Architected materials offer promising advancements in energy storage by enabling highly customizable, high-surface-area, ordered, and low-defect porous structures. This study investigates the current distribution and mass transport within complex 3D-printed lattice electrodes under flow-through conditions. Conductive lattices were fabricated using microstereolithography followed by pyrolytic carbonization. Lattice geometry effects were analyzed by varying the unit cell type [simple cubic (SC), body- and face-centered cubic (BCC/FCC), IsoTruss, and Octet], porosity, and current density. Current distribution uniformity was investigated using a model high-efficiency copper deposition reaction. Local film thickness distributions were predicted using a numerical model and validated experimentally using micro-X-ray computed tomography. Scaling relationships for informing electrochemical reaction conditions and current uniformity are formulated as a modified lattice-based Wagner number (Wa Lattice) and a corresponding inverse Damkohler number (Da Lattice -1). Validated models reveal that mass-transfer coefficients scale as Octet > IsoTruss > FCC ∼ BCC > SC. Inertial effects become significant at Reynolds number Re > 3 and are particularly pronounced in Octet structures due to an abundance of struts oriented away from the fluid flow direction. The study underscores the importance of electrode engineering and process conditions necessary to tailor mass transport and current uniformities to various device applications.

Lithium metal electrodes have high theoretical capacity (3860 mA h g -1 ), but they exhibit issues with poor cyclability and a propensity for dendrite formation. Previous research has used the Sand’s time to predict when concentration depletion at the surface of the electrode will result in the formation of a dendrite. However, the classical Sand’s time consistently overpredicts the dendrite onset time. Additionally, previous research has neglected the influence of the solid electrolyte interphase (SEI) on the concentration depletion at the electrode surface, despite the SEI having significantly higher transport resistance than liquid electrolytes. In this work, we show that by modeling a growing SEI, we can more accurately predict the onset time for the formation of dendrites on lithium metal electrodes. The model also shows that transport limitations within the SEI layer overshadow transport effects in the electrolyte, and that neglecting the effect of SEI is a severe limitation of existing models. To generalize the concept of Sand’s time we consider the chemical-potential gradient at the electrode surface as a descriptor of the likelihood of dendrite onset, with it being the driving force governing species flux. The results of the numerical model are sensitive to the SEI growth model and transport parameters, and the sensitivity of the model to different transport parameters is dependent on the applied current. This work emphasizes the need for improved SEI-characterization and understanding for developing predictive models that identify dendrite-free regimes and enable lithium-metal electrodes. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. This work was supported by the Lawrence Livermore National Laboratory LDRD 23-SI-002. LLNL-ABS-871542

Aqueous corrosion of metals is governed by formation and dissolution of a passivating, multi-component surface oxide. Unfortunately, a detailed atomistic description is challenging due to the compositional complexity and the need to consider multiple kinetic factors simultaneously. To this end, we combine experiments with a first-principles-derived, multiscale computational framework that transcends thermodynamic descriptions to explicitly simulate the kinetic evolution of surface oxides of Ni-Cr alloys as a function of composition, temperature, pH, and applied voltage. In the absence of pitting, we identify three distinct voltage regimes, which are kinetically dominated by oxide growth, dissolution, and competitive dissolution and reprecipitation. Evolving compositional gradients and oxide thickness are revealed, including a transition between a metastable Ni-Cr mixed oxide and a thick, porous Ni-dominated oxide. Beyond elucidating the underlying physics, we highlight the need for competing kinetics in models to properly predict the transition from passivation to corrosion. Our results provide a key step towards co-design of alloy composition alongside environmental conditions for sustainable use across a variety of critical energy and infrastructure applications.

Lithium-ion batteries (LiBs) are widely utilized in various commercial applications; however, their performance is constrained by operating temperature limits. Specifically, the energy capacity and charging rate of LiBs degrade significantly when temperatures drop below 0°C. This performance loss primarily results from the sluggish transport of lithium ions, as the conductivity of the electrolyte decreases with lower temperatures. Modeling of battery performance at low temperature can guide materials development and cell design to expand the temperature range LiB technology. In this work, we present a P2D model 1 featuring a manganese dioxide (MnO 2 ) cathode, a lithium metal anode, and a Generation 2 electrolyte. Our model incorporates electrochemical reactions, diffusion through the electrolyte, and diffusion through the solid phase. We have modified the DFN model to account for simultaneous intercalation and surface adsorption of lithium ions in the cathode material, which is essential for accurately capturing the pseudo-capacitive behavior of MnO 2 . The model has been validated against experimental data collected at C-rates ranging from 0.1 to 10 C and temperatures of -10°C and 30°C. The results show that the model reliably reproduces experimentally measured voltage response across a wide range of operating conditions. With the validated model, we carry out a sensitivity analysis with respect to some key material selections, such as the electrolyte composition and the MnO 2 phase. The analysis enhances our understanding of the limiting kinetics of LiBs at low temperature and provides insights into how to construct a well-balanced battery chemistry. References: Doyle, Marc, Thomas F. Fuller, and John Newman. "Modeling of galvanostatic charge and discharge of the lithium/polymer/insertion cell." Journal of the Electrochemical Society 140 (1993): 1526. This work was supported by Lawrence Livermore National Laboratory LDRD 23-SI-002. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL release number: LLNL-ABS-2001454

