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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Size‐Controlled Cobalt Nanoplates and Their Impact on Oxygen Evolution Catalysis

Controlling the size of nanoparticles is important in catalytic reactions, not only for tuning the surface area but also for modifying the electronic structure. However, achieving precise size control in 2D structures remains challenging. In this work, we demonstrate precise size control of cobalt nanoplates, ranging from 19 nm to 80 nm, which is achieved by tuning the ratio of two surfactants used in the synthesis. The 19 nm of Co nanoplates exhibit higher oxygen evolution reaction activity due to a higher proportion of {10$\overline{1}$1} to {0001} facets. In conclusion, this size control allows systematic investigation into how nanoplate dimensions influence catalytic performance in the oxygen evolution reaction, offering new insights into structure-activity relationships of cobalt nanocatalysts.

defect↗
DOE OSTI2021

Dynamic Distribution of High-Rate Data Processing from CERN to Remote HPC Data Centers

The prompt reconstruction of the data recorded from the Large Hadron Collider (LHC) detectors has always been addressed by dedicated resources at the CERN Tier-0. Such workloads come in spikes due to the nature of the operation of the accelerator and in special high load occasions experiments have commissioned methods to distribute (spill-over) a fraction of the load to sites outside CERN. The present work demonstrates a new way of supporting the Tier-0 environment by provisioning resources elastically for such spilled-over workflows onto the Piz Daint Supercomputer at CSCS. Furthermore, this is implemented using containers, tuning the existing batch scheduler and reinforcing the scratch file system, while still using standard Grid middleware. ATLAS, CMS and CSCS have jointly run selected prompt data reconstruction on up to several thousand cores on Piz Daint into a shared environment, thereby probing the viability of the CSCS high performance computer site as on demand extension of the CERN Tier-0, which could play a role in addressing the future LHC computing challenges for the high luminosity LHC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Evolution of Structural Order and Magnetic Anisotropy in Yb 0.5 (Co 1– x Fe x ) 3 Ge 3 through Doping of a Kagome Lattice

Kagome materials provide fruitful grounds for exploring the intersection of topology and magnetism. In this article, the single crystal growth of Yb 0.5 (Co 1–x Fe x ) 3 Ge 3 (x = 0.00, 0.25, 0.50, 0.75, and 1.00) is reported. As Fe is substituted into the Co-containing kagome net, the structure transforms from the disordered Y 0.5 Co 3 Ge 3 /CoSn-type hybrid structure to the ordered HfFe 6 Ge 6 -type structure. Diffusive scattering is observed in all doped concentrations that eventually converge to a single reflection in the Fe end member, ultimately doubling the unit cell along the c-axis. Anisotropic magnetic measurements were performed to evaluate how the magnetism of the kagome lattice is influenced by Fe substitution. Magnetic interactions are primarily observed along the c-axis. Additionally, a reorientation of the magnetic easy axis is observed with increasing Fe incorporation, highlighting how the magnetism of this material can be chemically tuned. Resistivity with unusual behavior observed in the doped compositions is also reported. Furthermore, the rationale behind the structural evolution from disordered to ordered is discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Palladium-Coated Platinum Powders with Tunable, Nanostructured Surfaces for Applications in Catalysis

Simultaneous control of nanoscale surface morphology and composition remains a challenge in preparing bimetallic catalysts, particularly at the large scale required for industrial application and with high-surface-area substrates. Atomic layer electroless deposition (ALED) is a scalable approach to prepare surface-modified metal powders in which elements more noble than the surface hydrides of the substrate metal are deposited layer-by-layer in a surface-limited fashion. In this paper, we demonstrate that high-surface-area Pt powder is a viable substrate for controlled deposition of Pd adlayers using this technique, with the potential for large-scale preparation, for use in electrocatalytic and catalytic applications such as fuel cells and functionalization of petrochemical feedstocks. Two different growth mechanisms have been proposed based on bulk and surface Pd atomic fractions obtained from atomic absorption spectroscopy and X-ray photoelectron spectroscopy, respectively. Further, spectral simulations were performed to strengthen the proposed growth mechanisms, favoring conformal growth in initial deposition followed by island formation in subsequent cycles. Observation of multiple pathways suggests a means of controlling adlayer surface morphology of ALED materials, in which an initial cycle of deposition sets the fractional coverage and subsequent cycles tune adlayer thickness.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A detailed study of interpretability of deep neural network based top taggers

