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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Scalable Real-Time Data Assimilation Framework for Predicting Turbulent Atmosphere Dynamics

AI-based foundation models like FourCastNet, GraphCast are revolutionizing weather and climate predictions but are not yet ready for operational use. Their limitation lies in the absence of a data assimilation system to incorporate real-time Earth system observations, crucial for accurately forecasting events like tropical cyclones. To overcome these obstacles, we introduce a generic real-time data assimilation framework and demonstrate its end-to-end performance on the Frontier supercomputer. This framework comprises two primary modules: an ensemble score filter (EnSF), which significantly outperforms the state-of-the-art data assimilation method, and a vision transformer-based surrogate capable of real-time adaptation through the integration of observational data. We demonstrate both the strong and weak scaling of our framework up to 1024 GPUs on the Exascale supercomputer, Frontier. Our results not only illustrate the framework's exceptional scalability on high-performance computing systems, but also demonstrate the importance of supercomputers in real-time data assimilation for weather and climate predictions.

Lu, Dan↗
DOE OSTI2021

Benchmark Testing on the IBM-Q Network

The goal of this project is to evaluate a proposed set of candidate benchmarks being developed by the Standards and Performance Metrics Technical Advisory Group (TAG) of the Quantum Economic Development Consortium (QED-C), of which LANL is a member. The QED-C Standards and Performance Metrics TAG has developed implementations of several benchmark codes with the hope and expectation that these codes will be helpful to QED-C members interested in investigating various quantum computer platforms. The benchmark set will be run on LANL’s access to the IBM-Q system with the intent to evaluate the set for scalability, correct execution, and coverage of the application space. The goal is for the QED-C Standards and Performance Metrics TAC to be able to produce a coherent, consistent, scalable set of benchmarks that will run on multiple quantum computing platforms and will be available to members of QED-C, including LANL.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Accelerating Manufacturing of Powder-Processed Strong, Lightweight and Thermally Stable Bulk Nanocrystalline Al Alloys via Engineered Interface States

The overarching goal of this program is to develop an integrated materials by design framework enabling a simple, scalable, and efficient manufacturing route for thermally stable nanocrystalline Al-based alloys with high specific strength over a range of service temperatures. The central scientific principle underpinning this program is the elucidation, and ultimately implementation in novel alloy design, of unique interfacial structures and chemistries driven by segregation in multi-component systems that give rise to unprecedented processability and properties. This program targeted nanocrystalline Al-based ternary alloys produced by mechanical alloying of powders followed by compaction and sintering with hot pressing, which are inherently scalable and inexpensive manufacturing routes, but when applied to nanocrystalline alloys are usually plagued by low density and/or poor retention of the intended nanostructures during processing. This program successfully demonstrated manufacturing of a bulk (>1 cm 3 ) nanocrystalline Al-based alloy with a combination of thermal stability, high temperature strength retention, and specific strength that exceeds the current-state-of-the-art of Al alloys. It is anticipated that the greatest technological impact will occur by demonstration of rapid and scalable manufacturing of bulk nanocrystalline Al alloys with exceptional thermal stability and mechanical performance, thus enabling increased energy efficiency in high performance power generation systems via: (i) replacement of existing components with lightweight Al-based alloys and (ii) increasing operating temperatures with property retention. The program focused on the development of a simple and efficient manufacturing route for thermally stable nanocrystalline Al-based alloys with high specific strength over a range of service temperatures. The program is expected to have direct impact on scalable and economic manufacturing of bulk nanocrystalline alloys. This program profited from the recent discovery by the project team of segregation-driven amorphous intergranular films in nanocrystalline metallic alloys that can be kinetically frozen-in at sub-solidus temperatures. These interfacial states (also known as amorphous complexions) comprise a large fraction of the total material in nanocrystalline alloys and are responsible for two beneficial characteristics that anchor the proposed work: (1) activated sintering leading to high density and (2) retained nanostructures leading to high strengths that approach a substantial fraction of the theoretical limit. More specifically, these engineered interfaces led to a three-fold benefit: (i) high-throughput materials processing with low energy budget and cost, (ii) exceptional thermal stability, and (iii) high specific strength at both room temperature and intermediate temperatures experienced during service.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Atomic Layer Deposition for Improved Biomass Conversion Catalysts

