Lifetime Of Li-ion Batteries Research Articles

Evaluating the Influence of SiOx on the Calendar Lifetime of Li Ion Batteries across Varied Temperatures and State of Charge Conditions

Lithium-ion batteries (LIBs) have a wide range of application in various fields, such as automotive and stationary applications. The incorporation of silicon (Si) in the anode is an attractive strategy to increase energy density and enable fast charging. This is due to the excellent theoretical specific capacity of Si, which exceeds 3000 mAh/g. However, due to the alloying behavior of Si, a significant volume change can be observed by Si based anodes when cycled. In literature the rapid cyclic degradation is related to these volume changes. A practical approach is to use silicon oxide (SiOx) as anode material, which undergoes lower volume changes during cycling but still exhibits a specific capacity >2000 mAh/g. Studies on the cycle life of SiOx-containing cells are frequently published in literature, but calendar life studies are scarce.Here, the calendar life of two different 1 Ah pouch cell configurations, possessing different anode chemistries, were investigated. One cell contained artificial graphite and 10% SiOx (SiO-cell) while the other cell only used artificial graphite as anode material (G-cell). Both cell configurations were built with an NMC811 cathode. 1 M LiPF6 in EC: EMC (3:7 (wt.)) + 2%wt. VC was used as electrolyte. Temperatures of 20 °C, 40 °C and 60 °C and state of charge (SoC) levels of 20%, 40%, 60%, 80% and 100% were investigated in this study. It has been observed that for 20 °C and 40 °C, the degradation rate of both cell types intensifies when stored at 100% SoC. At 60 °C, however, the capacity fade already starts intensifying drastically at around 60% SoC. The capacity fading during storage experiments of the SiO- cells, depending on the parameters tested, is higher by a factor of around 1.1 to 4.1 than the capacity fading of the G- cells. Interestingly, the capacity fade ratio of the SiO-cell to G-cell is at maximum when cells were stored below 40% SoC at 20 °C. When stored at low SoC, SiOx is the anode active material being lithiated majorly. These findings indicate that SiOx indeed causes stronger calendaric degradation compared to graphite. Hence, in future studies on SiOx based anodes calendaric degradation is an interesting topic to address additionally to cyclic degradation.

Physics-Informed Machine Learning for Battery Capacity Forecasting

Batteries, recognized as effective energy storage solutions, are considered the main facilitators of the world-wide transition towards clean and renewable energy sources. Among different types of batteries, lithium-ion (Li-ion) variants offer higher energy densities and relatively longer life spans when compared to other types. Nonetheless, a primary concern with these batteries is their lifetime. Batteries undergo various degradation mechanisms under storage and use, significantly impacting their lifespan. To this end, it is crucial to predict the degradation and lifetime of Li-ion batteries under given conditions.Researchers use three main methodologies to perform battery health diagnostics and to predict the lifetime of batteries. One approach revolves around using mechanistic, first-principle electrochemical models, also known as physics-based models. If equipped with proper thermodynamic theories, such models can show promising capabilities; however, holistic degradation prediction with these models is still challenging due to the computational complexities and the multitude of parameters that need to be fine-tuned in this approach. The other common strategy is to use empirical models to predict battery degradation. These models generally entail fewer parameters to be identified and are computationally less intensive to solve. Nonetheless, empirical models can suffer from the accuracy point-of-view as they are constrained to predict degradation trends introduced by certain degradation modes. Another common technique in battery life prediction is to utilize purely data-driven methods, such as machine learning (ML) algorithms, which also have shown promising results in the literature on rapid health predictions. However, these methods require large volumes of experimental data for training and testing ML models to ensure accuracy. In addition, data-driven methods are likely to extrapolate poorly to conditions beyond their training data and are indifferent towards the underlying degradation mechanisms. Recently, physics-informed machine learning (PI-ML) methods have garnered significant attention. They integrate physics-based or empirical models (developed based on physics) with a data-driven approach and allow one to train ML models on a smaller set of experimental data.To the best of the authors’ knowledge, the performance comparison between first-principle and empirical models when integrated within PI-ML remains unclear. Therefore, in this work, we aim to compare these two models when applied to prognostics (capacity forecasting and remaining useful life prediction) of a set of Li-ion batteries. To perform this study, we generate aging data for 40 Li-ion coin cells cycled under randomized conditions. Each cell undergoes a three-step charging stage followed by a two-step discharge stage. After obtaining the aging data, we will develop two PI-ML models, one equipped with a physics-based model and another with a set of empirical models. Both PI-ML models in this work will follow the sequential integration approach, where the training data for the final PI-ML model come from both experimental and computational data, the latter of which are obtained from the physics-based or empirical models. The parameters for the physics-based and empirical models are identified from another set of experimental data. Finally, the PI-ML models will be tested with experimental data obtained at different cycling conditions. The data flow for the sequential architecture of PI-ML is shown in the attached figure. This comparative study will help identify the performance of physics-based and empirical models when integrated into PI-ML. The main performance metric considered in this work is each model’s ability to extrapolate beyond the experimental training data set, hence aiding the final PI-ML model in generalizing to conditions not covered by its experimental training data set. Figure 1