Abstract Recent developments in the methods of explainable artificial intelligence (XAI) allow researchers to explore the inner workings of deep neural networks (DNNs), revealing crucial information about input–output relationships and realizing how data connects with machine learning models. In this paper we explore interpretability of DNN models designed to identify jets coming from top quark decay in high energy proton–proton collisions at the Large Hadron Collider. We review a subset of existing top tagger models and explore different quantitative methods to identify which features play the most important roles in identifying the top jets. We also investigate how and why feature importance varies across different XAI metrics, how correlations among features impact their explainability, and how latent space representations encode information as well as correlate with physically meaningful quantities. Our studies uncover some major pitfalls of existing XAI methods and illustrate how they can be overcome to obtain consistent and meaningful interpretation of these models. We additionally illustrate the activity of hidden layers as neural activation pattern diagrams and demonstrate how they can be used to understand how DNNs relay information across the layers and how this understanding can help to make such models significantly simpler by allowing effective model reoptimization and hyperparameter tuning. These studies not only facilitate a methodological approach to interpreting models but also unveil new insights about what these models learn. Incorporating these observations into augmented model design, we propose the particle flow interaction network model and demonstrate how interpretability-inspired model augmentation can improve top tagging performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Low-Carbon District Heating: Performance Modeling of Hybrid Solar, Heat Pump, and Thermal Storage Systems for District Thermal Energy in the United States

District heating requires thermal energy in the temperature range of 40 degrees C - 120 degrees C. Typically, the thermal energy input for these systems has largely been met through fossil energy. However, the temperature range is low enough that it presents an opportunity for low-carbon technologies such as solar thermal and electrified thermal generators like heat pumps to decarbonize the heat generation. In this paper, a heat pump model was applied to estimate the performance and economics of a real-world low-carbon district heating substation. This system is comprised of a flat plate solar collector field paired with a mechanical vapor compression heat pump and hot water thermal storage, augmented by gas-fired boilers. Plant data was used to tune the model and estimate the system's benefits in terms of both standard financial metrics (IRR and payback), and environmental metrics, including avoided CO2 emissions. The model is subsequently employed to estimate the technical and economic potential of solar + heat pump + ther-mal storage hybrid systems as retrofits for district heating systems in eight US Markets.

district heating↗
DOE OSTI2023

B—N–Bond–Embedded Triplet Terpolymers with Small Singlet–Triplet Energy Gaps for Suppressing Non–Radiative Recombination and Improving Blend Morphology in Organic Solar Cells

Suppressing the photon energy loss (E loss ), especially the non-radiative loss, is of importance to further improve the device performance of organic solar cells (OSCs). However, typical π-conjugated semiconductors possess a large singlet–triplet energy gap (ΔE ST ), leading to a lower triplet state than charge transfer state and contributing to a non-radiative loss channel of the photocurrent by the triplet state. Herein, a series of triplet polymer donors are developed by introducing a BNIDT block into the PM6 polymer backbone. Further, the high electron affinity of BNIDT and the opposite resonance effect of the B—N bond in BNIDT results in a lowered highest occupied molecular orbital (HOMO) and a largely reduced ΔE ST . Moreover, the morphology of the active blends is also optimized by fine-tuning the BNIDT content. Therefore, non-radiative recombination via the terminal triplet loss channels and morphology traps is effectively suppressed. The PNB-3 (with 3% BNIDT):L8-BO device exhibits both small ΔE ST and optimized morphology, favoring more efficient charge transfer and transport. Finally, the simultaneously enhanced V oc of 0.907 V, J sc of 26.59 mA cm –2 , and FF of 78.86% contribute to a champion PCE of 19.02%. Therefore, introducing B—N bonds into benchmark polymers is a possible avenue toward higher-performance of OSCs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Heavy ion irradiation effects on CrFeMnNi and AlCrFeMnNi high entropy alloys

