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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Sub-angstrom strain in high-entropy intermetallic boosts the oxygen reduction reaction in fuel cell cathodes

The strain effect of high-entropy intermetallic (HEI) catalysts on oxygen reduction reaction (ORR) performance remains largely unexplored, primarily due to the significant challenges associated with characterizing and calculating the intricate local coordination environments. Here, we design a nitrogen (N)-doped L1 0 -ordered PtCoNiFeCu intermetallic catalyst supported on Ketjenblack carbon (N-HEI/KB), and reveal the origin of the sub-angstrom strain in N-HEI and its impact on ORR performance by combining atomic-scale characterization and theoretical calculations. The synergistic interplay of the sub-angstrom strain, the pinning effect of metal-N bonds, and the high-entropy effect contribute to the competitive stability of N-HEI/KB catalysts, providing high current density of 1388 mA cm -2 at 0.7 V after 90,000 cycles even under harsh heavy-duty vehicle conditions. These findings broaden the avenues for designing high-performance high-entropy intermetallic cathode electrocatalysts.

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

Boosting the signal-to-noise of low-field MRI with deep learning image reconstruction

Recent years have seen a resurgence of interest in inexpensive low magnetic field (< 0.3 T) MRI systems mainly due to advances in magnet, coil and gradient set designs. Most of these advances have focused on improving hardware and signal acquisition strategies, and far less on the use of advanced image reconstruction methods to improve attainable image quality at low field. We describe here the use of our end-to-end deep neural network approach (AUTOMAP) to improve the image quality of highly noise-corrupted low-field MRI data. We compare the performance of this approach to two additional state-of-the-art denoising pipelines. We find that AUTOMAP improves image reconstruction of data acquired on two very different low-field MRI systems: human brain data acquired at 6.5 mT, and plant root data acquired at 47 mT, demonstrating SNR gains above Fourier reconstruction by factors of 1.5- to 4.5-fold, and 3-fold, respectively. In these applications, AUTOMAP outperformed two different contemporary image-based denoising algorithms, and suppressed noise-like spike artifacts in the reconstructed images. The impact of domain-specific training corpora on the reconstruction performance is discussed. The AUTOMAP approach to image reconstruction will enable significant image quality improvements at low-field, especially in highly noise-corrupted environments.

42 ENGINEERING↗
DOE OSTI2024

VpROM: a novel variational autoencoder-boosted reduced order model for the treatment of parametric dependencies in nonlinear systems

Reduced Order Models (ROMs) are of considerable importance in many areas of engineering in which computational time presents difficulties. Established approaches employ projection-based reduction, such as Proper Orthogonal Decomposition. The limitation of the linear nature of such operators is typically tackled via a library of local reduction subspaces, which requires the assembly of numerous local ROMs to address parametric dependencies. Our work attempts to define a more generalisable mapping between parametric inputs and reduced bases for the purpose of generative modeling. We propose the use of Variational Autoencoders (VAEs) in place of the typically utilised clustering or interpolation operations, for inferring the fundamental vectors, termed as modes, which approximate the manifold of the model response for any and each parametric input state. The derived ROM still relies on projection bases, built on the basis of full-order model simulations, thus retaining the imprinted physical connotation. However, it additionally exploits a matrix of coefficients that relates each local sample response and dynamics to the global phenomena across the parametric input domain. The VAE scheme is utilised for approximating these coefficients for any input state. This coupling leads to a high-precision low-order representation, which is particularly suited for problems where model dependencies or excitation traits cause the dynamic behavior to span multiple response regimes. Moreover, the probabilistic treatment of the VAE representation allows for uncertainty quantification on the reduction bases, which may then be propagated to the ROM response. The performance of the proposed approach is validated on an open-source simulation benchmark featuring hysteresis and multi-parametric dependencies, and on a large-scale wind turbine tower characterised by nonlinear material behavior and model uncertainty.

