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DOE OSTI2025

CyberMESA: Evaluation Procedures and Metrics for Charging Infrastructure Cybersecurity

A report detailing the cybersecurity evaluation and assessment procedures for EV charging infrastructure. This report is authored by three national lab contributors. INL, PNNL, NRL. The grid integration of Electric Vehicle Charging Infrastructure (EVCI) is a large and complex system of systems (SoS) made up of components from many manufacturers and integrated by various companies responsible for their operation and maintenance. This complexity makes it challenging to implement security standards like IEC 62443 across the entire infrastructure. This document aims to aid in the vulnerability assessments of individual devices, such as Electric Vehicle Supply Equipment (EVSE), to support vendors in adopting and implementing security standards such as UL 2900, NIST SP 800-53 and Common Criteria (CC) (ISO/IEC 15408). This document serves as a guide to help evaluate the cybersecurity posture of EVCI assets. It aims to provide a consistent method for evaluating EVCI, enabling cybersecurity research teams to systematically test a wide range of electric vehicle (EV) assets. The target audiences include cybersecurity research teams, vendor development teams, automotive OEMs, and third-party evaluators.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Multi-phase characterization of pitch-carbon coated nano-silicon anodes for lithium-ion batteries

Silicon (Si) is a leading next-generation Li-ion battery anode candidate that meets rigorous performance demands for portable power including enhanced power and energy density with robust cycling performance. However, a series of complex and interrelated reactions lead to reduced calendar life in Si-containing systems and therefore challenge practical adoption. In the present work, we probe the mechanisms underlying observed performance improvements by adding a pitch-carbon coating onto nano-Si material. We pair solid-phase (X-ray photoemission spectroscopy, Fourier-transform infrared), semi-volatile phase (solid-phase microextraction-gas chromatography-mass spectrometry), and gas-phase (gas chromatography-flame-ionization detector) characterization signals to comprehensively evaluate the impact of pitch-carbon coating on the evolution of the Si solid-electrolyte interphase (SEI) and the associated impacts on electrode/electrolyte reactivity. The pitch-carbon is found to serve as a physicochemical barrier, reducing the electro-active surface area for Si/electrolyte reactivity and preventing Si oxidation. Further, the pitch-carbon coating promotes the evolution of a more-favorable SEI by subsuming substantial functionality typically associated with the fluoroethylene carbonate (FEC) electrolyte additive - such as alkoxide scavenging and suppression of transesterification pathways - and by shifting the competitive electrolyte degradation pathways' favorability. The multi-phase characterization approach enables holistic end-products evaluation from complex (electro)chemical interfacial reactions, which informs a robust interpretation of the carbon coating's role in electrochemical performance improvements. The present mechanistic evaluation aids the rational design for improved nano-Si materials.

25 ENERGY STORAGE↗
DOE OSTI2020

CyDER: A Cyber Physical Co-simulation Platform for Distributed Energy Resources in Smartgrids

The CyDER project aimed at developing an open-source, modular and scalable co-simulation platform for power grids with large shares of Distributed Energy Resources (DERs). The project partners are the Lawrence Berkeley National Lab (LBNL), Lawrence Livermore National Lab (LLNL), PG&E, SolarCity, and ChargePoint. The prime recipient is LBNL; SolarCity and ChargePoint were partners for the project’s first two years. Increased DER integration introduces a number of challenges in power grid operation including a more dynamic interaction between the transmission grid and distribution grids, and increased modeling complexity. Although specialized software exists to precisely model different components of the power system, it is far from trivial to integrate all various models and perform a holistic simulation. Instead of replicating all models in a common simulation program, a commonly accepted approach to tackle this model diversity is to couple third-party simulators and models through a co-simulation platform that coordinates information exchange among the various components. Following this line of research, this project’s objective was to develop a co-simulation platform based on a widely accepted industrial standard called Functional Mockup Interface (FMI). Within this process, the project developed models compliant with the FMI standard, called Functional Mockup Units (FMUs), and used them to perform various operational and planning power system analyses. Relying and building upon an industrial standard is the main differentiation of this project compared with previous or parallel efforts in the co-simulation area. Particular emphasis was put on delivering software utilities to facilitate setting up and running co-simulations by end-users. Furthermore, a strong aspect of this project is demonstrating that co-simulation techniques can be used to perform Hardware-in-the-Loop (HIL) simulations that couple software components (e.g., simulated models) with hardware components (e.g., real devices such PV systems and batteries). The long-term goal of CyDER project is to help establish FMI as a powerful standard for co-simulation and promote adoption by electric utilities and other interested stakeholders. The main accomplishments of the project include the development of several FMUs including distribution and transmission grid models, PV inverters with Volt/Var/Watt controllers, batteries, and predictive optimal controllers. Additionally, a unique software package was developed, called SimulatorToFMU, which is capable of exporting any Python-driven simulator or Python script as an FMU. This is an important contribution towards establishing FMI as one of the main co-simulation standards, because more and more third-party programs for sub-system modeling and simulation are delivered with Python APIs. The CyDER platform was used to perform PV hosting capacity analyses in real utility feeders with and without smart inverter controls, battery storage, and EV charging. Smart inverter controls include conventional Volt/Var/Watt controls for reactive power support and active power curtailment, but also predictive controls that optimize the charging and discharging profile of the battery connected on the DC side in order to minimize the customer’s economic benefit. Finally, an important result of this project is delivering an experimental setup that consists of residential-scale PV inverters with battery storage, a real-time grid simulator with an ideal voltage source as grid emulator, and micro Phasor Measurement Units (PMUs). All these components and additional software modules are coupled to one another using the FMI standard and can be co-simulated with the CyDER platform.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

