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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Living Filter Designs for In-Line Recovery and Sorting of Critical materials

This project explored “bio-mining” of critical materials from electronic waste (E-waste) streams by developing living filters arrays capable of recovering these materials, focusing on the platinum group metals (PGMs) and rare earth elements (REEs). While highly toxic, E-waste is considered a valuable “urban mine” as it contains critical materials such as PGMs and REEs with orders of magnitude higher purity than the richest ores. The aim of the project was to: (1) develop mechanically robust, silk-based biomaterial filtration membranes that can capture REEs from dilute aqueous waste; (2) design and build 3D bioprinted living filters containing encapsulated electrochemically active bacteria (EAB) capable of bio-reducing PGMs and recovering them from waste streams; and (3) constructing combined living filter arrays using both components to efficiently capture REE and PGM from the same waste stream. The developed silk-based filtration membranes were self-assembled using silk-nanofibrils (SNFs) derived from silkworm (Bombyx mori) cocoons in conjunction with recombinant silk-elastin-like proteins (SELPs), which contained lanthanide-binding peptide tags (LBTs) with a high affinity and specificity towards REEs. These 100% biodegradable protein-based membranes were capable of recovering up to 85% of model REE ions (Tb 3+ ) filtered through the membrane, with ~50% recovery achieved in the presence of high concentrations (100X) of common interfering metals (Ca 2+ , Cu 2+ , Fe 3+ , Zn 2+ ). REE captured by the membranes were easily recovered by applying a low pH desorption buffer. The membranes also demonstrated substantial reusability, with only a 30% loss in binding capacity after 4 cycles of REE binding and recovery. To recover the PGMs, we created a bottom-up assembling strategy to construct a living hydrogel composed of a seamlessly integrated living catalyst, Shewanella loihica PV-4 (PV-4), for metal reduction, and their structural and functional linkers, bio-reduced graphene oxide (B-rGO). This hydrogel demonstrated a close to 90% recovery of model metal ions, Pd, from a simulated e-waste leaching stream with minimum-to-no biomass production. It’s also worth noting that the Pd recovery is initiated immediately after the introduction of living hydrogel, compared to conventional biocarriers that required start-up times within hours to days. Overall, these living hydrogels demonstrated superior bioactivity, structural integrity, and agility over existing biocarriers, which offers extensive opportunities to advance the biological metal recovery with unparallel efficiency, reduced energy/material consumption, and minimal environmental impact.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Fabrication, Modeling, and Testing of a Prototype for Particle Thermal Energy Storage Containment

Increasing penetration of variable renewable energy resources requires the deployment of energy storage at a range of durations. Long-duration energy storage (LDES) technologies will fulfill the need to firm variable renewable energy resource output throughout the year. Conventional electrochemical batteries (e.g., lithium-ion) are uneconomical in this role due to high energy capacity costs. Thermal energy storage (TES) is one promising technology for LDES applications because of its siting flexibility and ease of scaling. Particle-based TES systems use low-cost solid particles that have higher temperature limits than the molten salts used in traditional concentrated solar power systems. A key component in particle-based TES systems is the containment silo for the high-temperature (> 1100 degrees C) particles. This study combined experimental testing and computational modeling methods to design and characterize the performance of a particle containment silo for LDES applications. A containment silo prototype was built at a laboratory scale and used to validate a congruent transient finite element analysis (FEA) model. The validation compared the actual and predicted temperature profile through the prototype over six days as the particles cooled from their initial temperature. The performance of a commercial scale (> 5 GWhth) was then characterized using the validated model. The transient FEA model was subject to several charge-discharge cycles to mimic a possible operating schedule. The commercial-scale model predicted a storage efficiency in excess of 95% after five days of storage with a design storage temperature of 1200 degrees C. Insulation material and concrete temperature limits were considered as well. The validation of the methodology means the FEA model can simulate a range of scenarios for future applications. This work supports the development of a promising LDES technology with implications for grid-scale electrical energy storage, but also for thermal energy storage for industrial process heating applications.

