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NASA NTRSDate not supplied

Comparison of Pre- and Post-Flight Estimations of Pitch Damping Coefficients for Unguided Entry Vehicles

Introduction: Pre-flight predictions of pitch damping coefficient (𝐶!!+𝐶!"̇)curves are used in entry simulations to determine flight readiness and if any dynamic remediation strategies are required. Accurate characterization of these pitch damping coefficient curves is crucial for mission success. Historically, pre-flight estimations of these curves are derived experimentally either via ballistic range testing or with 1-degree-of-freedom (DOF) free-or forced-oscillation wind tunnel testing. Methodology:With post-flight best-estimated trajectories, a fitting procedure as described in Karlgaard, et. al. [1] is used to compare pre-and post-flight pitch damping coefficients. This technique relies on an assumed analytical form of the trajectory, a limited 3-DOF representation described in Schoenenbergerand Queen [2], which results in anEuler-Cauchy solution form.This solution assumes constant density,thus limited amplitude multi-peak windows of the trajectory are considered to populate the pitch damping-amplitudes pace. Fig. 1 shows preliminary estimations of the pitch damping coefficients estimated using the post-flight best estimated trajectoryfor MER B, using a3-amplitude-peak window. Important to note is that the Euler-Cauchy solution also assumes planar motion, thus coning or 𝛽contribution is not included. Further,the estimated post-flight pitch damping approximations and the pre-flight predictions shown are effective representations of pitch damping, or the integrated effect of the pitch damping coefficient over one pitch cycle at the corresponding cycle’s peak amplitude. Effective pitch damping coefficient curves provide more intuitive insights about where the vehicle is stable and permits readily processed comparisons between data-sets. It is important to note that most pitch damping curves, such as those reported in aerodatabases and utilized in flight mechanics trajectory simulations, are represented in instantaneous angle-of-attack space distinct from what is presented in Fig 1. The extracted post-flight pitch damping coefficient points show a wide range of values across a narrow band of amplitudes (Fig.1a), albeit centered on the published pre-flight approximation. This also applies to the prediction as a function of Mach in Fig1b, where the post-flight scatter points are centered around the pre-flight predictions, but the pre-flight predictions notably lack data aboveMach 5.Further tuning of the technique, such as changing the number of peaks considered in each stencil, resolving density in higher resolution, and employing more accurate fitting procedures (beyond scipy.curve_fit()), will be performed. PosterFocus:This study will apply this reconstruction method to the as-flown trajectories for the following unguided entry vehicles: MER A, MER B, IRVE3, Phoenix, Insight, Pathfinder, and SIAD. The pitch damping coefficient will be derived from these trajectories and compared with the pre-flight predictions. Comparing across different missions, entry environments, and vehicle geometries can inform where our pre-flight testing methodologies accurately capture the flight dynamics. Results will provide valuable insight into the accuracy of pre-flight predicted pitch damping curves. Beyond that, this method can shed light on how accurate these curves need to be, which can inform uncertainty ranges applied to pre-flight curves for other missions.

pitch damping coefficient↗
DOE OSTI2025

Correlating processing variables to material properties in recycled polypropylene: A data‐driven approach

Abstract Polypropylene (PP) is one of the most widely used plastics, yet its recycling remains limited, with less than 1% of solid waste PP being reprocessed. Mechanical recycling through extrusion is the most practical method, but inconsistent reprocessing conditions introduce variability in material properties. While temperature, screw speed, and residence time influence the thermomechanical stress applied during reprocessing, there are no standardized guidelines for optimizing these parameters. This study examines how these factors shape the properties of recycled PP, using conditions designed to mimic post‐industrial recycled (PIR) scrap. Residence time was measured using colorimetric tracking and correlated with molecular weight, viscosity, and mechanical properties over multiple extrusion cycles. Data‐driven modeling, including response surface methodology, support vector machines, and artificial neural networks, identified processing temperature as the dominant factor in material degradation, followed by residence time. Mechanical properties remained stable, while viscosity decreased predictably with increasing residence time. By linking reprocessing conditions to property evolution, this study provides a method to optimize processing parameters and reduce variability in recycled PP. These findings help manufacturers improve process control, making recycled PP more predictable for reuse in manufacturing. Highlights Study of PIR‐quality PP without additives or compatibilizers. Residence time analysis shows processing temperature drives PP property changes. Mark‐Houwink enables quick molecular weight checks for quality control. Models predict mechanical and rheological shifts in reprocessing. Optimized processing parameters minimize property degradation in recycling.