An experimentally validated electro-thermal EV battery pack model incorporating cycle-life aging and cell-to-cell variations

Lithium-ion batteries are used in a wide variety of applications. To meet the power and energy demands of these applications battery packs are composed of hundreds to thousands of cells. The electrical and thermal interactions between cells introduce additional complexity in the pack dynamics. To capture these effects, a battery pack model composed of 192 cells based on a first-generation (2012) Nissan Leaf battery pack is developed in MATLAB/Simulink/Simscape. Here, with this model, we simulate the electrical dynamics (using a first-order equivalent-circuit model), the thermal dynamics (using a first-order lumped-parameter thermal model), and the aging dynamics (using a semi-empirical severity factor-based model) of every cell in the pack and we also create a pack thermal model that explicitly captures the heat exchange between the modules, and the cells contained within, during operation. The models are calibrated and validated, both at the cell and pack level, with experimental data. Two different case studies of this pack model are investigated. In the first case study, an initial, normally-distributed, cell-to-cell capacity variation is introduced and its effect on the pack voltage and module temperatures is studied. In the second case study, we deliberately insert cells with lower than nominal capacity into the pack and we investigate how this type of initial cell-to-cell capacity variation affects the pack’s ability to deliver energy over time. Finally, we also study how parallel-connected cells can reduce the effects of cell-to-cell variations at the expense of increased aging of the pack overall.

25 ENERGY STORAGE↗
DOE OSTI2022

Exchange-Mediated Transport in Battery Electrolytes: Ultrafast or Ultraslow?

Understanding the mechanisms of charge transport in batteries is important for the rational design of new electrolyte formulations. Persistent questions about ion transport mechanisms in battery electrolytes are often framed in terms of vehicular diffusion by persistent ion–solvent complexes versus structural diffusion through the breaking and reformation of ion–solvent contacts, i.e., solvent exchange events. Ultrafast two-dimensional (2D) IR spectroscopy can probe exchange processes directly via the evolution of the cross-peaks on picosecond time scales. However, vibrational energy transfer in the absence of solvent exchange gives rise to the same spectral signatures, hiding the desired processes. Here we employ 2D IR on solvent resonances of a mixture of acetonitrile isotopologues to differentiate chemical exchange and energy-transfer dynamics in a comprehensive series of Li + , Mg 2+ , Zn 2+ , Ca 2+ , and Ba 2+ bis(trifluoromethylsulfonyl)imide electrolytes from the dilute to the superconcentrated regime. No exchange phenomena occur within at least 100 ps, regardless of the ion identity, salt concentration, and presence of water. All of the observed spectral dynamics originate from the intermolecular energy transfer. These results place the lower experimental boundary on the ion–solvent residence times to several hundred picoseconds, much slower than previously suggested. With the help of MD simulations and conductivity measurements on the Li + and Zn 2+ systems, we discuss these results as a continuum of vehicular and structural modalities that vary with concentration and emphasize the importance of collective electrolyte motions to ion transport. These results hold broadly applicable to many battery-relevant ions and solvents.