Operando Li metal plating diagnostics via MHz band electromagnetics

A nondestructive detection method for internal Li-metal plating in lithium-ion batteries is essential to improve their lifetime. Here, we demonstrate a direct Li-metal detection technology that focuses on electromagnetic behaviour. Through an interdisciplinary approach combining the ionic behaviour of electrochemical reactions at the negative electrode and the electromagnetic behaviour of electrons based on Maxwell’s equations, we find that internal Li-metal plating can be detected by the decrease in real part of the impedance at high-frequency. This finding enables simpler diagnostics when compared to data-driven analysis because we can correlate a direct response from the electronic behaviour to the metallic material property rather changes in the ionic behaviour. We test this response using commercial Li-ion batteries subject to extremely fast charging conditions to induce Li-metal plating. From this, we develop a battery sensor that detects and monitors the cycle-by-cycle growth of Li-metal plating. This work not only contributes to advancing future Li-ion battery development but may also serve as a tool for Li-metal plating monitoring in real-field applications to increase the useable lifetime of Li-ion batteries and to prevent detrimental Li-metal plating.

Probing the Formation of Cathode-Electrolyte Interphase on Lithium Iron Phosphate Cathodes via Operando Mechanical Measurements.

Interfacial instabilities in electrodes control the performance and lifetime of Li-ion batteries. While the formation of the solid-electrolyte interphase (SEI) on anodes has received much attention, there is still a lack of understanding the formation of the cathode-electrolyte interphase (CEI) on the cathodes. To fill this gap, we report on dynamic deformations on LiFePO4 cathodes during charge/discharge by utilizing operando digital image correlation, impedance spectroscopy, and cryo X-ray photoelectron spectroscopy. LiFePO4 cathodes were cycled in either LiPF6, LiClO4, or LiTFSI-containing organic liquid electrolytes. Beyond the first cycle, Li-ion intercalation results in a nearly linear correlation between electrochemical strains and the state of (dis)-charge, regardless of the electrolyte chemistry. However, during the first charge in the LiPF6-containing electrolyte, there is a distinct irreversible positive strain evolution at the onset of anodic current rise as well as current decay at around 4.0 V. Impedance studies show an increase in surface resistance in the same potential window, suggesting the formation of CEI layers on the cathode. The chemistry of the CEI layer was characterized by X-ray photoelectron spectroscopy. LiF is detected in the CEI layer starting as early as 3.4 V and LixPOyFz appeared at voltages higher than 4.0 V during the first charge. Our approach offers insights into the formation mechanism of CEI layers on the cathode electrodes, which is crucial for the development of robust cathodes and electrolyte chemistries for higher-performance batteries.

In-Operando Isothermal Microcalorimetry to Accelerate Screening of New Battery Chemistries