Conditional VAEs↗
DOE OSTI2020

Boosting the activity of transition metal carbides towards methane activation by nanostructuring

The interaction of methane with pristine surfaces of bulk MoC and Mo 2 C is known to be weak. In contrast, a series of X-ray photoelectron spectroscopy (XPS) experiments, combined with thermal desorption mass spectroscopy (TDS), for MoC y (y = 0.5–1.3) nanoparticles supported on Au(111)—which is completely inert towards CH 4 —show that these systems adsorb and dissociate CH 4 at room temperature and low CH 4 partial pressure. This industrially-relevant finding has been further investigated with accurate density functional theory (DFT) based calculations on a variety of MoC y supported model systems. The DFT calculations reveal that the MoC y /Au(111) systems can feature low C–H bond scission energy barriers, smaller than the CH 4 adsorption energy. Our theoretical results for bulk surfaces of Mo 2 C and MoC show that a simple Brønsted–Evans–Polanyi (BEP) relationship holds for C–H bond scission on these systems. However, this is not the case for methane activation on the MoC y nanoparticles as a consequence of their unique electronic and chemical properties. Finally, the discovery that supported molybdenum carbide nanoparticles are able to activate methane at room temperature paves the road towards the design of a new family of active carbide catalysts for methane activation and valorisation, with important implications in climate change mitigation and carbon cycle closure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Boosting the cycling stability of Ni-rich layered oxide cathode by dry coating of ultrastable Li 3 V 2 (PO 4 ) 3 nanoparticles

Nickel (Ni)-rich layered oxides such as LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NCM622) represent one of the most promising candidates for next-generation high-energy lithium-ion batteries (LIBs). However, the pristine Ni-rich cathode materials usually suffer from poor structural stability during cycling. In this work, we demonstrate a simple but effective approach to improve the cycling stability of the NCM622 cathode by dry coating of ultrastable Li 3 V 2 (PO 4 ) 3 -carbon (LVP-C) nanoparticles, which leads to a robust composite cathode (NCM622/LVP-C) without sacrificing the specific energy density compared with pristine NCM622. The optimal NCM622/LVP-C composite presents a high specific capacity of 162 mA h g -1 at 0.5 C and excellent cycling performance with 85.0% capacity retention after 200 cycles at 2 C, higher than that of the pristine NCM622 (67.6%). Systematic characterization confirms that the LVP-C protective layer can effectively reduce the side reactions, restrict the cation mixing of NCM622 and improve its structural stability. Moreover, the NCM622/LVP-C||graphite full cells also show a commercial-level capacity of 3.2 mA h cm -2 and much improved cycling stability compared with NCM622/LVP-C||graphite full cells, indicating the great promise for low-cost, high-capacity and long-life LIBs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Boosting solid oxide fuel cell performance via electrolyte thickness reduction and cathode infiltration

Increasing the power density and reducing the operating temperature of solid oxide fuel cells (SOFCs) is important for improving commercial viability. Here we discuss two strategies for achieving such improvements in Ni–YSZ supported SOFCs – electrolyte thickness reduction and cathode infiltration. Microstructural and electrochemical results are presented showing the effect of reducing YSZ/GDC electrolyte thickness from 8 to 2.5 μm, and the effect of PrO x infiltration into the LSCF–GDC cathode. Both of these measures are effective, particularly at lower temperatures, leading to an increase in the maximum power density at 650 °C from 0.4 to 0.95 W cm –2 , for example. Electrochemical impedance spectroscopy utilizing subtractive analysis shows that PrO x enhances the cathode charge transfer process. Reducing the electrolyte thickness reduces not only the cell ohmic resistance but also the electrode polarization resistance. Furthermore, the latter effect appears to be an artifact associated with a slight increase in the steam partial pressure at the anode due to minor gas leakage across the thinner electrolyte.