Co-free but Al-included medium/high entropy alloys (M/HEAs) have gained increasing interests due to their lower cost and the potential to tune the multi-phase microstructure. The irradiation response of two Co-free HEAs, face-centered cubic (FCC) CrFeMnNi with limited Cr enriched α' phase and body-centered cubic (BCC) AlCrFeMnNi with B2s phase and nanoprecipitates were explored. Ion irradiations using 5 MeV Fe 2+ ions were performed at 500°C to a peak fluence of 50 and/or 100 displacements per atom (dpa). In dual-phase AlCrFeMnNi, there was no significant radiation induced segregation or chemical intermixing at the coherent matrix (FeCrMn-rich)/second phase (AlNi-rich) boundaries. In CrFeMnNi, limited voids were only detected at the peak damage location of ~ 50 dpa. On the other hand, voids were widely distributed in AlCrFeMnNi: under 50 and 100 dpa irradiation conditions, voids were found with larger dimension and denser distribution in the FeCrMn-rich matrix, smaller and slightly lower density in an AlNi-rich second phase. In addition, the diameter of the FeCMn-rich nanoprecipitates didn't reveal any tendency of dissolution or growth. This is correlated with their superior structural stability against irradiation. Significant radiation-induced hardening (increases from 3.8 ± 0.2 GPa to 4.7 ± 0.6 GPa) was measured in CrFeMnNi, but only ~ 4% hardness increase (from 7.4 ± 0.8 GPa to 7.7 ± 0.4 GPa) was noted in AlCrFeMnNi. Finally, in addition to the radiation-induced defects, such as voids, dislocation loops and point defects, other factors, such as chemical short-range ordering may play an important role.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Electric Field Control of Magnetic Skyrmion Helicity in a Centrosymmetric 2D van der Waals Magnet

Two-dimensional van der Waals magnets hosting topological magnetic textures, such as skyrmions, show promise for spintronics and quantum computing. Electrical control of these topological spin textures is crucial for enhancing operational performance and functionality. Here, using electron microscopy combined with in situ electric and magnetic biasing, we show that the skyrmion helicity in insulating Cr 2 Ge 2 Te 6 can be controlled by the direction of the external electric field applied during the field cooling process. The electric field-tuned helicity remains stable at low temperature, even amid variations in magnetic and electric fields. Our theoretical investigation reveals that nonzero Dzyaloshinskii-Moriya interactions between nearest neighbors, induced by the electric field, change their sign upon reversing the electric field direction, thereby facilitating helicity selection. The electrical control of magnetic helicity demonstrated in this study can be extended to other centrosymmetric skyrmion-hosting magnets, paving the way for future device designs in topological spintronics and quantum computing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Tailoring electron transfer pathway for photocatalytic N 2 -to-NH 3 reduction in a CdS quantum dots-nitrogenase system