Heterogeneous catalysts are a key enabler of the transition towards a sustainable, bio-based economy for fuels and chemicals. However, the harsh conditions in many biomass conversion processes lead to nanoparticle sintering, support collapse, and metal leaching in conventional PGM catalysts. Next-generation catalysts must be developed to address these stability challenges. This presentation will discuss ongoing work between the Catalytic Carbon Transformation & Scale-Up Center at NREL and various industrial partners to develop scalable, cost-effective atomic layer deposition (ALD) coatings for improving the performance of biomass conversion catalysts. Substantial focus will be devoted to the benefits of TiO2 ALD coatings on supported Pd hydrogenation catalysts. Ten cycles of TiO2 ALD were found to dramatically improve the activity of a conventional Pd/Al2O3 catalyst towards aromatic hydrogenation, despite partial coverage of the Pd sites by the ALD layer. Subsequent advanced characterization and atomic-scale computational modeling revealed that the ALD coating influenced the adsorption strength of hydrogenation surface intermediates in unexpected ways, leading to higher reaction rates. Reaction testing after exposure to sulfur impurities, high temperature oxidation, and hydrothermal treatment demonstrated the improved stability of the ALD-coated catalyst. Additionally, the ALD synthesis process was found to be scalable over two orders of magnitude with minimal deviation in synthesized catalyst properties. These results were contextualized with cost models of industrial ALD coating and aromatic hydrogenation processes to further refine the value proposition of ALD coatings. Given the demonstrated improvements in hydrogenation, TiO2 ALD coatings have also been applied to supported Pt catalysts for use in other biomass conversion reactions, such as hydrodeoxygenation for production of sustainable aviation fuel (SAF) and the oxidation of glucose for bio-derived gluconic acid. Recent findings from these experimental campaigns will also be shared. ALD technology holds great potential in the development of next-generation catalysts for biofuels and bioproducts and this work constitutes an important examination of the impact of ALD coatings in a variety of reaction environments.

bioenergy↗
NASA NTRS2020

Pterodactyl: The Development and Performance of Guidance Algorithms for a Mechanically Deployed Entry Vehicle

Pterodactyl is a NASA Space Technology Mission Directorate (STMD) project focused on developing a design capabilityfor optimal, scalable, Guidance and Control (G&C) solutions that enable precision targeting for Deployable Entry Vehicles(DEVs). This feasibility study is unique in that it focuses on the rapid integration of targeting performance analysis withstructural &packaging analysis, which is especially challenging for new vehicle and mission designs. This paper will detailthe guidance development and trajectory design process for a lunar return mission, selected to stress the vehicle designsand encourage future scalability. For the five G&C configurations considered, the Fully Numerical Predictor-CorrectorEntry Guidance (FNPEG) was selected for configurations requiring bank angle guidance and FNPEG with Uncoupled

Johnson, Breanna↗
DOE OSTI2024

Addressing GPU memory limitations for Graph Neural Networks in High-Energy Physics applications

Introduction Reconstructing low-level particle tracks in neutrino physics can address some of the most fundamental questions about the universe. However, processing petabytes of raw data using deep learning techniques poses a challenging problem in the field of High Energy Physics (HEP). In the Exa.TrkX Project, an illustrative HEP application, preprocessed simulation data is fed into a state-of-art Graph Neural Network (GNN) model, accelerated by GPUs. However, limited GPU memory often leads to Out-of-Memory (OOM) exceptions during training, due to the large size of models and datasets. This problem is exacerbated when deploying models on High-Performance Computing (HPC) systems designed for large-scale applications. Methods We observe a high workload imbalance issue during GNN model training caused by the irregular sizes of input graph samples in HEP datasets, contributing to OOM exceptions. We aim to scale GNNs on HPC systems, by prioritizing workload balance in graph inputs while maintaining model accuracy. Our paper introduces diverse balancing strategies aimed at decreasing the maximum GPU memory footprint and avoiding the OOM exception, across various datasets. Results Our experiments showcase memory reduction of up to 32.14% compared to the baseline. We also demonstrate the proposed strategies can avoid OOM in application. Additionally, we create a distributed multi-GPU implementation using these samplers to demonstrate the scalability of these techniques on the HEP dataset. Discussion By assessing the performance of these strategies as data loading samplers across multiple datasets, we can gauge their effectiveness in both single-GPU and distributed environments. Our experiments, conducted on datasets of varying sizes and across multiple GPUs, broaden the applicability of our work to various GNN applications that handle input datasets with irregular graph sizes.

