Li-ion Coin Cells Research Articles

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

A Data-Driven Quality Control Method for Li-Ion Cells

The urgency to develop innovative electrochemical energy storage systems has increased exponentially as many governments across the world adopt net-zero strategies that rely heavily on transport electrification. This means that ensuring the repeatability and reproducibility of electrochemical data produced in battery research is one of the most important issues in the race to a carbon neutral economy. Li-ion batteries, the most mature and competitive battery technology currently available, has had some of its most significant advances in the discovery of new electrode materials, hence there is large research interest in this.Academic institutions have particular strengths and long experience in materials discovery, however, deployment of these materials in commercial devices lags behind for various reasons. One problem is the lack of quantitative parameters for quality control in electrochemical measurement as well as the difficulty of precisely evaluating cells prior to cycling. Cell assembly is a complex process with several steps, all of which could contribute to a faulty cell. Lack of reproducibility, especially when comparing from laboratory to laboratory, often ensue as a result. To optimize space and resource utilization many researchers do their testing in coin cells; the proliferation of best practice guides for coin-cell fabrication and measurement highlights the advantages of this cell format.(1-4) However, a simple quantitative method of quality control is still lacking.Figure 1: Graphical identification of outlier cells prone to poor cycling. OCV of pristine coin cells, NMC 811 half-cells. Outlier cells (black trace, bottom, red trace top) can be easily identified prior to cycling.In this presentation we demonstrate a proof-of-concept development of a quality control process based on the time evolution of the open circuit potential (OCV) of pristine Li-ion coin cells, and how that can be used to discard faulty cells before cycling. A pass/fail criterion is developed based on the OCV transients by fitting the behaviour of more than 20 different cells to a sigmoidal function, the goodness of fit is then compared. We found that cells that fall below a certain R2 value have shorter cycle life under the same cycling conditions. The threshold values showed a dependence on cell chemistry. Additionally, the graphical representation of the transients allows for identifying outliers that had significantly worse electrochemical performance (figure 1), therefore the goodness of fit can be used to quantitatively gauge the quality of the cells prior to cycling.The establishment of a quantitative pass/fail criterion makes the quality control process amenable to automation. To demonstrate this, we developed a Python program that takes experimental OCV transients as inputs to automate the data analysis. The program can process information from virtually hundreds of data files in a short period of time, easily identifying outlier cells. A spreadsheet file with the raw and transformed data, as well as with the generated plots is created for each transient OCV, allowing users to explore the data manually, if necessary.In summary, we have used data from a large number of coin cells to empirically fit a quantitative quality control parameter, establish a pass/fail criterion based on OCV transients, and develop code to greatly save time and resources and establish a statistical analysis of the effectiveness of the assembly process. This innovative data-driven approach showed great promise to improve repeatability and reproducibility in measuring the performance of new materials and cell-chemistries in a systematic and quantitative way.

A Statistical Design Approach on Electrochemical Impedance Spectroscopy of NMC Li-Ion Battery

Robust development of energy storage materials requires a deep understanding of the relationship between the operation conditions and electrochemical properties. The influences of cell potential and environmental temperature on battery dynamics of commercially available LiNiMnCoO2(NMC)/graphite(C) coin cells were statistically investigated and discussed by using electrochemical impedance spectroscopy measurements and Taguchi statistical design. The Taguchi method reduced the variation in the electrochemical process with an experimental design; therefore, number and duration of impedance measurements were minimized. This design tested three levels for each categorical factor that are the cell potential and the cell temperature. The third level of both potential and temperature optimized the dynamic parameters of the batteries. The calculated signal-to-noise ratio and delta values for the cell temperature were higher for each battery resistance than that of the cell potential. In addition, the calculated probability, P value, was also lower (around zero) for the cell temperature. Thus, the temperature was determined to be the most significant factor, suggesting that this factor should be constrained carefully when the battery dynamics is desired to be optimized. In this paper, the electrochemical impedance spectroscopy method combined with the Taguchi design was performed to offer an unprecedented insight into the effects of the factors on the elements of the equivalent circuit model of the Li-ion coin cells.