The combination of abiotic photosensitizers with purified enzymes in a biohybrid system offers a promising pathway to utilizing light to accomplish challenging chemical transformations and provides insights into the rational photocatalytic system design for efficient solar-to-chemical energy conversion. In this work, we demonstrate a hybrid photocatalytic system for ammonia production from N2 by combining cadmium sulfide quantum dots (CdS QDs) and Mo-nitrogenase from Azotobacter vinelandii, composed of the iron protein (FeP) and the molybdenum-iron protein (MoFeP). Photoexcited electrons from the CdS QD are delivered by an electron transfer mediator through the FeP to the catalytic MoFeP. The complete system was optimized for the ligand on the CdS QDs, mediators, and reaction conditions. The best results were achieved with β-mercaptoethanol as a QD ligand. The mediator test revealed that 1,1'-bis(3-sulfonatopropyl)-4,4'-bipyridinium (SPr)2V (-0.4 V vs. NHE) supports the reduction of protons and N 2 to H 2 and ammonia catalyzed by nitrogenase. However, in the presence of 1,1'-trimethylene-2,2'-bipyridinium TQ (-0.54 V vs. NHE) as a mediator, nitrogenase catalysis resulted in remarkably more products. The UV-vis and in situ potentiometric studies revealed that better performance with TQ is achieved due to the significantly more negative solution potential allowing for efficient reduction of FeP. As a result, the quantum yield for conversion of absorbed photons to ammonia attains 16%, far exceeding that of previously reported nitrogenase-based systems. This work reveals the importance of tuning the electron transfer pathways in photocatalytic systems and illustrates a potent strategy for efficient electronic coupling of a photosensitizer and an N 2 reduction catalyst.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Data-Driven RANS Turbulence Closures for Forced Convection Flow in Reactor Downcomer Geometry

Recent progress in data-driven turbulence modeling has shown its potential to enhance or replace traditional equation-based Reynolds-averaged Navier-Stokes (RANS) turbulence models. Here, this work utilizes invariant neural network (NN) architectures to model Reynolds stresses and turbulent heat fluxes in forced convection flows (when the models can be decoupled). As the considered flow is statistically one dimensional, the invariant NN architecture for the Reynolds stress model reduces to the linear eddy viscosity model. To develop the data-driven models, direct numerical and RANS simulations in vertical planar channel geometry mimicking a part of the reactor downcomer are performed. Different conditions and fluids relevant to advanced reactors (sodium, lead, unitary-Prandtl-number fluid, and molten salt) constitute the training database. The models enabled accurate predictions of velocity and temperature, and compared to the baseline k–τ turbulence model with the simple gradient diffusion hypothesis, do not require tuning of the turbulent Prandtl number. The data-driven framework is implemented in the open-source graphics processing unit–accelerated spectral element solver nekRS and has shown the potential for future developments and consideration of more complex mixed convection flows.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Single-hole physics in GaAs/AlGaAs double quantum dot system with strong spin–orbit interaction

There is rapidly expanding interest in exploiting the spin of valence-band holes rather than conduction-band electrons for spin qubit semiconductor circuits composed of coupled quantum dots. The hole platform offers stronger spin–orbit interaction (SOI), large difference between in-dot-plane and out-of-dot-plane g-factors, i.e. g-factor anisotropy, and a significantly reduced hyperfine coupling to nuclei in the host material. These attributes collectively can deliver fast all-electric coherent spin manipulation, efficient spin-flip inter-dot tunneling channels, a voltage tunable effective g-factor, a g-factor adjustable to nearly zero in an appropriately oriented external magnetic field, and long spin relaxation and coherence times. In this work, we review our recent work on the physics of heavy holes confined in a planar GaAs/AlGaAs double quantum dot system with strong SOI. For a single-hole, we have performed resonant tunneling magneto-spectroscopy to extract spin-flip and spin-conserving tunneling strengths, implemented spin-flip Landau–Zener–Stückelberg–Majorana (LZSM) interferometry, determined the spin relaxation time T 1 as a function of magnetic field using a fast single-shot latched charge technique, electrically tuned the effective g-factor revealed by electric dipole spin resonance, and found signatures of the hyperfine interaction and dynamic nuclear polarization with holes. For two-holes, we have measured the energy spectrum in the presence of strong SOI (and so not limited by Pauli spin blockade), quantified the heavy-hole (HH) g-factor anisotropy on tilting the magnetic field, described a scheme to employ HHs whose g-factor is tunable to nearly zero for an in-plane magnetic field for a coherent photon-to-spin interface, and observed a well-defined LZSM interference pattern at small magnetic fields on pulsing through the singlet-triplet anti-crossing.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Load Profile Inpainting for Missing Load Data Restoration and Baseline Estimation