Quantum dots (QDs) are promising materials for optoelectronic applications, but their widespread adoption requires controllable, selective, and scalable deposition methods. While traditional methods like spin coating and drop casting are suitable for small-scale deposition onto flat substrates, and ink-jet printing offers precision for small areas, these methods struggle with conformal deposition onto non-planar, large area substrates or selective deposition onto large area chips. Electrophoretic deposition (EPD) is an efficient and versatile technique capable of achieving conformal and selective area deposition over large areas, but its application to QD films has been limited. Previous EPD studies on QD films used QDs with native ligands, which hinder charge transport in optoelectronic devices. Here, we combined in-solution ligand exchange with EPD to deposit dense PbSe QD films. Through solvent engineering, we controlled the growth rate of PbSe QD films and used an in situ quartz crystal microbalance to measure the growth rate as a function of applied potential. We demonstrated the efficacy of this methodology by conformally depositing PbSe QD films onto textured silicon substrates via EPD and fabricating infrared photodetectors. The responsivity of the as-fabricated IR PDs at 1200 nm was similar to 0.01 A W-1 and response times were 4.6 ms (on) and 4.7 ms (off).

It is well recognized that the performance of commercial Li-ion batteries can significantly degrade at low temperatures due to sluggish ion transport in bulk electrolyte, increased resistance at interfaces and severe Li plating and dendrite growth that could lead to catastrophic cell failure. In this talk, we address the low temperature performance constraints of the electrolyte components from atomistic modeling and demonstrate the critical importance to balance viscosity and ionic speciation that dictate the overall conductivity of Li-ion in model electrolyte. We further discuss how speciation in the bulk electrolyte could affect Li-ion desolvation pathways and associated kinetics at interfaces. Through rigorous data analysis, we resolve species-specific transport properties of the electrolyte, its correlation to temperature and concentration, and provide valuable insights for future design of functional electrolytes for low temperature applications. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and supported by the Laboratory Directed Research and Development program under the tracking number of 23-SI-005.

Manganese dioxide (MnO 2 ) deposition/dissolution (Mn 2+ /MnO 2 ) chemistry, involving a two‐electron‐transfer process, holds promise for safe and eco‐friendly large‐scale energy storage. However, challenges like electrode/electrolyte interface environment fluctuations (H + and H 2 O activity), irreversible Mn degradation, and limited understanding of degradation mechanisms hinder the reversibility of the Mn 2+ /MnO 2 conversion. This study demonstrates a vanadyl/pervanadyl (VO 2+ /VO 2 + ) redox‐mediated interface designed for high‐energy Mn 2+ /MnO 2 batteries. Unlike flow systems, this work uncovers, for the first time, the mechanism of a static redox‐mediated interface in regulating interfacial H + and H 2 O activities. Significantly, the VO 2+ /VO 2 + chemical redox mediation targets Mn 3+ intermediates, suppressing their hydrolysis and enabling 100% Mn 2+ /MnO 2 conversion. The redox‐mediated interface enhances the Mn redox electron transfer process, achieving a stable ≈95% coulombic efficiency and ultrahigh capacity of 100 mAh cm − 2 with an areal energy density of 111 mWh cm − 2 , outperforming flow systems. The electrode also exhibits an average specific capacity of 593 mAh g −1 , approaching the theoretical limit of 616 mAh g −1 , and a specific energy density of 721 Wh kg −1 at high MnO 2 loadings (50–150 mg cm −2 ). The findings highlight the critical role of interfacial redox mediation in regulating H + and H 2 O activities and underscore the significance of interface dynamics.