Influence of the Ambient Storage of LiNi0.8Mn0.1Co0.1O2 Powder and Electrodes on the Electrochemical Performance in Li-ion Technology

Nickel-rich LiNi0.8Mn0.1Co0.1O2 (NMC811) is one of the most promising Li-ion battery cathode materials and has attracted the interest of the automotive industry. Nevertheless, storage conditions can affect its properties and performance. In this work, both NMC811 powder and electrodes were storage-aged for one year under room conditions. The aged powder was used to prepare electrodes, and the performance of these two aged samples was compared with reference fresh NMC811 electrodes in full Li-ion coin cells using graphite as a negative electrode. The cells were subjected to electrochemical as well as ante- and postmortem characterization. The performance of the electrodes from aged NM811 was beyond expectations: the cycling performance was high, and the power capability was the highest among the samples analyzed. Materials characterization revealed modifications in the crystal structure and the surface layer of the NMC811 during the storage and electrode processing steps. Differences between aged and fresh electrodes were explained by the formation of a resistive layer at the surface of the former. However, the ageing of NMC811 powder was significantly mitigated during the electrode processing step. These novel results are of interest to cell manufacturers for the widespread implementation of NMC811 as a state-of-the-art cathode material in Li-ion batteries.

Redox Potential Tuning of s-Tetrazine by Substitution of Electron-Withdrawing/Donating Groups for Organic Electrode Materials.

Herein, we tune the redox potential of 3,6-diphenyl-1,2,4,5-tetrazine (DPT) by introducing various electron-donating/withdrawing groups (methoxy, t-butyl, H, F, and trifluoromethyl) into its two peripheral benzene rings for use as electrode material in a Li-ion cell. By both the theoretical DFT calculations and the practical cyclic voltammetry (CV) measurements, it is shown that the redox potentials (E1/2) of the 1,2,4,5-tetrazines (s-tetrazines) have a strong correlation with the Hammett constant of the substituents. In Li-ion coin cells, the discharge voltages of the s-tetrazine electrodes are successfully tuned depending on the electron-donating/withdrawing capabilities of the substituents. Furthermore, it is found that the heterogeneous electron transfer rate (k0) of the s-tetrazine molecules and Li-ion diffusivity (DLi) in the s-tetrazine electrodes are much faster than conventional electrode active materials.

In-Situ Lithium-Ion Batteries Thermal Runaway Detection and Overcharge Performance Analysis with Internal Resistance Temperature Detector

Thermal safety is the main roadblock for applications of high energy density lithium-ion batteries (LIBs) and catastrophic LIB failure has long been a public concern. There have been numerous LIB safety testing standards and many LIB safety management devices, including isolating shutdown separators, protective electrode coatings, safety valve, etc., that are proposed for LIB service safety and reliability improvement. Despite the application of LIB tests and safety devices, thermal runaway is still reported as a major threat to equipment and personal safety. In order to improve the in-service safety, the battery management system (BMS) and safety devices need to examine and analyze the LIB performance in a real-time manner so the rapid thermal runaway progress can be detected and prevented at an early stage. Due to the complex nature and rapid reaction rate of thermal runaway, BMS and safety device with capability of comprehensive in-situ analysis of LIB thermal runaway progress have seldomly been reported. A simple BMS capable of examining the LIB thermal safety and detecting thermal runaway related reactions needs to be developed.Existing LIB thermal safety management systems typically rely on temperature sensors including thermocouples, thermistors, fiber bragg-grating sensors, etc. Despite their success in LIB surface temperature measurement, they cannot be applied for direct electrode temperature measurement, which is crucial for thermal runaway detection and prevention. Existence of thermal resistance between the battery surface and electrodes also impedes the development of quick responding LIB temperature monitoring systems based on surface temperature measurements. To address this issue, we propose the application of resistance temperature detectors (RTDs) in LIBs with the help of additive manufacturing. By embedding RTDs into operating LIBs, reliable in-situ monitoring of the electrode temperature can be achieved, which is beneficial for early detection and prevention of thermal runaway. In this work, thermal runaway in LIBs was triggered by overcharge and external short circuit (ESC). Battery temperature was recorded by the internal RTD embedded on the electrodes and external RTD mounted on the battery surface. Significant temperature difference of ~9 ºC and ~20 ºC were detected between the electrode and battery surface in ESC and overcharge of small lab-fabricated Li-ion coin cells. The temperature difference can be as high as ~200 ºC for large capacity Li-ion pouch cells. In ESC, the internal RTD detected thermal runaway ~ 10 times faster than the external RTD despite of the battery type. Besides, the internal RTDs can provide accurate electrode temperature contour and comparison of anode and cathode temperatures during regular operation and thermal runaway of LIBs. The solid electrolyte interface (SEI) which is comprised of reduced electrolytic compounds like ROCO2Li, (CH2OCO2Li)2 and ROLi, can contribute to heat generation in LIB thermal runaway. The effect of SEI can be analyzed with in-situ examination of cathode and anode temperatures. Transient temperature difference captured by the internal RTD indicated that anode is the critical electrode and contributes more to the heat generated in thermal runaway. This helps to optimize temperature sensor arrangement for more effective monitoring and prevention of thermal runaway.The internal RTD also provides opportunity for in-situ analysis of chemical reactions in thermal runaway. Gas generated in thermal runaway has a high concentration of CO, H2, CH4, etc., which is prone to ignition and explosion. The generated gas can affect LIB structure as it causes deformation of electrodes and separators. Although this is hard to be detected with most basic BMS, it can be examined with electrode and battery surface temperature comparison, as the LIB thermal resistance is changed during gas accumulation. Different modes of thermal runaway can be differentiated by analyzing the temperature profiles, which allows for customized thermal runaway prevention and control strategy.