Screening new cell chemistries using traditional electrochemical methods is a time prohibitive process that significantly slows the pace of research. These methods involve cycling the cell until signs of degradation or sufficient capacity fade are evident, and typically take months to complete. In-operando isothermal microcalorimetry is an established but underutilized technique for measuring the activity of parasitic, or non-reversible reactions during charge cycling [1,2,3,4]. A parasitic reaction is a blanket term for any side reactions that occur within a battery, including solvent breakdown, lithium plating, self-discharge reactions, and growth or decomposition of the solid electrolyte interphase. Battery formulations with high parasitic heat are strongly correlated with early cell failure. Compared to electrochemical cycling, the average parasitic heat over the full voltage range can be determined in a time frame as low as 2 weeks, allowing researchers to realize a time savings up to 75%. Additional time savings are also possible if only a narrow voltage range is of interest.In this study, we present results that demonstrate the measurement of the parasitic heat of a commercial 18650 lithium-ion battery using the TA Instruments Battery Cycler Microcalorimeter Solution. This method involves slow galvanostatic cycling at isothermal conditions with a simultaneous measurement of heat flow, voltage, and applied current. The parasitic heat is isolated from the total heat flow using the Integration-Subtraction method, with calculations performed automatically by the software [1]. The coulombic efficiency is also measured per cycle, showing an inverse relationship to the parasitic power. As a screening tool, this data could be used to select battery formulations most likely to meet performance goals in long-term cycling experiments, rather than wasting valuable time and lab space on a trial-and-error approach. The results highlight how in-operando isothermal microcalorimetry is a powerful screening tool for investigating the efficiency of new cell chemistries and electrolyte formulations in a fraction of the time compared to traditional methods.[1] L.J. Krause, L.D. Jensen, V.L. Chevrier. Measurement of Li-Ion Battery Electrolyte Stability by Electrochemical Calorimetry. J. Electrochem. Soc. 2017, 164 (4), A889-A896.[2] L.J. Krause, L.D. Jensen, J.R. Dahn. Measurement of Parasitic Reactions in Li Ion Cells by Electrochemical Calorimetry. J. Electrochem. Soc. 2012, 159 (7), A937-A943.[3] J.C. Burns, Adil Kassam, N.N. Sinha, L.E. Downie, Lucie Solnickova, B.M. Way, J.R. Dahn. Predicting and Extending the Lifetime of Li-Ion Batteries. J. Electrochem. Soc. 2013, 160, A1451.[4] E. R. Logan, A. J. Louli, Matthew Genovese, Simon Trussler,and J. R. Dahn. Investigating Parasitic Reactions in Anode-Free Li Metal Cells with Isothermal Microcalorimetry. J. Electrochem. Soc. 2021, 168, 060527.

Broad Transfer Learning Network based Li-ion battery lifetime prediction model

The Broad Transfer Learning Network (BTLN) model uses only one-third of the parameters as the common neural network does to achieve the similar prediction performance that a Multi-Layer Perceptron (MLP) model has. This brings considerable benefits to AI-related studies that highly rely on computational power. This study also proposed a feature mapping technique that applied a linear transformation to the original features to improve the performance of various learning models. This study combines both broad learning and transfer learning techniques. Data augmentation is used to expand the training dataset. It proves that, under certain conditions, the model with a broader network can perform better. The broad network structure can act as an effective feature extractor. The transform learning algorithm can increase the training efficiency due to decreased trainable parameters. The performance improvement of neural network models is particularly remarkable. The performance improves by 3.5% without any change to the model architecture. In this paper, the performance of the BTLN model proposed based on Root Mean Square Error (RMSE) improves by 18.5%. Compared to common neural network models, the training parameters and overall parameters are lowered to 14.57% and 36.28%, respectively.

Electricity price arbitrage in utility-scale PV-plus-battery systems

In this paper, we use MHOGA software for the optimization of an AC-coupled utility-scale PV-plus-battery system. Batteries are used for price arbitrage, being charged with the photovoltaic (PV) generation during hours of low electricity price and discharged during hours of high price. The correct estimation of the battery lifetime has great importance in the calculation of the net present value, to do this advanced models for estimating the Li-ion battery lifetime (considering cycle and calendar ageing) are used. With present components costs, considering the Spanish SPOT price of 2021 with an expected increase of 1% annual, the AC coupled utility-scale PV-plusbattery isn’t economically viable comparing to the PV-only system. If electricity hourly price was multiplied by two, in certain cases adding battery to the PV system would be profitable.

Surface Analysis of Pristine and Cycled NMC/Graphite Lithium-Ion Battery Electrodes: Addressing the Measurement Challenges.

