_(4)as a low cost long cycle life cathode for lithium ion batteries

The present commercial spinel LiMn_(2)O_(4) delivers only 90 m Ah/g–115 m Ah/g,far lower than the theoretical specific capacity.It degrades fast caused by the Jahn–Teller effect,Mn dissolution and related side reactions that consume Li inventory.In this work,Zr doping is employed to improve the structural stability and electrochemical performance of spinel LiMn_(2)O_(4).Li_(1.06)Mn_(1.94-x)Zr_xO_4(x=0,0.01,0.02,0.04)have been successfully synthesized by a simple solid-state reaction method and evaluated as cathode for lithium ion batteries(LIB).Li_(1.06)Mn_(1.92)Zr_(0.02)O_4 is superior cathode material with a high capacity of 122 m Ah/g at 1-C rate;long cycle stability,98.39%retention after 100 cycles at 1-C rate,excellent high rate performance 107.1 m Ah/g at 10-C rate,and high temperature performance 97.39%retention after 60 cycles.These are thought to be related to Zr doping effectively stabilizing the spinel LiMn_(2)O_(4),by forming stronger Zr–O bonds in the octahedron,suppressing the Jahn–Teller effect,thus improving electrochemical performance.

Accurate and efficient remaining useful life prediction of batteries enabled by physics-informed machine learning

The safe and reliable operation of lithium-ion batteries necessitates the accurate prediction of remaining useful life(RUL).However,this task is challenging due to the diverse ageing mechanisms,various operating conditions,and limited measured signals.Although data-driven methods are perceived as a promising solution,they ignore intrinsic battery physics,leading to compromised accuracy,low efficiency,and low interpretability.In response,this study integrates domain knowledge into deep learning to enhance the RUL prediction performance.We demonstrate accurate RUL prediction using only a single charging curve.First,a generalisable physics-based model is developed to extract ageing-correlated parameters that can describe and explain battery degradation from battery charging data.The parameters inform a deep neural network(DNN)to predict RUL with high accuracy and efficiency.The trained model is validated under 3 types of batteries working under 7 conditions,considering fully charged and partially charged cases.Using data from one cycle only,the proposed method achieves a root mean squared error(RMSE)of 11.42 cycles and a mean absolute relative error(MARE)of 3.19%on average,which are over45%and 44%lower compared to the two state-of-the-art data-driven methods,respectively.Besides its accuracy,the proposed method also outperforms existing methods in terms of efficiency,input burden,and robustness.The inherent relationship between the model parameters and the battery degradation mechanism is further revealed,substantiating the intrinsic superiority of the proposed method.

In Situ Formation of LiF-Rich Carbon Interphase on Silicon Particles for Cycle-Stable Battery Anodes

Silicon(Si)is a potential high-capacity anode material for the next-generation lithium-ion battery with high energy density.However,Si anodes suff er from severe interfacial chemistry issues,such as side reactions at the electrode/electrolyte interface,leading to poor electrochemical cycling stability.Herein,we demonstrate the fabrication of a conformal fl uorine-containing carbon(FC)layer on Si particles(Si-FC)and its in situ electrochemical conversion into a LiF-rich carbon layer above 1.5 V(vs.Li^(+)/Li).The as-formed LiF-rich carbon layer not only isolates the active Si and electrolytes,leading to the suppression of side reactions,but also induces the formation of a robust solid-electrolyte interface(SEI),leading to the stable interfacial chemistry of as-designed Si-FC particles.The Si-FC electrode has a high initial Coulombic effi ciency(CE)of 84.8%and a high reversible capacity of 1450 mAh/g at 0.4 C(1000 mA/g)for 300 cycles.In addition,a hybrid electrode consisting of 85 wt%graphite and 15 wt%Si-FC,and mass 2.3 mg/cm^(2) loading delivers a high areal capacity of 2.0 mAh/cm^(2) and a high-capacity retention of 93.2%after 100 cycles,showing the prospects for practical use.

CNTs@S composite as cathode for all-solid-state lithium-sulfur batteries with ultralong cycle life

The main challenges in development of traditional liquid lithium-sulfur batteries are the shuttle effect at the cathode caused by the polysulfide and the safety concern at the Li metal anode arose from the dendrite formation.All-solid-state lithium-sulfur batteries have been proposed to solve the shuttle effect and prevent short circuits.However,solid-solid contacts between the electrodes and the electrolyte increase the interface resistance and stress/strain,which could result in the limited electrochemical performances.In this work,the cathode of all-solid-state lithium-sulfur batteries is prepared by depositing sulfur on the surface of the carbon nanotubes(CNTs@S)and further mixing with Li10GeP2S12 electrolyte and acetylene black agents.At 60℃,CNTs@S electrode exhibits superior electrochemical performance,delivering the reversible discharge capacities of 1193.3,959.5,813.1,569.6 and 395.5 mAhg^-1 at the rate of 0.1,0.5,1,2 and 5 C,respectively.Moreover,the CNTs@S is able to demonstrate superior high-rate capability of 660.3 mAhg^-1 and cycling stability of 400 cycles at a high rate of 1.0 C.Such uniform distribution of the CNTs,S and Li10GeP2S12 electrolyte increase the electronic and ionic conductivity between the cathode and the electrolyte hence improves the rate performance and capacity retention.

