Rechargeable lithium-ion batteries are a staple of modern society, providing power to a significant portion of the world's electronics and rapidly replacing older power sources. The advent of widely available electric cars with batteries of up to 200 kWh, with an increasing emphasis on fast charging, has only increased their importance. Lithium-ion battery electronic and ionic properties are largely determined by the microstructure of the battery electrode film and can be heavily influenced by relatively small variations in film makeup, including the formation of voids or distribution of carbon and binder. Prior to this research, electrical properties, which are some of the most important characteristics to battery cost, performance, and safety, were either difficult or, in the case of contact resistance, impossible to directly measure. This dissertation focuses on the development and use of a micro-surface probe for measurement and mapping of lithium-ion battery film electronic characteristics. The measurement apparatus, inversion and mapping routines, and experimental data presented provide manufacturers and researchers with a better understanding of battery heterogeneity and the influence of microstructure on electrical properties. The micro-surface probe was used to map spatial variation on both a macro and micro scale; compare physical, electrical, and ionic properties; and validate tests that were previously used to estimate electronic parameters. Experiments on commercial-quality battery electrode films showed higher micro-heterogeneity than was previously assumed by a significant margin. Additionally, electronic and ionic properties were shown to not always be inversely related and some physical explanations for observed variation were explored. Macro-variations were measured and shown to exist across electrode films which were previously assumed to be uniform. Finally a comparison to the mechanical peel test, a common test used in industry as a proxy measurement of electrical contact resistance, proved the peel test to be inconclusive and showed that it will not always accurately reflect electrical properties of films. Direct measurements of both electrical conductivity and contact resistance provide a new and important tool to advance understanding and development of lithium-ion batteries. The magnitude of the measured resistivities and their significant variation demonstrates that a better understanding of film properties is needed and will significantly influence our understanding of modern battery parameters and the effects of manufacturing techniques on battery performance.

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When an anode electrode potential is larger than the lowest unoccupied molecular orbital (LUMO) of the electrolyte, Li-ions and electrolyte molecules will participate in reduction reactions on the anode surface and form a solid electrolyte interface (SEI) layer. Active Li-ion consumption in the formation reactions is the main source of capacity loss (>50) and ageing in Li-ion batteries (LIBs). Due to the fast-occurring and complex nature of the electrochemical processes, conventional experimental techniques are not a feasible approach for capturing and characterizing the SEI formation phenomenon. The lack of experimental data and consequently the absence of potential parameters for crystal structures in this layer makes molecular dynamics~(MD) simulations inapplicable to it. Also, due to the multi-component multi-layer structure of the SEI, the smallest system representing an SEI layer is too large for employing the principles of quantum mechanics~(QM), that traditionally work with much smaller system sizes. Addressing this, this thesis presents a novel computational framework for coupling QM and MD calculations to simulate a system with the size limits of MD simulations independent of the experimental data. The QM evaluates sub-atomic properties such as energy barriers against diffusion and employs seven new algorithms to estimate potential parameters as the input of the MD simulations. Then MD simulations forecast SEI's properties including density, Young's Modules, Poisson's Ratio, thermal conductivity, and diffusion coefficient mechanisms. The output of the QM and MD calculations are employed to develop two macro-scale mathematical models for predicting battery ageing and battery performance, incorporating the impact of the SEI layer in addition to the cathode, anode, and separator parts. Finally, the results obtained have been validated with respect to the experimental data in different operational conditions. / Thesis / Doctor of Philosophy (PhD) / The limited lifespan of expensive batteries is the main obstacle to electrification of the transport sector, despite its necessity for addressing the current environmental issues. Li+/electrolyte reduction on the electrode surface is responsible for more than 50% of capacity loss and the consequent ageing is a complex and fast-occurring phenomenon (few ns) that cannot be easily resolved using conventional experimental and computational techniques. This thesis presents the development of some computational frameworks and demonstrates their employment to investigate this phenomenon from a multi-scale perspective, i.e., from a few electrons to an entire battery length scale, with the operating cycles ranging from a few ps to several months, employing Quantum Mechanics, Molecular Dynamics, and Macro-Scale Modeling. The frameworks have been successfully validated with respect to experimental data from the literature and have been applied successfully to highlight the parameters that impact ageing in batteries. The findings presented in this thesis can be used as the base for further research on next-gen durable batteries with liquid and solid-state electrolytes.