This study revisits the three-point sampling of the simplified Butler-Volmer equation to address the limitations of strong potentiodynamic polarization, which can introduce irreversible damage and uncertainty in corrosion analysis. The method extracts electrochemical kinetic parameters while minimizing polarization effects, evaluates noise sensitivity relative to overpotential, and accounts for errors from signal noise, OCP drift, ohmic resistance, and mass-transfer constraints. Verified against the Tafel extrapolation method for aluminum corrosion across a wide pH range, this low-polarization approach enables accurate evaluations with specific error estimates, offering a robust alternative to linear polarization resistance methods that assume constant Tafel slopes.

Several strategies have been developed to mitigate the dendritic growth of metallic lithium. One promising approach is the use of three-dimensional (3D) framework electrodes for lithium-metal storage. These electrodes feature a large surface area and high porosity, which help to reduce local lithium plating current densities. Their porous topology acts as a scaffold for lithium deposition and stripping, thereby enhancing both mechanical integrity and lithium accessibility. The objective of this study is to identify the characteristics—such as geometry and material properties—necessary for achieving stable cycling at current densities relevant to vehicle electrification. To accomplish this, we have developed a computational method to track material growth driven by electrodeposition within complex geometries. This method involves adapting a background mesh to the evolving volume of material, ensuring that the finite-element discretization remains conforming to the moving boundary. With these new tools, we analyze the conditions under which porous anode architectures effectively self-regulate current density and mitigate dendrite growth. One criterion consists in analyzing the maximum and the spatial distribution of the local overpotential, since it directly relates to the likelihood of dendrite growth. Finally, we investigate the trade-offs between surface area, energy density, and mechanical robustness in the design of microstructures for anode-free batteries. This work was supported by Lawrence Livermore National Laboratory LDRD SI 23-SI-002. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Electrochemical energy storage (EES) and conversion devices (e.g. batteries, supercapacitors, and reactors) are emerging as primary methods for global efforts to shift energy dependence from limited fossil fuels towards sustainable and renewable resources. These devices, while showing great potential for meeting some key metrics set by conventional technologies, still face significant limitations. For example, an EES device tends to exhibit large energy density (e.g. lithium-ion battery) or power density (e.g. supercapacitor), but not both. This inability of a single device to simultaneously achieve both metrics represents a major obstacle to widespread adoption of EES devices. Similarly, many catalytic processes depend on expensive platinum group metals (PGM) because non-PGM materials have poor performance or durability. Though the integration of 2D materials (e.g. graphene, dichalcogenides, MXene, etc.) into electrochemical devices has yielded some exciting results towards tackling these issues, significant improvements are still needed. One approach to optimizing the performance of these devices is to focus on one of the fundamental processes that occur in these systems: mass (or charge) transport. The efficient transport of ions within EES and conversion devices is critical to realizing better performance and durability. The pore structure of the electrode is a key factor in determining this transport phenomena, but in many cases, engineering the pore structure in a highly deterministic fashion can be challenging. In this work, we explore a number of additive manufacturing methods (e.g. direct ink write, projection microstereolithography, etc.) to engineer the pore structure of device electrodes. We also determine effective electrode geometries using both simple theory and topology optimization techniques. The topology optimization couples the solution of the forward electrochemical problem over the full electrode domain with gradient-based optimization. The output of our code is a three-dimensional CAD representation which optimizes over specific performance metrics and which can be used to print functional electrodes. This work provides a systematic path toward automated design and fabrication of engineered electrodes with precise control over the fluid and species distribution. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Lithium-ion batteries (LIBs) have become a core portable energy storage technology due to their high energy density, longevity, and affordability. Nevertheless, their use in low-temperature environments is challenging due to significant Li-metal plating and dendrite growth, sluggish Li-ion desolvation kinetics, and suppressed Li-ion transport. In this study, we employ classical molecular dynamics simulations to provide a mechanistic understanding of the impact of temperature- and concentration-effects on the ionic conductivity of a prototypical battery electrolyte, lithium hexafluorophosphate in ethylene carbonate (LiPF6/EC). We further investigate the interplay between temperature and ionic speciation via a graph-based clustering analysis that resolves species-specific ionic conductivity contributions. Using these findings, we formulate two fundamental design principles governing electrolyte performance: one for ambient temperature and another for low-temperature conditions. The modeling framework outlined in this work provides a foundation for identifying design principles that can be used to rationally improve the low-temperature performance of LIBs. Formulating and establishing design principles to improve low-temperature performance of battery electrolytes.

