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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Functionalization of Cathode–Electrolyte Interface with Ionic Liquids for High-Performance Quasi-Solid-State Lithium–Sulfur Batteries: A Low-Sulfur Loading Study

We introduce a quasi-solid-state electrolyte lithium-sulfur (Li–S) battery (QSSEB) based on a novel Li-argyrodite solid-state electrolyte (SSE), Super P–Sulfur cathode, and Li-anode. The cathode was prepared using a water-based carboxymethyl cellulose (CMC) solution and styrene butadiene rubber (SBR) as the binder while Li6PS5F0.5Cl0.5 SSE was synthesized using a solvent-based process, via the introduction of LiF into the argyrodite crystal structure, which enhances both the ionic conductivity and interface-stabilizing properties of the SSE. Ionic liquids (IL) were prepared using lithium bis(trifluoromethyl sulfonyl)imide (LiTFSI) as the salt, with pre-mixed pyrrolidinium bis(trifluoromethyl sulfonyl)imide (PYR) as solvent and 1,3-dioxolane (DOL) as diluent, and they were used to wet the SSE–electrode interfaces. The effect of IL dilution, the co-solvent amount, the LiTFSI concentration, the C rate at which the batteries are tested and the effect of the introduction of SSE in the cathode, were systematically studied and optimized to develop a QSSEB with higher capacity retention and cyclability. Interfacial reactions occurring at the cathode–SSE interface during cycling were also investigated using electrochemical impedance spectroscopy, cyclic voltammetry, and X-ray photoelectron spectroscopy supported by ab initio molecular dynamics simulations. This work offers a new insight into the intimate interfacial contacts between the SSE and carbon–sulfur cathodes, which are critical for improving the electrochemical performance of quasi-solid-state lithium–sulfur batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

CO 2 Methanation on Cu-Cluster Decorated Zirconia Supports with Different Morphology: A Combined Experimental In Situ GIXANES/GISAXS, Ex Situ XPS and Theoretical DFT Study

We report that subnanometer copper tetramer-zirconia catalysts turn out to be highly efficient for CO 2 hydrogenation and its conversion to methane. The cluster size and substrate morphology are controlled to optimize the catalytic performance. The two types of zirconia supports investigated are prepared by atomic layer deposition (~ 3 nm thick film) and supersonic cluster beam deposition (nanostructured film, ~ 100 nm thick). The substrate plays a crucial role in determining the activity of the catalyst as well as its cyclability over repeated thermal ramps. A temperature-programmed reaction combined with in situ X-ray characterization reveals the correlation between the evolution in the oxidation state and catalytic activity. Ex situ photoelectron spectroscopy indicates Cu clusters with stronger interactions with the nanostructured film, which can be the cause for the higher activity of this catalyst. Density functional theory calculations based on the Cu 4 O 2 cluster supported on a ZrOx subunit reveal low activation barriers and provide mechanism for CO 2 hydrogenation and its conversion to methane. Altogether, the results show a new way to tune the catalytic activity of CO 2 hydrogenation catalysts through controlling the morphology of the support at the nanoscale.

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

Enhanced prediction of Cs removal by CST from Hanford tank waste with K accountability

Abstract The treatment of Hanford tank waste is one of the most challenging environmental cleanup activities to date. To expedite the processing of liquid waste stored in underground tanks in Washington State it is necessary to remove the significant dose contributor, 137 Cs. Crystalline silicotitanate ion exchanger is currently used to remove 137 Cs from the aqueous phase of Hanford tank wastes in preparation for vitrification at the Waste Treatment and Immobilization Plant (WTP). Improving the understanding of potassium impacts on ion exchange behavior of Cs will help in the operation of a critical component of one of the most complex treatment processes in the world today. Optimization of this process can result in significant cost savings and less waste production. Toward this effort, a series of batch contact tests varied in potassium concentration were conducted to look at the impact of potassium concentration on Cs distribution. Experimental distribution ratios ( K d ) were compared to the distribution ratios predicted using the ZAM model. A significant underprediction of Cs capacity in the presence of potassium was seen with the existing model. A revision of the equilibrium constants was determined and provided a statistically better fit for determining the Cs K d values in tank waste matrices.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Preparation and Photocatalytic Hydrogen Production of TiO 2 /(AlMnCoNiZn) 3 O 4 Nanocomposites