ENERGY STORAGE↗
DOE OSTI2021

Designing Modules to Prevent Reverse Bias Degradation in Perovskite Solar Cells when Partial Shading Occurs

When a solar cell in a panel is shaded, the illuminated cells can place a large reverse bias on the shaded cell to attempt to force current through it. Although the panel can continue to produce power, the reverse bias can cause significant problems for the shaded cell. In the case of perovskite solar modules, Joule heating and irreversible electrochemical reactions will degrade the cell. Some photovoltaic technologies use bypass diodes to solve this problem. To prevent both a perovskite cell and an all-perovskite tandem cell from falling into reverse bias breakdown while shaded, no more than two cells per bypass diode are allowed, which is likely to be prohibitively expensive for many applications. Herein, how many solar cells can be protected by one bypass diode in single-junction and multijunction perovskite modules is explored. It is easier to incorporate bypass diodes into modules with singulated cells than with monolithic panels. It is shown that perovskite–silicon tandems can be protected with fewer bypass diodes than with single-junction perovskite modules. Furthermore, it is suggested that if bypass diodes cannot be feasibly incorporated, then the panels should be deployed in utility-scale power plants.

14 SOLAR ENERGY↗
DOE OSTI2025

Identifying High Ionic Conductivity Compositions of Ionic Liquid Electrolytes Using Features of the Solvation Environment

Binary mixtures of ionic liquids with molecular solvents are gaining interest in electrochemical applications due to the improvement in their performance over neat ionic liquids. Dilution with suitable molecular solvents can reduce the viscosity and facilitate faster diffusion of ions, thereby yielding substantially higher ionic conductivity than that for a pure ionic liquid. Although viscosity and diffusion coefficients typically behave as monotonic functions of concentration, ionic conductivity often passes through a peak value at an optimum molar ratio of the molecular solvent to the ionic liquid. The ionic conductivity maximum is generally explained in terms of a balance between the ease of charge transport and the concentration of the charge carriers. In this work, fluctuation in the local environment surrounding an ion is invoked as a plausible explanation for the ionic conductivity mechanism with a binary mixture of 1-ethyl-3-methylimidazolium tetrafluoroborate and ethylene glycol as an example. The magnitude of the dynamism in the local environment is captured by measuring the spatial and temporal features of the solvation environment. Standard deviation in the number of ions in the solvation environment serves as a spatial feature, while the cage correlation lifetimes for oppositely charged ions within the first solvation shell serve as a temporal feature. Large standard deviations in the cluster ion population and short cage correlation lifetimes are indicators of highly dynamic ionic environment at the molecular level and consequently yield high ionic conductivity. Such compositions were found to be in good agreement with the optimum ionic liquid mole fractions obtained through experimental measurement. Short cage correlation lifetimes enable the identification of optimum mixture compositions using simulation trajectories significantly shorter than those required to implement the Nernst–Einstein or Einstein formalisms for calculating ionic conductivity. We validated the applicability of this approach across force fields and in six ionic liquid-molecular solvent electrolytes formed with combination of cations, anions, and solvents. We offer a computationally efficient approach of screening ionic liquid-molecular solvent binary mixture electrolytes to identify molar ratios that yield high ionic conductivity.

25 ENERGY STORAGE↗
DOE OSTI2023

Optimization of Energy Storage System Economics and Controls by Incorporating Battery Degradation Costs in REopt

The use of stationary electrochemical energy storage systems utilizing lithium-ion batteries has increased rapidly as the production scale and price for lithium-ion batteries has decreased. These energy storage systems are crucial for maintaining grid resiliency, especially for grids operating with high penetration of renewable energy generation assets or for with a variety of distributed energy generation and storage systems. One challenging factor for the development of battery energy storage systems is estimating the proper sizing, in terms of both power and energy, that minimizes total costs over the lifetime of the systems; this calculation is difficult in simple cases, where a battery is costed independently, but is extremely challenging when building loads and electrical generation by photovoltaic resources are also considered. REopt is a techoeconomic optimization tool developed by NREL to address these challenges. Previously, battery degradation has been priced by simply assuming a 10-year replacement schedule for battery systems. However, this does not account for varying degradation trends observed across real-world batteries, or allow for batteries to be operated in a degradation-aware manner that optimizes battery dispatch based on operating costs. This work incorporates a battery life model into REopt. This battery life model is simple, so that it may be solvable within the constrains of a mixed-integer linear optimization problem, but is fit to accelerated aging data recorded in the lab. To achieve the best possible accuracy for lifetime estimates given these constraints, parameters for the battery life model in REopt are estimated by fitting 20-year simulations of battery life after identifying state-space battery degradation model from accelerated aging data. Comparisons of battery life predicted in REopt and from the state-space battery degradation model to ensure validity of lifetime estimates made by REopt. Battery life and cost is optimized by controlling three decision to minimize system life cost: battery sizing, daily state-of-charge, and daily energy-throughput. The cost of battery degradation as a function of these control variables is then estimated assuming two possible maintenance strategies: replacement, where the entire battery system is replaced if cell reach an end-of-life capacity threshold; and augmentation, which establishes a fund to pay for continual purchase of new batteries to maintain the initial energy capacity of the system. These two strategies offer conservative (for replacement) and optimistic (for augmentation) bounds for total system cost. The degradation cost incurred by these strategies is then used to control battery dispatch decisions, operating the battery in a degradation-aware manner that maximizes battery lifetime while also providing energy when favorable. Because the mixed-integer linear program has perfect foresight of future energy needs, batteries with degradation costs are always operated using 'just-in-time' charging, which is unrealistic, as no energy is left in the storage system to perform other energy services or to serve as emergency back-up power. To combat this, an inequality constraint on the average annual state-of-charge is imposed, and the sensitivity of system cost to average stored energy, e.g., the cost of system resiliency, can be quantified. Analysis of results has several conclusions, for instance, oversizing of battery storage systems is not a cost burden when battery storage is an optimal solution, as any additional battery capacity can simply be utilized to avoid costs of purchasing energy from a utility.