Lee, Claire Songhyun↗
DOE OSTI2023

Enhancing the Electrochemical Performance of Aqueous Processed Li-Ion Cathodes with Silicon Oxide Coatings

Lithium-ion battery cathode materials suffer from bulk and interfacial degradation issues, which negatively affect their electrochemical performance. Oxide coatings can mitigate some of these problems and improve electrochemical performance. However, current coating strategies have low throughput, are expensive, and have limited applicability. In this article, we describe a low-cost and scalable strategy for applying oxide coatings on cathode materials. Here, we report synergistic effects of these oxide coatings on the performance of aqueously processed cathodes in cells. The SiO 2 coating strategy developed herein improved mechanical, chemical, and electrochemical performance of aqueously processed Ni-, Mn- and Co-based cathodes. This strategy can be used on a variety of cathodes to improve the performance of aqueously processed Li-ion cells.

25 ENERGY STORAGE↗
DOE OSTI2020

Towards scalable dataframe systems

Dataframes are a popular abstraction to represent, prepare, and analyze data. Despite the remarkable success of dataframe libraries in R and Python, dataframes face performance issues even on moderately large datasets. Moreover, there is significant ambiguity regarding dataframe semantics. In this paper we lay out a vision and roadmap for scalable dataframe systems. To demonstrate the potential in this area, we report on our experience building Modin, a scaled-up implementation of the most widely-used and complex dataframe API today, Python's pandas. With pandas as a reference, we propose a simple data model and algebra for dataframes to ground discussion in the field. Given this foundation, we lay out an agenda of open research opportunities where the distinct features of dataframes will require extending the state of the art in many dimensions of data management. We discuss the implications of signature dataframe features including flexible schemas, ordering, row/column equivalence, and data/metadata fluidity, as well as the piecemeal, trial-and-error-based approach to interacting with dataframes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Multifunction Hydrophobic Ligand Engineered Cd(S, Se)/ZnS Quantum Dots for Stabilizing Highly Efficient Carbon‐Based Perovskite Solar Cells

The long-term operational stability of perovskite solar cells (PSCs) remains a key challenge impeding their commercialization, particularly due to ambient environments (e.g., moisture, oxygen, heat)-induced degradation. Carbon electrode-based PSCs have emerged as cost-effective and relatively stable alternatives to metal electrode-based devices due to carbon materials' hydrophobic behavior, yet they still lag in both long-term durability and power conversion efficiency (PCE). In this work, an ultrathin hydrophobic ligand-modified core–shell Cd(S,Se)/ZnS quantum dots (QDs) capping layer is introduced as a multifunctional interfacial modifier for carbon-electrode-based PSCs. This oleic acid ligand-modified QDs capping layer exhibits inherent hydrophobicity, effectively serving as a moisture barrier to retard perovskite degradation under ambient conditions. Furthermore, the strong interfacial bonding between the QDs and perovskite halide surfaces leads to efficient trap state passivation, reducing trap density and creating a more uniform electrical contact. The modified QDs/perovskite interface also features an elevated conduction band edge, promoting improved charge extraction. As a result, devices incorporating this quantum dot capping layer retain 98% of their initial PCE after 450 h of ambient aging and achieve a champion efficiency of 20.74%. As a result, this strategy highlights the potential of hydrophobic ligand-modified chalcogenide QDs as surface modifiers to enhance both the stability and performance of carbon-based PSCs, offering a promising route toward scalable fabrication of durable perovskite solar modules.

14 SOLAR ENERGY↗
DOE OSTI2023

Silicon-Lattice-Matched Boron-Doped Gallium Phosphide: A Scalable Acousto-Optic Platform

The compact size, scalability, and strongly confined fields in integrated photonic devices enable new functionalities in photonic networking and information processing, both classical and quantum. Gallium phosphide (GaP) is a promising material for active integrated photonics due to its high refractive index, wide bandgap, strong nonlinear properties, and large acousto-optic figure of merit. Here, this study demonstrates that silicon-lattice-matched boron-doped GaP (BGaP), grown at the 12-inch wafer scale, provides similar functionalities as GaP. BGaP optical resonators exhibit intrinsic quality factors exceeding 25,000 and 200,000 at visible and telecom wavelengths, respectively. It further demonstrates the electromechanical generation of low-loss acoustic waves and an integrated acousto-optic (AO) modulator. High-resolution spatial and compositional mapping, combined with ab initio calculations, indicate two candidates for the excess optical loss in the visible band: the silicon-GaP interface and boron dimers. These results demonstrate the promise of the BGaP material platform for the development of scalable AO technologies at telecom and provide potential pathways toward higher performance at shorter wavelengths.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Sequential Separation of Linear, Mono–, and Di–Branched Hexane Isomers on a Robust Coordination Polymer with Nonbonding Flexibility