Photocatalytic water splitting is a promising strategy for addressing the global energy crisis and environmental pollution. In this study, spinel-type high-entropy oxide (HEO) nanoparticles, (AlMnCoNiZn) 3 O 4 , were successfully synthesized via a solution combustion method. TiO 2 /(AlMnCoNiZn) 3 O 4 nanocomposites with varying molar ratios were subsequently fabricated through solid-state sintering, and their photocatalytic water-splitting performance was systematically investigated. The hydrogen production rate initially increased and then decreased with increasing TiO 2 content. The optimal nanocomposite achieved a hydrogen evolution rate of 1450 μmol·h −1 ·g −1 under simulated sunlight irradiation, which is 2.2 times higher than that of pure TiO 2 nanoparticles. In addition, the TiO 2 /(AlMnCoNiZn) 3 O 4 nanocomposites exhibited significantly improved photocorrosion resistance compared with TiO 2 nanoparticles. After 12 h irradiation under a 500-W high-pressure mercury lamp, the hydrogen production rates of the nanocomposites and pure TiO 2 retained 79.3% and 5.47% of their initial values, respectively. These results demonstrate the important role of (AlMnCoNiZn) 3 O 4 and other HEOs in enhancing the photocatalytic performance of nanoheterojunction catalysts. Lastly, this work broadens the potential applications of (AlMnCoNiZn) 3 O 4 and related HEO materials in the field of photocatalysis.

Heterojunction↗
DOE OSTI2023

Lower Bounds on Quantum Annealing Times

The adiabatic theorem provides sufficient conditions for the time needed to prepare a target ground state. While it is possible to prepare a target state much faster with more general quantum annealing protocols, rigorous results beyond the adiabatic regime are rare. Here, we provide such a result, deriving lower bounds on the time needed to successfully perform quantum annealing. The bounds are asymptotically saturated by three toy models where fast annealing schedules are known: the Roland and Cerf unstructured search model, the Hamming spike problem, and the ferromagnetic p-spin model. Our bounds demonstrate that these schedules have optimal scaling. Herein, our results also show that rapid annealing requires coherent superpositions of energy eigenstates, singling out quantum coherence as a computational resource.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Ultracoherent SRF Cavity-Based Multi-Qudit Platform with Error-Resilient Control

Superconducting radio-frequency (SRF) cavities offer a promising platform for quantum computing due to their long coherence times, yet integrating nonlinear elements like transmons for control often introduces additional loss. We report a multimode quantum system based on a 2-cell elliptical shaped SRF cavity, comprising two cavity modes weakly coupled to an ancillary transmon circuit, designed to preserve coherence while enabling efficient control of the cavity modes. We mitigate the detrimental effects of the transmon decoherence through careful design optimization that reduces transmon-cavity couplings and participation in the dielectric substrate and lossy interfaces, to achieve single-photon lifetimes of 20.6\,ms and 15.6\,ms for the two modes, and a pure dephasing time exceeding 40\,ms. This marks an order-of-magnitude improvement over prior 3D multimode memories. Leveraging sideband interactions and novel error-resilient protocols, including measurement-based correction and post-selection, we achieve high-fidelity control over quantum states. This enables the preparation of Fock states up to $N = 20$ with fidelities exceeding 95\%, the highest reported to date to the authors' knowledge, as well as two-mode entanglement with an estimated coherence-limited fidelities of 99.9\% after post-selection. These results establish our platform as a robust foundation for quantum information processing, allowing for future extensions to high-dimensional qudit encodings.