Phase transformations are a challenging problem in materials science, which lead to changes in properties and may impact performance of material systems in various applications. We introduce a general framework for the analysis of particle growth kinetics by utilizing concepts from machine learning and graph theory. As a model system, we use image sequences of atomic force microscopy showing the crystallization of an amorphous fluoroelastomer film. To identify crystalline particles in an amorphous matrix and track the temporal evolution of the particle dispersion, we have developed quantitative methods of 2D analysis. 700 image sequences were analyzed using a neural network architecture, achieving 0.97 pixel-wise classification accuracy as a measure of the correctly classified pixels. The growth kinetics of isolated and impinged particles were tracked throughout time using these image sequences. The relationship between image sequences and spatiotemporal graph representations was explored to identify the proximity of crystallites from each other. The framework enables the analysis of all image sequences without the requirement of sampling for specific particles or timesteps for various materials systems.

The properties of rechargeable lithium-ion batteries are determined by the electrochemical and kinetic properties of their constituent materials as well as by their underlying microstructure. The discovery of 2D and 3D mesoscale architectures tailored to diverse applications remain an open challenge and it cannot be approached empirically. In this work, we leverage the design flexibility offered by several additive manufacturing methods (e.g. direct ink write, projection micro-stereolithography, etc.) to engineer the architecture of device electrodes. To explore this vast design space, we employ theoretical analyses and topology optimization techniques to determine printable electrode shapes. Our analyses produce general design guidelines, and three-dimensional CAD representations that optimize the battery architecture over specific performance metrics. In this talk, we show examples of electrode design driven by extreme operating conditions (e.g., low temperature) or by mechanical resilience. We also demonstrate an integrated workflow for model validation and guided experiments. For Li-metal anodes, our objective is to identify regimes of morphologically stable growth--where deleterious effects of dendrite growth might be avoided by microstructural design. For manganese-oxide cathodes, we develop physical models that capturethe pseudocapacitive response of the material and use them in inverse analyses to optimize the cathode architectures.

Rechargeable batteries that incorporate shaped three-dimensional electrodes have been shown to have increased power and energy densities when compared to a conventional geometry, i.e. a planar cathode and anode that sandwich an electrolyte. Electrodes can be shaped to enable a higher active material loading, while keeping ion transport distances small. However, the relationship between electrical and mechanical performance of shaped electrodes remains poorly understood. Many electrode designs have been explored, where the electrodes are individually shaped or intertwined, and advances in manufacturing and shape/topology optimization have made such designs a reality. Here, we explore sinusoidal half cells and interdigitated full cells. First, we use a simple electrostatics model to understand the cell resistance as a function of shape. We focus on low-temperature conditions, where the electrolyte conductivity decreases relative to that of the electrode; here, LiPF6 EC:DMC electrolyte and MnO2 electrode are considered. Next, we use a chemo-mechanics model to examine the stress that arises due to intercalation-driven volume expansion. We show that shaped electrodes provide a significant reduction in resistance in low-temperature conditions, however, they exhibit unfavorable stress concentrations. Overall, we find that the fully interdigitated electrodes may provide the best balance with respect to this resistance-stress trade-off.

MnO 2 polymorphs show distinct advantages and disadvantages when used as cathode material for Li-ion batteries (LIBs).

The efficient transport of charge species within energy storage devices is critical to realizing both large power and energy densities, especially when operating under extreme conditions (e.g. ultralow temperatures, high charge/discharge rates, etc.). A number of resistances can contribute to sluggish ion/electron transport in a cell such as charge transfer at interfaces, electrolyte resistance, electrode resistance, and diffusive transport within porous electrodes. Several strategies have been pursued to address these transport limitations. Electrolyte engineering is an effective approach as it can influence both electrolyte resistance and charge transfer resistances. Electrode materials discovery and development is another popular strategy as the charge storage mechanism and electrode resistance play a key role in kinetics of the device. Within electrode materials development, engineering of the electrode pore architecture is an extremely effective strategy to decrease the diffusive transport lengths and electrode resistances. This pore engineering can be achieved through synthetic chemistry for small pores (e.g. <10 um) and via additive manufacturing for larger pores (> 10 um). Here we show how electrolyte engineering and electrode materials development can be used to overcome sluggish transport in graphene-based electrodes. Particular focus will be given to the use of synthetic means to tune to the properties of a graphene aerogel scaffold (e.g. surface area, pore size, mechanical properties) and additive manufacturing to define the larger pore structure to facilitate uniform deposition of active materials (e.g. MnO 2 ) and improve energy density and rate capability of the energy storage device. We explore a number of additive manufacturing techniques (e.g. direct ink write, projection microstereolithography, etc.) to print a variety of lattice structures and computer-guided designs to determine the optimal electrode architecture. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

