Growth Of Solid Electrolyte Interface Research Articles

Effect of Solvent Segregation on the Performance of Lithium-Ion Batteries

The pseudo two-dimensional (P2D) model is one of the most powerful tools in modelling lithium-ion batteries (LIBs) 1, in that it can describe the complex electrochemical and thermal behaviours of LIBs with high fidelity yet maintain relatively high computing efficiency. To achieve that, many assumptions have been made, one of which is the single solvent assumption. However, most electrolytes used in LIBs uses multiple solvents to balance the requirements of conductivity, diffusivity and viscosity 2. Therefore, the single solvent assumption indicates that all solvents move as a single entity.However, previous experimental studies have shown that Li+ preferentially attracts cyclic carbonates (like ethylene carbonate, EC) rather than linear carbonates (such as ethyl-methyl carbonate, EMC) to form ion-solvent clusters 3. During charge/discharge, ion-solvent clusters move between the positive and negative electrodes to constitute ionic current. At the electrolyte-electrolyte interface, Li+ de-solvates from the clusters and intercalates into the electrode, or vice versa. Such process will induce concentration gradients of both solvents and lithium ions; the solvent concentration has been ignored in the P2D model. The simplification means the current P2D model fails to capture two important phenomena: (1) many electrolyte properties - including conductivity, diffusivity, and thermodynamic factors - are sensitive to the solvent concentration 4; (2) the solvent components in the ion-solvent clusters are preferentially consumed by interfacial side reactions such as the growth of solid-electrolyte interface (SEI) 3.To fill this gap, we add an extra governing equation for the solvent concentration (in our case, EC) which allows us to describe an electrolyte with two solvents and one salt. We also include a cross diffusion term to consider the dragging effect between the working solvent (EC) and lithium ions. For the charge conservation equation, we directly use measured liquid junction potential as a function of both solvent and lithium-ion concentration, which avoids possible errors brought by identifying the thermodynamic factors.To elucidate the effect of solvent segregation, we compare the overpotential and concentration profile of Li ion and EC at the end of 3C discharge of the normal DFN (single case) and our revised model (double case). The revised model predicts opposite EC concentration compared with Li+, which has been observed by Wang et al. 5 For a high value of , the dragging effect between Li+ and EC is more significant, inducing high concentration gradients of both species. The EC overpotential can be as high as 10 mV and further affects the rate performance of LIBs. This revised model captures more complicated transport mechanisms in the electrolyte and opens the chance of linking the microscopic understanding on solvation structure to a continuum level model. Reference: (1) Newman, J.; Thomas-Alyea, K. E. Electrochemical Systems; 2004.(2) Xu, K. Electrolytes and interphases in Li-ion batteries and beyond. Chem Rev 2014, 114 (23), 11503-11618. DOI: 10.1021/cr500003w.(3) Xu, K. Solvation Sheath of Li+ in Nonaqueous Electrolytes and Its Implication of Graphite/ Electrolyte Interface Chemistry. J. Phys. Chem. C 2007.(4) Ding, M. S.; Xu, K.; Zhang, S. S.; Amine, K.; Henriksen, G. L.; Jow, T. R. Change of Conductivity with Salt Content, Solvent Composition, and Temperature for Electrolytes of LiPF6 in Ethylene Carbonate-Ethyl Methyl Carbonate. Journal of The Electrochemical Society 2001, 148 (10). DOI: 10.1149/1.1403730.(5) Wang, A. A.; Greenbank, S.; Li, G.; Howey, D. A.; Monroe, C. W. Current-driven solvent segregation in lithium-ion electrolytes. Cell Reports Physical Science 2022, 3 (9). DOI: 10.1016/j.xcrp.2022.101047. Figure 1

Reversible growth of solid electrolyte interface enhances charge capacity in cobalt sulfide-carbon nanotube anodes

The development of high-performance anode materials for lithium-ion batteries is a critical aspect of advancing energy storage technology. This study presents a novel approach to improve the charge capacity of anodes by harnessing the reversible growth of the solid electrolyte interface (SEI). This work focuses on cobalt sulfide (Co9S8) nanoparticles incorporated into a porous carbon nanotube (CNT) structure. Through a two-step pyrolysis process, Co9S8CNT composites, characterized by their conductive and mechanically robust CNT matrix are successfully synthesized. These Co9S8CNT anodes exhibit excellent initial charge capacity (560.5 mAh g−1 at 100 mA g−1) and remarkable stability, with a charge capacity of 633 mAh g−1 after 1000 cycles at 1000 mA g−1, accompanied by a Coulombic efficiency exceeding 99 %. Notably, this investigation reveals that the growth of the SEI plays a pivotal role in enhancing the charge capacity. Through in-situ Raman spectroscopy and other analytical techniques, it is suggested that the reversible reduction of organic solvent molecules within the large polymeric SEI is responsible for the increased charge capacity. This unique phenomenon is characterized by changes in the SEI's composition, driven by the charge and discharge processes. This study is a novel attempt to report a SEI's reversible growth that results in improved charge capacity, contrasting with prior research where SEI growth typically leads to capacity loss. Understanding this stable system provides valuable insights into increasing the cycle life and charge capacity of anodes, not only for transition metal sulfides but also for broader applications in energy storage.