Identification of Battery State of Health By Combining Machine Learning and Impedance Spectroscopy

The possibility of diagnosing Li-ion battery’s state of health (SoH) and remaining useful life from electrochemical impedance spectra (EIS) using Machine Learning is investigated. The Gaussian Process (GP) with automatic relevance determination is used to identify degradation patterns without relying on any equivalent circuit models. The experiment consists of continuous charge-discharge cycling of commercial Li-ion coin cells. With the GP model trained with the entire spectrum measured on identical cells cycled under the same condition, the cycle number of a testing cell can be predicted by providing the corresponding EIS data. The trained GP model selected one frequency that is most indicative for the battery degradation, indicating the potential that the battery SoH can be diagnosed by measuring impedance at certain frequencies instead of taking a full-range EIS. Moreover, the GP model trained with all sets of data is able to identify the cycle number without knowing temperature or SoC, showing the possibility of developing a universal diagnosis methodology for battery management systems. [1] R. R. Richardson, M. A. Osborne, D. A. Howey, J. Power Sources , Vol. 357, 31 Jul. 2017, pp209-219 [2] M. Galeotti, L. Cina, C. Giammanco, S. Cordiner, A. D. Carlo, Energy , 89 (2015) 678-686 Figure 1

Reproducibility of Li-ion cell reassembling processes and their influence on coin cell aging

Abstract Extracting coin cells from industrially manufactured Li-ion cells is a commonly used method to investigate the state-of-health of the electrode material. However, the influence of the reassembling process on coin cell performance and its reproducibility is not clearly described in the literature. For this intention, we develop a preparation procedure to extract the cell material out of these original cells and build coin cells. The measurements of the reassembled Li-ion coin cells reveal a similar relative standard deviation in capacity to commercially cells at begin of life. Furthermore, the coin cells show a stable aging behavior with a mean capacity loss of about 5% after 300 full cycles at 25 °C. The washing of the electrodes before the reassembly does not decrease the relative standard deviation in capacity at begin of life and during the cyclic aging. The relative standard deviation in impedance is larger for the washed coin cells. In addition, we analyze the influence of the separator on the aging of the coin cells. Coin cells with a double-layer separator, consisting of polypropylene fiber and a polyethylene membrane, show a lower variation in capacity at begin of life and a lower loss in capacity over cycle aging than coin cells with the separator from the original cell.