Kim, T. [Northwestern U.]↗
DOE OSTI2026

Ultracoherent superconducting cavity-based multiqudit platform with error-resilient control

Superconducting radio-frequency (SRF) cavities offer a promising platform for quantum computing due to their long coherence times, yet integrating nonlinear elements like transmons for control often introduces additional loss. We report a multimode quantum system based on a 2-cell elliptical-shaped SRF cavity, comprising two cavity modes weakly coupled to an ancillary transmon circuit, designed to preserve coherence while enabling efficient control of the cavity modes. We mitigate the detrimental effects of the transmon decoherence through careful design optimization that reduces transmon-cavity couplings and participation in the dielectric substrate and lossy interfaces, to achieve single-photon lifetimes of 20.6 ms and 15.6 ms for the two modes, and a pure dephasing time exceeding 40 ms. This marks an order-of-magnitude improvement over prior 3D multimode memories. Leveraging sideband interactions and novel error-resilient protocols, including measurement-based correction and post-selection, we achieve high-fidelity control over quantum states. This enables the preparation of Fock states up to N = 20 with fidelities exceeding 95%, the highest reported to date to the authors' knowledge, as well as two-mode entanglement with an estimated coherence-limited fidelities of 99.9% after post-selection. These results establish our platform as a robust foundation for quantum information processing, allowing for future extensions to high-dimensional qudit encodings.

Lu, Yao [Fermilab] (ORCID:000000020413698X)↗
DOE OSTI2026

Ultracoherent superconducting cavity-based multiqudit platform with error-resilient control

Superconducting radio-frequency (SRF) cavities offer a promising platform for quantum computing due to their long coherence times, yet integrating nonlinear elements like transmons for control often introduces additional loss. We report a multimode quantum system based on a 2-cell elliptical-shaped SRF cavity, comprising two cavity modes weakly coupled to an ancillary transmon circuit, designed to preserve coherence while enabling efficient control of the cavity modes. We mitigate the detrimental effects of the transmon decoherence through careful design optimization that reduces transmon-cavity couplings and participation in the dielectric substrate and lossy interfaces, to achieve single-photon lifetimes of 20.6 ms and 15.6 ms for the two modes, and a pure dephasing time exceeding 40 ms. This marks an order-of-magnitude improvement over prior 3D multimode memories. Leveraging sideband interactions and novel error-resilient protocols, including measurement-based correction and post-selection, we achieve high-fidelity control over quantum states. This enables the preparation of Fock states up to N = 20 with fidelities exceeding 95%, the highest reported to date to the authors' knowledge, as well as two-mode entanglement with an estimated coherence-limited fidelities of 99.9% after post-selection. These results establish our platform as a robust foundation for quantum information processing, allowing for future extensions to high-dimensional qudit encodings.

Lu, Yao [Fermilab] (ORCID:000000020413698X)↗
DOE OSTI2025

Ultracoherent superconducting cavity-based multiqudit platform with error-resilient control

Superconducting radio-frequency (SRF) cavities offer a promising platform for quantum computing due to their long coherence times, yet integrating nonlinear elements like transmons for control often introduces additional loss. We report a multimode quantum system based on a 2-cell elliptical shaped SRF cavity, comprising two cavity modes weakly coupled to an ancillary transmon circuit, designed to preserve coherence while enabling efficient control of the cavity modes. We mitigate the detrimental effects of the transmon decoherence through careful design optimization that reduces transmon-cavity couplings and participation in the dielectric substrate and lossy interfaces, to achieve single-photon lifetimes of 20.6 ms and 15.6 ms for the two modes, and a pure dephasing time exceeding 40 ms. This marks an order-of-magnitude improvement over prior 3D multimode memories. Leveraging sideband interactions and novel error-resilient protocols, including measurement-based correction and post-selection, we achieve high-fidelity control over quantum states. This enables the preparation of Fock states up to $N = 20$ with fidelities exceeding 95%, the highest reported to date to the authors' knowledge, as well as two-mode entanglement with an estimated coherence-limited fidelities of 99.9% after post-selection. These results establish our platform as a robust foundation for quantum information processing, allowing for future extensions to high-dimensional qudit encodings.