Estela‐García, John E. [Polymer Engineering Center↗
DOE OSTI2026

Leveraging generative artificial intelligence to bridge domain gaps in wind turbine research

A central challenge in wind turbine health monitoring is the scarcity of real-world data due to limited instrumentation, leading researchers to rely on simulation models that often suffer from reduced fidelity. However, even within simulation environments, discrepancies arise because of modeling assumptions, and configuration fidelities, creating domain gaps that limit the transferability of learned representations. Here, to investigate domain translation under controlled conditions, this project explores the use of generative artificial intelligence, specifically cycle-consistent generative adversarial networks (CGANs), to bridge the gap between OpenFAST simulation models representing 1.5 MW and 5 MW wind turbines. A physics-informed CGAN architecture is introduced, where a simplified turbine tower dynamics model is incorporated into the training loss to ensure physically consistent outputs. Quantitative results showed moderate to high agreement in frequency-domain features. Incorporating the physics-informed loss function improved the R 2 values by 30%, reduced the RMSE from 1.39 to 1.1 m/s 2 , and reduced training time by 82%. Furthermore, under increased turbulence intensity (IEC Category A), the RMSE remained stable at approximately 1.1 m/s 2 . While the present study is entirely simulation-based, it establishes a pipeline for evaluating physics-informed generative domain translation, which may serve as a foundation for future simulation-to-reality validation studies.

17 WIND ENERGY↗
DOE OSTI2023

Computationally Accelerated Discovery and Experimental Demonstration of High-Performance Materials for Advanced Solar Thermochemical Hydrogen Production