Model Parameterization of Li-Ion Cell with Blended Cathodes

The high power and high energy density of the Li-ion batteries (LIBs) are highly desirable for automotive applications which can be achieved by using cathodes with higher specific energy and rate capability. The existing cathode materials have various merits and demerits such as LiMn2O4 (LMO) has good rate capability, high power and low cost but lower energy and higher capacity fade due to manganese dissolution; LiNixMnyCo1-x-yO2 (NMC) has higher energy with issues of lower power and operating voltage; LiFePO4 (LFP) has higher energy, lower voltage and better thermal stability but very low electronic conductivity and lithium diffusivity; LiCoO2 (LCO) has higher energy but poor thermal stability and Co toxicity [1-2]. The blending of two cathode materials has been used in an attempt to overcome these shortcomings, to enhance the energy and power densities, as well as life cycle of the batteries [1]. In this regard, the blend of NMC and LMO has been used in commercial cells which has better performance with lower price than LCO [1]. The optimization of the blend’s percentage is a critical aspect to enhancing the electrochemical performance that requires several experimental iterations and is quite expensive and time consuming. Very few studies on mathematical modelling of the blended electrodes to optimize the composition of the blends have been performed [2-3]. This technique can minimize the number of experiments required to design the electrodes which can lead to improved cycle life and electrochemical performance of the batteries. In this study, different blends of LMO and NMC will be used as a cathode to fabricate Li-ion coin cells against the graphite anode. The electrochemical performance of these cells will be analysed using galvanostatic charge-discharge, electrochemical impedance spectroscopy, and cyclic voltammetry. In addition 3-electrode cells will be utilised to determine the open circuit potential (OCP) and lithium diffusivity in the solid matrix of the different blended cathodes and anodes through galvanostatic intermittent titration technique (GITT). Electrode thickness, porosity, particle size will also be measured in these cases, and a correlation for the OCPs will be fitted based on the blend compositions which will be used as an input for the numerical modelling of these cells. The pseudo 2-D electrochemical model [4] will be used to imitate the charge-discharge behaviour of the graphite-LMO:NMC cells. This study will pave the way to numerically analyse the cycling performance of the LIBs using the blended systems and would assist the development of the battery management systems for these battery chemistries.

(Invited) Ultrathin Polymer Electrode Coatings to Stabilize Electrochemical Interfaces in Lithium-Ion Batteries

Safety and performance of Li-ion batteries lie at the electrochemical interfaces. Local surface chemistry and electrochemistry at the battery negative electrode will dictate whether stable intercalation or unstable deposition processes are favored. This talk will present the environmental, electrochemical and chemical effects, namely temperature, current density and negative electrode surface coatings, have on the nucleation, growth and morphology of electrodeposited lithium. We use initiated chemical vapor deposition (iCVD) to generate ultrathin polymer coatings with thickness control at the nanoscale [1], even on complex three-dimensional (3D) substrates [2] such as carbonaceous negative composite electrodes. The siloxane-based polymers most commonly generated by iCVD contain ether-like functionalities that support the solvation and transport of Li+ salts, such that they are readily transformed into Li-ion conductors [3]. Polymer-modified electrodes are assembled into Li-ion coin cells containing liquid electrolytes, in which we examine such properties as specific power, coulombic efficiency, cycle life, and tolerance to overcharge/overdischarge conditions. In-situ optical microscopy observation of galvanostatic plating and stripping experiments provides valuable understanding of morphology, growth behavior, and propensity to form internal short circuits. These observations are then coupled with cell impedance changes detected through electrochemical impedance spectroscopy to develop advanced diagnostic and fault detection techniques. Tenhaeff, W.E.; Gleason, K.K. Func. Mater. 2010, 18, 979.Sassin, M.B.; Long, J.W.; Wallace, J.M.; Rolison, D.R. Horizons 2015, 2, 502.Reeja-Jayan, N. Chen, J. Lau, J. A. Kattirtzi, P. Moni, A. Liu, I. G. Miller, R. Kayser, A. P. Williard, B. Dunn, and K. Gleason, Macromolecules 48, 5222 (2015).