Lithium-ion batteries are the most ubiquitous energy storage devices in our everyday lives. However, their energy storage capacity fades over time due to chemical and structural changes in their components, via different degradation mechanisms. Understanding and mitigating these degradation mechanisms is key to reducing capacity fade, thereby enabling improvement in the performance and lifetime of Li-ion batteries, supporting the energy transition to renewables and electrification. In this endeavor, surface analysis techniques are commonly employed to characterize the chemistry and structure at reactive interfaces, where most changes are observed as batteries age. However, battery electrodes are complex systems containing unstable compounds, with large heterogeneities in material properties. Moreover, different degradation mechanisms can affect multiple material properties and occur simultaneously, meaning that a range of complementary techniques must be utilized to obtain a complete picture of electrode degradation. The combination of these issues and the lack of standard measurement protocols and guidelines for data interpretation can lead to a lack of trust in data. Herein, we discuss measurement challenges that affect several key surface analysis techniques being used for Li-ion battery degradation studies: focused ion beam scanning electron microscopy, X-ray photoelectron spectroscopy, Raman spectroscopy, and time-of-flight secondary ion mass spectrometry. We provide recommendations for each technique to improve reproducibility and reduce uncertainty in the analysis of NMC/graphite Li-ion battery electrodes. We also highlight some key measurement issues that should be addressed in future investigations.

Investigation on Tethered Anion Effects in Solid Polymer Electrolytes for Li-Ion Batteries

Solid polymer electrolytes (SPEs) have been proposed to reduce concentration polarizations within batteries by immobilizing anions to the polymer matrix, which can help stabilize the electrodeposition process and extend Li-ion battery lifetime. Unfortunately, single-ion conducting SPEs continue to suffer from poor conductivity due to coupling with the slow segmental mobility of polymer chains and poor ion pair dissociation. Our group systematically investigated how different tethered anions affect the Li-ion conduction and polymer segmental mobility. Copolymers were synthesized using a common neutral monomer, poly(ethylene glycol) methyl ether methacrylate (PEGMA), with a series of different anionic monomers: 4-styrene sulfonate, 4-styrene phosphonate, 4-styrene TFSI, and methacrylate TFSI. These monomers presented a series of anions of varying strength with the same styrene structure, sulfonate vs. phosphonate vs. TFSI, as well as exploring structural monomer changes for the same TFSI anion, styrene vs. methacrylate, that allows for systematic changing of polymer electrolyte properties. Each copolymer series was further expanded by changing the composition of neutral-to-anionic monomers, ranging from 10-67 mol% anionic. The increased ion exchange capacity of the phosphonate groups led to a high degree of ion aggregation that exhibited hard mechanical properties and very low Li-ion conductivities. Increasing the electron delocalization of the ions from sulfonate to TFSI greatly improved the conductivities and lowered activation energies of ion transport, with methacrylate being slightly better than styrene. Implications of these results will be discussed for next-generation polymer electrolyte design.

Theory of Layered-Oxide Cathode Degradation in Li-ion Batteries by Oxidation-Induced Cation Disorder

Disorder-driven degradation phenomena, such as structural phase transformations and surface reconstructions, can significantly reduce the lifetime of Li-ion batteries, especially those with nickel-rich layered-oxide cathodes. We develop a general free energy model for layered-oxide ion-intercalation materials as a function of the degree of disorder, which represents the density of defects in the host crystal. The model accounts for defect core energies, long-range dipolar electrostatic forces, and configurational entropy of the solid solution. In the case of nickel-rich oxides, we hypothesize that nickel with a high concentration of defects is driven into the bulk by electrostatic forces as oxidation reactions at the solid-electrolyte interface reduce nickel and either evolve oxygen or oxidize the organic electrolyte at high potentials (>4.4 V vs Li/Li+). The model is used in battery cycling simulations to describe the extent of cathode degradation when using different voltage cutoffs, in agreement with experimental observations that lower-voltage cycling can substantially reduce cathode degradation. The theory provides a framework to guide the development of cathode compositions, coatings and electrolytes to enhance rate capability and enhance battery lifetime. The general theory of cation-disorder formation may also find applications in electrochemical water treatment and ion separations, such as lithium extraction from brines, based on competitive ion intercalation in battery materials.

The significance of detecting imperceptible physical/chemical changes/reactions in lithium-ion batteries: a perspective

The lifetime of Li-ion batteries (LIBs) is highly dependent on the imperceptible physical/chemical changes/reactions that occur on/between the electrodes and electrolyte.