Effects of Cathode Loadings on the Performance of the LiNi0.8Mn0.1Co0.1O2 Cathode in Lithium Batteries

LiNixMnyCozO2 (NMCs, x + y + z = 1) represent one promising cathode material for next-generation lithium-ion batteries (LIBs) and beyond, due to their high specific capacity and low cost.1-3 The current commercialized batteries tend to utilize high loadings of cathode materials and thin Li anodes for producing higher energy densities. However, a systematic study on the effects of cathode loadings is missing. To this end, we recently conducted a comparative study on the effects of different cathode loadings on the performance of LiNi0.8Mn0.1Co0.1O2 (NMC811). The NMC811 loading ranges from 2 – 14 mg/cm2. The resultant Li||NMC811 cells were tested for their capacity retention and sustainable capacity at different C-rates. Our study revealed that the cathode loadings have remarkably affected the cell performance. With increasing NMC811 loadings, the cells are more liable to fade in their capacity, due to a faster growth of solid electrolyte interface (SEI) on NMC811 particles and thereby a more sluggish Li-ion transportation. We also noticed that the Li anode side had remarkable effects on the Li||NMC811 cells. Particularly, we demonstrated that a polymeric surface coating via molecular layer deposition could protect the Li anode from degradation and thereby sustain Li||NMC811 cells for a better performance. Therefore, we concluded that the performance of the Li||NMC811 cells suffers from the issues of both the NMC811cathode and Li anode. It is significant to address their issues simultaneously for high performance.

Probe Growth and Degradation of SEI at Multivalent Battery Systems

Solid Electrolyte Interface (SEI) has not been widely reported for multivalent battery systems. Question such as whether there’s a SEI growth at the interface of the metal anode and the multivalent electrolytes is unclear. How the SEI is formed and its evolution with the electrochemical process is not known. Our lab has spent a great deal of efforts of understanding the role of SEI, its composition and evolution for multivalent electrolyte systems, and this work aims to give an overview of the recent research efforts with the use of the operando electroanalytical methods that reveal the SEI evolution for multivalent battery designs.

Safety Evaluation of Temperature-Dependent Aging Mechanisms of Li-Ion Batteries Using ARC Tests with Multiple Online Sensors

Compared to many other characteristics of Li-ion batteries, the safety behavior is a critical property and should be examined carefully. Especially manufacturers and most studies only focus on the safety of pristine cells. However, the safety behavior can drastically change dependent on the prior aging conditions such as ambient temperature. Especially low temperature aged cells with Li plating show a drastically decreased safety behavior [1]. Moreover, cells aged at higher temperatures with a distinct solid-electrolyte-interface (SEI) layer on the anode show an increased onset of self-heating leading to improved safety [2]. Post-Mortem analysis of aged cells confirmed the two dominating aging mechanisms: Li plating and SEI growth for low and high temperature range, respectively.Heat-wait-seek (HWS) tests under quasi-adiabatic conditions in an accelerated rate calorimeter (ARC) are a well-known method to evaluate the safety behavior of Li-ion batteries and can reveal critical temperatures such as the onset of self-heating. HWS tests on cells aged at different temperatures until different state-of-health (SOH) reveal the trend that a more pronounced aging increases or decreases the onset of self-heating depending on whether SEI growth or Li plating is the dominating aging mechanism.In addition to the temperature measurement, multiple sensors for voltage, resistance, strain, and ultrasonic transmission and reflection were placed on the pouch cell for a better understanding of the ongoing processes while the HWS tests. The benefit of these sensors is that they are cheap, allowing them to be widely implemented. Furthermore, an externally coupled mass spectrometer provides information about the gases produced and released after venting of the cell [3]. By Correlating different sensors signals, critical events on the way to the thermal runaway can be reliably identified or even predict in an early stage.Hence, the HWS tests on Li-ion batteries aged at different temperatures in combination with the multi sensor study provide a comprehensive understanding of the influence of temperature dependent aging state on the safety behavior of Li-ion pouch cells. Acknowledgment We gratefully acknowledge the German Federal Ministry of Education and Research (BMBF) for the financial support of the projects AnaLiBa (03XP0347C) and MiCha (03XP0317C) within the AQua cluster.