Amorphous phosphorus chalcogenide as an anode material for lithiumion batteries with high capacity and long cycle life

The ever-increasing demands for modern energy storage applications drive the search for novel anode materials of lithium(Li)-ion batteries(LIBs) with high storage capacity and long cycle life, to outperform the conventional LIBs anode materials. Hence, we report amorphous ternary phosphorus chalcogenide(aP_(4)SSe_(2)) as an anode material with high performance for LIBs. Synthesized via the mechanochemistry method, the a-P_(4)SSe_(2) compound is endowed with amorphous feature and offers excellent cycling stability(over 1500 mA h g^(-1) capacity after 425 cycles at 0.3 A g^(-1)), owing to the advantages of isotropic nature and synergistic effect of multielement forming Li-ion conductors during battery operation. Furthermore,as confirmed by ex situ X-ray diffraction(XRD) and transmission electron microscope(TEM), the a-P_(4)SSe_(2)anode material has a reversible and multistage Li-storage mechanism, which is extremely beneficial to long cycle life for batteries. Moreover, the autogenous intermediate electrochemical products with fast ionic conductivity can facilitate Li-ion diffusion effectively. Thus, the a-P_(4)SSe_(2)electrode delivers excellent rate capability(730 mA h g^(-1)capacity at 3 A g^(-1)). Through in situ electrochemical impedance spectra(EIS) measurements, it can be revealed that the resistances of charge transfer(R_(SEI)) and solid electrolyte interphase(R_(Ct)) decrease along with the formation of Li-ion conductors whilst the ohmic resistance(R_(Ω)) remains unchanged during the whole electrochemical process, thus resulting in rapid reaction kinetics and stable electrode to obtain excellent rate performance and cycling ability for LIBs. Moreover, the formation mechanism and electrochemical superiority of the a-P_(4)SSe_(2)phase, and its expansion to P_(4)S_(3-x)Se_(x)(x = 0, 1, 2, 3) family can prove its significance for LIBs.

Graphene quantum dots as sulfiphilic and lithiophilic mediator toward high stability and durable life lithium-sulfur batteries

The development of lithium-sulfur(Li-S) battery as one of the most attractive energy storage systems among lithium metal batteries is seriously hindered by low sulfur utilization, poor cycle stability and uneven redeposition of Li anode. It is necessary to propose strategies to address the problems as well as improve the electrochemical performance. One of the effective solutions is to improve the sulfiphilicity of sulfur cathode and the lithiophilicity of the Li anode. Herein, we reported that a synergistic functional separator(graphene quantum dots(GQDs)-polyacrylonitrile(PAN) @polypropylene(PP) separator)improved the electrochemical activity of sulfur cathode as well as the stability of Li anode. GQDs induced uniform Li^(+)nucleation and deposition, which slowed down the passivation of Li anode and avoided shortcircuit. Further, three-dimensional network constructed by electrospinning nanofibers and the polar functional groups of GQDs could both effectively inhibit the shuttle of LiPSs and improve the sulfur utilization. The stability of Li-S battery was improved by the synergistic effect. In addition, GQDs and electrospinning nanofibers protector increased lifetime of separators. Benefiting from the unique design strategy, Li//Li symmetric battery with GQDs-PAN@PP separators exhibited stably cycling for over 600 h. More importantly, the Li-S full batteries based GQDs-PAN@PP separators enabled high stability and desirable sulfur electrochemistry, including high reversibility of 558.09 mA h g^(-1)for 200 cycles and durable life with a low fading rate of 0.075% per cycle after 500 cycles at 0.5 C. Moreover, an impressive areal capacity of 3.23 mA h cm^(-2)was maintained under high sulfur loading of 5.10 mg cm^(-2). This work provides a new insight for modification separator to improve the electrochemical performance of Li-S/Li metal batteries.