Underpotential Lithium Plating on Graphite Anodes Caused by Temperature Heterogeneity

Rechargeability and operational safety of commercial lithium (Li)-ion batteries demand further improvement. Plating of metallic Li on graphite anodes is a critical reason for Li-ion battery capacity decay and short circuit. It is generally believed that Li plating is caused by the slow kinetics of graphite intercalation, but in this paper, we demonstrate that thermodynamics also serves a crucial role. We show that a non-uniform temperature distribution within the battery can make local plating of Li above 0 V vs. Li0/Li+ (room temperature) thermodynamically favorable. This phenomenon is caused by temperature dependent shifts of the equilibrium potential of Li0/Li+. Supported by simulation results, we confirm the likelihood of this failure mechanism during commercial Li-ion battery operation, including both slow and fast charging conditions. This work furthers the understanding of non-uniform Li plating and will inspire future studies to prolong the cycling lifetime of Li-ion batteries.

A New Energy Storage System Configuration to Extend Li-Ion Battery Lifetime for a Household

A new home energy storage system (HESS) configuration using lithium-ion batteries is proposed in this article. The proposed configuration improves the lifetime of the energy storage devices. The batteries in this system can be charged by either using solar panels when solar energy is available or by using the grid power when the electricity cost is at its lowest rate during off-peak hours. In the proposed configuration, the battery bank is split into two sections, and the pulsed charge-discharge method is employed. This method helps to prolong the life of the lithium-ion batteries while maximizing the solar energy utilization that leads to reduce the consumer's total energy cost. In order to demonstrate the benefits of the proposed method, different modes of operation are discussed in detail along with the simulation results. A prototype was developed to demonstrate the performance of the proposed system experimentally.

Underpotential Lithium Plating on Graphite Anodes Caused By Temperature Heterogeneity

Rechargeability and operational safety of commercial lithium (Li)-ion batteries demand further improvement. Plating of metallic Li on graphite anodes is a critical reason for Li-ion battery capacity decay and short circuit. It is generally believed that Li plating is caused by the slow kinetics of graphite intercalation, but in this paper, we demonstrate that thermodynamics also serves a crucial role. We show that a non-uniform temperature distribution within the battery can make local plating of Li above 0 V vs. Li+/Li0 (room temperature) thermodynamically favorable. This phenomenon is caused by temperature dependent shifts of the equilibrium potential of Li+/Li0. Supported by simulation results, we confirm the likelihood of this failure mechanism during commercial Li-ion battery operation, including both slow and fast charging conditions. This work furthers the understanding of non-uniform Li plating and will inspire future studies to prolong the cycling lifetime of Li-ion batteries.

How Can Insights from Degradation Modelling Inform Operational Strategies to Increase the Lifetime of Li-Ion Batteries in Islanded Mini-Grids?