Ceramic Fillers for Improved Lithium-Sulfur Batteries

With the decarbonization of transportation, the demand for electric vehicles (EVs) and batteries that can power these EVs has been increasing. Lithium-ion-based batteries are already well-established and are considered the main chemistries to power current EVs. However, limited specific energy (< 300 Wh/kg) prevents these batteries from having high mileage vehicles. Lithium-sulfur batteries are considered the most promising next-generation energy storage system as they high theoretical capacity (~1675 mAhg-1), low cathode materials cost, and cell energy densities that can exceed 700 Wh/kg [1,2]. However, some major drawbacks prevent the Li-S battery system from being applicable in energy devices and hinder its commercialization, that include low power density and rapid capacity degradation during their cycling life. In addition, the lithium metal anode in Li-S batteries bring various issues to the forefront such as continuous solid electrolyte interface growth, dendrite formation, and loss of active lithium and electrolyte. These issues are further exacerbated at high C-rates which increases the possibility of an internal short-circuit and sudden cell failure [3]. In order to promote longer life cycles and prevent sudden cell failure, a thorough understanding of the cell’s electrochemical behavior is crucial for the development of a stable and practical Li-S battery system. The introduction of oxide fillers such TiO2, Al2O3, SiO2, etc. has been previously studied in various lithium-ion systems and has been shown to improve the cell’s lithium-ion transport properties, which in turn improve the performance of Li-S cells [4]. When used as interlayers they can also trap soluble polysulfides diffusing out of the cathode and reduce their crossover to the anode which helps reduce the shuttle effect of said polysulfides.In the present study, the use of a polysulfide immobilizing system to reduce sulfur loss and improve capacity retention has been demonstrated. The galvanostatic charge-discharge cycling study shows that cells retain higher capacity during the course of cycling. The initial capacity for Li-S cells with the filler average 1300+ mAh/g (C/10) while the capacity stabilizes around 1000 mAh/g after 3 cycles (C/5). The capacity retention at C/5 after 75 cycles was approximately 875 mAh/g which represents a rate 0.17% drop per cycle. When compared to control cells, the cells containing no fillers had lower initial capacity that averaged 1050 mAh/g and that rapidly declined to stabilize around 650 mAh/g. However, after this major drop, the cells remained stable no with measurable drop after 75 cycles. The behavior indicates that the cells with fillers delayed the effect of sulfur loss experienced in cells without fillers; however, the slow capacity drop that ensued, indicates that while polysulfide trapping was efficient it was unable to fully prevent it. The effect of fillers on the Coulombic efficiency (CE) also supports the polysulfide “trapping” mechanism and shows the ability of the cell to reduce the shuttle effect that contributes to lower CE values. Further electrochemical studies have been performed to understand the mechanisms of the improvement of the cell.

How Cyclic Aging at Different Temperatures Affects Safety of Li-Ion Pouch Cells

Li-ion battery safety behavior is critical and should be examined carefully. However, safety testing is typically performed only on pristine cells. This neglects the significant effect of aging conditions, such as ambient temperature, on safety behavior. For example, aging at low temperatures results in Li plating and thus drastically reduces safety [1–3]. Cells aged at higher temperatures with a pronounced solid-electrolyte-interface (SEI) layer on the anode show an increased onset of self-heating leading to improved safety [3,4].The temperature dependent cyclic aging behavior of commercial Li-ion pouch cells is evaluated using an Arrhenius plot. Further Post-Mortem analyses of aged cells from both branches of the V-shaped Arrhenius plot confirm two dominant aging mechanisms: Li plating and SEI growth for the low and high temperature ranges, respectively.Heat-wait-seek (HWS) tests under quasi-adiabatic conditions in an accelerated rate calorimeter (ARC) are used to evaluate safety behavior and identify critical temperatures such as the onset of self-heating. Multiple sensors (voltage, resistance, temperature, strain, and ultrasonic transmission) are placed on the pouch cell to provide a better understanding of the processes taking place during HWS tests. These sensors show that some critical events, such as the onset of swelling, venting, or separator melting, are only slightly affected by aging. In contrast, the onset of self-heating depends on the aging mechanism and state of health (SOH) of the cell, as a more pronounced aging has a greater impact on the change in safety. This knowledge can be used, for example, by cell manufacturers to estimate the minimum safety of aged cells based on tests of new cells.

A review of the use of Mxenes as hosts in lithium metal anodes and the anode formation

Severe dendritic growth and volume expansion are easily induced during the cycling process when lithium metal is used as an anode electrode directly. These problems cause the solid electrolyte interface (SEI) layer to break and re-form, which consumes the active lithium metal and electrolyte, thereby reducing the Coulomb efficiency and rapid capacity. Designing a host matrix with rapid mass transfer and enough storage space to promote lithium homogeneous deposition, hence reducing the repeated SEI growth and the formation of dead lithium, is an effective method to address the concerns mentioned above issues. MXenes with two-dimensional layered structures have been regarded as feasible hosts for stabilizing lithium due to their superior electrical conductivity, sizeable interlayer space, abundant lithiophilic surface functional groups, and excellent mechanical properties. In this review, we first summarized the multiple synthesis methods of MXenes, including etching the precursor MAX phase, chemical vapor deposition, UV-induced etching, and mechanochemical et al. Various synthesis methods would induce different surface termination and lamellar structures, affecting lithium metal nucleation and growth behavior. Subsequently, pure MXene, MXene-carbon and MXene-non carbon hybrid compounds applied for lithium metal anode hosts were introduced, focusing on alleviating noticeable volume changes and inhibiting lithium dendrite growth. Finally, some modification strategies and potential research prospects were summarized and prospected.