25 ENERGY STORAGE↗
DOE OSTI2020

Boosted piezoelectricity with excellent thermal stability in tetragonal NaNbO 3 -based ceramics

The realization of high piezoelectric performance and excellent temperature stability simultaneously in Pb-free ceramics is the key for replacing Pb-containing perovskites in the industry. In this study, large piezoelectric performance (d 33 = 354 pC N –1 ) was achieved in a wide temperature sinterable potassium-free NaNbO 3 –BaTiO 3 –BaSnO 3 system, which is twice more than the piezoelectricity found in NaNbO 3 –BaTiO 3 binary ceramics. Structural refinement of high-energy synchrotron powder diffraction data suggests a single tetragonal structure with P4bm symmetry for the studied NaNbO 3 -based Pb-free ceramic. The results indicate that the small axial ratio favoring polarization reorientation benefits strong piezoelectricity, while the large oxygen octahedron tilt enhances the stability of the P4bm structure during the changing temperature according to the in situ high-energy synchrotron X-ray diffraction measurements and provides the foundation for the excellent thermal stability (20–100 °C) of the piezoelectric properties. Furthermore, a single tetragonal phase with a tiny axial ratio and large oxygen octahedron tilt effectively balances the piezoelectricity and thermal stability in Pb-free systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Boosting electrochemical reaction and suppressing phase transition with a high-entropy O3-type layered oxide for sodium-ion batteries

Complex phase transitions induced by interlayer slides in layered cathode materials lead to poor cycling stability and rate capability for sodium-ion batteries. Herein, we design and prepare a new six-component high-entropy oxide (HEO) layered cathode O3–Na(Fe 0.2 Co 0.2 Ni 0.2 Ti 0.2 Sn 0.1 Li 0.1 )O 2 to enable highly reversible electrochemical reaction and phase-transition behavior. The HEO cathode exhibits good cycling performance (capacity retention of ~81% after 100 cycles at 0.5C) and outstanding rate capability (capacity of ~81 mA h g –1 at 2.0C) due to the higher sodium diffusion coefficient (above 5.75 × 10 –11 cm 2 s –1 ) than most reported O3-type cathodes. Moreover, the high-entropy cathode has superior compatibility with the hard carbon anode and delivers a specific capacity of 90.4 mA h g –1 (energy density of ~267.5 W h kg –1 ). Ex situ X-ray diffraction proves that the high-entropy designing effectively suppresses the intermediate phase change to achieve reversible O3–P3 phase evolution, and in turn stabilizes the layered structure. X-ray absorption spectroscopy and Mössbauer spectrum of 57 Fe suggest that Ni 2+ /Ni 3.5+ , Co 3+ /Co 3.5+ , and part of Fe 3+ /Fe 3.5+ redox reaction contribute the charge compensation. Finally, the enhanced performance can be attributed to the disordered distribution of multi-component transition metals in HEO suppressing the ordering of electric charges and sodium vacancies, thereby inhibiting the interlayer slide and phase transition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Tuning the Co/Fe ratio in BaCo x Fe 0.8– x Zr 0.1 Y 0.1 O 3– δ , a promising triple ionic and electronic conducting oxide, to boost electrolysis and fuel cell performance