In-Situ and First Principles Characterization of Alpha-Manganese Oxide (MnO2)

Alpha manganese oxide (α-MnO2) is of interest as a cathode material for lithium-ion batteries and as an electrode/electrocatalyst for hybrid Li-ion/Li-O2 systems. It has a tunnel structure with large 2x2 channels that accommodate different species such as Ba2+, K+, NH4 +, or H3O+/H2O. Characterization and modeling of the insertion and removal of Li, oxygen, and H3O+/H2O species under electrochemical cycling and heating is important for understanding how MnO2 acts as a hybrid Li-ion/Li-O2 battery material. In this talk, we will discuss our work in using in-situ synchrotron X-ray diffraction (XRD), X-ray absorption near-edge spectroscopy (XANES), in-situ UV resonance Raman spectroscopy, and density functional theory (DFT) calculations, to unravel the changes in α-MnO2during electrochemical cycling as well as dehydration process. We found evidence of oxygen incorporation and partial removal during electrochemical cycling, as well as two-stage water removal during heating. Both processes involve facile oxygen diffusion through the center of 2x2 tunnels. Keywords: MnO2, in-situ XRD, DFT Reference: Z.-Z. Yang, D. Ford, J.-S. Park, Y. Ren, S. Kim, H. Kim, T. Fister, M. K. Y. Chan,# M. M. Thackeray,# “Probing the release and uptake of water in α-MnO2•xH2O,” Chemistry of Materials 29, 1507–1517 (2017).Z. Yang, L. Trahey, Y. Ren, M. K. Y. Chan,# C. Lin, J. Okasinski, and M. M. Thackeray, “In-Situ High-Energy Synchrotron X-ray Diffraction Studies and First Principles Modeling of α-MnO2 Electrodes in Li-O2 and Li-ion Coin Cells,” Journal of Materials Chemistry A 3, 7389-7398 (2015). Acknowledgements: This work was supported as a part of the Center for Electrochemical Energy Science, an Energy Frontier Research Center funded by the US Department of Energy, Office of Science, Basic Energy Sciences under award number DE-AC02–06CH11. Use of the Advanced Photon Source, a US DOE Office of Science User Facility operated by Argonne National Laboratory, was supported by DOE under Contract No. DE-AC02-06CH11357. Use of the Center for Nanoscale Materials, an Office of Science user facility, was supported by the U. S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. DE-AC02-06CH11357. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. Figure 1

Interfacial Control at Lithium-Ion Electrodes Using Ultrathin Polymer Coatings Generated By Initiated Chemical Vapor Deposition

Interfacial processes at the surfaces of charge-storing materials in Li-ion batteries have a great impact on such critical operational characteristics as rate capabilities, cycle and calendar life, and safety. Solid-electrolyte interfaces (SEIs) that form spontaneously in situ serve to control surface reactivity in most Li-ion systems, yet may not yield optimized electrode and battery performance. Recent advancements in deposition protocols for nanoscale coatings open new opportunities to pursue deliberately designed & applied surface coatings at Li-ion electrodes. Initiated chemical vapor deposition (iCVD) has emerged as a promising route to generate ultrathin polymer coatings with thickness control at the nanoscale [1], even on complex, porous substrates [2], while also being readily adaptable to scaled manufacturing. As a further benefit for electrochemical applications, the siloxane-based polymers most commonly generated by iCVD contain ether-like functionalities that support the solvation and transport of Li+ salts, transforming them into Li-ion conductors [3]. We are exploring iCVD protocols as a means to apply nanometers-thick polysiloxanes at the surfaces of commercially available powder-composite electrodes, including graphite-based anodes and metal oxide/phosphate-containing cathodes. The performance of polymer-modified electrodes is assessed in conventional Li-ion coin cells, in which we assess such properties as specific power, irreversible capacity (e.g., due to SEI formation), coulombic efficiency and cycle life, as we vary the thickness of the polymer coating from 5–50 nm. Test cells containing these electrodes are also subjected to more extreme operating conditions (overcharge and overdischarge; high-rate charging at low temperatures) to assess the benefits of the nanoscale polymer coating for suppressing undesirable reactions at the electrode/electrolyte interface. Tenhaeff, W.E.; Gleason, K.K. Adv. Func. Mater. 2010, 18, 979.Sassin, M.B.; Long, J.W.; Wallace, J.M.; Rolison, D.R. Mater. Horizons 2015, 2, 502.B. Reeja-Jayan, N. Chen, J. Lau, J. A. Kattirtzi, P. Moni, A. Liu, I. G. Miller, R. Kayser, A. P. Williard, B. Dunn, and K. Gleason, Macromolecules 48, 5222 (2015)