This paper introduces a Generative Adversarial Nets (GAN) based, Load Profile Inpainting Network (Load-PIN) for restoring missing load data segments and estimating the baseline for a demand response event. The inputs are time series load data before and after the inpainting period together with explanatory variables (e.g., weather data). Here, we propose a Generator structure consisting of a coarse network and a fine-tuning network. The coarse network provides an initial estimation of the data segment in the inpainting period. The fine-tuning network consists of self-attention blocks and gated convolution layers for adjusting the initial estimations. Loss functions are specially designed for the fine-tuning and the discriminator networks to enhance both the point-to-point accuracy and realisticness of the results. We test the Load-PIN on three real-world data sets for two applications: patching missing data and deriving baselines of conservation voltage reduction (CVR) events. We benchmark the performance of Load-PIN with five existing deep-learning methods. Our simulation results show that, compared with the state-of-the-art methods, Load-PIN can handle varying-length missing data events and achieve 15-30% accuracy improvement.

14 SOLAR ENERGY↗
DOE OSTI2023

Adaptive Deep Reinforcement Learning Algorithm for Distribution System Cyber Attack Defense With High Penetration of DERs

With grid modernization, smart inverters are increasingly used to execute advanced controls for distribution network reliability. However, this also increases the cyber-attack space. Here this paper focuses on the defense approaches to restore the system to normal operation circumstances in the presence of cyber-attacks. A unique deep reinforcement learning (DRL) method is developed to minimize voltage violations and reduce power losses for impacted feeders. The defense problem is reformulated as a Markov decision-making process to dynamically control DERs while minimizing load shedding. This is achieved via an improved soft actor-critic (SAC)-based DRL algorithm, which can govern DER set points and load-shedding scenarios in discrete and continuous modes via the auto-tune entropy and Gaussian policy features. Numerical comparison results on the modified IEEE 123-node system with other control approaches, such as Volt-VAR (VV), Volt-Watt (VW), and model predictive control (MPC) show that the proposed method can eliminate voltage violations and provide feasible control actions that perform complete mitigation of cyber-threats.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A numerical investigation of coal particle modeling for the inlet section of a pressurized oxy-combustion burner

Concerns over climate change have led to numerous efforts to develop low-carbon technologies, and pressurized oxy-combustion (POC) is a promising candidate to reduce carbon emissions in the power industry. Designing an effective burner for such technologies is vital for the development of these and other coal combustion technologies. Because of the high pressure, the volume fraction of coal particles at the fuel inlet of the pressurized oxy-combustor burner is close to or even higher than the maximum limit for commercial CFD codes (e.g., ANSYS FLUENT). At these high particle volume fractions, the interactions among particles, fluid flow and wall need to be re-evaluated. The present computational work is a first step in a systematic analysis of the influence of various parameters, like method of particle release, release location, and particle size, in a pilot-scale POC combustor, developed at Washington University in St. Louis (WUSTL). In the POC process, pulverized coal is burned under elevated pressure in an O2-CO2 environment. Specifically, a 15-bar, 100 kWth, POC combustor is modeled employing Ansys FLUENT commercial sodtware using the Reynolds-Averaged Navier-Stokes (RANS) approach. It is revealed that for this pilot-scale, pressurized burner, velocity profiles in the near-wall region exhibit some anomalies. In order to investigate the influence of particle loading in the near-wall region, particle release location was investigated. The numerical simulations incorporate the coupling between the turbulent flow and the particles. A sensitivity investigation of particle release location found that by tuning the release location, the velocity profile can be consistent with the pure gas flow velocity profile. More importantly, the particle releasing location also affects flame stability. Particle size was also found to have a significant impact on particle trajectory, flame stability and temperature. Finally, Large Eddy Simulations (LES) were performed and compared with the results from two-dimensional RANS.