This project achieved its overarching goal of accelerating the discovery and validation of solar thermochemical hydrogen (STCH) materials through a tightly integrated approach that combined high-throughput computational screening, advanced machine learning (ML), and experimental testing. Guided by the objectives outlined in the Statement of Project Objectives (SOPO), our work fulfilled all major milestones across four technical tasks and delivered scientific breakthroughs and practical tools that significantly exceeded the original scope of the project. We began by addressing the challenge of predicting material phase stability through machine learning. A novel Python module was developed to generate thousands of meaningful features from composition, structure, and electronic properties, enabling rapid and reproducible ML model development. Using these tools, we trained a model to predict temperature-dependent Gibbs energies (G(T)) for inorganic crystalline materials with near-chemical accuracy—roughly 40 meV/atom—marking the first such descriptor of its kind. We also introduced a new machine-learned tolerance factor, τ, that accurately predicted perovskite formability with over 90% success, outperforming traditional heuristic models, such as the Goldschmidt tolerance factor. These capabilities allowed for rapid and accurate predictions of phase stability across a vast oxide composition space, setting the stage for high-throughput thermodynamic screening. Building on this foundation, we conducted an extensive computational screening of candidate STCH oxide materials. Over 1.1 million perovskite compositions were evaluated using the τ descriptor, leading to the identification of more than 27,000 predicted stable structures. Using density functional theory (DFT), we refined over 68,000 multinary perovskite structures and computed oxygen vacancy formation energies for over 1,300 ternary and double perovskites. These calculations enabled us to isolate compounds with redox behavior consistent with STCH requirements and resulted in a public dataset now hosted on the Materials Project. Recognizing that thermodynamic screening alone is insufficient, we addressed kinetic limitations by developing a suite of tools to estimate transition state (TS) energies for key redox reactions. We implemented a novel bounding approach that provides lower and upper estimates of TS energies with dramatically reduced computational cost, requiring less than 10% of the CPU time of a full nudged elastic band (NEB) calculation while maintaining high accuracy. This enabled rapid evaluation of over 200 reaction pathways across 90 materials. To further accelerate screening, we developed a SISSO-based ML model to predict diffusion barriers with a 96.7% success rate in classifying fast vs. slow materials, supporting a robust, data-driven framework for assessing redox kinetics. Experimental validation was critical to confirming the predictive power of our models. We synthesized and tested a wide array of candidate materials, including Mn-doped hercynite and several Gd- and La-based perovskites. Notably, Sr 0.4 Gd 0.6 Mn 0.6 Al 0.4 O 3 (SGMA) and Gd 0.5 La 0.5 Co 0.5 Fe 0.5 O 3 (GLCF) emerged as leading STCH materials, exhibiting robust redox cycling and high hydrogen yields exceeding 150 µmol H 2 /g per cycle. These materials also retained over 50% of their hydrogen productivity under high-conversion conditions (H 2 O:H 2 = 1333:1), demonstrating strong thermodynamic favorability and promising performance under industrially relevant scenarios. Additional candidates, such as La 2 MnNiO 6 (L2MN), were found to produce even higher yields than ceria under standard STCH conditions. Our collaborators at Sandia National Laboratories confirmed these findings using high-temperature X-ray diffraction and thermogravimetric analysis, observing stable phase evolution and reversible redox activity. In several respects, the project went beyond the goals initially outlined in the SOPO. We published 17 peer-reviewed articles, including a large dataset of over 66,000 theoretical perovskites and a new structure prediction method (SPuDS-DFT) that accurately identifies ground-state structures at a fraction of the cost of traditional DFT. We demonstrated that our machine-learned G(T) model offers accuracy rivaling quasiharmonic calculations while being orders of magnitude faster. In partnership with the Materials Project, we made our datasets openly available, providing a powerful new resource for the broader materials science community. The combined computational and experimental advances of this project represent a significant advance in STCH materials discovery. By creating a robust, generalizable, and open workflow for thermodynamic and kinetic screening, and validating key findings through synthesis and reactor testing, we have provided a practical and scalable pathway for the rapid identification of new redox-active materials. The tools, data, and materials developed under this project are already supporting ongoing research and have laid the groundwork for the next generation of solar fuel technologies.

08 HYDROGEN↗
DOE OSTI2022

Sulfur Geochemistry Destabilizes Population Oscillations of Wild Rice ( Zizania palustris )

Abstract Elevated inputs of sulfate to freshwater systems can increase sulfide concentrations in anoxic soils and subsequently destabilize aquatic plant populations, but the interactions between sulfate, other geochemical cycles, and interannual plant population cycles are poorly understood. Increased sulfate loading increases mineralization of nitrogen from litter, but the sulfide produced during this process can limit nitrogen uptake by plants. In some cases, iron may mitigate sulfide's impacts on plants by precipitating iron sulfide. We examined the interannual effects of sulfate loading on mesocosm populations of wild rice, an emergent aquatic plant that undergoes population oscillations and is sensitive to sulfide. Using experimental mesocosms with self‐perpetuating populations, we investigated how population dynamics respond to manipulations of surface water sulfate (10 mg L −1 or 300 mg L −1 ), sediment iron (4.3 mg g −1 or 10.9 mg g −1 dry weight), and shoot litter (present or removed). Populations exposed to constant 10 mg L −1 sulfate concentrations had stable biomass oscillations of approximately 3‐year periods, consistent with previous studies that demonstrated litter‐driven oscillations in nitrogen availability. Populations exposed to 300 mg L −1 sulfate concentrations produced fewer and smaller seeds and declined to extinction in 6 years or less. We did not find a strong effect of iron loading or litter removal on wild rice biomass or seed production. Our observations show the potential of elevated surface water sulfate to rapidly destabilize wild rice populations under varying iron and organic carbon concentrations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Steering the methanol steam reforming reactivity of intermetallic Cu–In compounds by redox activation: stability vs . formation of an intermetallic compound–oxide interface