Operando Analysis of the Gassing and Swelling Behavior of Lithium-ion Pouch Cells during Formation

Improving the energy density of lithium-ion batteries advances the use of novel electrode materials having a high specific capacity, such as nickel-rich cathodes and silicon-containing anodes. These materials exhibit a high level of gas evolution during formation, which poses a safety hazard during operation. Analyzing the gas volume and the gassing duration is thus crucial to assess material properties and determining suitable formation procedures. This paper presents a novel method for evaluating both gassing and swelling simultaneously to determine the operando gas evolution of pouch cells with volume resolutions below 1 μl. Dual 1D dilatometry is performed using a cell expansion bracket which applies a quasi-constant force on the cell, thus providing reproducible formation conditions. The method was validated using the immersion bath measurement method and NCM/graphite pouch cells were compared to high-energy NCA/silicon-graphite pouch cells. Silicon-containing cells exhibited gas evolution higher by a factor of seven over ten successive cycles, thus demonstrating the challenges of high-silicon anodes. The concurrent dilation analysis further revealed a constant thickness increase over the formation, indicating continuous SEI growth and lithium loss. Consequently, the method can be used to select an ideal degassing time and to adjust the formation protocols with respect to gas evolution.

Interfacial-Catalysis-Enabled Layered and Inorganic-Rich SEI on Hard Carbon Anodes in Ester Electrolytes for Sodium-Ion Batteries.

Constructing a homogenous and inorganic-rich solid electrolyte interface (SEI) can efficiently improve the overall sodium-storage performance of hard carbon (HC) anodes. However, the thick and heterogenous SEI derived from conventional ester electrolytes fails to meet the above requirements. Herein, an innovative interfacial catalysis mechanism is proposed to design a favorable SEI in ester electrolytes by reconstructing the surface functionality of HC, of which abundant CO (carbonyl) bonds are accurately and homogenously implanted. The CO (carbonyl) bonds act as active centers that controllably catalyze the preferential reduction of salts and directionally guide SEI growth to form a homogenous, layered, and inorganic-rich SEI. Therefore, excessive solvent decomposition is suppressed, and the interfacial Na+ transfer and structural stability of SEI on HC anodes are greatly promoted, contributing to a comprehensive enhancement in sodium-storage performance. The optimal anodes exhibit an outstanding reversible capacity (379.6 mAh g-1 ), an ultrahigh initial Coulombic efficiency (93.2%), a largely improved rate capability, and an extremely stable cycling performance with a capacity decay rate of 0.0018% for 10 000 cycles at 5 A g-1 . This work provides novel insights into smart regulation of interface chemistry to realize high-performance HC anodes for sodium storage.

Capacity Degradation and Aging Mechanisms Evolution of Lithium-Ion Batteries under Different Operation Conditions

Since lithium-ion batteries are rarely utilized in their full state-of-charge (SOC) range (0–100%); therefore, in practice, understanding the performance degradation with different SOC swing ranges is critical for optimizing battery usage. We modeled battery aging under different depths of discharge (DODs), SOC swing ranges and temperatures by coupling four aging mechanisms, including the solid–electrolyte interface (SEI) layer growth, lithium (li) plating, particle cracking, and loss of active material (LAM) with a P2D model. Additionally, the mechanisms causing accelerated capacity to drop near a battery’s end of life (EOL) were investigated systematically. The results indicated that when the battery operated with a high SOC range, the capacity was more prone to accelerated degradation near the EOL. Among the four degradation mechanisms, li plating was mainly sensitive to the operation temperature and SOC swing ranges, while the SEI growth was mainly sensitive to temperature. Furthermore, there was an inhibitory interaction between li plating and SEI growth, as well as positive feedback between LAM and particle cracking during battery aging. Additionally, we discovered that the extremely low local porosity around the anode separator could cause the ‘knee point’ of capacity degradation.

Quantitative investigation of the cycling behavior and SEI formation of tin through time-resolved microgravimetry

Insufficient understanding on the mechanism of electrode failure restricts the development of sensitive electrode materials such as tin-based alloys. Here-in, a non-destructive and time-resolved in-situ characterization method is proposed for the investigation of the electrode failure. The cycling behavior of tin electrode and the evolution of the Solid-Electrolyte Interface (SEI) were investigated via combining quartz crystal micro-gravimetry (QCM) with cyclic voltammetry (CV). Key findings were further confirmed by ex-situ SEM, TEM and XPS. Remarkably, opposite to the general behavior, SEI thickness grows linearly with the electrode's thickness. This is ascribed to the continuous cracking and oxidization of Sn. However, below a critical thickness (Xo), the SEI growth by cracking (Xsn > Xo) transitions to diffusion-controlled growth (Xsn ≤ Xo). Surprisingly, after serious fracture of Sn, the QCM mass spectrometry reveals, the mass of Li2O also cycled reversibly along with Li insertion. Despite the general belief that the SEI is formed before the lithiation, the inorganic SEI mainly composed of Li2O and Li2CO3 unexpectedly forms in the later cycles during the lithiation. This inorganic part of the SEI plays the most important role of stabilizing the SEI. Preventing its formation, by using an unsuitable voltage window, results in a completely porous non-self-limiting SEI along with a porous electrode.