The triple conducting oxide BaCo 0.4 Fe 0.4 Zr 0.1 Y0.1O 3–δ (BCFZY4411), which accommodates simultaneous transport of protons, oxygen ions, and p-type electronic carriers, has been intensively investigated in recent years as a high-performance positive electrode material for fuel cell and electrolysis applications. The heavy Co and Fe-based transition metal doping in BCFZY4411 ensures adequate electrical conductivity while the multiple oxidation states of Co and Fe assist the electrocatalytic and redox ability. Despite the considerable role of Co and Fe transition metal doping in controlling electrochemical activity, however, the study of alternative BCFZY compositions with varying Co/Fe ratios has not yet been pursued. Here, we evaluate the electrochemical performance of a series of BaCo x Fe 0.8–x Zr 0.1 Y0.1O 3–δ compositions with varying Co/Fe ratio (x = 0.1, 0.2, 0.4, 0.6, 0.7) and use oxygen ion tracer diffusion and in situ high-temperature X-ray diffraction to investigate the effect of Co/Fe ratio on electrocatalytic activity, electronic conductivity, oxygen ion incorporation and transport kinetics, and thermomechanical behavior. We find that Co-rich BCFZY7111 yields the highest performance due to exceptionally high oxygen vacancy diffusion and shows a lower and more linear thermal expansion behavior compared to Fe-rich compositions. A protonic ceramic button cell incorporating a BCFZY7111 positive electrode yields a peak power density of 695 mW cm –2 under fuel cell mode and an electrolysis current density of 1976 mA cm –2 at 1.4 V at 600 °C, underscoring the promise of this new BCFZY electrode composition.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Boosting the performance of reversible solid oxide electrochemical cells with a novel hybrid oxygen electrode, Pr 1.39 Ba 0.14 Sr 0.53 Co 1.48 Fe 0.76 O 6- δ -Ba 0.66 Sr 0.34 CoO 3- δ

Solid oxide electrochemical cells (SOECs) stand out as a highly promising clean energy technology that offers several benefits, showing significant potential to play a pivotal role in the transition towards a sustainable and low-carbon energy future. SOECs can efficiently convert the chemical energy stored in fuels to electricity in fuel cell mode, and produce various chemicals from abundant feedstocks (e.g., CO 2 , H 2 O) and intermittent solar/wind-based renewable electricity. Despite extensive efforts that have been devoted to designing novel materials and optimizing SOEC manufacturing processes, aiming to achieve enhanced energy efficiency, the current SOECs still suffer from poor performance, which is mainly due to the sluggish oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) kinetics. To address this challenge, in this work, we have successfully designed an in situ formed hybrid oxygen electrode material (Pr 1.39 Ba 0.14 Sr 0.53 Co 1.48 Fe 0.76 O 6- δ -Ba 0.66 Sr 0.34 CoO 3- δ ), which significantly improves the surface oxygen exchange coefficient and bulk oxygen-ion diffusion coefficient, enhancing the OER and ORR electrocatalytic activities. Further, the SOECs equipped with this newly developed oxygen electrode achieved exceptional performance for power generation using both hydrogen and propane as the fuels. At 750 °C, a peak power density of 2.4 W cm -2 was obtained with H 2 as the fuel. Additionally, the SOECs attain unprecedented performance in steam electrolysis mode. A current density of 4.4 A cm -2 was achieved at 1.3 V and 750 °C, which represents the highest performance among all yttria-stabilized zirconia (YSZ) electrolyte-based SOECs. The SOECs also deliver remarkable stability during the accelerated stability testing, highlighting the great potential of Pr 1.39 Ba 0.14 Sr 0.53 Co 1.48 Fe 0.76 O 6- δ -Ba 0.66 Sr 0.34 CoO 3- δ as a high-performance oxygen electrode for next generation SOECs.

08 HYDROGEN↗
DOE OSTI2023

Constructing a square-like copper cluster to boost C–C coupling for CO 2 electroreduction to ethylene

The CO 2 electroreduction reaction (CO 2 ER) to ethylene (C 2 H 4 ) offers the dual promise of lowering CO 2 emission while storing energy from renewable electricity, for which the development of highly efficient electrocatalysts is of great significance. Herein, by means of density functional theory (DFT) computations, we designed an electrocatalyst for CO 2 -to-C 2 H 4 conversion by anchoring a Cu 5 cluster supported on a MoS 2 monolayer with an S monovacancy (Cu 5 @MoS 2 ). Our results revealed that one Cu atom of the Cu 5 cluster was embedded into the framework of the defective MoS 2 monolayer, while the other four Cu atoms form a square-like island over the substrate surface. Interestingly, the C–C coupling between two *CO species can easily occur on the unique square-like active site with a low kinetic barrier of 0.56 eV to form the key *C 2 O 2 intermediate, which can then be hydrogenated to the C 2 H 4 product with a very low limiting potential (–0.32 eV). Significantly, alkaline conditions (pH = 13) are beneficial to further promote C 2 H 4 synthesis. Finally, our work may offer a new avenue to precisely modulate the structures of Cu clusters for converting CO 2 into high-value target products.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Synergistic effects of Pd single atoms and nanoclusters boosting SnO 2 gas sensing performance