battery↗
DOE OSTI2023

Crystalline versus Glassy Nature of Iron Phosphate Waste Forms Subjected to Different Slow Cooling Curves

This report provides experimental details and associated results on the elemental distributions (compositions), crystalline/amorphous phase distributions, and microstructures for iron phosphate reference materials (DPF5-336) made with different cooling curves and starting from different temperatures (i.e., 1050°C and 1200°C). The primary goal of this work was to evaluate the properties of the DPF5- 336 reference material after it was melted and cooled at different rates to simulate the cooling profile of different types of canisters. Crystal fractions across the SCC#2, SCC#3, and SCC#5 samples were all similar ranging in crystal content of 35.66–41.14 mass% with amorphous fractions being the balance (64.34–58.86 mass%, respectively). This shows that the heat treatment profile did not seems to greatly affect either the total crystal content or the phase distributions. The quenched sample was almost completely amorphous (99.55 mass%) with very small peaks identified as Li 3 Fe 2 (PO 4 ) 3 whereas the SCC-treated materials showed peaks for what appear to be ten separate phases present in various concentrations. Another goal of these experiments was to see how the phase distribution affected chemical durability of these waste forms, but that information is being collected at Argonne National Laboratory and will be published in a separate report

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Tandem Electrocatalytic CO 2 Reduction with Efficient Intermediate Conversion over Pyramid-Textured Cu–Ag Catalysts

If combined with renewably generated electricity, electrochemical CO 2 reduction (E-CO 2 R) could be used as a sustainable source of chemicals and fuels. Tandem catalysis approaches are attractive for providing the product selectivity, which would be required for commercial applications. Here, we demonstrate a two-step tandem electrocatalytic E-CO 2 R with efficient conversion of the intermediate species. The catalyst scaffold is Si(100), which is etched to form a textured surface consisting of micron-sized pyramid structures with the {111} facets. Two metals are used in the electrocatalytic cascade: Ag is employed to perform a two-electron reduction of CO 2 to the intermediate CO, and Cu performs conversion to more reduced products. Using high-angle physical vapor deposition, we form separated, micron-scale areas of the two electrocatalysts on opposite sides of the pyramids, with their relative surface coverages being tunable with the deposition angle. Compared to the textured scaffolds with blanket Ag and Cu used as controls, bimetallic pyramid tandem catalysts have higher current densities and much lower faradic efficiencies (FE) for CO. These effects are due to efficient conversion of the CO formed on Ag to more reduced products on Cu. Methane is the main product to be enhanced by the cascade pathway: a bimetallic catalyst with approximately equal coverages of Ag and Cu produces methane with a FE of 62% at -1.1 V RHE , corresponding to a partial current density of 12.7 mA cm -2 . We estimate an intermediate conversion yield for the CO intermediate of 80-90%, which is close to the mass-transport limited value predicted by reaction-diffusion simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Technology Strategy Assessment: Findings from Storage Innovations 2030 Supercapacitors