25 ENERGY STORAGE↗
DOE OSTI2024

Consequences of plane-strain and plane-stress assumptions in fully coupled chemo-mechanical Li-ion battery models

In Li-ion battery research, it is common to simulate chemo-mechanical phenomena in reduced dimensions (e.g., 2-D) as opposed to fully resolve these complex physics in 3-D. It is common to assume either (1) the out-of-plane strain is negligible (commonly referred to as plane-strain), or (2) the out-of-plane stress is negligible (commonly referred to as plane-stress). However, there is typically little consideration as to the quantitative consequences of these approximations. Furthermore, the influence of these out-of-plane assumptions can be compounded and convoluted when chemo-mechanics models implement so-called “fully coupled” formulations, where the local species concentrations influence the stress-state and the stress-state influences the local species fluxes. Here, the present manuscript explores the implications of using plane-stress and plane-strain assumptions in 2-D as compared to simulating a full 3-D electrode particle. This comparative study includes simulating both isotropic and anisotropic particle intercalation where the particles can be surrounded by either a liquid or solid electrolyte. Additionally, common Li-ion battery-model metrics such as the state-of-stress, intercalation fraction distribution, and specific capacity are compared, while also considering the effects of particle size and C-rate. As alternatives to the pure plane-strain and plane stress approximations, two modified plane-strain assumptions are found to better approximate the fully coupled chemo-mechanical 3-D behavior.

25 ENERGY STORAGE↗
DOE OSTI2026

4D insights into lithium-ion battery sidewall rupture during thermal runaway

Thermal runaway (TR), characterized by rapid exothermic reactions, presents a serious safety risk in lithium-ion batteries (LiBs). External triggers such as high temperatures, mechanical abuse, or internal short circuits (ISCs) can initiate TR, often resulting in sidewall rupture, which may escalate to catastrophic battery pack failure. In this study, we developed and applied high-speed synchrotron imaging techniques to investigate sidewall rupture mechanisms in LiBs subjected to different triggering scenarios. Using in situ 4D tomographic imaging, we visualized the dynamic evolution of sidewall rupture with high spatial and temporal resolution. The results revealed distinct failure behaviors linked to each trigger, underscoring the complex and condition-specific nature of sidewall breach and battery failure. These insights highlight the critical importance of implementing tailored safety strategies across diverse applications. Our findings demonstrate the powerful potential of synchrotron high-speed tomography as a diagnostic tool for advanced safety testing and cell qualification.

25 ENERGY STORAGE↗
DOE OSTI2026

Hidden features in the OH-stretching spectra of amino acid decorated air–water interfaces

Chemical reactivity at the air–water interface is governed by the interfacial solvation of reactive species. For instance, during aqueous amino acid-based CO 2 absorption, water reorganizes around the reactive sites and couples dynamically with reaction pathways, facilitating the reaction. In this context, surface-sensitive vibrational sum-frequency generation (vSFG) spectroscopy can probe the OH stretch vibrations of interfacial water and determine the solvation structures around reactants and products, thereby furthering our understanding of the role of interfacial solvation. However, vSFG spectra of the air–water interface in the presence of charged species can be remarkably complex; key species-bound local water structures with distinct orientations may be hidden beneath prominent vSFG peaks arising from water–water hydrogen bonds and remain difficult to resolve. Here, we measure and compute vSFG spectra of the water OH stretch at air–water interfaces decorated with amino acids in their zwitterionic and anionic forms, as well as equimolar mixtures of these forms with bicarbonate. The latter represents post-CO 2 -absorption conditions. We find that computing depth- and frequency-dependent spectral densities—decomposed into contributions from water molecules hydrogen-bonded exclusively to other water molecules, exclusively to amines, exclusively to carboxylates, or shared between these polar/charged groups—is indispensable for accurate interpretation of the vSFG spectra. Key findings include orientational flip-flop in water sub-layers, strong carboxylate-water H-bonding, and water orientational ordering extending into the bulk aqueous phase induced by anionic amino acids. Here, this study provides a computational spectroscopic platform for improved understanding of interfacial solvation relevant to interfacial reactivity.