The applications of Li-ion batteries in the electronics and vehicle industry is increasing at a very rapid pace. This is primarily due to superior properties such as high specific energy storage and power as well as wider operation temperature ranges. Additional potential for improved properties is connected to capacity losses with time and the thereby resulting limitations of lifetime of batteries. The lifetime of a battery is strongly related to the mechanical and chemical degradation of the active material of electrodes during repeated electrochemical reactions at charging and discharging. To identify this phenomenon from a mechanical perspective, the mechanical properties of the electrode active layers should be characterized. Additionally, with the aid of mechanical properties, realistic electro-chemo-mechanical models should be developed to comprehend the mechanisms causing capacity fade. In the first part of this thesis, macroscopic material properties of the active layers of Li-ion battery electrodes were measured with a unique bending test technique. Contrary to methods previously used; it is capable to overcome the challenges that were encountered in other traditional testing techniques. In papers 1 and 2 this bending test technique (U-shaped bending test), is used to characterize the elastic and viscoelastic behavior of NMC cathodic and graphite anodic active layers, respectively. By using single-sided thin electrode specimens in U-shape bending tests, it was possible to distinguish tensile and compressive elastic and viscoelastic behavior of the electrode active materials. The tensile Young’s moduli of cathodic and anodic active layers are found as 0.73 GPa and 1 GPa, respectively. On the other hand, the compressive Young’s moduli show a stiffening behavior at increasing strains. Stiffnesses between 1.3 GPa and 2.8 GPa for the cathodic active layer, and between 1 GPa and 3.8 GPa for the anodic active layer were recorded. This compressive behavior of the electrode active layers is expected as a result of the porous nature of the materials. In addition, the viscoelastic behavior of the electrode active layers is expressed through Prony series. It was observed that the behavior can be described by a short term (minutes) and a long term (hours, days) relaxation. In paper 3, a statistical representative volume element is introduced to predict the elastic properties of a dry cathodic electrode active layer. A porous cathodic electrode active layer that is composed of NMC active particles and polymeric binder material with conductive carbon additives is modeled as a face-centered-cubic structure. Several particle-binder and particle-particle interaction conditions are repeated 50 times with random orientations. Based on the statistics for each interaction case, Young’s modulus is estimated. The results show a good agreement with the experimental findings from Paper 1. Furthermore, particle-particle and particle-binder contact force distributions are calculated for 3% of particle swelling. The characteristics of the force distributions are correlated with the typical material failures in the active layer such as particle cracking and binder debonding. The statistical data obtained here are also used to improve an analytical model that was previously derived to estimate the elastic properties of active porous layers. The analytical model, complemented by the statistical results, showed an excellent agreement with the finite element simulations. / <p>QC 230124</p>

This work presents novel modeling and experimental techniques that provide insight into liquid-phase mass transport and electron transfer processes in lithium-ion batteries. These included liquid-phase ionic mass transport (conduction and diffusion), lithium diffuion in the solid phase and electronic transport in the solid phase. Fundamental understanding of these processes is necessary to efficiently design and optimize lithium-ion batteries for different applications. To understand the effect of electrode structure on the electronic resistance of the cathode, we tested power performance of cathodes with combinations of three different carbon conductivity additives: vapor-grown carbon fibers (CF), carbon black (CB) and graphite (GR). With all other factors held constant, cathodes with a mixture of CF+CB were found to have the best power-performance, followed by cells containing CF only and then by CB+GR. Thus, the use of carbon fibers as conductive additive was found to improve the power performance of cells compared to the baseline (CB+GR). The enhanced electrode performance due to the fibers also allows an increase in energy density while still meeting power goals. About one-third of the available energy was lost to irreversible processes when cells were pulse-charged or discharged at the maximum rate allowed by voltage-cutoff constraints. We developed modeling and experimental techniques to quantify tortuosity in electrolyte-filled porous battery structures (separator and active-material film). Tortuosities of separators were measured by two methods, AC impedance and polarization-interrupt, which produced consistent results. The polarization-interrupt experiment was used similarly to measure effective electrolyte transport in porous films of cathode materials, particularly films containing lithium iron phosphate. An empirical relationship between porosity and the tortuosity of the porous structures was developed. Our results demonstrate that the tortuosity-dependent mass transport resistance in porous separators and electrodes is significantly higher than that predicted by the oft-used Bruggeman relationship. To understand the dominant resistances in a lithium battery, we developed and validated a model for lithium iron phosphate cathode. In doing so we considered unique physical features of this active material. Our model is unusual in terms of the range of experimental conditions for which it is validated. Various submodel and experimental techniques were used to find physically realistic parameters. The model was tested with different discharge rates and thicknesses of cathodes, in all cases showing good agreement, which suggests that the model takes into account physical realities with different thicknesses. The model was then used to find the dominant resistance for the tested cathodes. The model suggests that the inter-particle contact resistance between carbon and the active-material particles was a dominant resistance for the tested cathodes.