Accurate prediction of remaining useful life for lithium-ion battery using deep neural networks with memory features

Li-ion batteries degrade with time and usage, caused by factors like the growth of solid electrolyte interface (SEI), lithium plating, and several other irreversible electrochemical reactions. These failure mechanisms exacerbate degradation and reduce the remaining useful life (RUL). This paper highlights the importance of feature engineering and how a careful presentation of the data can capture the hidden trends in the data. It develops a novel framework of deep neural networks with memory features (DNNwMF) to accurately predict the RUL of Li-ion batteries using features of current and previous n cycles. The results demonstrate that introducing memory in this form significantly improves the accuracy of RUL prediction as root mean square error (RMSE) decreases more than twice with memory compared to without memory. The optimal value of n, referred to as nopt, is also determined, which minimizes the prediction error. Moreover, the number of optimization parameters reduces by more than an order of magnitude if an autoencoder is used in conjunction with the proposed framework (DNNwMF). The framework in this paper results in a trade-off between accuracy and computational complexity as the accuracy improves with the encoding dimensions. To validate the generalizability of the developed framework, two different datasets, i) from the National Aeronautics and Space Administration’s Prognostic Center of excellence and ii) from the Center for Advanced Life Cycle Engineering, are used to validate the results.

Experimental Study of the Degradation Characteristics of LiFePO4 and LiNi0.5Co0.2Mn0.3O2 Batteries during Overcharging at Low Temperatures

Battery overcharging can occur due to capacity and internal resistance variations among cells or battery management system failure that both accelerate battery degradation, which is more likely at low temperatures because of the large polarization effect. This study experimentally investigated the battery degradation characteristics during charging of LiFePO4 (LFP)/Graphite batteries at voltages of 3.65–4.8 V and Li(Ni0.5Co0.2Mn0.3)O2 (NCM)/Graphite batteries at 4.2–4.8 V at −10 °C with currents of 0.2–1 C. The results showed that the LFP cell capacities decreased linearly with an increasing number of cycles, while the NCM cell capacities faded in three trends with an increasing number of cycles under different conditions with linear fading, accelerated fading, and decelerated fading. The incremental capacity curves and differential voltage curves showed that the LFP cell degradation was mainly caused by the loss of lithium inventory (LLI), with some effect from the loss of active material (LAM). In the NCM cells, both the LLI and LAM significantly contributed to the degradation. Combined with internal battery morphology observations, the LAM mainly occurred at the anode, and the main side reactions leading to the LLI with lithium plating and solid electrolyte interface growth also occurred at the anode.

Electrochemical modeling, Li plating onsets and performance analysis of thick graphite electrodes considering the solid electrolyte interface formed from the first cycle

Based on a crack dominated solid electrolyte interface (SEI) resistance, an electrochemical model considering the SEI formed from the first cycle is established to investigate the comprehensive influence of electrode thickness, solid volume fraction and C-rate on the performance of thick graphite electrodes. Reasonable agreement is obtained for the simulated and measured charge and discharge profiles of Li/graphite cells including the first cycle. The periodic evolution of SEI film resistance during the cycles can be well interpreted by the mechanism based on the growth of SEI crack. The potential drop over SEI is found to contribute little to the polarization during Li inter- and deintercalation, and the electrode porosity reduction caused by SEI growth has larger effect for thick electrode than traditional thin electrode. The cell voltages, total potential drop of the electrode, state of charge and ratio of SEI capacity to the total capacity at the onsets of Li plating are analyzed. A linear relationship is developed for the Li plating onset voltages with the increasing of electrode thicknesses, solid volume fractions and C-rates. Finally, the performance of Li/graphite cells with electrode thicknesses (δ) ranging from 100 μm to 500 μm, solid volume fractions (εs) ranging from 0.35 to 0.6 and C-rates ranging from 0.05C to 0.5C is simulated and compared. The ionic migration limitation is aggravated by the growth of SEI for electrodes thicker than 300 μm as the solid volume fraction increases. The maximal areal capacity appears around δ = 500 μm and εs = 0.4, with a rate performance of 13.8 mAh cm−2, 13.6 mAh cm−2 and 13.1 mAh cm−2 at 0.1C, 0.2C and 0.5C, respectively.

Toward more realistic microgrid optimization: Experiment and high-efficient model of Li-ion battery degradation under dynamic conditions

Accurate and high-efficient battery life prediction is critical for microgrid optimization and control problems. Extracted from EV (electric vehicle)-PV(photovoltaics)-battery-based microgrid working profiles, five sets of accelerated aging experiments are conducted on LFP (graphite-LiFePO4) cells to reflect the effect of different energy storage capacities on battery degradation. Apart from SEI (solid electrolyte interface) growth and LAM (loss of active materials), lithium plating is likely to occur after prolonged cycling under the DOD (depth of discharge) range of over 80% when there are current pulses of around 1.5C. As for the degradation modelling, to efficiently solve while maintaining prediction accuracy, this work develops a reduced-order semi-empirical model (ROSEM) to compute fastly for control algorithms. The model reveals physical mechanisms and thus can generalize across actual conditions compared with another four semi-empirical models. The proposed ROSEM can precisely predict nonlinear battery degradation with less than 1.6% relative errors, and the computation duration for 500 cycles is less than 5s. The margin of simulation errors can be further narrowed to 0.6% with the correction of ANN (artificial neural network).