Minigrids are expected to play a key role in achieving universal access to electricity. The International Energy Agency estimates that 25% of people gaining access to electricity by 2030 will do so through a mini-grid1. Generation is often paired with a battery, primarily lead acid or li-ion in this context. Battery storage can help to displace the use of diesel generators, through providing solutions to the mismatch between daytime solar photovoltaic (PV) generation and evening demand.Batteries are a key cost component of mini-grids. However, how to economically choose and operate batteries in an off-grid context is often unclear2. Factors such as ambient temperature and high State of Charge (SOC) have been shown to significantly increase the rate of capacity fade in li-ion batteries3. A good understanding of battery degradation is required to maximise lifetime and reduce costs. Derating strategies, informed by degradation modelling, limit charging/discharging currents under conditions that will accelerate capacity fade. These methods can be implemented for little cost, having been shown to be able to effectively manage factors such as battery temperature and SOC4,5. Through limiting current, derating will have implications for system reliability. Therefore, it is important to fully understand the impact of these strategies in off-grid systems.This study uses a mini-grid simulation and optimisation tool (Continuous Lifetime Optimisation of Variable Electricity Resources, CLOVER)6,7 and coupled electrothermal and semi-empirical degradation models for a Lithium Iron Phosphate cell (Full Battery System Model, FBSM) to model capacity fade for two locations in the global south. The first location has a milder climate more suitable for li-ion operation (Gitaraga, Rwanda), whereas the second exhibits more extreme temperatures (Bhinjpur, India). CLOVER was used to optimally size solar mini-grid systems and to calculate financial and environmental variables. FBSM was used to model battery aging, considering factors such as cell self-heating, observing the impact of calendar aging and 3 separate cycle aging mechanisms. The model was also used to evaluate the effect of derating strategies on battery degradation, in terms of capacity fade. In the first instance, these are calculated with no derating, and in the second with simple derating strategies based on limiting SOC and battery temperature operating windows. Important factors for mini-grid operation such as battery lifetime, unmet energy fraction, and Levelised Cost of Used Electricity (LCUE) are considered.This study finds calendar aging to be the most significant degradation mechanism for all scenarios investigated, causing a minimum of 87% of total capacity loss. Calendar aging is primarily a function of ambient temperature and SOC.Extreme highs and lows in ambient temperature are found to accelerate degradation. In the case study, PV and battery size was relatively high with respect to the load, resulting in relatively low battery currents, and a tendency of the system towards high SOC levels. Low currents exhibited mean that the significance of joule losses is found to be very small, thus the influence of cell self-heating was found to be negligible.SOC derating to achieve an average SOC of 50% is found to increase battery lifetime by over 11 years through limiting time spent at high SOC, without impacting on the system reliability. Temperature derating is able to increase battery lifetime for a maximum of 2.3 years. Derating led to increases in the unmet energy fraction and frequency of blackouts. However, these increases did not result in any change to the emissions intensity of electricity or the LCUE. Capacity fade observed for one of the systems investigated in both Gitaraga and Bhinjpur has been shown in Figure 1.Therefore, it is shown that derating strategies are a low-cost method that can increase battery lifetime, without increasing the cost of electricity or emissions intensity. Thus, improving the financial viability of mini-grids. Insights from degradation modelling enable better decision making regarding the operation of li-ion batteries in this context. Acknowledgements This work was kindly supported by the EPSRC Faraday Institution Multi-Scale Modelling Project (EP/S003053/1, grant number FIRG003). References IEA, Energy Access Outlook, (2017).S. Few, O. Schmidt, and A. Gambhir, Energy Sustain. Dev., 48, 1–10 (2019) https://doi.org/10.1016/j.esd.2018.09.008.M. Schimpe et al., J. Electrochem. Soc., 165, A181–A193 (2018).J. V. Barreras, T. Raj, and D. A. Howey, in Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society,, p. 4956–4961, IEEE (2018) https://ieeexplore.ieee.org/document/8592901/.M. Schimpe, J. V. Barreras, B. Wu, and G. J. Offer, in PRiME 2020/238th ECS Meeting,, Honolulu, HI, USA.P. Sandwell, (2018).P. Sandwell, N. Ekins-Daukes, and J. Nelson, Energy Procedia, 130, 139–146 (2017). Figure 1

Underpotential lithium plating on graphite anodes caused by temperature heterogeneity.

Rechargeability and operational safety of commercial lithium (Li)-ion batteries demand further improvement. Plating of metallic Li on graphite anodes is a critical reason for Li-ion battery capacity decay and short circuit. It is generally believed that Li plating is caused by the slow kinetics of graphite intercalation, but in this paper, we demonstrate that thermodynamics also serves a crucial role. We show that a nonuniform temperature distribution within the battery can make local plating of Li above 0 V vs. Li0/Li+ (room temperature) thermodynamically favorable. This phenomenon is caused by temperature-dependent shifts of the equilibrium potential of Li0/Li+ Supported by simulation results, we confirm the likelihood of this failure mechanism during commercial Li-ion battery operation, including both slow and fast charging conditions. This work furthers the understanding of nonuniform Li plating and will inspire future studies to prolong the cycling lifetime of Li-ion batteries.

Theory of battery ageing in a lithium-ion battery: Capacity fade, nonlinear ageing and lifetime prediction

Forecasting the lifetime of Li-ion batteries is a critical challenge that limits the integration of battery electric vehicles (BEVs) into the automotive market. Cycle-life performance of Li-ion batteries is intrinsically linked to the fundamental understanding of ageing mechanisms. In contrast to most previous studies which utilise empirical trends (low real-time information) or rough simplifications on mathematical models to predict the lifetime of a Li-ion battery, we deployed a novel ageing formulation that includes heterogeneous dual-layer solid electrolyte interphase (SEI) and lithium-plating ageing mechanisms with porosity evaluation. The proposed model is parameterized and optimized for mass transport and ageing parameters based on fresh and an aged cell and validated against our experimental results. We show that our advanced ageing mechanisms can accurately calculate experimentally observed cell voltage and capacity fade with respect to cycling number and can predict future fade for new operating scenarios based on constant-current and a dynamic power profile cycling experimental data consisting of high discharge C-rates and fast-charging periods. Our model is able to capture the linear and nonlinear (knee-point) capacity fade characteristics with a high accuracy of 98% goodness-of-fit-error and we compared our model performance with well-accepted existing model in literature.