To compare the inherent methanol steam reforming properties of intermetallic compounds and a corresponding intermetallic compound–oxide interface, we selected the Cu–In system as a model to correlate the stability limits, self-activation and redox activation properties with the catalytic performance. Three distinct intermetallic Cu–In compounds – Cu 7 In 3 , Cu 2 In and Cu 11 In 9 – were studied both in an untreated and redox-activated state resulting from alternating oxidation–reduction cycles. The stability of all studied intermetallic compounds during methanol steam reforming (MSR) operation is essentially independent of the initial stoichiometry and all accordingly resist substantial structural changes. The inherent activity under batch MSR conditions is highest for Cu 2 In, corroborating the results of a Cu 2 In/In 2 O 3 sample accessed through reactive metal–support interaction. Under flow MSR operation, Cu 7 In 3 displays considerable deactivation, while Cu 2 In and Cu 11 In 9 feature stable performance at simultaneously high CO 2 selectivity. Here, the missing significant self-activation is most evident in the operando thermogravimetric experiments, where no oxidation is detected for any of the intermetallic compounds. In situ X-ray diffraction allowed us to monitor the partial decomposition and redox activation of the Cu–In intermetallic compounds into Cu 0.9 In 0.1 /In 2 O 3 (from Cu 7 In 3 ), Cu 7 In 3 /In 2 O 3 (from Cu 2 In) and Cu 7 In 3 /Cu 0.9 In 0.1 /In 2 O 3 (from Cu 11 In 9 ) interfaces with superior MSR performance compared to the untreated samples. Although the catalytic profiles appear surprisingly similar, the latter interface with the highest indium content exhibits the least deactivation, which we explain by formation of stabilizing In 2 O 3 patches under MSR conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A Comparative Analysis of Lithium-Ion Battery Chemistries for Cold-Climate Maritime Applications

Energy storage, primarily in the form of electrochemical batteries, is critical for enabling integration of marine energy (e.g., power from waves and currents) with end-use applications at sea due to the periodicity of the resources and requirement of consistent, smooth power delivery. Powering high-latitude coastal or ocean-based observing systems has been identified as a high value-proposition use case, exemplifying the concept of Powering the Blue Economy. An existing power system implementation for such a platform uses solar panels coupled to rechargeable lithium-ion batteries, augmented by a non-rechargeable backup bank used to power heaters in winter months. As wave energy is a potential resource for powering this and similar use cases and is strongest when solar power is most limited, it was hypothesized that integration of wave power would alleviate some of the challenges in cold climates related to energy storage. In this work, we investigate the use case scenario in simulation and perform a comparative test of commercially-available lithium-ion battery chemistry formulations to determine the most appropriate choice for the application. The experiment compared the most commonly-used lithium-based battery types (NCM, NCA, and LFP) in laboratory conditions emulating a battery enclosure thermally coupled to freezing seawater using an industrial battery performance tester in PNNL's arctic simulation lab. Battery strings were repeatedly cycled (i.e., charged, discharged, rested) and their usable capacity was measured. Both NCM and NCA strings exhibited degradation upon cycling, while the LFP string maintained stable operation through over 700 complete cycles. Though lower in baseline capacity, LFP are recommended for this and similar low-temperature applications with access to high levels of bulk charging current (e.g., from high-energy wave events) and their use may reduce the cost and complexity of battery conditioning and protection apparatus.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Regenerative Solid Interfaces Enhance High-Performance All- Solid-State Lithium Batteries