Electrochemical capacitors, which are commercially called supercapacitors or ultracapacitors, are a family of energy storage devices with remarkably high specific power compared with other electrochemical storage devices. Supercapacitors do not require a solid dielectric layer between the two electrodes, instead they store energy by accumulating electric charge on porous electrodes filled with an electrolyte solution and separated by an insulating porous membrane. Supercapacitors offer large specific capacitance and high power output. They can be charged and discharged very quickly, offer excellent cycle life and long operational life, and operate over a broad temperature range. The major drawbacks of supercapacitors are low energy density and a high self-discharge rate. For example, a supercapacitor passively discharges from 100% to 50% in a month compared with only 5% for a lithium-ion battery [1]. The high capital cost and low energy density of supercapacitors make the unit cost of energy stored ($/kWh) more expensive than alternatives such as batteries. Their attributes make them attractive for uses in which frequent small charges/discharges are required (e.g., ensuring power quality or providing frequency regulation). Their attributes and cost make them less attractive for long-duration energy storage, which favors technologies with low self-discharge that cost less per unit of energy stored.

25 ENERGY STORAGE↗
DOE OSTI2023

Review of Carbon Support Coordination Environments for Single Metal Atom Electrocatalysts (SACS)

This topical review focuses on the distinct role of carbon support coordination environment of single-atom catalysts (SACs) for electrocatalysis. The article begins with an overview of atomic coordination configurations in SACs, including a discussion of the advanced characterization techniques and simulation used for understanding the active sites. A summary of key electrocatalysis applications is then provided. These processes are oxygen reduction reaction (ORR), oxygen evolution reaction (OER), hydrogen evolution reaction (HER), nitrogen reduction reaction (NRR), and carbon dioxide reduction reaction (CO 2 RR). The review then shifts to modulation of the metal atom-carbon coordination environments, focusing on nitrogen and other non-metal coordination through modulation at the first coordination shell and modulation in the second and higher coordination shells. Representative case studies are provided, starting with the classic four-nitrogen-coordinated single metal atom (M$-$N 4 ) based SACs. Bimetallic coordination models including homo-paired and hetero-paired active sites are also discussed, being categorized as emerging approaches. The theme of the discussions is the correlation between synthesis methods for selective doping, the carbon structure–electron configuration changes associated with the doping, the analytical techniques used to ascertain these changes, and the resultant electrocatalysis performance. In conclusion, critical unanswered questions as well as promising underexplored research directions are identified.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.

Artificial Intelligence (AI)↗
DOE OSTI2022

Enhanced physics-constrained deep neural networks for modeling vanadium redox flow battery

Numerical simulation has become indispensable in advancing cost-effective process optimization and control of flow batteries. We propose an enhanced version of the physics-constrained deep neural network (PCDNN) approach to provide high-accuracy voltage predictions in the vanadium redox flow batteries (VRFBs). The purpose of the PCDNN approach is to enforce the physics-based zero-dimensional (0D) VRFB model in a neural network to assure model generalization for various battery operation conditions. However, limited by the simplifications of the 0D model, the PCDNN cannot capture sharp voltage changes in the extreme SOC regions. To improve the accuracy of voltage prediction at extreme ranges, we introduce a second (enhanced) DNN to mitigate the prediction errors carried from the 0D model itself and call the resulting approach enhanced PCDNN (ePCDNN). By comparing with experimental data, we demonstrate that the ePCDNN approach can accurately capture the voltage response throughout the charge–discharge cycle, including the tail region of the voltage discharge curve. The loss function for training the ePCDNN is designed to be flexible by adjusting the weights of the physics-constrained DNN and the enhanced DNN. In conclusion, this allows the ePCDNN framework to be transferable to battery systems with variable physical model fidelity.

25 ENERGY STORAGE↗
DOE OSTI2022

Electrochemical Hydrogenation of CO on Cu(100): Insights from Accurate Multiconfigurational Wavefunction Methods

Copper (Cu) remains the most efficacious electrocatalyst for electrochemical CO 2 reduction (CO 2 R). Its activity and selectivity are highly facet-dependent. We recently examined the commonly proposed rate-limiting CO hydrogenation step on Cu(111) via embedded correlated wavefunction (ECW) theory and demonstrated that only this higher-level theory yields predictions consistent with potential-dependent experimental kinetics. Here, to understand the differing activities of Cu(111) and Cu(100) in catalyzing CO 2 R, we explore CO hydrogenation on Cu(100) using ECW theory. We predict that the preferred pathway involves the reduction of adsorbed CO (*CO) to *COH via proton-coupled electron transfer (PCET) at working potentials, although *CHO also may form with a kinetically accessible but higher barrier. In contrast, our earlier work on Cu(111) concluded that *COH and *CHO formation via PCET are equally feasible. Furthermore, this work illustrates one possible origin of the facet dependence of CO 2 R mechanisms and products on Cu electrodes and sheds light on how the selectivity of CO 2 R electrocatalysts can be controlled by the surface morphology.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Modulating Solvation Structure in Concentrated Aqueous Organic Redox Flow Battery Electrolyte for Solubility and Transport Enhancement via Polycomplex Ion