Experimental assessment and model development of cycling behavior in Li-ion coin cells

The electrochemical performance of mesocarbon microbeads (MCMB)-lithium manganese oxide (LMO) spinel cells is examined by cyclic voltammetry, galvanostatic cycling and electrochemical impedance spectroscopy. The loss in capacity in full-cells is attributed to occurrence of parasitic reactions at the two electrodes. The contribution of each electrode in full-cell degradation is ascertained through testing of MCMB and LMO half-cells, with the former exhibiting a faster rate of degradation as compared to the latter. Lithium diffusion coefficient of MCMB and LMO electrodes are determined using the galvanostatic intermittent titration technique at various stages of cycling. The experimentally measured parameters are used to simulate the electrochemical behavior of MCMB and LMO half-cells. The computed capacity and cell potential variation show good agreement with experimentally obtained data for half-cells at 1C and 2C currents. The MCMB half-cell simulations reveal that loss in discharge capacity occurs due to thickening of SEI film, increase in gas formation and loss in cyclable lithium. Simulations of LMO half-cells show that capacity loss with cycling is a result of reduction in active material, increase in surface resistance with inactive material deposition and loss in cyclable lithium.

(Invited) Comparative First Principles Studies of Hybrid Li-Ion/Li-Oxygen Battery Materials

In the Center for Electrochemical Energy Science (CEES) Energy Frontier Research Center, we are investigating a new class of energy storage materials – hybrid Li-ion/Li-oxygen materials – that combine transition metal and oxygen redox chemistries to deliver high energy storage capacity [1, 2, 3]. The electrochemical reactions, structural and electronic structure evolution of these materials are complex, requiring a combination of in-depth characterization and first principles modeling. In this talk, we will report on a comparison study of several examples of hybrid Li-ion/Li-oxygen materials using density functional theory calculations. We will discuss the structural and electronic structure reasons for differences in reaction pathways and competition between transition metal vs oxygen redox chemistries. Insight towards selecting and designing promising hybrid battery materials gleaned from the comparison will be discussed. [1] L. Trahey, C. S. Johnson, J. T. Vaughey, S.-H. Kang, L. J. Hardwick, S. A. Freunberger, P. G. Bruce, M. M. Thackeray, “Activated Lithium-Metal-Oxides as Catalytic Electrodes for Li-O2 Cells,” Electrochemical and Solid-State Letters, 2011, 14, A64. [2] M. M. Thackeray, M. K. Y. Chan, L. Trahey, S. Kirklin, and C. Wolverton, “Vision for Designing High-Energy, Hybrid Li Ion/Li–O2 Cells,” Journal of Physical Chemistry Letters, 2013, 4, 3607. [3] Z. Yang, L. Trahey, Y. Ren, M. K. Y. Chan, C. Lin, J. Okasinski, and M. M. Thackeray, “In-Situ High-Energy Synchrotron X-ray Diffraction Studies and First Principles Modeling of α-MnO2 Electrodes in Li-O2 and Li-ion Coin Cells,” Journal of Materials Chemistry A, 2015, 3, 7389.

Effect of Metal Ions Doping on the Structural and Electrochemical Properties of Olivine LiFePO4