Li, Lei↗
DOE OSTI2021

Optimizing the self-assembly of conjugated polymers and small molecules through structurally programmed non-covalent control

Organic conjugated polymers and oligomers are key electronic materials for applications such as transistors, photovoltaics, and light emitting devices due to their potential for solution processability, mechanical flexibility, and precise structure-based tuning compared to inorganic materials. In dilute environments, the optoelectronic properties of conjugated polymers are largely governed by their constitutional structure and, to a lesser degree, their solution-state intramolecular configuration. In the solid state, intramolecular conformation and intermolecular electronic coupling impact these properties substantially, especially in relation to device performance. Therefore, an increasingly important area of research concerning conjugated materials is developing design strategies aimed at optimizing the solid-state packing for electronic applications. Programming solid-state packing arrangements through discrete non-covalent interactions is an emerging strategy within the context of conjugated polymers. This review focuses on the use of the two most prevalent discrete and directional interactions used to dictate the self-assembly of conjugated polymers and oligomers—hydrogen bonds and chalcogen bonds. Further, we also discuss how these design motifs can imbue conjugated materials with appealing physical properties while simultaneously retaining or improving electronic capabilities.

36 MATERIALS SCIENCE↗
DOE OSTI2021

NO x adsorption with CO and C 2 H 4 on Pd/SSZ-13: Experiments and modeling

A transient monolith model containing microkinetic schemes for NO uptake and release over Pd/SSZ-13 without and with reductants CO or C2H4 is presented. The scheme involves three cationic Pd species (Z – [PdOH] + , Z – Pd 2+ Z – , Z – Pd + ) as the active sites during uptake of NO, CO and C 2 H 4 , and their desorption and conversion at higher temperature. Kinetic parameters are estimated through a combination of density functional theory (DFT) estimates and a fit of uptake, desorption and conversion data. The tuned model is validated at different uptake temperatures, ramp rates, and flowrates. A “degree of uptake control” parameter is defined that helps to identify the step(s) that are uptake controlling. The model helps to interpret the data features and is used to identify operating conditions to meet application-relevant performance metrics, including NO trapping efficiency and NO release temperature. Furthermore, the model demonstrates higher NO uptake on Pd/SSZ-13 compared to Pd/ZSM-5.

42 ENGINEERING↗
DOE OSTI2022

New bipolar host materials for high power efficiency green thermally activated delayed fluorescence $\mathrm{OLEDs}$

We report four bipolar molecules, namely m-CzPym, p-CzPym, m-CzTrz, and p-CzTrz, with carbazole (Cz) donor and a benzonitrile-substituted pyrimidine (Pym) or triazine (Trz) acceptor core were synthesized and characterized. The electron deficiency of heteroaryl cores together with the substitution pattern of benzonitrile were employed to tune the energy levels as well as the thermally activated delayed fluorescence (TADF) characteristics. The four molecules exhibited TADF behavior with inferior photoluminescent quantum yields (PLQYs) that limit their applications as emitters. These bipolar molecules were employed as TADF host materials for the benchmark TADF emitter 4CzIPN to achieve high-performing green TADF organic light-emitting diodes (OLEDs). Among the molecules, m-CzPym-hosted TADF-OLEDs achieved a maximum external quantum efficiency (EQE max ) of 31.5%, maximum power efficiency (PE max ) of 95.6 lm/W, and maximum current efficiency (CE max ) of 100.2 cd/A. Notably, p-CzPym-hosted TADF-OLEDs also achieved a PE max of 116.5 lm/W, turn-on voltage of 2.5 V, and impressive low efficiency roll-off performance (>89% of EQE max at 5000 cd/m 2 ), representing one of the highest efficiencies ever reported in 4CzIPN-doped devices. The high device efficiency can be ascribed to the balanced ambipolar carrier-transporting character of the host materials and high PLQY as well as the outstanding light outcoupling efficiency of the emitting layer.

42 ENGINEERING↗