Aqueous organic redox flow batteries hold great promise as a technology for creating economical grid energy storage using sustainable materials. Nonetheless, the solubility limit presents a universal barrier for all redox-active organic molecules. In this paper, a new approach is proposed to surpass the solubility limit by manipulating the solvation structure with polycomplex ion additives (PIA). Using poly(3,4-ethylenedioxythiophene) polystyrenesulfonate colloids as one example, its role in dismantling the rigid supramolecular clusters within the highly concentrated 7,8-dihydroxyphenazine-2-sulfonic acid electrolyte is investigated. 1 H and 23 Na NMR spectra and molecular dynamics simulation studies demonstrate that the bipolar structure of the PIA effectively disrupts the aggregations of DHPS and Na + ion in the highly concentrated anolyte, thus rendering a more flexible solvation structure and less restrictive ion transport, leading to substantially improved battery performance of an AORFB cell. The anolyte with PIA achieved 1.6 M and 74.3 Ah L –1 anolyte energy capacity.

25 ENERGY STORAGE↗
DOE OSTI2025

X-ray Micro-Computed Tomography for Structural Analysis of All-Solid-State Battery at Pouch Cell Level

Characterizing the microstructure of all-solid-state batteries (ASSBs) during fabrication and operation is vital for their advancement, particularly as scaling to pouch cell levels introduces challenges in probing large-scale microstructural evolution. This work highlights the potential of synchrotron X-ray micro-computed tomography (sXCT) as a nondestructive, rapid (<30 min), and high-resolution technique for visualizing and quantifying key microstructural features, including overhang, porosity, contact loss, active surface area, and tortuosity, in all-solid-state pouch cells. The large field of view (up to millimeters) of sXCT enables detailed analysis at an industry-relevant scale, bridging the gap between laboratory research and commercial applications. Furthermore, integrating realistic sXCT-derived 3D models into multiphysics simulations could provide insights into chemo-mechanical degradation, particularly at the edges of the pouch cells, offering a pathway for designing robust, high-performance ASSBs. This perspective establishes sXCT as an indispensable tool for advancing both the understanding and the engineering of next-generation energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2023

Origin of Rapid Delithiation In Secondary Particles Of LiNi 0.8 Co 0.15 Al 0.05 O 2 and LiNi y Mn z Co 1− y − z O 2 Cathodes

Abstract Most research on the electrochemical dynamics in materials for high‐energy Li‐ion batteries has focused on the global behavior of the electrode. This approach is susceptible to misleading analyses resulting from idiosyncratic kinetic conditions, such as surface impurities inducing an apparent two‐phase transformation within LiNi 0.8 Co 0.15 Al 0.05 O 2 . Here, nano‐focused X‐ray probes are used to measure delithiation operando at the scale of secondary particle agglomerates in layered cathode materials during charge. After an initial latent phase, individual secondary particles undergo rapid, stochastic, and largely uniform delithiation, which is in contrast with the gradual increase in cell potential. This behavior reproduces across several layered oxides. Operando X‐ray microdiffraction (‐XRD) leverages the relationship between Li content and lattice parameter to further reveal that rate acceleration occurs between Li‐site fraction ( x Li ) ≈0.9 and ≈0.5 for LiNi 0.8 Co 0.15 Al 0.05 O 2 . Physics‐based modeling shows that, to reproduce the experimental results, the exchange current density ( i 0 ) must depend on x Li , and that i 0 should increase rapidly over three orders of magnitude at the transition point. The specifics and implications of this jump in i 0 are crucial to understanding the charge‐storage reaction of Li‐ion battery cathodes.