Characterization and Model-Based Investigation of Lithium-Ion Battery Cell Formation

The formation process of lithium-ion battery cells is one of the main contributors to the overall cell cost [1]. During this process step the solid electrolyte interface (SEI) is initially built. It is agreed upon that the composition and morphology of the SEI influences the safety and aging behaviour of the battery cell. However, the processes behind the initial build-up are not fully understood due to the manifold influencing factors, such as electrolyte composition, electrode structure, temperature, and formation protocol, which all impact the complex nanoscale processes at the interface [2,3,4]. High experimental effort is needed to investigate and optimize this process. Detailed multiscale models based on first principles can provide insights into the SEI formation but require many parameters that are difficult to determine and are also associated with uncertainty [5,6]. Therefore, those approaches are limited in terms of exploration and optimization of the formation process. Hence, there is a need for novel methods that enable to obtain information about the SEI growth and investigate the influential factors to effectively accelerate the development process. Here, we suggest a model-based approach that uses lumped growth models that can quickly be identified by using differential voltage data of formation experiments. Further, models are applied to simulate the impact of the formation protocol on the SEI formation with minimal experimental effort.Firstly, we present a parameter identification process for the applied growth model, which is based on a slow formation protocol and a reference measurement in a 3-electrode setup. The parameterization of the SEI model is conducted by combining coulometry and differential voltage analysis (DVA). Shifts of distinct peaks, i.e. feature, within the anode potential curve during the formation and the reference measurement are used to deduce the capacity loss due to the SEI growth. Using the SEI density and surface area of the electrode, the capacity loss is converted into an effective layer thickness, which is used to fit the parameters of the growth model. Within the SEI model different growth mechanisms can be implemented and compared. It is demonstrated that this approach can show differences in the SEI formation for a variation of electrolyte compositions, i.e. the electrolyte additives as can be seen in Figure 1. Afterwards, a simulation study for different formation protocols is presented. The identified growth model has been coupled with a pseudo-2-dimensional (P2D) model. Simulations are also compared to experimental data for various formation protocols and are shown to be in good agreement. Simulations reveal that the final effective film thickness is only slightly affected by current magnitude and mainly depends on the formation time as well as the anode potential. Furthermore, it can be seen that higher formation currents affect the homogeneity of the SEI across the electrode negatively.To sum up, the DVA analysis of the formation yields information about the SEI growth. This can be used to parametrize SEI growth models and investigate film growth mechanisms for different electrolyte compositions. Coupling growth models with P2D models enables to explore the influence of the formation protocols. To conclude, this novel approach enables to significantly accelerate the optimization of battery cell formation. In future work the approach could be refined to enable application to full cell voltage data, which would allow its use within battery production lines and could support end of line testing.[1] A. Kwade, W. Haselrieder, R. Leithoff, A. Modlinger, F. Dietrich, K. Dröder, Current status and challenges for automotive battery production technologies, Nature Energy, 2018, 3, DOI: 10.1038/s41560-018-0130-3[2] G. E. Blomgren, Liquid electrolytes for lithium and lithium-ion batteries, Journal of Power Sources, 2003, 119, DOI: 10.1016/S0378-7753(03)00147-2[3] S. J. An, J. Li, C. Daniel, D. Mohanty, S. Nagpure, D. L. Wood, The state of understanding of the lithium-ion-battery graphite solid electrolyte interphase (SEI) and its relationship to formation cycling, Carbon, 2016, 105, DOI: 10.1016/j.carbon.2016.04.008.[4] K. Xu, Electrolytes and interphases in Li-ion batteries and beyond, Chemical reviews, 2014, 114(23), DOI: 10.1021/cr500003w.[5] A. Wang, S. Kadam, H. Li, S. Shi, Y. Qi, Review on modeling of the anode solid electrolyte interphase (SEI) for lithium-ion batteries, npj Computational Materials, 2018, 4, DOI: 10.1038/s41524-018-0064-0[6] F. Röder, R. D. Braatz, U. Krewer, Multi-scale simulation of heterogeneous surface film growth mechanisms in lithium-ion batteries, Journal of the Electrochemical Society, 2017, 164 (11), DOI: 10.1149/2.0241711jes. Figure 1

Ageing Rate of Li-Ion Battery Cells As a Function of Temperature, C-Rate, and State of Health