Nickel Impurities in the Solid-Electrolyte Interphase of Lithium-Metal Anodes Revealed by Cryogenic Electron Microscopy

Summary Dissolution of transition metals from high-voltage cathodes and their incorporation into the solid-electrolyte interphase (SEI) of carbonaceous anodes drastically reduces the lifetime of Li-ion batteries. The effects of dissolved transition metals on the performance of carbonaceous anodes are well characterized; however, the impact on Li-metal anode performance and the SEI is rarely considered. Here, we use cryogenic electron microscopy to reveal the impact of dissolved Ni on the SEI formation process on Li-metal. A link between Ni incorporation into the SEI and the failure of Li-metal batteries is established. We find that Ni is reduced into its metallic state and incorporates as small clusters into the SEI, locally changing the chemistry and nanostructure of the SEI. These chemical and nanostructure changes locally modify the Li-ion and electron transport properties of the SEI, accelerating electrolyte decomposition, increasing formation of “dead” Li, and ultimately causing failure.

Quantitative spatiotemporal Li profiling using nanoindentation

The rate capability and lifetime of Li-ion batteries is largely dictated by the composition dynamics of the electrodes. We set forth a nanoindentation approach to probe the spatiotemporal Li profile using the functional dependence of the mechanical properties on Li composition. This mechanics-informed material dynamics allows us to measure the composition-dependent diffusivity, assess the rate-limiting process in Li reactions, and quantitatively evaluate the stress regulation on Li transport. The experiments show that Li diffusivity in amorphous Si varies exponentially by three orders of magnitude from the pristine to the fully lithiated state. Lithiation in amorphous Si is limited by diffusion at the micron scale. We further evaluate the thermodynamic driving force for Li diffusion by including the material non-ideality and mechanical stresses. Through computational modeling, we find that the composition dependence of the Li diffusivity in general creates an asymmetry on the rate capability during lithiation versus delithiation. In Si, the exponential dependence results in a fast lithiation that proceeds via a steep concentration gradient compared to a slow and relatively smooth delithiation. This asymmetric behavior appears to be a root cause of Li trapping and loss of the deliverable capacity in Si. This work sheds light on the thermodynamics of Li transport and the lithiation kinetics of amorphous Si. It demonstrates the potential of operando nanoindentation in the mechanics-informed understanding of Li chemistry and aiding battery research beyond mechanical measurement.

How the Binder/Solvent Formulation Impacts the Electrolyte Reactivity/Solid Electrolyte Interphase Formation and Cycling Stability of Conversion Type Electrodes

Conversion/alloying type materials are of great interests in term of electrochemical performance for Li-ion batteries and beyond. To address their large volume change (typically >200%) during cycling, tailoring the binder/solvent system used for the electrode formulation together with the use of electrolyte additives are the most used and efficient approaches. However, only few studies have investigated the role of the binder/solvent formulation on the electrolyte reactivity/solid electrolyte interphase (SEI) formation and its composition. To tackle this issue, gas chromatography coupled with electron impact mass spectrometry and X-ray photoelectron spectroscopy analysis were used to understand the long term cycling stability (100 cycles) of NbSnSb-based electrodes. It is showed that CMC-H2O and PAA-H2O formulations favored the formation of a more homogeneous SEI while maintaining efficient active/conducting particles bridging, which results in high cycling stability. PVDF-NMP and PAA-NMP led, however, to much lower coulombic efficiency and higher irreversible capacity correlated with the formation of thick SEI with a concomitant disconnection of active particles. These results highlight that CMC and PAA act as artificial SEI and/or as SEI stabilizers. Overall, this work should benefit to all researchers working on improving, through electrode formulation, the lifetime of Li-ion batteries and beyond.