Tin(IV) oxide-supported Pd is a promising heterogenous catalyst for CO oxidation relevant for environmental cleanup reactions. In this study, an atomically dispersed Pd catalyst on SnO 2 (ADC Pd/SnO 2 ) hybrid material is successfully synthesized via a straightforward wet chemistry method and is found to exhibit superior performance toward CO sensing. Ex situ EXAFS analysis confirms the formation of single Pd atoms and small Pd nanoclusters stabilized on the SnO 2 (110) surface. Further, the material exhibits high efficiency in generating adsorbed O 2 - as well as high activity in catalyzing CO oxidation at low temperatures, resulting in exceptional sensitivity and selectivity toward CO in comparison to pure SnO 2 and Pd nanoparticles loaded on SnO 2 respectively. In situ FTIR measurements unravel CO adsorption kinetics on ADC Pd/SnO 2 under reaction conditions, and a possible sensing mechanism is put forth in which CO is transformed into CO 2 by reaction with active oxygen species; and concurrently, carbon-related species (bicarbonates and carbonates) are formed and decomposed into CO 2 .

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

Boosting RDataFrame performance with transparent bulk event processing

RDataFrame is ROOT’s high-level interface for Python and C++ data analysis. Since it first became available, RDataFrame adoption has grown steadily and it is now poised to be a major component of analysis software pipelines for LHC Run 3 and beyond. Thanks to its design inspired by declarative programming principles, RDataFrame enables the development of highperformance, highly parallel analyses without requiring expert knowledge of multi-threading and I/O: user logic is expressed in terms of self-contained, small computation kernels tied together by a high-level API. This design completely decouples analysis logic from its actual execution, and opens several interesting avenues for workflow optimization. In particular, in this work we explore the benefits of moving internal data processing from an event-by-event to a bulkby-bulk loop. This refactoring dramatically reduces the framework’s runtime overheads; in collaboration with the I/O layer it improves data access patterns; it exposes information that optimizing compilers might use to auto-vectorize the invocation of user-defined computations; finally, while existing user-facing interfaces remain unaffected, it becomes possible to additionally offer interfaces that explicitly expose bulks of events, useful e.g. for the injection of GPU kernels into the analysis workflow. In order to inform similar future R&D, design challenges will be presented, as well as an investigation of the relevant timememory trade-off backed by novel performance benchmarks.

Guiraud, Enrico↗
DOE OSTI2023

Generation of entangled-photons by a quantum dot cascade source in polarized cavities: Using cavity resonances to boost signals and preserve the entanglements

Motivated by recent advances in the development of single photon emitters for quantum information sciences, here we design and formulate a quantum cascade model that describes cascade emission by a quantum dot (QD) in a cavity structure while preserving entanglement that stores information needed for single photon emission. The theoretical approach is based on a photonic structure that consists of two orthogonal cavities in which resonance with either the first or second of the two emitted photons is possible, leading to amplification and rerouting of the entangled light. The cavity–QD scheme uses a four-level cascade emitter that involves three levels for each polarization, leading to two spatially entangled photons for each polarization. By solving the Schrodinger equation, we identify the characteristic properties of the system, which can be used in conjunction with optimization techniques to achieve the “best” design relative to a set of prioritized criteria or constraints in our optical system. The theoretical investigations include an analysis of emission spectra in addition to the joint spectral density profile, and the results demonstrate the ability of the cavities to act as frequency filters for the photons that make up the entanglements and to modify entanglement properties. The results provide new opportunities for the experimental design and engineering of on-demand single photon sources.

Chemistry↗