Li ion rechargeable batteries have better performance over the other competitive rechargeable batteries due to their higher operative voltage (around 3-4 v range), high-energy storage capacity, low self-discharge, and high cycleability. For the application in high power devices (various consumer electronic products such as laptop, camcorder, etc.) the discharge capacity of Li ion batteries at higher current rate required is to be improved. As diffusion of lithium ions inside the active material particles is the rate-limiting step of intercalation process, faster Li+ diffusion in the electrode materials could improve the rate capabilities of Li ion batteries. Olive LiFePO4 is a very promising cathode material used in lithium ion batteries, due to its environmental friendliness, high theoretical capacity (170 mAhg-1), low cost of precursors, high reversibility of Li+ insertion/extraction, good thermal stability, and lack of toxicity. In spite of these attractive features, LiFePO4 requires further modifications to overcome limitations such as poor electronic conductivity and slow lithium ion diffusion. In this work we have synthesized olivine LiFe1-xMxPO4 (M = Nb, Yb, Sb, Mg)(LFMPO) powders by chemical synthesis and co-precipitation method. The synthesized powders were used to prepare cathodes for Li ion coin cells. The structural and electrochemical properties were investigated using X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared, Raman spectroscopy, cyclic voltammetry and charge-discharge studies, respectively. The phase pure and crystalline quality of the materials was studied from XRD peaks and their line widths respectively. 7Li magic angle spinning nuclear magnetic resonance were used to compare the cation arrangement in the undoped and doped powders. The cyclic voltammetry of both the cathodes revealed the reversible nature of Li-ion intercalation in the cell. The dopant induced structural and stoichiometric modifications were correlated with the voltage cycling and charge discharge characteristics of these cathode materials.

Hybrid Li-Ion/Li-Oxygen Battery Materials

In the Center for Electrochemical Energy Science (CEES) EFRC, we are investigating a new class of energy storage materials – hybrid Li-ion/Li-oxygen materials – that combine lithium ion and lithium oxygen capacity to deliver high energy storage capacity [1,2]. In this talk, we will discuss our synthesis, characterization, and first principles modeling efforts of these hybrid Li-ion/Li-oxygen materials, in an attempt to understand their electrochemical performance and reaction mechanisms. We will report on the in-situ observations of structural changes during electrochemical cycling, and accompanying first principles studies, in prototypical hybrid materials, Li5FeO4 and αMnO2 [3]. We will present results of high throughput computational searches for new hybrid materials [4]. Challenges and future prospects of hybrid materials will also be discussed. [1] L. Trahey, C. S. Johnson, J. T. Vaughey, S.-H. Kang, L. J. Hardwick, S. A. Freunberger, P. G. Bruce, M. M. Thackeray, “Activated Lithium-Metal-Oxides as Catalytic Electrodes for Li-O2 Cells,” Electrochemical and Solid-State Letters, 2011, 14, A64.[2] M. M. Thackeray, M. K. Y. Chan, L. Trahey, S. Kirklin, and C. Wolverton, “Vision for Designing High-Energy, Hybrid Li Ion/Li-O2 Cells,” Journal of Physical Chemistry Letters, 2013, 4, 3607.[3] Z. Yang, L. Trahey, Y. Ren, M. K. Y. Chan, C. Lin, J. Okasinski, and M. M. Thackeray, “In-Situ High-Energy Synchrotron X-ray Diffraction Studies and First Principles Modeling of α-MnO2 Electrodes in Li-O2 and Li-ion Coin Cells,” Journal of Materials Chemistry A, 2015, 3, 7389.[4] S. Kirklin, M. K. Y. Chan, L. Trahey, M. M. Thackeray, C Wolverton, “High-throughput screening of high-capacity electrodes for hybrid Li-ion-Li-O2 cells,” Physical Chemistry Chemical Physics, 2014, 16, 22073. Figure 1

Effect of Different Conductive Additives on Electrochemical Performance of Li-Ion Coin Cells