The ageing rate and consequentially service life of mass-produced lithium-ion batteries depends on many external and internal factors. Some of the more important ones are the charge-discharge rate, ambient temperature, electrode thickness and state of health (SoH). This makes the estimation of the lifetime of battery cells very challenging and time-consuming. This motivates the development of models capable of determining the ageing behavior of a battery cell with relatively little experimental data.In this study1 we build on our previous work2,3 and use Arrhenius plots of the ageing rate to analyze the service life of battery cells in a relatively simple and straightforward way. We cycle aged two types of cells – commercial 5 Ah high-energy 21700 cells with Si/graphite anode (≈3 % Si) and LixNi0.90Co0.05Al0.05O2 + LiyNiO2 (NCA + LNO) cathode and lab-made 0.1 Ah pouch cells with LixNi0.33Mn0.33Co0.33O2 (NMC111) cathode and graphite anode. The ageing is ensured by systematically cycling the cells in a temperature range of -15 °C to 60 °C at various C-rates (0.2 C – 1 C).The capacity fade data is analyzed to obtain the ageing rate (% of SoH per cycle) as a function of temperature, which forms the V-shaped Arrhenius plots shown in Figure 1. Each set of data clearly shows two slopes that cross at intermediate temperatures. As shown previously experimentally2,3 and theoretically,4 the slopes correspond to two ageing mechanisms – lithium plating in the low temperature region and growth of solid-electrolyte interface (SEI) at high temperature region. The intersection of the two Arrhenius slopes denotes a transition between the dominating ageing mechanism and also denotes the optimum temperature at which the battery cell has the highest service life.By analyzing the data, we show that the crossover temperature shifts towards higher temperature values with increasing C-rate and increasing thickness of the anode, as both increase the electrode area-normalized current. The crossover temperature depends on the SoH of the battery. The precise trend depends on the cell chemistry, as we observe increase of the crossover temperature for one type of cells and decrease of crossover temperature for the other type of cells. The shift of the crossover temperature to lower temperatures observed in pouch cells could be explained by a more rapid loss of cyclable lithium, whereas the shift towards higher C-rates observed in commercial 21700 cells can be observed due to increasing practical C-rates as the electrodes degrade and loose some of their initial capacity. By using relatively little input data, we are able to predict the temperature- and C-rate-dependent end of life of a battery cell with good precision.Evaluating the Arrhenius-type dependences of the ageing rate of the battery cells provides valuable insights for use in battery management systems and extending the service life of battery cells. Acknowledgements Gints Kucinskis acknowledges Latvian Council of Science project “Cycle life prediction of lithium-ion battery electrodes and cells, utilizing current-voltage response measurements”, (no. LZP-2020/1-0425). The part of the research performed at ZSW was carried out in the framework of the industrial collective research program (IGF no. 20884 N/2). It was supported by the Federal Ministry for Economic Affairs and Energy (BMWi) through the AiF (German Federation of Industrial Research Associations eV) based on a decision taken by the German Bundestag. References G. Kucinskis, M. Bozorgchenani, M. Feinauer, M. Kasper, M. Wohlfahrt-Mehrens, T. Waldmann, submited to J. Power Sources.T. Waldmann, M. Wilka, M. Kasper, M. Fleischhammer, and M. Wohlfahrt-Mehrens, J. Power Sources, 262, 129–135 (2014) https://linkinghub.elsevier.com/retrieve/pii/S0378775314004352.M. Bozorgchenani, G. Kucinskis, M. Wohlfahrt-Mehrens, and T. Waldmann, J. Electrochem. Soc., 169, 030509 (2022) https://iopscience.iop.org/article/10.1149/1945-7111/ac580d.X.-G. Yang and C.-Y. Wang, J. Power Sources, 402, 489–498 (2018) https://linkinghub.elsevier.com/retrieve/pii/S0378775318310462. Figure 1. Arrhenius plots based on ageing rate for (a-e) commercial 21700 cells at 100 %, 95 %, 90 %, 85 % and 80 % of SoH and (f,g) lab-made pouch cells at 100 % and 95 % SoH. Figure 1

Determination of Leakage Currents Via Voltage Hold and Voltage Relaxation Method Using High Precision Coulometry - a Comparison and Optimization Study