A Hybrid Ensemble Deep Learning Approach for Early Prediction of Battery Remaining Useful Life

Accurate estimation of the remaining useful life(RUL)of lithium-ion batteries is critical for their large-scale deployment as energy storage devices in electric vehicles and stationary storage.A fundamental understanding of the factors affecting RUL is crucial for accelerating battery technology development.However,it is very challenging to predict RUL accurately because of complex degradation mechanisms occurring within the batteries,as well as dynamic operating conditions in practical applications.Moreover,due to insignificant capacity degradation in early stages,early prediction of battery life with early cycle data can be more difficult.In this paper,we propose a hybrid deep learning model for early prediction of battery RUL.The proposed method can effectively combine handcrafted features with domain knowledge and latent features learned by deep networks to boost the performance of RUL early prediction.We also design a non-linear correlation-based method to select effective domain knowledge-based features.Moreover,a novel snapshot ensemble learning strategy is proposed to further enhance model generalization ability without increasing any additional training cost.Our experimental results show that the proposed method not only outperforms other approaches in the primary test set having a similar distribution as the training set,but also generalizes well to the secondary test set having a clearly different distribution with the training set.The PyTorch implementation of our proposed approach is available at https://github.com/batteryrul/battery_rul_early_prediction.

Research Progress in Improving the Cycling Stability of High-Voltage LiNi0.5Mn1.5O4 Cathode in Lithium-Ion Battery

High-voltage lithium-ion batteries(HVLIBs) are considered as promising devices of energy storage for electric vehicle, hybrid electric vehicle, and other high-power equipment. HVLIBs require their own platform voltages to be higher than 4.5 V on charge. Lithium nickel manganese spinel LiNi_(0.5)Mn_(1.5)O_4(LNMO) cathode is the most promising candidate among the 5 V cathode materials for HVLIBs due to its flat plateau at 4.7 V. However, the degradation of cyclic performance is very serious when LNMO cathode operates over 4.2 V. In this review, we summarize some methods for enhancing the cycling stability of LNMO cathodes in lithium-ion batteries, including doping, cathode surface coating,electrolyte modifying, and other methods. We also discuss the advantages and disadvantages of different methods.

Data-driven prognostics and remaining useful life estimation for lithium-ion battery: A Review

As an important and necessary part in the intelligent battery management systems(BMS),the prognostics and remaining useful life(RUL)estimation for lithium-ion batteries attach more and more attractions.Especially,the data-driven approaches use only the monitoring data and historical data to model the performance degradation and assess the health status,that makes these methods flexible and applicable in actual lithium-ion battery applications.At first,the related concepts and definitions are introduced.And the degradation parameters identification and extraction is presented,as the health indicator and the foundation of RUL prediction for the lithium-ion batteries.Then,data-driven methods used for lithium-ion battery RUL estimation are summarized,in which several statistical and machine learning algorithms are involved.Finally,the future trend for battery prognostics and RUL estimation are forecasted.

Tailored architecture of composite electrolyte for all-solid-state sodium batteries with superior rate performance and cycle life

Seeking for composite electrolytes reinforced all-solid-state sodium ion batteries with superior long lifespan and rate performance remains a great challenge.Here,a unique strategy to tailor the architecture of composite electrolyte via inserting polymer chains into a small quantity of sulfate sodium grafted C_(48)0H_(28)O_(32)Zr_(6)(UIOSNa)is proposed.The intimate contact between polymer segments and UIOSNa with limited pore size facilitates the anion immobilization of sodium salts and reduction of polymer crystallinity,thereby providing rapid ion conduction and reducing the adverse effect caused by the immigration of anions.The tNa+grafting of-SO_(3)Na groups on fillers allows the free movement of more sodium ions to further improve and ionic conductivity.Consequently,even with the low content of UIOSNa fillers,a high ionic conductivity of 6.62×10^(-4) S·cm^(-1) at 60℃ and a transference number of 0.67 for the special designed composite electrolyte are achieved.The assembled all-solid-state sodium cell exhibits a remarkable rate performance for 500 cycles with 95.96%capacity retention at a high current rate of 4 C.The corresponding pouch cell can stably work for 1000 cycles with 97.03%capacity retention at 1 C,which is superior to most of the reported composite electrolytes in the literature.

Engineering molecular regulation for SiO_(x) with long-term stable cycle and high Coulombic efficiency as lithium-ion battery anodes

In the current situation where the practical application of silicon anode materials encounters great challenges,silicon oxide(SiO_(x),0≤x≤2)has attracted the attention of researchers due to its relatively small volume expansion,stable cycling performance,and low cost,which is possible to realize commercial applications earlier than silicon anode.However,it remains a challenge to prepare SiO_(x)materials with long-term stable cycling performance and high Coulombic efficiency using low-cost methods.In this work,SiO_(x)anode material with high Coulombic efficiency and good long-term cycling stability was prepared at a low cost by hydrolysis of siloxane and in situ polymerization of phenolic resin.The hydrolysis of siloxane was further regulated by different silane coupling agents to regulate the size and microstructure of prepared SiO_(x)materials,which displayed the substantially improved electrochemical performance.The excellent electrochemical performance of SiO_(x)prepared by regulated hydrolysis of siloxane with silane coupling agents is attributed to the effect of silane coupling agent on size and microstructure of SiO_(x),revealing that the strategy of modulating the hydrolysis of siloxane by silane coupling agent is a potential method to prepare high-performance SiO_(x)materials.