Kim, Taeyoon [Fermilab; Northwestern U.]↗
DOE OSTI2023

Neutron Imaging of Al6061 Prepared by Solid-State Friction Stir Additive Manufacturing

Solid-state Friction Stir Additive Manufacturing has recently gained attention as a result of its capacity to fabricate large-scale parts while preserving the mechanical properties of the feedstock material. However, the correlation between the quality of layer-by-layer bonding of the deposited metal and processing parameters has remained unknown. Neutron imaging techniques, with 90% total transmission per cm, are employed for Al6061 parts fabricated by MELD ® Technology as a non-destructive evaluation approach for the first time to investigate the layer-by-layer structure of a stadium-shaped ingot in different sections. The post-processed results show the fabricated parts with an optimized set of processing parameters are void-free. However, the hydrocarbon-based feedstock lubricant segregates between the layers, which consequently may lead to non-uniform weaker mechanical properties along the build direction and stimulate crack initiation during mechanical loading. The tensile test results show 14% lower strain-to-failure values in alleged contaminated areas in transmission imaging results. Additionally, layer bonding is significantly impacted by hot-on-hot and hot-on-cold layer deposition schemes, especially for larger layer thicknesses.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Enhancing perovskite electrocatalysis through synergistic functionalization of B-site cation for efficient water splitting

The family of perovskite oxides is a promising class of catalysts for diverse energy conversion processes including water splitting. In this work, a facile two-step manipulation (in-situ exsolution and post-sulfurization) strategy was proposed and applied to LaCo 0.2 Fe 0.8 O 3 (LCF) perovskite parent, through which, the electronic state, spatial immersion and intrinsic activity of B-site cobalt (Co) were stepwise tuned at nanoscale proximity accordingly (i.e., lattice Co ions segregated Co 0 → embedded CoS 2 ). Impressively, the as-prepared catalyst (S-LCF) obtains an emergent oxygen deficient microstructure seamlessly pinned with uniformly distributed CoS 2 nanoparticles (NPs), which demonstrates enhanced performance toward both oxygen evolution reaction (OER) and hydrogen evolution reaction (HER), and shows good stability in overall water splitting. The density functional theory (DFT) calculations illustrate the optimized metal-oxygen covalency and hydrogen adsorption Gibbs free energy (Δ G H *) on S-LCF, which further buttresses the prominence of our B-site cation engineering tactics.

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

Crystal Structure and Preparation of Li7La3Zr2O12 (LLZO) Solid-State Electrolyte and Doping Impacts on the Conductivity: An Overview

As an essential part of solid-state lithium-ion batteries, solid electrolytes are receiving increasing interest. Among all solid electrolytes, garnet-type Li7La3Zr2O12 (LLZO) has proven to be one of the most promising electrolytes because of its high ionic conductivity at room temperature, low activation energy, good chemical and electrochemical stability, and wide potential window. Since the first report of LLZO, extensive research has been done in both experimental investigations and theoretical simulations aiming to improve its performance and make LLZO a feasible solid electrolyte. These include developing different methods for the synthesis of LLZO, using different crucibles and different sintering temperatures to stabilize the crystal structure, and adopting different methods of cation doping to achieve more stable LLZO with a higher ionic conductivity and lower activation energy. It also includes intensive efforts made to reveal the mechanism of Li ion movement and understand its determination of the ionic conductivity of the material through molecular dynamic simulations. Nonetheless, more insightful study is expected in order to obtain LLZO with a higher ionic conductivity at room temperature and further improve chemical and electrochemical stability, while optimal multiple doping is thought to be a feasible and promising route. This review summarizes recent progress in the investigations of crystal structure and preparation of LLZO, and the impacts of doping on the lithium ionic conductivity of LLZO.