Air-water interface↗
DOE OSTI2022

Optimization of Water-Alternating-CO2 Injection Field Operations Using a Machine-Learning-Assisted Workflow

Summary This paper will present a robust workflow to address multiobjective optimization (MOO) of carbon dioxide (CO2)-enhanced oil recovery (EOR)-sequestration projects with a large number of operational control parameters. Farnsworth unit (FWU) field, a mature oil reservoir undergoing CO2 alternating water injection (CO2-WAG) EOR, will be used as a field case to validate the proposed optimization protocol. The expected outcome of this work would be a repository of Pareto-optimal solutions of multiple objective functions, including oil recovery, carbon storage volume, and project economics. FWU’s numerical model is used to demonstrate the proposed optimization workflow. Because using MOO requires computationally intensive procedures, machine-learning-based proxies are introduced to substitute for the high-fidelity model, thus reducing the total computation overhead. The vector machine regression combined with the Gaussian kernel (Gaussian-SVR) is used to construct proxies. An iterative self-adjusting process prepares the training knowledge base to develop robust proxies and minimizes computational time. The proxies’ hyperparameters will be optimally designed using Bayesian optimization to achieve better generalization performance. Trained proxies will be coupled with multiobjective particle swarm Optimization (MOPSO) protocol to construct the Pareto-front solution repository. The outcomes of this workflow will be a repository containing Pareto-optimal solutions of multiple objectives considered in the CO2-WAG project. The proposed optimization workflow will be compared with another established methodology using a multilayer neural network (MLNN) to validate its feasibility in handling MOO with a large number of parameters to control. Optimization parameters used include operational variables that might be used to control the CO2-WAG process, such as the duration of the water/gas injection period, producer bottomhole pressure (BHP) control, and water injection rate of each well included in the numerical model. It is proved that the workflow coupling Gaussian-SVR proxies and the iterative self-adjusting protocol is more computationally efficient. The MOO process is made more rapid by squeezing the size of the required training knowledge base while maintaining the high accuracy of the optimized results. The outcomes of the optimization study show promising results in successfully establishing the solution repository considering multiple objective functions. Results are also verified by validating the Pareto fronts with simulation results using obtained optimized control parameters. The outcome from this work could provide field operators an opportunity to design a CO2-WAG project using as many inputs as possible from the reservoir models. The proposed work introduces a novel concept that couples Gaussian-SVR proxies with a self-adjusting protocol to increase the computational efficiency of the proposed workflow and to guarantee the high accuracy of the obtained optimized results. More importantly, the workflow can optimize a large number of control parameters used in a complex CO2-WAG process, which greatly extends its utility in solving large-scale MOO problems in various projects with similar desired outcomes.

Energy & Fuels↗
DOE OSTI2021

A Segregated Approach for Modeling the Electrochemistry in the 3-D Microstructure of Li-Ion Batteries and Its Acceleration Using Block Preconditioners

Abstract Battery performance is strongly correlated with electrode microstructure. Electrode materials for lithium-ion batteries have complex microstructure geometries that require millions of degrees of freedom to solve the electrochemical system at the microstructure scale. A fast-iterative solver with an appropriate preconditioner is then required to simulate large representative volume in a reasonable time. In this work, a finite element electrochemical model is developed to resolve the concentration and potential within the electrode active materials and the electrolyte domains at the microstructure scale, with an emphasis on numerical stability and scaling performances. The block Gauss-Seidel (BGS) numerical method is implemented because the system of equations within the electrodes is coupled only through the nonlinear Butler–Volmer equation, which governs the electrochemical reaction at the interface between the domains. The best solution strategy found in this work consists of splitting the system into two blocks—one for the concentration and one for the potential field—and then performing block generalized minimal residual preconditioned with algebraic multigrid, using the FEniCS and the Portable, Extensible Toolkit for Scientific Computation libraries. Significant improvements in terms of time to solution (six times faster) and memory usage (halving) are achieved compared with the MUltifrontal Massively Parallel sparse direct Solver. Additionally, BGS experiences decent strong parallel scaling within the electrode domains. Last, the system of equations is modified to specifically address numerical instability induced by electrolyte depletion, which is particularly valuable for simulating fast-charge scenarios relevant for automotive application.