Enormous increase in energy demand and depletion of fossil fuel resources have been drawing researchers towards alternative energy sources. In this connection, lithium-ion batteries (LIBs) are being used as power sources in automobile sector to drive electric vehicles (EVs) and hybrid-electric vehicles (HEVs). For these power applications, LIBs should be capable of high discharge capacity with longer cycle life at high discharge rate. Application of LIBs at high current increase the rate of capacity loss by rapid increase in rate-associated side reactions such as electrolyte decomposition, active material dissolution, SEI film formation and gas generation1,2. As a solution to these difficulties, various groups have put efforts to find out new materials for electrodes and electrolytes. Some work has also been directed in the area of modern additives for cathode, anode, and electrolyte which can enhance battery capacity for longer life at high discharge rate especially in case of EVs and HEVs. A review of the current academic and industry practices has revealed a lack of standard on the exact amount of conductive additives that should be added to the active material3. The amount of the active material should be highest for higher energy density and better discharge capacity and at the same time sufficient amount of conductive additive should be added to provide proper conduction network for electronic movement. In addition, the effect of addition of nanostructured additives requires significant attention and needs to be studied as well. These nanostructured additives have better electronic conductivity and higher surface area than conventional additives which may result in improved electrochemical performance of the cell4. However, nanomaterials are much costlier than simple additives, limiting their application as conduction agent. A carefully controlled mixture amount of these advanced with traditional additives is required for better capacity retention and higher discharge capacity while keeping a close control on the cost of fabrication. In this work, we examine the effect of various conductive additives and their combinations to fabricate 2032 coin cells to achieve higher discharge capacity with improved cycle life at low cost. In this connection, electrodes will be prepared by using carbon black (CB), single-walled carbon nanotubes (SWCNTs), multi-walled carbon nanotubes (MWCNTs) and combinations of CB & SWCNTs, CB & MWCNTs, SWCNTs & MWCNTs and CB & CWCNTs & MWCNTs with LiMn2O4as the active material. Schematic representation of the electrodes using these conductive additives is shown in Figure 1. The cell fabricated by using these electrodes will be analyzed for capacity retention, discharge capacity and cycling performance. Electrochemical impedance spectroscopy (EIS) will be employed to analyze the aging effects and rate of capacity degradation of cells by quantifying the growth of internal resistances with cycling. The morphological and structural changes of electrodes due to cycling will be examined by using SEM and XRD techniques respectively at fresh and cycled stage. The results obtained from this study will be expected to frame a standard on the amount of conductive additives to be added during electrode fabrication to result in improved cycling performance of these cells.

In situ high-energy synchrotron X-ray diffraction studies and first principles modeling of α-MnO2 electrodes in Li–O2 and Li-ion coin cells

In situ synchrotron diffraction and first principles modeling shows structural changes in α-MnO2 during cycling in Li–O2 battery cells, as lithium and oxygen are incorporated into and removed from tunnels in the structure.

Enhanced autonomic shutdown of Li-ion batteries by polydopamine coated polyethylene microspheres

Thermally triggered autonomic shutdown of a Lithium-ion (Li-ion) battery is demonstrated using polydopamine (PDA)-coated polyethylene microspheres applied onto a battery anode. The microspheres are dispersed in a buffered 10 mM dopamine salt solution and the pH is raised to initiate the polymerization and coat the microspheres. Coated microspheres are then mixed with an aqueous binder, applied onto a battery anode surface, dried, and incorporated into Li-ion coin cells. FTIR and Raman spectroscopy are used to verify the presence of the polydopamine on the surface of the microspheres. Scanning electron microscopy is used to examine microsphere surface morphology and resulting anode coating quality. Charge and discharge capacity, as well as impedance, are measured for Li-ion coin cells as a function of microsphere content. Autonomous shutdown is achieved by applying 1.7 mg cm−2 of PDA-coated microspheres to the electrode. The PDA coating significantly reduces the mass of microspheres for effective shutdown compared to our prior work with uncoated microspheres.

Electrochemical performances of Cu6Sn5-modified Sn anode with multi-layer structure for Li-ion cell

To better understand the influence of morphology and structure on the electrochemical performance of the anode materials, thick Sn film was prepared by pulse electrodeposition on Cu substrate and Cu6Sn5-modified Sn film was formed with a facile method by post deposition heat treatment of Sn film at 232 ± 2 °C in argon for 12 h. X-Ray diffraction (XRD) and scanning electron microscopy (SEM) were used to characterize the composition and morphology of Cu6Sn5-modified Sn film. The Cu6Sn5-modified Sn film was directly assembled in Li-ion coin cells as the anode and studied by charge/discharge and AC impedance. A thick Sn film was used as the control to compare its electrochemical performances with Cu6Sn5-modified Sn film. The Cu6Sn5-modified Sn anode is a multi-layer structure with unique morphology of a surface continuous layer and a micron-crystalline layer, and exhibited strong correlation between cyclic properties and its structure as well as morphology. The Cu6Sn5-modified Sn anode showed increased capacity compared with the Sn anode. The micro-crystallite layer displayed the highest capacity and capacity retention.