Remaining Useful Life Estimation of Lithium-Ion Battery Based on Gaussian Mixture Ensemble Kalman Filter

The remaining useful life(RUL)prediction is a crucial indicator for the lithium-ion battery health prognostic.The particle filter(PF),used together with an empirical model,has become one of the most well-accepted techniques for RUL prediction.In this work,a novel filtering algorithm,named the Gaussian mixture model(GMM)-ensemble Kalman filter(EnKF)is proposed.It embeds the Gaussian mixture model in the EnKF framework to cope with the non-Gaussian feature of the system state space,and meanwhile address some of the major shortcomings of the PF.The GMM-EnKF and the PF are both applied on public data sets for RUL prediction and the simulation results show superiority of our proposed approach to the PF.

Progress and challenges of prelithiation technology for lithium-ion battery

Prelithiation technology is widely considered a feasible route to raise the energy density and elongate the cycle life of lithium-ion batteries.The principle of prelithiation is to introduce extra active Li ions in the battery so that the lithium loss during the first charge and long-term cycling can be compensated.Such an effect does not need to change the major electrode material or battery structure and is compatible with the majority of current lithium-ion battery production lines.At this stage,various prelithiation methods have been reported,some of which are already in the pilot-scale production stage.But there is still no definitive development roadmap for prelithiation.In this review,we first introduce the influence of prelithiation on electrochemical performance from a theoretical point of view and then compare the pros and cons of different prelithiation methods in different battery manufacturing stages.Finally,we discuss the challenges and future development trends of prelithiation.We aim to build up a bridge between academic research and industrial application.Some engineering problems in the promotion of prelithiation technique are extensively discussed,including not only the implementation of prelithiation but also some collateral issues on battery designing and management.

Flexible rechargeable Ni//Zn battery based on self-supported NiCo_2O_4 nanosheets with high power density and good cycling stability

The overall electrochemical performances of Ni-Zn batteries are still far from satisfactory, specifically for rate performance and cycling stability Herein, we demonstrated a high-performance flexible Ni//Zn battery with outstanding durability and high power density based on selfsupported NiCo_2 O_4 nanosheets as cathode and Zn nanosheets as anode. This Ni//Zn battery is able to deliver a remarkable capacity of183.1 mAh g^(-1) and a good cycling performance(82.7% capacity retention after 3500 cycles). More importantly, this battery achieves an admirable power density of 49.0 kW kg^(-1) and energy density of 303.8 Wh kg^(-1), substantially higher than most recently reported batteries. With such excellent electrochemical performance, this battery will have great potential as an ultrafast power source in practical application.

B-doped and La_(4)NiLiO_(8)-coated Ni-rich cathode with enhanced structural and interfacial stability for lithium-ion batteries

Ni-rich layered oxides are considered promising cathodes for advanced lithium-ion batteries(LIBs)in the future,owing to their high capacity and low cost.However,the issues on structural and interfacial stability of Ni-rich cathodes still pose substantial obstacles in the practical application of advanced LIBs.Here,we employ a one-step method to synthesize a B-doped and La_(4)NiLiO_(8)-coated LiNi_(0.82)5Co_(0.115)Mn_(0.06)O_(2)(BL-1)cathode with reliable structure and interface,for the first time.The La_(4)NiLiO_(8)coating layer can prevent cathodes from electrolyte assault and facilitate Li+diffusion kinetics.Moreover,B-doping can effectively restrain the pernicious H_(2)-H_(3) phase transition and adjust the orientation of primary particles to a radial alignment,which is obstructive to the arise of microcracks induced by the change of anisotropic volume.Specifically,when tested in pouch cells,the BL-1 cathode exhibits outstanding capacity retention of 93.49%after 500 cycles at 1 C.This dual-modification strategy dramatically enhances the stability of the structure and interface for Ni-rich cathode materials,consequently accelerating the commercialization process of high-energy–density LIBs.

A review of deep learning approach to predicting the state of health and state of charge of lithium-ion batteries

In the field of energy storage,it is very important to predict the state of charge and the state of health of lithium-ion batteries.In this paper,we review the current widely used equivalent circuit and electrochemical models for battery state predictions.The review demonstrates that machine learning and deep learning approaches can be used to construct fast and accurate data-driven models for the prediction of battery performance.The details,advantages,and limitations of these approaches are presented,compared,and summarized.Finally,future key challenges and opportunities are discussed.