All-solid-state Lithium batteries (ASSLBs) have gained widespread attention in recent years. However, their performance is still largely limited by the poor transport properties and stability of the solid-solid interfaces (SSIs). In this study, we report a new strategy for creating a reversible interface with good conductivity and self-adaptive mechanical properties for high-performance all-solid-state lithium batteries (ASSLBs). The interface is formed in situ from nanosized lithium iodide (LiI), a component of the solid-state electrolyte (SSE), which flows plastically along the SSE interfaces under high pressure due to its high ductility. Moreover, LiI segregates and enriches along the Li/SSE interfaces, reversibly enhancing Li plating/stripping due to its lithophilicity and high ionic conductivity. This dynamic LiI interface enables stable operation of metallic Li anode (>1000 h) at high current densities and elevated temperatures, and long-term cycling of all-solid-state Li-sulfur batteries (>250 cycles) with high sulfur utilization rate (>1400 mAh g-1) and areal capacity (>2 mAh cm-2). This study reveals a unique role of LiI in building robust SSIs and provides new insights into the design of novel SSEs and interfaces for high-performance ASSLBs.

Yu, Zhaoxin↗
DOE OSTI2021

Quantification of Variation in Combustion Instability Amplitude in a Multi-Nozzle Can Combustor

In this work, we quantify the level of variation in unstable combustion oscillation amplitudes and identify the source of this variation in a multi-nozzle can combustor. At conditions where pollutant emissions are reduced, lean-premixed combustors can undergo thermoacoustic instability when pressure and heat release rate oscillations couple. A commonly used method for suppressing instability is fuel staging, which is a method where fuel is unevenly distributed between nozzles in a multi-nozzle combustor. Our work follows others who have characterized the effect of fuel staging on combustion instability and the mechanisms by which it works during both steady-state and transient operation. One of the outcomes from our previous work was that certain instability operating points display a high level of pressure oscillation amplitude variation. Instead of oscillating at a constant limit-cycle amplitude, the pressure oscillation amplitude varies significantly in time. In this work, we use the concept of permutation entropy to quantify the level of variation in the pressure fluctuation amplitude. We correlate the level of variation with a number of state variables over a range of operating conditions, 291 test cases in all. These state variables include mixture equivalence ratio; transient timescale, amplitude, and direction; hardware temperatures; gas temperatures; and thermoacoustic damping and growth rates. Significant pressure oscillation amplitude variation occurs when the thermoacoustic damping rate is low. The damping and growth rates can be low for a number of reasons, but they are highly correlated with the metal temperature of the centerbody, where the flames are anchored; lower temperatures result in lower damping rates during stable operation and lower growth rates during unstable operation. These results show the importance of the thermal boundary condition on the time-dependent behavior of the thermoacoustic instability.

Westfall, Seth↗
NASA NTRS1994

Influence of ocean surface conditions on atmospheric vertical thermodynamic structure and deep convection

The authors analyze the influence of Sea Surface Temperature (SST) and surface wind divergence on atmospheric thermodynamic structure and the resulting effects on the occurrence of deep convection using National Meteorological Center radiosonde data and International Satellite Cloud Climatology Program data for July 1983-July 1985. The onset of deep convection requires not only the existence of positive convective available potential energy (CAPE), but also an unstable planetary boundary layer (PBL). A stable PBL is observed to suppress deep convection even when CAPE is positive. Variations of SST have a major effect on CAPE, but surface wind divergence can also affect deep convection by changing the lapse rate in the lower troposphere and humidity in the PBL. Specifically, when SST is greater than or equal to 28 C, CAPE is always positive, and surface wind divergence does not qualitatively change the buoyancy profile above the PBL. Strong surface wind divergence, however, stabilizes the PBL so as to suppress the initiation of deep convection. In warm SST regions, CAPE is greater than 0 regardless of assumptions about condensate loading, although the pseudoadiabatic limit is more consistent with the observed deep convection than the reversible moist-adiabatic limit under these circumstances. When SST is less than 27 C, CAPE is usually negative and inhibits convection, but strong surface wind convergence can destabilize the inversion layer and moisten the PBL enough to make the atmosphere neutrally stable in the mean. As a result, deep convection is generally enhanced either when SST is greater than or equal to 28 C in the absence of strong surface wind divergence or when strong surface wind convergence occurs even if SST is less than 27 C. The anomalous suppression of deep convection in the warm area of the equatorial west Pacific lying between the intertropical convergence zone (ITCZ) and south Pacific convergence zone (SPCZ) is probably caused by dryness in the PBL and an inversion in that area. The seasonal cycles of deep convection and surface wind divergence are in phase with the maximum solar radiation and lead SST for one to three months in the central Pacific. The change of PBL relative humidity plays a critical role in the changeover to convective instability in this case. The seasonal change of deep convection and associated clouds seems not to have important effects on the seasonal change of local SST in the central Pacific.