25 ENERGY STORAGE↗
DOE OSTI2020

Surface SiO 2 Thickness Controls Uniform-to-Localized Transition in Lithiation of Silicon Anodes for Lithium-Ion Batteries

Silicon is a promising anode material for lithium-ion batteries because of its high capacity, but its widespread adoption has been hampered by a low cycle life arising from mechanical failure and the absence of a stable solid–electrolyte interphase (SEI). Understanding SEI formation and its impact on cycle life is made more complex by the oxidation of silicon materials in air or during synthesis, which leads to SiO x coatings of varying thicknesses that form the true surface of the electrode. Here, the lithiation of SiO 2 -coated Si is studied in a controlled manner using SiO 2 coatings of different thicknesses grown on Si wafers via thermal oxidation. SiO 2 thickness has a profound effect on lithiation: below 2 nm, SEI formation followed by uniform lithiation occurs at positive voltages versus Li/Li + . Si lithiation is reversible, and SiO 2 lithiation is largely irreversible. Above 2 nm SiO 2 , voltammetric currents decrease exponentially with SiO 2 thickness. For 2–3 nm SiO 2 , SEI formation above 0.1 V is suppressed, but a hold at low or negative voltages can initiate charge transfer whereupon SEI formation and uniform lithiation occur. Cycling of Si anodes with an SiO 2 coating thinner than 3 nm occurs at high Coulombic efficiency (CE). If an SiO 2 coating is thicker than 3–4 nm, the behavior is totally different: lithiation at positive voltages is strongly inhibited, and lithiation occurs at poor CE and is highly localized at pinholes which grow over time. As they grow, lithiation becomes more facile and the CE increases. Pinhole growth is proposed to occur via rapid transport of Li along the SiO 2 /Si interface radially outward from an existing pinhole, followed by the lithiation of SiO 2 from the interface outward.

25 ENERGY STORAGE↗
DOE OSTI2022

A compendium and meta-analysis of flatband potentials for TiO2, ZnO, and SnO2 semiconductors in aqueous media

Semiconductor/electrolyte interfaces are of great interest to numerous scientific fields including renewable energy, (photo)electrochemistry, and energy storage. The semiconductor flatband potential is a key parameter in locating the conduction band minimum or valence band maximum of the semiconductor material in electrolyte. Despite its importance for quantifying the energetic location of the semiconductor bands, literature reports for the same material demonstrate significant variability in the flatband potential. In this compendium and meta-analysis, reported flatband potentials of the common semiconductor materials TiO2, SnO2, and ZnO in aqueous electrolyte were compiled and assessed to quantify the spread in literature flatband potentials as well as determine the factors that lead to the significant spread. For TiO2, SnO2, and ZnO, literature flatband potentials referenced to the reversible hydrogen electrode span a range of nearly 2 V each. Flatband potential tabulations were separated by variables such as the solution pH, the crystalline polymorph, the crystal facet, the morphology, and the dimensions or combinations of these variables to assess the factors that contribute to the observed spread. Important and surprising findings from these categorizations are summarized: (1) Even for the narrowest categorizations, the spread in flatband potential is still large. (2) Flatband potentials of TiO2 and SnO2 follow the expected Nernstian dependence with solution pH. ZnO materials deviate from this Nernstian dependence. (3) In the aggregate, there is no statistically significant difference in the reported flatband potentials of anatase and rutile TiO2. Single crystal tabulations were the only distributions to have statistically significant differences in the flatband potential between anatase and rutile TiO2. (4) Anatase TiO2 materials with a nanotube morphology appear to have a +400 mV difference in mean flatband potential compared to all other morphologies, but we argue that this is likely due to widespread misuse of the Mott–Schottky analysis. Other interesting findings are revealed within the spread of literature flatband potentials, and possible explanations are provided to generate discussion. We also briefly review and discuss common techniques that were used to determine the flatband potential and the pitfalls/criticisms of these techniques. Last, we discuss some ways in which future research on the determination of the flatband potential can be performed to improve the reliability of reported values and the quality of the work. In total, the results from this meta-analysis suggest multiple factors can affect the measured flatband potential and that an abundance of caution should be applied when attempting to quantify the flatband potential of complex or nanostructured systems.