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The accurate and reliable estimation of the State-of-Charge (SOC) and State-of-Health (SOH) of Li-ion batteries is paramount to the safe and reliable operation of any electrified vehicle. Not only is accuracy and reliability necessary, but these estimation techniques must also be practical and intelligent since their use in real world applications can include noisy input signals, varying ambient conditions and incomplete or partial sequences of measured battery data. To that end, a novel framework, utilizing deep learning techniques, is considered whereby battery modelling and state estimation are performed in a single unified step. For SOC estimation, two different deep learning techniques are used with experimental data. These include a Recurrent Neural Network with Long Short-Term Memory (LSTM-RNN) and a Deep Feedforward Neural Network (DNN); each one possessing its own set of advantages. The LSTM-RNN achieves a Mean Absolute Error (MAE) of 0.57% over a fixed ambient temperature and a MAE of 1.61% over a dataset with ambient temperatures increasing from 10°C to 25°C. The DNN algorithm, on the other hand, achieves a MAE of 1.10% over a 25°C dataset while, at -20°C, a MAE of 2.17% is obtained. A Convolutional Neural Network (CNN), which has the advantage of shared weights, is used with randomized battery usage data to map raw battery measurements directly to an estimated SOH value. Using this strategy, average errors of below 1% are obtained when using fixed reference charge profiles. To further increase the practicality of this algorithm, the CNN is trained and validated over partial reference charge curves. SOH is estimated with a partial reference profile with the SOC ranging from 60% to 95% and achieves a MAE of 0.81%. A smaller SOC range is then used where the partial charge profile spans a SOC of 85% to 95% and a MAE of 1.60% is obtained. Finally, a fused convolutional recurrent neural network (CNN-RNN) is used to perform combined SOC and SOH estimation over constant charge profiles. This is performed by feeding the estimated SOH from the CNN into a LSTM-RNN, which, in turn, estimates SOC with a MAE of less than 0.5% over the lifetime of the battery. / Thesis / Doctor of Philosophy (PhD)

Li-ion battery technologies have transformed the consumer electronics and electric vehicles landscape over the last few decades. Single-crystal cathode materials with controllable physical properties including size, morphology, and crystal facets can aid researchers in developing relationships between physical characteristics, chemical properties, and electrochemical performance. High-voltage LiNi_0.5Mn_1.5O₄ (LNMO) materials are desirable as cathodes due to their low cost, low toxicity, and high capacity and energy density making them promising to meet increasing consumer demands for battery materials. However, transition metal dissolution, interfacial instability, and capacity fading plague these materials when paired with graphite, limiting their commercial capability. Furthermore, variation in Ni/Mn ordering can lead to complex multiphase co-existence and changes in Mn oxidation state and electrochemical performance. These properties can be adjusted during synthesis using a facile and tunable molten salt synthesis method. This dissertation focuses on the investigation of chemical and structural heterogeneities of LNMO prepared under different synthetic conditions at different length scales. In Chapter 2, the influences of molten salt synthesis parameters on LNMO particle size, morphology, bulk uniformity, and performance are evaluated revealing the difficulty of reproducible cathode synthesis. We utilize the X-ray nanodiffraction technique throughout this work, which provides high-resolution structural information. We develop a method to measure and relate lattice strain to phase distribution at the tens of nanometers scale. In Chapter 3, mapping lattice distortions of LNMO particles with varying global Mn oxidation states reveals inherent structural defects and distortion heterogeneities. In Chapter 4, we examine lattice distortion evolution upon chemical delithiation, Mn dissolution behaviors, and evaluate the chemical delithiation method as a means to replicate electrochemical cycling conditions. We further investigate lattice distortion spatially via in situ nanodiffraction during battery cycling in Chapter 5, illustrating the capabilities of the measurement to provide practical understanding of cathode transformations. From intra-particle to electrode materials level, heterogeneities that arise in cathode materials can