Fu, Rong↗
DOE OSTI2024

Ferrocene Bis(Sulfonate) Salt as Redoxmer for Fast and Steady Redox Flow Desalination

Desalination is considered a promising solution to alleviate water shortages, yet current methods are often restricted, due to challenges like high energy consumption, significant cost, or limited desalination capacity. In this study, we present a novel approach of redox flow desalination (RFD) utilizing the highly aqueous-soluble and reversible redox-active compound, potassium 1,1'-bis(sulfonate) ferrocene (1,1'-FcDS). This water-soluble organic compound yielded stable and rapid desalination, sustaining extended operation without notable decay and achieving an impressive desalination rate of up to 457.5 mmol·h -1 ·m -2 and energy consumption as low as 40.2 kJ·mol NaCl -1 . Specifically, the RFD device effectively desalinated a 50 mM NaCl solution to potable standards within 6000 s using 1,1'-FcDS. It maintained an average energy consumption of 178.16 kJ·mol NaCl -1 and exhibited negligible deterioration in desalination rate, energy efficiency, and charge efficiency throughout a rigorous 12,000 s cycling test. Furthermore, the versatility of this method was demonstrated by effectively treating saline water with varying initial concentrations from 10 mM to 50 mM, showcasing its potential across a broad spectrum of applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Molten Salt Electrolytes: Computational Analysis of Transport, Electrochemical Properties and Designing New Mixtures

Electric aircraft propulsion has gained a traction over the last decade due to possible high-energy density electrochemistries with reasonable cycle life and identification of non-flammable chemistries that can guarantee much better safety. Commercial Li-ion batteries cannot reach such high capacities because of weight limitations that arise from the widely used intercalation electrodes. Also, use of organic electrolytes make them highly susceptible to fire on exposure to air and humidity. Currently, use of Lithium metal anode along with conversion electrochemistries such as Li-O2 and Li-S are being pursued to achieve such high energy densities. Safer inorganic solid-state electrolytes, recently discovered Water-in-Salt electrolytes, molten salt electrolytes are some of the alternatives being pursued for a safer/non-flammable battery. Of these safer alternatives, molten-salt electrolytes offer some attractive properties: liquid at operating temperatures resulting in better electrode-wetting, stable interface with Li-metal anodes and good ionic conductivity; their only drawback being high operating temperatures. In this talk, we will discuss some of the computational studies, driven via atomistic simulations, of the properties of molten-salt electrolytes including transport mechanism and interface stability. We will also discuss predicting electrochemical properties of these high-temperature electrolytes. Further, we will discuss a thermodynamic approach to predicting new molten-salt eutectics with lower melting points.

Molten Salt Electrolytes↗
DOE OSTI2026

Controlled lithium stripping enables a stable interface for long-cycling anode-free solid-state batteries