Patel, Milan Y. (ORCID:0000000291948141)↗
DOE OSTI2020

Electrolyte Oxidation Pathways in Lithium-Ion Batteries

The mitigation of decomposition reactions of lithium-ion battery electrolyte solutions is of critical importance in controlling device lifetime and performance. However, due to the complexity of the system, exacerbated by the diverse set of electrolyte compositions, electrode materials, and operating parameters, a clear understanding of the key chemical mechanisms remains elusive. In this work, operando pressure measurements, solution NMR, and electrochemical methods were combined to study electrolyte oxidation and reduction at multiple cell voltages. Two-compartment LiCoO 2 /Li cells were cycled with a lithium-ion conducting glass–ceramic separator so that the species formed at each electrode could be identified separately and further reactions of these species at the opposite electrode prevented. One principal finding is that chemical oxidation (with an onset voltage of ~4.7 V vs Li/Li + for LiCoO 2 ), rather than electrochemical reaction, is the dominant decomposition process at the positive electrode surface in this system. This is ascribed to the well-known release of reactive oxygen at higher states-of-charge, indicating that reactions of the electrolyte at the positive electrode are intrinsically linked to surface reactivity of the active material. Soluble electrolyte decomposition products formed at both electrodes are characterized, and a detailed reaction scheme is constructed to rationalize the formation of the observed species. The insights on electrolyte decomposition through reactions with reactive oxygen species identified through this work have a direct impact on understanding and mitigating degradation in high-voltage/higher-energy-density LiCoO 2 -based cells, and more generally for cells containing nickel-containing cathode materials (e.g., LiNi x Mn y Co z O 2 ; NMCs), as they lose oxygen at lower operating voltages.

25 ENERGY STORAGE↗
DOE OSTI2023

Fe-single-atom catalyst nanocages linked by bacterial cellulose-derived carbon nanofiber aerogel for Li-S batteries

Li-S battery (LSB) is promising for achieving high capacity. Still, its development is hindered by the complex redox process with sluggish kinetics and particularly the resulting lithium polysulfides (LiPS) shuttle effects. Single-atom catalysts (SACs), with their maximized atom utilization, could effectively chemisorb soluble LiPSs and expedite the sulfide conversion reaction kinetics. Here we report incorporating Fe single metal atom catalyst (Fe-SAC) in the sulfur cathode design and its electrocatalytic effects. Fe-doped ZIF-8 nanocages were introduced into a cheap biomass bacteria cellulose. A pyrolysis process converted them into an aerogel structure with Fe-SAC-functionalized N-doped carbon nanocages linked by a carbon nanofiber network (FeSA-NC@CBC), which was applied as a scaffold to fabricate freestanding and binder-free sulfur cathodes. He we conducted electrochemical measurements to reveal Fe-SAC functions including lowering energy barriers for S 8 reduction to liquid-phase LiPSs and further to solid-phase Li 2 S 2 /Li 2 S and accelerating Li 2 S 2 /Li 2 S nucleation and deposition, as corroborated by our theoretical calculation results. Benefiting from the synergistic effects of highly active Fe-SAC and three-dimensional conductive network, the sulfide reaction kinetics is improved, which can diminish LiPS shuttle effects and therefore improve LBS rate performance and cycling stability. Accordingly, the fabricated FeSA-NC@CBC composite cathode delivers an excellent rate capability at 2C with a reversible capacity of 840 mAh/g and a long-term cyclic stability of 800 mAh/g at 1C after 500 cycles.

25 ENERGY STORAGE↗
DOE OSTI2025

Numerical and experimental analysis of mechanically induced failure in electric vehicle battery modules

Mitigating thermal runaway and cell-to-cell propagation is essential for improving the safety of electric and hybrid vehicles. Enhancing digital twin capabilities to predict battery mechanical abuse is particularly critical for automotive and aerospace applications, where crashworthiness is a key concern. Understanding failure conditions and propagation in battery modules during mechanical abuse is complex due to interactions between structural deformation, heat transfer, electrochemical processes, exothermic reactions and mechanical fracture. While prior studies have focused on modeling cell-level behavior, extending these models to module or pack level is necessary for a system level understating of electric vehicle safety. This study develops coupled large deformation finite element models that simultaneously solve for electrochemistry, material failure, internal short circuit and thermal runaway propagation. The models account for mechanical and thermal interactions between lithium-ion cells and other battery components while the contact interfaces are evolving with time. Model-predicted voltage, temperature and force responses are compared with experimental data for validation. The results demonstrate that the approach captures key failure mechanisms, including thermal propagation through heat transfer, electrical propagation from short circuits in parallel-connected cells, and mechanical propagation via penetration and crack formation. These findings show that computational models are valuable tools for understanding battery module failure and providing insight that can reduce the need for extensive experimental testing.