Efficient separation of hexane isomers is a crucial process for upgrading gasoline. Herein, the sequential separation of linear, mono-, and di-branched hexane isomers by a robust stacked 1D coordination polymer termed as Mn-dhbq ([Mn(dhbq)(H 2 O) 2 ], H 2 dhbq = 2,5-dihydroxy-1,4-benzoquinone) is reported. The interchain space of the activated polymer is of optimal aperture size (5.58 Å) that could exclude 2,3-dimethylbutane, while the chain structure can discriminate n-hexane with high capacity (1.53 mmol g –1 at 393 K, 6.67 kPa) by high-density open metal sites (5.18 mmol g –1 ). With the temperature- and adsorbate-dependent swelling of interchain spaces, the affinity between 3-methylpentane and Mn-dhbq can be deliberately controlled from sorption to exclusion, and thus a complete separation of ternary mixture can be achieved. Column breakthrough experiments confirm the excellent separation performance of Mn-dhbq. Furthermore, the ultrahigh stability and easy scalability further highlight the application prospect of Mn-dhbq for separation of hexane isomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Synthesis of graphene-like carbon from biomass pyrolysis and its applications

Two-dimensional graphene materials attracted much attention worldwide because of their superior performance in electronic devices, sensors, and energy storage. However, its application is limited by high cost and insufficient production. The work to find out a simple and environmentally friendly process is highly needed. Designed pyrolysis of biomass precursors can derive graphene-like materials. This review summarizes some typical preparation processes for graphene-like materials synthesis from biomass carbonization via pyrolysis, including salt-based activation, template-based confinement, chemical blowing, coupling with hydrothermal carbonization pretreatment, post exfoliation, and some other methods. The operation of these methods and the performance of obtained graphene-like materials were closely highlighted. The scalability of the techniques and the applications of the biomass graphene-like carbon were also discussed. Some advanced characterization methods, such as SEM, TEM, AFM, Raman, and XPS to determine the graphene-like structure and graphitization degree were also discussed. In the end, some current challenges and future perspectives of the synthesis of these graphene-like materials were concluded.

pyrolysis, graphene, biomass, application, scalabi↗
DOE OSTI2022

High voltage stable cycling of all-solid-state lithium metal batteries enabled by top-down direct fluorinated poly (ethylene oxide)-based electrolytes

Poly (ethylene oxide) (PEO)-based solid-state polymer electrolytes (SPEs) show prospects in all-solid-state lithium metal batteries. However, they suffer from low ionic conductivity at room temperature and interfacial instability with high voltage cathodes for long-term cycling. In this work, top-down fluorinated PEOs (F-PEOs) for the all-solid-state electrolytes, which are scalable and cost-effective, are developed to improve the battery performance. We demonstrate, that by enhancing the disordering of the F-PEO matrix, the SPE achieves a maximum Li + conductivity of 1.1 x 10 -4 S cm -1 at 40 °C, which is 20 times higher than the baseline. By forming robust cathode/SPE and Li/SPE interfaces, the F-PEO-based SPEs demonstrate stable cycling in the LiFePO 4 /Li and LiNi 0·8 Mn 0·1 Co 0·1 O 2 /Li (3-4.4 V, 500 cycles, capacity retention of 91.6%) based all-solid-state batteries at 40 °C. Therefore, our work highlights the significance of "disordering engineering" for energy storage materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

An algorithm for resolving intragranular orientation fields using coupled far-field and near-field high energy $\mathrm{X}$-ray diffraction microscopy