Anode-free solid-state batteries (AFSSBs) are a promising route toward achieving high energy density. In these cells, the anode contains no pre-stored lithium (Li). Instead, the entire Li inventory originates from the cathode and is freshly deposited onto a bare current collector during charging. However, achieving uniform and defect-free Li plating on this bare current collector remains a major challenge, often resulting in low Li plating/stripping efficiency and rapid capacity decay. Here, for the first time, operando neutron imaging is employed to visualize Li plating/stripping behavior in an anode-free full cell with LiNi0.82Mn0.07Co0.11O2 (NMC) as the cathode. Operando measurements reveal that complete stripping of Li leaves isolated Li residues on the current collector, which degrades the interfacial contact between the current collector and the solid-state electrolyte. To mitigate this interfacial issue and promote more uniform Li deposition, we implement a discharge-cutoff-voltage strategy that intentionally retains a thin residual Li layer after stripping. This preserved Li-containing interfacial reservoir not only improves interfacial contact but also serves as an in situ formed seed layer that enables more homogeneous subsequent Li plating. As a result, the optimized anode-free cell with limited stripping depth exhibits excellent long-term cycling stability, maintaining a discharge capacity of 112.1 mAh g−1 with a capacity retention of 80.6% and an average coulombic efficiency of approximately 99.9% after 500 cycles at 0.25 C. In contrast, the cell with a conventional discharge cutoff voltage of 2.8 V exhibits rapid capacity decay, retaining only 59.7 mAh g−1 after 50 cycles with a capacity retention of 40.7%. This work demonstrates that limiting deep stripping to preserve a thin Li-containing interfacial layer can effectively improve the cycling stability of sulfide-based AFSSBs.

Wang, Jiwei [Northeastern University, Boston]↗
DOE OSTI2022

Multifunctional transitional metal-based phosphide nanoparticles towards improved polysulfide confinement and redox kinetics for highly stable lithium-sulfur batteries

The shuttle effect and the sluggish redox kinetics of lithium polysulfides (LiPSs) are the major issues impeding the practical applications of lithium-sulfur batteries (LSBs). Herein, a highly-efficient Ni 2 P electrocatalyst supported on N, P co-doped graphene (Ni 2 P@NPG) is developed via a simple “recrystallization-self-assembly” method to address the above issues. Here, the ultrafine Ni 2 P nanoparticles ensure abundant adsorption-diffusion-conversion interfaces for accelerating LiPSs transformation and Li 2 S deposition, which extremely decreases the accumulation of LiPSs in the electrolyte and therefore prevents the migration of LiPSs. Their superior catalytic performance is demonstrated by reduced Gibbs free energy changes of rate-limiting step based on the systematic theoretical calculations and the reduced shuttle effect is tested by the three-dimensional reconstructions of Raman depth profiles. Benefiting from these synergistic effects, the LSBs with Ni 2 P@NPG modified separators present a superior cycling performance with an average capacity decay rate of 0.048 % per cycle at 1C around the 400 cycles and a high-rate capacity of 731 mAh/g at 2C. Even with a high-sulfur loading of 3.53 mg cm –2 , the cell can still contain a reversible capacity of 809 mAh/g at 0.2C with a remarkable columbic efficiency of 98.4 %.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Lithium-ion hopping weakens thermal stability of LiPF 6 carbonate electrolytes

Lithium hexafluorophosphate (LiPF 6 )-based carbonate electrolytes are widely used in commercial lithium-ion batteries (LIBs), but their thermal instability limits the cycle life and safety of LIBs at elevated temperatures. Few studies have yielded insight into the initial PF 6 — decomposition reaction that promotes thermal instability of LiPF6-based electrolytes. Here, we find that lithium-ion hopping assisted by the overall reorientational motion of propylene carbonate molecules facilitates PF 6 — decomposition at elevated temperatures in 1 M LiPF 6 /propylene carbonate electrolyte. Further, we demonstrate that urea additives, by preventing lithium-ion hopping, suppress the initial LiPF 6 decomposition reaction and enhance the thermal stability of the electrolyte. LIB cell tests with LiNi 0.6 Mn 0.2 Co 0.2 O 2 ||Li 4 Ti 5 O 12 show improved LIB performance at elevated temperatures with the thermally stabilized electrolyte. This study provides key insights into the design of thermally stable LiPF 6 -based carbonate electrolytes for improving the cycle life, calendar life, and safety of LIBs in elevated-temperature applications.