dictate performance properties and degradation mechanisms and are necessary for researchers to understand for the improvement of Li-ion battery systems. The development of the nanodiffraction measurements aids in our understanding of inherent and dynamic materials chemical and structural heterogeneities. / Doctor of Philosophy / The invention of rechargeable Li-ion batteries in the 1990s has undeniably revolutionized modern civilization. Cell phones, laptops, grid energy storage, and electric vehicles have become fundamental fixtures of the 21st century. As technologies improve and requirements for advanced renewable energy storage have increased, researchers have sought to design longer lasting, faster charging, and more lightweight batteries. Modifying and finding new positive electrode materials is one way to improve the capabilities of modern batteries as their properties are governed by fundamental chemistry. High-voltage LiNi_0.5Mn_1.5O₄ (LNMO) is one such material that can allow for fast charging and high energy storage capacity, but its commercialization is hindered by complex physical and chemical properties, which can limit its lifetime in batteries. Large, particles with well-defined shapes are desirable to improve the stability of the materials; however, understanding their defects and structural heterogeneities is vital to continued optimization and requires advanced characterization techniques. In this dissertation, we characterize the physical phases and chemical properties of LNMO samples prepared under different conditions resulting in different particle shapes, sizes, and chemical distributions. An advanced X-ray nanodiffraction technique is used to measure phase distributions within individual particles while lab-based analytical techniques and electrochemical testing can determine bulk properties and battery performance of materials. Overall, the aim of this work is to develop techniques to measure structural and chemical heterogeneities of cathode materials at different length scales and to understand how they influence properties and performance in batteries. This work provides valuable insights into the inherent and dynamic properties of high-voltage electrode materials useful to advance our understanding of how these materials fail and to aid researchers in creating design principles to develop stable, high-performing future generations of rechargeable batteries.

Li-ion batteries (LIBs) have achieved remarkable success in electric vehicles (EVs), consumer electronics, grid energy storage, and other applications thanks to a wide range of electrode materials that meet the performance requirements of different application scenarios. Cathodes are an essential component of LIBs, which governs the performance of commercial LIBs. Layered transition metal oxide, i.e., LiNixCoyMn1-x-yO2 (NMC), is one family of cathodes that are widely applied in the prevailing commercial LIBs. With increasing demand for high energy density, the development of layered oxide cathodes is towards high Ni content because Ni redox couples majorly contribute to the battery capacity. Meanwhile, the battery community has been making tremendous efforts to eliminate Co in layered cathodes due to its high cost, high toxicity, and child labor issues during Co mining. However, these Ni-rich Co-free cathodes usually suffer from low electrochemical and structural stability. Several strategies are adopted to enhance the stability of Ni-rich Co-free cathodes, such as doping, coating, and synthesizing single crystal particles. However, the design principles and synthesis mechanisms of these approaches have not been fully understood. Herein, we design and synthesize stable Ni-rich and low/no-Co layered oxide cathodes by manipulating the chemical and structural properties of cathode particles. Our studies reveal the cathode formation mechanisms and shed light on the cathode design through complementary synchrotron microscopic and spectroscopic characterization methods. In Chapter 1, the motivation for LIB research is introduced from the perspective of its indispensable role in achieving carbon neutrality. We then comprehensively introduce the status of LIBs at present, including assessing their sustainability, worldwide supply chain and manufacturing, and cathode materials. Subsequently, we focus on the Co-free layered oxide cathodes and discuss their structure, limitations, and strategies to address the challenges. Finally, we discuss single crystal Ni-rich layered oxide cathodes and the challenges and strategies associated with their synthesis. In Chapter 2, we investigate the dopant