25 ENERGY STORAGE↗
DOE OSTI2025

Understanding (La,Sr)(Co,Fe)O$_{3-δ}$ Phase Instability within SOECs Using a Combined Experimental and Atomistic Modeling Approach

Understanding the onset of degradation in the air electrode within solid oxide electrolysis cells (SOECs), and the subsequent impact on cell performance, is a critical step in mitigating the performance losses and stability issues of SOECs. In an effort to identify early onset degradation phenomena, SOECs were characterized as fabricated and after testing potentiostatically at 1.3 V for 1000 h at 750 °C. SOEC air electrodes composed of a 1:1 composite of La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3–δ (6428-LSCF) and Gd 0.1 Ce 0.9 O 1.95 (GDC) were studied using synchrotron X-ray diffraction (XRD), scanning transmission electron microscopy coupled with energy dispersive X-ray spectroscopy (STEM-EDS), and X-ray absorption near-edge spectroscopy (XANES) to evaluate the changes in the air electrode structurally and chemically. These techniques show the migration of Sr species from the air electrode through pores in the GDC barrier layer, progressing to the electrolyte boundary, where it accumulates and reacts with (Zr 0.84 Y 0.16 )O 2–δ (YSZ) to form SrZrO 3 . Microscopy results are paired with atomistic simulations to better understand the relationship between the thermodynamic instability of 6428-LSCF and cell fabrication/testing conditions. First-principles calculations reveal that LSCF-6428 is not stable during cell manufacturing and testing conditions, which supports the experimental identification of secondary phases in both as-fabricated and tested cells. Together, these results demonstrate that the challenging environments encountered by SOECs during cell manufacturing and operation lead to instabilities of the target 6428-LSCF anode material and underscore the need for more durable, high-performing SOEC components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Microstructure‐Dependent Sodium Storage Mechanisms in Hard Carbon Anodes

Sustainable energy storage is essential to support the transition to renewables and meet the increasing demand for energy. Sodium‐ion batteries (NIBs) are attractive for grid‐scale energy storage due to the abundance and low cost of sodium, sustainability of other battery components, and electrochemical performance. Hard carbon (HC) is a leading anode material for NIBs, but its complex microstructure complicates the understanding of sodium storage mechanisms. Using X‐ray total scattering and density functional theory calculations, this study clarifies how HC's microstructural variations influence sodium storage across the slope (high potential) and plateau (low potential) regions of the potential capacity curve. In the slope region, sodium initially adsorbs at high‐binding energy defect sites and subsequently intercalates between graphene layers, adsorbing at low‐binding energy defect sites, correlating with different slopes observed during initial sodiation. Initial irreversibility arises from sodium trapping at surface defects and solid electrolyte interface formation. In the plateau region, sodium simultaneously intercalates and fills pores, influenced by pore size, interlayer spacing, and defect concentration. HCs with larger pore sizes form larger sodium clusters. In conclusion, the proposed mechanism underscores the role of microstructure engineering in enhancing HC performance and advancing NIBs for grid‐scale energy storage.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Semiconducting Zn x Mo 3 S 13 -GO Chalcocarbogel: A High-Capacity and Stable Sulfur-Equivalent Conversion-Based Electrode for Lithium-Ion Batteries

Lithium–sulfur batteries with a sulfur electrode offer a theoretical capacity of ∼1672 mAh g –1 , but rapid capacity loss mainly constrains their practical application. This work introduces a semiconducting and amorphous Zn x Mo 3 S 13 -GO (x = 0.5) chalcocarbogel sulfur-equivalent electrode with superior capacity and stability for lithium-ion batteries (LIBs). The Zn x Mo 3 S 13 -GO is synthesized in solution under ambient conditions, and its local structure contains S–S, M-Q (M = Mo, Zn; Q = S, O), C–S, and Mo–Mo bonding motifs with Mo coordination environment closely related to Mo 3 S 13 anions, as determined by X-ray photoelectron spectroscopy, synchrotron X-ray scattering, X-ray absorption spectroscopy, and ab initio molecular dynamics simulations. The Li/Zn x Mo 3 S 13 -GO cell offers an initial discharge capacity of 1019 mAh g –1 at a rate of C/3. After the activation cycles, the Li/Zn x Mo 3 S 13 -GO cell demonstrates good cycling stability, retaining a discharge capacity of 519.4 mAh g –1 after 250 cycles with ∼99.98% Coulombic efficiency and excellent rate capabilities. Moreover, it provides an initial discharge capacity of ∼574 mAh g –1 and maintains a retention capacity of 279 mAh g –1 at 1C after 625 cycles. The Lewis acidic Zn 2+ ion enhances the Lewis basic polysulfide anchoring ability and reduces the dissolution of polysulfides produced during the redox process through Zn–S covalent interaction, while the semiconducting and amorphous structure of the chalcocarbogel increases the electrical and ionic conductivity. Furthermore, this work highlights chalcocarbogels’ potential for developing high-capacity and stable electrodes for LIBs.

25 ENERGY STORAGE↗