The ability to uniformly electrodeposit metallic coatings onto geometrically complex substrates plays a significant role in developing specialized applications from coating detailed RF components to depositing catalytic coatings onto ordered foams electrodes for electrochemical flow reactors. However, there presently lacks guidelines for electrodeposition in porous media due to the problem’s multi-scale complexity. We present a framework for deconvoluting this process through continuum-level modeling and experimental validation of electrodeposited copper onto additively manufactured conductive lattice structures. Through numerical simulations we can predict thickness profiles and validate the model prediction and coating quality through micro-computed tomography. We further devise scaling laws with the aim of facilitating control over deposition uniformities on different lattice architectures and dimensions under fluid flow. In extension, the manufacturing platform for functionalized electrodes is extended to battery applications as use in novel electrode geometries within rechargeable secondary batteries as well as plating thickness evolution in custom redox flow battery cathodes for grid scale energy storage. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 within the LDRD program 20-ERD-056. LLNL-ABS-847849.

Potentiodynamic polarization is a standard approach for probing corrosion, yet it is fundamentally limited by the need for large overpotentials which can cause irreversible damage and introduce uncertainty due to ohmic resistance and mass-transport corrections. In this work, we present a new analytical method based on a three-point sampling scheme of the Butler-Volmer equation which is applied to aluminum corrosion over a broad pH range. The method enables the accurate calculation of corrosion current density and Tafel slopes in the vicinity of the corrosion potential, circumventing the need for significant destructive polarization conditions commonly used in Tafel slope analysis. The accuracy of the three-point analytical approach was examined by considering various sources of error, including signal noise, ohmic resistance, and mass transfer limitations that may cause the current response to deviate from the charge transfer process described by the Butler-Volmer equation. The findings recommend an appropriate overpotential window for non-destructive corrosion rate monitoring that minimizes these potential noise sources. Furthermore, the reliability of the approach was demonstrated by comparing the kinetic parameters of aluminum corrosion extracted using the three-point method to those extracted using the traditional Tafel extrapolation method. Three pH environments – acidic, neutral, and basic – were tested. These environments exposed different primary noise sources, such as instrument noise at low pH, mass-transfer effects due to oxide formation at neutral pH, and environmental noise due to gas formation at high pH. In all cases, the three-point analytical method successfully mitigated these challenges and confirmed its ability to extract viable and trustworthy data within a low overpotential window. This new method offers a less-destructive alternative for monitoring electrochemical systems that change over time and offers a valuable tool for understanding and identifying key materials features and environmental factors that control corrosion kinetics.

Phase transformations in materials systems can be tracked using atomic force microscopy (AFM), enabling the examination of surface properties and macroscale morphologies. In situ measurements investigating phase transformations generate large datasets of time-lapse image sequences. The interpretation of the resulting image sequences, guided by domain-knowledge, requires manual image processing using handcrafted masks. This approach is time-consuming and restricts the number of images that can be processed. In this study, we developed an automated image processing pipeline which integrates image detection and segmentation methods. We examine five time-series AFM videos of various fluoroelastomer phase transformations. The number of image sequences per video ranges from a hundred to a thousand image sequences. The resulting image processing pipeline aims to automatically classify and analyze images to enable batch processing. Using this pipeline, the growth of each individual fluoroelastomer crystallite can be tracked through time. We incorporated statistical analysis into the pipeline to investigate trends in phase transformations between different fluoroelastomer batches. Understanding these phase transformations is crucial, as it can provide valuable insights into manufacturing processes, improve product quality, and possibly lead to the development of more advanced fluoroelastomer formulations.

This study presents a novel method to correlate the mass and charge transfer kinetics during the electrophoretic deposition of nanocrystal films by using a purpose-built double quartz crystal microbalance combined with simultaneous current-measurement. Our data support a multistep process for film formation: generation of charged nanocrystal flux, charge transfer at the electrode, and polarization of neutral nanocrystals near the electrode surface. The polarized particles are then subject to dielectrophoretic forces that reduce diffusion away from the interface, generating a sufficiently high neutral particle concentration at the interface to form a film. The correlation of mass and charge transfer enables quantification of the nanocrystal charge, the fraction of charged nanocrystals, and the initial sticking coefficient of the particles. These quantities permit calculation of the film thickness, providing a theoretical basis for using concentration and voltage as process parameters to grow films of targeted thicknesses.