Raju, Md Mozammal (ORCID:0000000319040523)↗
DOE OSTI2022

Nanoscale solid-state nuclear quadrupole resonance spectroscopy using depth-optimized nitrogen-vacancy ensembles in diamond

Nuclear magnetic resonance (NMR) and nuclear quadrupole resonance (NQR) spectroscopy of bulk quantum materials have provided insight into phenomena, such as quantum phase criticality, magnetism, and superconductivity. With the emergence of nanoscale 2D materials with magnetic phenomena, inductively detected NMR and NQR spectroscopy are not sensitive enough to detect the smaller number of spins in nanomaterials. The nitrogen-vacancy (NV) center in diamond has shown promise in bringing the analytic power of NMR and NQR spectroscopy to the nanoscale. However, due to depth-dependent formation efficiency of the defect centers, noise from surface spins, band bending effects, and the depth dependence of the nuclear magnetic field, there is ambiguity regarding the ideal NV depth for surface NMR of statistically polarized spins. In this work, we prepared a range of shallow NV ensemble layer depths and determined the ideal NV depth by performing NMR spectroscopy on statistically polarized 19 F in Fomblin oil on the diamond surface. We found that the measurement time needed to achieve a signal-to-noise ratio of 3 using XY8-N noise spectroscopy has a minimum at an NV ensemble depth of 5.5 ± 1.5 nm for ensembles activated from 100 ppm nitrogen concentration. To demonstrate the sensing capabilities of NV ensembles, we perform NQR spectroscopy on the 11 B of hexagonal boron nitride flakes. We compare our best diamond to previous work with a single NV and find that this ensemble provides a shorter measurement time with excitation diameters as small as 4 μm. Furthermore, this analysis provides ideal conditions for further experiments involving NMR/NQR spectroscopy of 2D materials with magnetic properties.

2D materials↗
DOE OSTI2022

Fast-forwarding quantum simulation with real-time quantum Krylov subspace algorithms

Quantum subspace diagonalization (QSD) algorithms have emerged as a competitive family of algorithms that avoid many of the optimization pitfalls associated with parameterized quantum circuit algorithms. While the vast majority of the QSD algorithms have focused on solving the eigenpair problem for ground, excited-state, and thermal observable estimation, there has been a lot less work in considering QSD algorithms for the problem of quantum dynamical simulation. In this work, we propose several quantum Krylov fast-forwarding (QKFF) algorithms capable of predicting long-time dynamics well beyond the coherence time of current quantum hardware. Our algorithms use real-time evolved Krylov basis states prepared on the quantum computer and a multi-reference subspace method to ensure convergence towards high-fidelity, long-time dynamics. In particular, we show that the proposed multi-reference methodology provides a systematic way of trading off circuit depth with classical post-processing complexity. Further, we also demonstrate the efficacy of our approach through numerical implementations for several quantum chemistry problems including the calculation of the auto-correlation and dipole moment correlation functions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Short-depth circuits for efficient expectation-value estimation

The evaluation of expectation values Tr[$\rho \mathcal{O}$] for some pure state $\rho$ and Hermitian operator $\mathcal{O}$ is of central importance in a variety of quantum algorithms. Near-optimal techniques have been developed in the past and require a number of measurements N approaching the Heisenberg limit N = O(1/ ε) as a function of target accuracy ε. The use of quantum phase estimation (QPE) requires, however, long circuit depths C = O(1/ ε) making its implementation difficult on near-term noisy devices. The more direct strategy of operator averaging is usually preferred as it can be performed using N = O(1/ε 2 ) measurements and no additional gates aside from those needed for the state preparation. In this work we use a simple but realistic model to describe the bound state of a neutron and a proton (the deuteron) to show that the latter strategy can require an overly large number of measurements in order to achieve a prefixed relative target accuracy ε r . Further, we propose to overcome this problem using a single step of QPE and classical postprocessing. This approach leads to a circuit depth C = O (ε μ ) (with μ ≥ 0) and to a number of measurements N = O (1/ε 2 + ν ) for 0 < ν ≤ 1 and a much smaller prefactor. We provide detailed descriptions of two implementations of our strategy for ν = 1 and ν ≈ 0.5 and derive appropriate conditions that a particular problem instance has to satisfy in order for our method to provide an advantage.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Solid-State Mixed-Potential Electrochemical Sensors for Natural Gas Leak Detection and Quality Control (Final Technical Report)

