Lithium-ion battery electrodes exhibit complex interplay among multiple electrochemically coupled transport processes, which rely on the underlying functionality and relative arrangement of different constituent phases. The electrochemically inactive solid phases (e.g., conductive additive and binder, referred to as the secondary phase), while beneficial for improved electronic conductivity and mechanical integrity, may partially block the electrochemically active sites and introduce additional transport resistances in the pore (electrolyte) phase. In this work, the role of mesoscale interactions and inherent stochasticity in porous electrodes is elucidated in the context of short-range (interface) and long-range (transport) characteristics. The electrode microstructure significantly affects kinetically and transport-limiting scenarios and thereby the cell performance. The secondary-phase morphology is also found to strongly influence the microstructure-transport-kinetics interactions. Apropos, strategies have been proposed for performance improvement via electrode microstructural modifications.

Battery performance is strongly correlated with electrode microstructural properties. Of the relevant properties, the tortuosity factor of the electrolyte transport paths through microstructure pores is important as it limits battery maximum charge/discharge rate, particularly for energy-dense thick electrodes. Tortuosity factor however, is difficult to precisely measure, and thus its estimation has been debated frequently in the literature. Herein, three independent approaches have been applied to quantify the tortuosity factor of lithium-ion battery electrodes. The first approach is a microstructure model based on three-dimensional geometries from X-ray computed tomography (CT) and stochastic reconstructions enhanced with computationally generated carbon/binder domain (CBD), as CT is often unable to resolve the CBD. The second approach uses a macro-homogeneous model to fit electrochemical data at several rates, providing a separate estimation of the tortuosity factor. The third approach experimentally measures tortuosity factor via symmetric cells employing a blocking electrolyte. Comparisons have been made across the three approaches for 14 graphite and nickel-manganese-cobalt oxide electrodes. Analysis suggests that if the tortuosity factor were characterized based on the active material skeleton only, the actual tortuosities would be 1.35-1.81 times higher for calendered electrodes. Correlations are provided for varying porosity, CBD phase interfacial arrangement and solid particle morphology.

Typical lithium-ion battery electrodes are porous composites comprised of active material, conductive additives, and polymeric binder, with liquid electrolyte filling the pores. The mesoscale morphology of these constituent phases has a significant impact on both electrochemical reactions and transport across the electrode, which can ultimately limit macroscale battery performance. We reconstruct published X-ray computed tomography (XCT) data from a NMC333 cathode to study mesoscale electrode behavior on an as-manufactured electrode geometry. We present and compare two distinct models that computationally generate a composite binder domain (CBD) phase that represents both the polymeric binder and conductive additives. We compare the effect of the resulting CBD morphologies on electrochemically active area, pore phase tortuosity, and effective electrical conductivity. Both dense and nanoporous CBD are considered, and we observe that acknowledging CBD nanoporosity significantly increases effective electrical conductivity by up to an order of magnitude. Properties are compared to published measurements as well as to approximate values often used in homogenized battery-scale models. All reconstructions exhibit less than 20% of the standard electrochemically active area approximation. Order of magnitude discrepancies are observed between two popular transport simulation numerical schemes (finite element method and finite volume method), highlighting the importance of careful numerical verification.

Electrode processing based on the state-of-the-art materials represents a scientific opportunity toward a cost-effective measure for improving the lithium-ion battery performance. In this regard, perhaps the most important is the drying step in a typical non-aqueous based slurry processing which can profoundly impact the electrode microstructure and hence performance. Solvent evaporation during drying plays a critical role in the redistribution of the particulate phases consisting of active particle, conductive additive and binder. In this work, we attempt to provide a mechanistic understanding of the role of solvent evaporation on the electrode characteristics and performance via a combined experimental and theoretical analysis. This study elucidates that a non-uniform distribution of the constituent phases, especially the relatively mobile conductive additive and binder, can develop which depends on the solvent evaporation, particle diffusion and sedimentation attributes. Experimental results and theoretical analysis reveal the impact of evaporation rate on the conductive additive and binder distribution in the electrode microstructure and resulting electrochemical performance. Our analysis has shown that a slower two-stage drying, as opposed to a high-rate single-stage drying, allows for a favorable distribution of binder and conductive additive, thus reducing internal cell resistance and improving electrochemical performance. Increasing concerns about depleting fossil fuel reserves, energy security, and climate change have given rise to interest in the adoption of renewable energy in place of traditional, petroleum-based fuels. The implementation and usage of renewable energies have been limited due to lack of efficient storage and transportation infrastructure. Recent improvements in the energy density and durability of lithiumion batteries (LIBs) have made them an increasingly attractive means of energy storage. [1][2][3][4] Further improvements in lithium-ion technology would increase the viability of widespread adoption of electric vehicles and renewable energy integration into the electric grid. For example, improvements in the capacity of LIBs would not only improve the effective range of electric vehicles, 5,6 but also improve their cycle life by reducing the depth of discharge, which in turn increases the viability of LIBs for use in grid energy storage applications. 7The performance of Li-ion batteries depends on the electrode materials, the choice of electrolyte, and the cell architecture.4,8 A typical LIB positive electrode (cathode) is composed of a combination of Li-containing active material, conductive additive, polymeric binder, and pore space that is filled with an electrolyte. Typically, these are created by casting out and drying a thin film of slurry containing these multi-phase components. 19 but little attention is paid to the physical understanding of the electrode processing. The importance of this electrode preparation step cannot be overemphasized. In addition to determining the cel...

Electrochemical systems function via interconversion of electric charge and chemical species and represent promising technologies for our cleaner, more sustainable future. However, their development time is fundamentally limited by our ability to identify new materials and understand their electrochemical response. To shorten this time frame, we need to switch from the trial-and-error approach of finding useful materials to a more selective process by leveraging model predictions. Machine learning (ML) offers data-driven predictions and can be helpful. Herein we ask if ML can revolutionize the development cycle from decades to a few years. We outline the necessary characteristics of such ML implementations. Instead of enumerating various ML algorithms, we discuss scientific questions about the electrochemical systems to which ML can contribute.

Thermo-electrochemical extremes continue to remain a challenge for lithium-ion batteries. Contrary to the conventional approach, we propose herein that the electrochemistry-coupled and microstructure-mediated cross talk between the positive and negative electrodes ultimately dictates the off-equilibrium-coupled processes, such as heat generation and the propensity for lithium plating. The active particle morphological differences between the electrode couple foster a thermo-electrochemical hysteresis, where the difference in heat generation rates changes the electrochemical response. The intrinsic asymmetry in electrode microstructural complexations leads to thermo-electrochemical consequences, such as cathode-dependent thermal excursion and co-dependent lithium plating otherwise believed to be anode-dependent.

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Conventionally, battery electrodes are rationalized as homogeneous reactors. It proves to be an erroneous interpretation for fast transients, where mass transport limitations amplify underlying heterogeneities. Given the lack of observability of associated fast spatiotemporal dynamics, redox activity in inhomogeneous electrodes is superficially explored. We resort to a physics-based description to examine the extreme fast charging of lithium-ion battery electrodes. Representative inhomogeneity information is extracted from electrode tomograms. We discover such electrodes to undergo preferential intercalation, localized lithium plating and nonuniform heat generation as a result of distributed long- and short-range interactions. The spatial correlations of these events with the underlying inhomogeneity are found to be nonidentical. Investigation of multiple inhomogeneity fields reveals an exponential scaling of plating severity and early onset in contrast to the homogeneous limit. Anode and cathode inhomogeneities couple nonlinearly to grow peculiar electrodeposition patterns. These mechanistic insights annotate the complex functioning of spatially nonuniform electrodes.