Here, we present a novel algorithm for reconstructing spatial intragranular lattice orientation fields using both far-field and near-field high energy X-ray diffraction microscopy (HEDM) measurements. An established far-field indexing algorithm is modified to include lattice orientation distribution information (grain orientation envelopes) in addition to average grain orientations. The near-field data reduction algorithm utilizes this enriched far-field orientation data as a seed for reconstructing intragranular spatial maps of lattice orientation from the diffraction images. The primary benefit of the new algorithm is a significant decrease in the number of trial calculations that must be performed in the reconstruction process compared to existing methodologies while maintaining scalability. The resulting gains in efficiency facilitate the use of relatively modest computational resources and improve throughput at the point of measurement. We provide two example applications: volumetric orientation field reconstructions for a Ti-Al alloy both before and after the application of 3% uniaxial strain. The results showcase the efficiency of the new method and the ability to resolve subtle changes in microstructure, which are associated with incipient plastic deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Utilizing the unique charge extraction properties of antimony tin oxide nanoparticles for efficient and stable organic photovoltaics

Simultaneously enhancing device performance and longevity, as well as balancing the requirements on cost, scalability, and simplification of processing, is the goal of interface engineering of organic solar cells (OSCs). In our work, we strategically introduce antimony (Sb 3+ ) cations into an efficient and generic n-type SnO 2 nanoparticles (NPs) host during the scalable flame spray pyrolysis synthesis. Accordingly, a significant switch of conduction property from an n-type character to a p-type character is observed, with a corresponding shift in the work function (WF) from 4.01 ± 0.02 eV for pristine SnO 2 NPs to 5.28 ± 0.02 eV for SnO 2 NPs with 20 mol. % Sb content (ATO). Both pristine SnO 2 and ATO NPs with fine-tuned optoelectronic properties exhibit remarkable charge carrier extraction properties, excellent UV resistance and photo-stability being compatible with various state-of-the-art OSCs systems. The reliable and scalable pristine SnO 2 and ATO NPs processed by doctor-blading in air demand no complex post-treatment. Our work offers a simple but unique approach to accelerate the development of advanced interfacial materials, which could circumvent the major existing interfacial problems in solution-processed OSCs.

14 SOLAR ENERGY↗
DOE OSTI2020

Integrated Reference Electrodes in Anion-Exchange-Membrane Electrolyzers: Impact of Stainless-Steel Gas-Diffusion Layers and Internal Mechanical Pressure

Alkaline-membrane electrolyzers operating in pure water might provide scalable low-cost H 2 production but currently lag in performance and durability compared to commercial technologies. Typically, membrane–electrode assemblies (MEAs) are optimized in electrolyzers by changing one parameter at a time and assessing the resulting system performance via two-electrode polarization and impedance measurements. These approaches are limited in their ability to assign performance changes and durability to specific electrodes or processes. We integrate a reference electrode with the MEA to separate anode and cathode responses in both polarization and impedance measurements. Here we illustrate the power of the approach by showing how the fiber diameter of stainless-steel gas-diffusion layers (GDLs) affects performance solely at the anode, while changing the thickness of the cathode GDL simultaneously affects the performance of the anode and cathode due to changes in internal pressure from mechanical compression. This finding was obscured in conventional two-electrode measurements. The work thus guides both high-performance alkaline-membrane water-electrolyzer development and illustrates a useful strategy to study structure–activity relationships in the MEA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Bound Exciton Complexes in Near-Infrared Emitting Quantum Shells

Near-infrared (NIR) light sources based on colloidal semiconductor nanocrystals (NCs) represent a scalable, low-cost alternative to epitaxial semiconductor platforms. However, their performance remains hindered by rapid Auger recombination, a problem that is particularly pronounced in narrow-bandgap materials. Here, we report on CdS/HgS/CdS and CdS/HgCdSe/ ZnS quantum shells (QSs), a class of spherical quantum wells specifically engineered for a suppression of nonradiative Auger processes. Fabricated QSs exhibit tunable NIR emission with photoluminescence quantum yields reaching ∼60% below 1000 nm and up to 30% near 1300 nm. Optical gain and stimulated emission were observed in CdS/HgS/CdS QSs. In contrast, CdS/HgCdSe/ZnS QSs displayed a photoinduced absorption in lieu of optical gain despite demonstrating a comparatively stronger Auger suppression. Transient absorption spectroscopy revealed that this phenomenon arises from the formation of bound multiexciton complexes that induce long-lived sub-bandgap multiexciton states. The observation of such bound excitonic clusters at room temperature offers a pathway toward nonlinear NIR photonic phenomena, including biexciton−exciton cascade emission, optical modulation, and singleexciton gain.

Auger recombination↗