Parasitic side reactions on the surface of the anode and the cathode of lithium-ion batteries contribute significantly to calendar and cyclic aging [1, 2]. In order to investigate these parasitic side reactions, such as solid electrolyte interface growth, this study focuses on two methods broadly utilized to determine leakage currents: the voltage hold and the voltage relaxation method. Regarding the voltage relaxation method, the open circuit voltage (OCV) decay is observed over weeks without allowing active electrode de-/lithiation [3] and subsequently, a small pulse is performed to calculate the leakage current [4]. For the voltage hold method, a defined voltage is kept constant, which compensates the parasitic side effects and allows active electrode de-/lithiation to maintain the state of charge (SoC) [5, 6].To compare these methods, different results are found in literature. On the one hand, both methods were reported to deliver individual results [3, 7], while other research activities [8] found the variance only at 100% SoC.Therefore, voltage hold and voltage relaxation were compared in this study, utilizing high precision coulometry (HPC). The measurements were conducted on 16 commercial LGChem INR18650MJ1 cylindrical cells at 25 °C, 40 °C and 55 °C and different SoCs of 10%, 50%, 90%, and 100% SoC, respectively. The cells were preconditioned to each SoC and were subsequently stored for 30 days to minimize relaxation and anode overhang effects. Afterwards, voltage hold and voltage relaxation measurements were carried out for 21 days at each temperature and SoC. In addition to the discharge pulse, an incremental capacity analysis (ICA) was conducted for all three temperatures through the whole voltage range to compare and validate the results obtained.The measurements of this study delivered similar results for the voltage hold and the voltage relaxation method, especially at 10% SoC and 50% SoC. Consequently, the voltage hold did not contribute to additional parasitic side reactions from allowing active de-/lithiation of the electrode. Minor deviations were found for 90% SoC and 100% SoC, for which one possible explanation may be the flat shape of the OCV curve, among others. In addition, the results show a strong dependency on the pulse length and strength.This study was part of the project ExZellTUM III, funded by the German Federal Ministry of Education and Research (BMBF) under grant number 03XP0255, supervised by Project Management Jülich (PTJ).Literature [1] Smith, A.; Burns, J.; Dahn, J.: A high precision study of the coulombic efficiency of Li-ion batteries, In: Electrochemical and Solid-State Letters 13, p. A177, 2010 [2] Birkl, C. R.; Roberts, M. R.; McTurk, E.; Bruce, P. G.; Howey, D. A.: Degradation diagnostics for lithium ion cells, In: Journal of Power Sources 341, p. 373-386, 2017 [3] Zilberman, I.; Sturm, J.; Jossen, A.: Reversible self-discharge and calendar aging of 18650 nickel-rich, silicon-graphite lithium-ion cells, In: Journal of Power Sources 425 (9), p. 217-226, 2019 [4] Schmidt, J. P.; Weber, A.; Ivers-Tiffée, E.: A novel and fast method of characterizing the self-discharge behaviour of lithium-ion cells using a pulse-measurements technique, In: Journal of Power Sources 274, p.1231-1238, 2015 [5] Lewerenz, M.; Käbitz, S.; Knips, M.; Münnix, J.; Schmalstieg, J.; Warnecke, A.; Uwe Sauer, D.: New method evaluating currents keeping the voltage constant for fast and highly resolved measurement of Arrhenius relation and capacity fade, In: Journal of Power Sources 353, p.144-151, 2017 [6] Vadivel, N. R.; Ha, S.; He, M.; Dees, D.; Trask, S.; Polzin, B.; Gallagher, K. G.: On leakage current measured at high cell voltages in lithium-ion batteries, In: Journal of The Electrochemical Society, 164 (2), p. 508-A517, 2017 [7] Theiler, M.; Endisch, C.; Lewerenz, M.: Float Current Analysis for Fast Calendar Aging Assessment of 18650 Li(NiCoAl)O2/Graphite Cells, In: Batteries 7 (2), p. 22–22, 2021 [8] Käbitz, S.; Gerschler, J. B.; Ecker, M., Yurdagel, Y.; Emmermacher, B.; André, D.; Mitsch, T.; Uwe Sauer, D.: Cycle and calendar life study of a graphite LiNi1/3Mn1/3Co1/3O2 Li-ion high energy system. Part A: Full cell characterization, In: Journal of Power Sources 239, p. 572-583, 2013

Model-Informed Si Electrode Design Considering Dynamic Pore-Closure and Stack Pressure Effects

Silicon is novel Li-ion battery anode chemistry with exceptional theoretical energy densities. However, this alloying material has significant challenges with non-passivating solid-electrolyte interface (SEI) formation and significant chemo-mechanics issues. These issues have been studied extensively at the particle-level. However, extensive SEI formation and dynamic particle chemo-mechanics need to be accounted for when designing the overall electrode microstructure. For example, Si particle expansion can result in electrolyte pore-closure. During charging (Si lithiation), Si particles near the separator lithiate faster than Si near the current-collector. Thus, Si particles near the separator begin to expand faster and close-off electrolyte access to particles near the current collector. This heterogeneous through-plane lithiation then results in low overall electrode utilization, especially at high rates (i.e.,>1 C). The “choking off” effect is a result of a strong feedback between heterogeneous lithiation, Si expansion, and electrolyte pore closure.To aid in Si electrode design and account for dynamic particle expansion/contraction, the standard pseudo-2D battery model is reformulated to account for finite-strain chemo-mechanics. This model explores the trade-offs between initial electrode porosity, electrode thickness, rate-capability, and external pressure. Additionally, the model implements simplified SEI growth dynamics to explore how SEI growth effects should be accounted for in electrode design.The Figure illustrates polarization responses for a 1C charge for a Si/NMC532 cell. The different colors indicate different initial anode porosities. As shown in Figure a, the low initial porosity cases results in significant polarization, but additional gains after 50% initial porosity are significantly diminished. These results are shown for an external pressure of 15 psi. Figure b illustrates the cell thickness as a function of time. As illustrated, the lower porosity case starts at a shorter initial thickness. For all cases, the cell thickness increases as Si lithiates/expands. Figure c illustrates the anode porosity at the cut-off voltage as a function of anode thickness. As shown, the lower initial porosity case has significant pore-closure on the right-side at the separator interface. The higher initial porosity cases have increased anode lengths because the Si utilization is improved due to the reduced pore-closer effects. The graphic illustrates the main features of the reformulated pseudo-2D battery model. Figure 1