25 ENERGY STORAGE↗
DOE OSTI2021

Stable bismuth-antimony alloy cathode with a conversion-dissolution/deposition mechanism for high-performance zinc batteries

Although a large number of intercalation cathode materials for aqueous Zn batteries have been reported, limited intercalation capacity precludes achieving a higher energy density. Here, for this work, we develop a high-performance aqueous Zn battery based on BiSb alloy (Bi 0.5 Sb 0.5 ) using a high-concentrated strong-basic polyelectrolyte. We demonstrate that a conversion-dissolution/deposition electrochemical mechanism (BiSb ↔ Bi + SbO 2 – ↔ Bi + SbO 3 – ↔ Bi 2 O 3 ) through in situ X-ray diffraction (XRD), Raman, and ex-situ X-ray photoelectron spectrometry (XPS) characterizations with the help of density functional theory calculations. The BiSb cathode delivers large capacity of 512 mAh g –1 at 0.3 Ag –1 and superior rate capability of 90 mAh g –1 even at 20 Ag –1 , and long-term cyclability with capacity retentions of 184 mAh g –1 after 600 cycles at 0.5 Ag –1 and 130 mAh g –1 after 1300 cycles at 1 Ag –1 . Remarkably, even at temperatures as low as –10 and –20 °C, capacities of 210 and 197 mAh g –1 are reserved at 1 Ag –1 , respectively. Moreover, the prepared pouch Zn//BiSb battery delivers a high energy density of 303 Wh kg –1 BiSb at 0.3 Ag –1 . When coupled with a high concentration polyelectrolyte, the Zn/BiSb battery exhibits an excellent performance over a wide temperature range (–40 to 40 °C). Our research reveals the metal cathode is promising for Zn batteries to achieve a high performance with the unique mechanism and alloys can be an effective approach to stabilize metal electrodes for cycling.

25 ENERGY STORAGE↗
DOE OSTI2024

Adding labile carbon to peatland soils triggers deep carbon breakdown

Peatlands store vast amounts of carbon, with deep peat carbon remaining stable due to limited thermodynamic energy and transport. However, climate change-induced increases in labile carbon inputs could destabilize these stores. Here, we combined DNA stable isotope probing with stable isotope-assisted metabolomics employing a multi-platform approach to investigate microbial dynamics driving deep peat carbon degradation upon labile carbon (e.g., glucose) amendment. Our findings highlight the vulnerability of deep peat carbon, as glucose addition triggers the breakdown of older organic matter. By uniquely integrating these techniques, we identified active glucose metabolizers to specific microbial populations and mapped carbon flow through microbial networks, elucidating their role in priming recalcitrant carbon mineralization. This multi-omics approach offers crucial insights into how changing resources reshape the peatland microbiome, enhancing our understanding of deep carbon processing, and refining model parameterization to predict microbial responses and carbon cycle feedbacks under global change pressures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Enhanced oxidation resistance of (Mo 95 W 5 ) 85 Ta 10 (TiZr) 5 refractory multi-principal element alloy up to 1300°C

Refractory-metal-based alloys are a potential replacement of current nickel-based superalloys due to their excellent mechanical strength at extremely high temperatures. However, severe oxidation in a high-temperature working environment limits their application. To address this challenge, a two-step coating process (including a Mo precoat and a Si-B pack cementation) was applied to an innovative refractory multi-principal element alloy (RMPEA) (Mo 95 W 5 ) 85 Ta 10 (TiZr) 5 . The coating is composed of an aluminoborosilica glass layer on top of a RMPEA-Si-B multilayered structure. Here, the coating effectively protects the RMPEA from oxidation in high-temperature environments, as demonstrated by phase-stable operation at 10–20% higher temperatures over state-of-the-art systems without any forced-cooling system. Following an isothermal exposure at 1300 °C, the weight change of the coated sample follows a paralinear kinetics with a minor weight loss of 4.2 mg/cm 2 after 50 h. Thermal cycling tests between 1300 °C and room temperature in air resulted in the total weight gain of only 2.6 mg/cm 2 after 450 cycles. The coating shows an excellent adherence to the substrate with a boride layer acting as a barrier that maintains the coating integrity. This two-step Mo-Si-B coating method can be adapted to provide environmental resistance to a wide range of RMPEA.

36 MATERIALS SCIENCE↗