redistribution, phase propagation, and local chemical changes of layered oxides at multiple length scales using a multielement-doped LiNi0.96Mg0.02Ti0.02O2 (Mg/Ti-LNO) as a model platform. We observed that dopants Mg and Ti diffuse from the surface to the bulk of cathode particles below 300 °C long before the formation of any layered phase, using a range of synchrotron spectroscopic and imaging diagnostic tools. After calcination, Ti is still enriched at the cathode particle surface, while Mg has a relatively uniform distribution throughout cathode particles. Our findings provide experimental guidance for manipulating the dopant distribution upon cathode synthesis. In Chapter 3, we synthesized Mn(OH)2-coated single crystal LiNiO2 (LNO) and used it as the platform to monitor the Mn redistribution and the structural and chemical evolution of the LNO cathode. We use in situ transmission X-ray microscopy (TXM) to track the Mn tomography inside the LNO particle and Ni oxidation state evolution at various temperatures below 700 °C. We further reveal chemical and structural changes induced by different extents of Mn diffusion at ensemble-averaged scale, which validates the results at the single particle scale. The ion diffusion behavior in the cathode is highly temperature dependent. Our study provides guidance for ion distribution manipulation during cathode modification. In Chapter 4, we successfully fabricated a surface passivation layer for NMC particles via a feasible quenching approach. A combination of bulk and surface structural characterization methods show the correlation of surface layer with bulk chemistry including valence state and charge distribution. Our design enables high interfacial stability and homogeneous charge distribution, impelling superior electrochemical performance of NMC cathode materials. This study provides insights into the cathode surface layer design for modifying other high-capacity cathodes in LIBs. In Chapter 5, we use statistical tools to identify the significance of multiple synthetic parameters in the molten salt synthesis of single crystal Ni-rich NMC cathodes. We also create a prediction model to forecast the performance of synthesized single crystal Ni-rich NMC cathodes from the input of synthetic parameters with relatively high prediction accuracy. Guided by the models, we synthesize single crystal LiNi0.9Co0.05Mn0.05O2 (SC-N90) with different particle sizes. We find large single crystals show worse capacity and cycle life than small single crystals especially at high current rates due to slower Li kinetics. However, large single crystal has higher thermal stability potentially because of smaller specific surface area. The findings of particle size effect on the performance provide insights into size engineering while developing next-generation single crystal Ni-rich NMC cathodes. The statistical and prediction models developed in this study can guide the molten salt synthesis of Ni rich cathodes and simplify the optimization process of synthetic parameters. Chapter 6 summarizes our efforts on the novel design and fundamental understanding of the state-of-the-art cathodes. We also provide our future perspectives for the development of LIBs. / Doctor of Philosophy / Lithium-ion batteries (LIBs) have been studied for decades and are widely applied in electronics and vehicles because of their high energy density and long lifetime. With the increasing demand for higher energy density, particularly in electric vehicles, the development of Ni-based layered oxide cathode materials has been focused on increasing the Ni content. Meanwhile, decreasing or eliminating Co has become a consensus due to its high cost, toxicity, and human rights issues during mining. Enhancing the stability of these Ni-rich and low/no-Co layered oxide cathodes is challenging yet crucial to their practical applications. Herein, we design and synthesize multiple Ni-rich and low/no-Co layered cathodes through ion distribution engineering and structure modification at various length scales. We also investigate the dopant redistribution, phase propagation, and local chemical changes during layered oxides cathode formation through a combination of complementary characterization methods at different length scales. In addition, we provide guidance for synthesis optimization by statistical correlations and performance prediction models with the input of synthetic conditions. Overall, this dissertation provides insights into the design and synthesis principles of Ni-rich low/no-Co layered oxide cathode, which can facilitate the transition to a sustainable future with next-generation LIBs.