25 ENERGY STORAGE↗
DOE OSTI2024

Dynamic cycling enhances battery lifetime

Laboratory aging campaigns benchmark and elucidate the complex degradation behavior of lithium-ion batteries, and are critical not only for developing new battery chemistries and cell designs but also for engineering reliable battery management systems. Critically, these laboratory experiments aim to quantify and capture realistic aging mechanisms. In this study, we systematically compare dynamic discharge profiles representative of electric vehicle driving to the well-accepted constant-current profiles. Surprisingly, we discovered that dynamic discharge enhances lifetime substantially compared to constant current discharge. Specifically, for the same average current and voltage window, varying the dynamic discharge profile leads to an increase of up to 38 % in equivalent full cycles at end-of-life. Explainable machine learning reveals the importance of low-frequency current pulses as well as time-induced aging under these realistic discharge conditions. Our work quantifies the importance of evaluating new battery chemistries and designs with realistic load profiles, and highlights the opportunities to revisit our understanding of aging mechanisms at the chemistry, materials, and cell levels.

25 ENERGY STORAGE↗
DOE OSTI2020

Progression to Compatibility Evaluations in Flowing Molten Salts

Molten salt compatibility with structural alloys has been identified as a key issue for the development of Generation 3 concentrating solar power (CSP) systems with thermal storage. To accelerate this evaluation to pumped systems, the goal of this project was to conduct thermal convection loop (TCL) experiments with a peak temperature of ≥700°C and a typical temperature gradient of ~100°C. The experiments indicated that conventional ~16wt.%Cr Ni-based alloys are compatible up to 700°C with purified (i.e. low O) or dried (low H₂O) industrial-sourced Mg-K-Na chloride salt with <10 μm/yr loss. This two-year project was conducted based on the experimental and mechanistic understanding developed more than 60 years ago at Oak Ridge National Laboratory (ORNL). The first TCL experiment met the <15 μm/yr corrosion metric for this project with specimens of Ni-based alloy 600 exposed at 580°-700°C for 1000 h and post-exposure room temperature tensile tests showed minimal degradation. The second TCL experiment successfully deployed an electrochemical sensor from Argonne National Laboratory and had a peak temperature of 750°C but only ran for ~110 h due to a furnace failure. Both experiments used highly purified industrial-sourced salt with an O content of ~3 μg O/g salt and a Mg addition of 0.04 wt.%. In the second year, the Chloride Collective developed a more economical drying procedure such that the O content was much higher (>20,000 μg O/g salt). A third TCL experiment was conducted with a sensor and a peak temperature of 700°C using dried salt from the same industrial source and increased NaCl content (~20 wt.%). In addition to a 0.05% Mg addition to the salt, a Mg coupon was added in the coldest part of the loop which dissolved during the experiment. Again, small mass changes were noted for specimens of alloys 600 and C276 but the values were slightly higher than those measured in purified salt with Mg. A thin non-continuous and non-adherent oxide layer was deposited on most specimens containing Mg, Si and Al but Cr depletion also was observed. Both years included facilities qualification crucible experiments and then capsule experiments to confirm a baseline isothermal reaction rate. The first year capsule experiment led to the conclusion that the two-stage ORNL purification process using NH₄Cl and CCl₄ left the salt with a high Cl potential and a Mg addition (~0.05wt.%) was needed to lower the potential. The second year capsule experiments at 600° and 700°C found little difference in depth of attack for 0-0.25%Mg additions. In general, the complex reactions where salt can be trapped in the porous surface layer of metal indicated that mass change is an unreliable metric and average depth of Cr depletion is a better metric for assessing the extent of attack. These results have created a new baseline that is contrary to the recent published literature for chloride salts where mass losses have been reported that can be extrapolated to very significant annual metal loss rates. Chloride salt corrosion can be controlled and the results also indicate that salt purification to low O levels may not be necessary. However, additional TCL experiments are needed at different times and temperatures to generate important engineering information such as temperature dependent corrosion rates and reaction rate laws for extrapolation to long-term behavior and isolate the effect of salt additives and impurities.

36 MATERIALS SCIENCE↗