Mitigation of methane emissions are a critical factor to limiting the impact of the natural gas industry on global climate change. Throughout the period of 2020-2024, the University of New Mexico and its commercialization partner and subcontractor, SensorComm Technologies, Inc. (SCT), have worked together to develop a low-cost Artificial Intelligence (AI)-driven Internet of Things (IoT)-based multi-gas sensor platform for methane emissions detection. In the final year of the project, we extended this work to include hydrogen detection in support of a transition to a hydrogen economy where hydrogen could be transported through existing natural gas infrastructure. Mixed potential electrochemical sensors were first prototyped by ceramic additive manufacturing and then transitioned to conventional ceramic manufacturing tape casting and screen-printing technologies in preparation for mass production. Demonstrated limits of detection of 5 ppm of methane in natural gas and 1 ppm of hydrogen were measured. These limits of detection are among the lowest of solid-state electrochemical sensors that have been reported in the literature or available in the industry. Machine learning algorithms were developed to identify natural gas mixtures with > 98% accuracy level and quantify methane concentrations at 97% accuracy. The presence of hydrogen could also be identified, and its concentration quantified at these accuracy levels. These algorithms were optimized for running on portable computing hardware which enabled > 1 Hz processing rates. A portable packaged IoT system was integrated with the electrochemical sensor in collaboration with SCT. The package consists of readout electronics with < 1 mV resolution, sensor temperature control, and data transmission over cellular wireless and/or Wi-Fi networks. Field testing was performed in two rounds at Colorado State University’s Methane Emissions Technology Evaluation Center (CSU METEC). The first round of testing demonstrated successful measurements of methane from an underground natural gas leak of 20 standard liters per minute (SLPM), which agreed with previously published literature using more sophisticated and expensive analytical equipment. The second round of testing showed that an above ground leak of 2 SLPM of hydrogen could be detected at 32 ft. This project has resulted in six published peer reviewed journal articles, over ten presentations at professional conferences, and one full patent application filed in 2023. Future work on this project includes increased sensitivity, higher production yields, and applications in the hydrogen safety and flare emissions monitoring spaces.

03 NATURAL GAS↗
DOE OSTI2026

Quantum Computing in Next-Generation Transportation Optimization

We explore how quantum computing (QC) can advance transportation optimization, with a focus on two high-impact areas: traffic signal control and vehicle electrification with grid integration. As transportation systems grow in complexity, classical optimization methods increasingly struggle to deliver scalable and efficient solutions, particularly for real-time, data-rich environments. This work identifies key challenges within these two domains where QC may offer advantages, particularly in handling combinatorial decision spaces and dynamic constraints. We begin by outlining the limitations of classical approaches for traffic signal control optimization and electric vehicle charging coordination, highlighting where computational limitations arise. Previous quantum formulations are presented and new formulations are proposed to demonstrate how emerging quantum algorithms, including quantum annealing and the Quantum Approximation Optimization Algorithm, could be leveraged to reformulate and address these problems. We also evaluate the suitability of current quantum hardware and discuss recent trends that indicate when QC may become a viable tool for transportation applications. While acknowledging the present limitations of QC technologies, this poster emphasizes the importance of preparing quantum-compatible models today. By reviewing and establishing formulations that align with the strengths of quantum algorithms, researchers and practitioners can better position themselves to take advantage of QC advancements as they occur. This work aims to provide a practical, forward-looking perspective on the near-term potential of quantum computing in transportation optimization.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Microstructural evaluation of thin-wall sections of 316L stainless steel produced by laser powder-bed fusion processing

The synthesis of thin wall sections that are only 0.4 mm thick is achieved with LPBF AM. Sample preparation is optimized using metallographic polishing to produce samples with only 0.3 um rms roughness for scanning electron microanalysis with EBSD and EDS. A fully austenitic 316L phase is found without evidence of secondary phases. Unlike some AM products that can readily evidence composition segregation due to solute rejection as attributable to temperature gradients within the solidification

Jankowski, Alan F. [Sandia National Laboratories (↗