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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

HP-MDR: High-performance and Portable Data Refactoring and Progressive Retrieval with Advanced GPUs

Scientific applications produce vast amounts of data, posing grand challenges in the underlying data management and analytic tasks. Progressive compression is a promising way to address this problem, as it allows for on-demand data retrieval with significantly reduced data movement cost. However, most existing progressive methods are designed for CPUs, leaving a gap for them to unleash the power of today’s heterogeneous computing systems with GPUs.In this work, we propose HP-MDR, a high-performance and portable data refactoring and progressive retrieval framework for GPUs. Our contributions are four-fold: (1) We carefully optimize the bitplane encoding and lossless encoding, two key stages in progressive methods, to achieve high performance on GPUs; (2) We propose pipeline optimization and incorporate it with data refactoring and progressive retrieval workflows to further enhance the performance for large data process; (3) We leverage our framework to enable high-performance data retrieval with guaranteed error control for common Quantities of Interest; (4) We evaluate HP-MDR and compare it with state of the arts using five real-world datasets. Experimental results demonstrate that HP-MDR delivers an average 13.68 × and 6.31 × throughput in data refactoring and progressive retrieval tasks, respectively. It also leads to 11.22 × throughput for recomposing required data representations under Quantity-of-Interest error control and 6.04 × performance for the corresponding end-to-end data retrieval, when compared with state-of-the-art solutions.

Li, Yanliang [University of Oregon]↗
DOE OSTI2024

Accurate machine-learning predictions of coercivity in high-performance permanent magnets

Increased demand for high-performance permanent magnets in the electric vehicle and wind-turbine industries has prompted the search for cost-effective alternatives. Discovering magnetic materials with the desired intrinsic and extrinsic permanent magnet properties presents a significant challenge to researchers because of issues with the global supply of rare-earth elements, material stability, and a low maximum magnetic energy product BH max . While first-principles density functional theory (DFT) predicts materials’ magnetic moments, magnetocrystalline anisotropy constants, and exchange interactions, it cannot compute extrinsic properties such as coercivity (H c ). Although it is possible to calculate H c theoretically with micromagnetic simulations, the predicted value is larger than the experiment by almost an order of magnitude due to the Brown paradox. To circumvent these issues, we employ machine-learning (ML) methods on an extensive database obtained from experiments, DFT calculations, and micromagnetic modeling. The use of a large experimental dataset enables realistic H c predictions for materials such as Ce-doped Nd 2 ⁢Fe 14 ⁢B, comparing favorably against micromagnetically simulated coercivities. Remarkably, our ML model accurately identifies uniaxial magneto-crystalline anisotropy as the primary contributor to H c . With DFT calculations, we predict the Nd-site-dependent magnetic anisotropy behavior in Nd 2 ⁢Fe 14 ⁢B, confirming that Nd 4⁢g sites mainly contribute to uniaxial magnetocrystalline anisotropy, and also calculate the Curie temperature (T c ). Finally, both calculated results are in good agreement with the experiments. The coupled experimental dataset and ML modeling with DFT input predict H c with far greater accuracy and speed than was previously possible using micromagnetic modeling. Further, we reverse engineer the grain-boundary and intergrain exchange coupling with micromagnetic simulations by employing the ML predictions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Demonstration and Evaluation of Lightweight High Performance Quad-Pane Windows

Ten high-performance quad-pane windows (five quad-pane with suspended film and five quad-pane with thin glass) were installed at Building 41 of the Denver Federal Center in Colorado as part of a demonstration project to assess their thermal performance, life cycle costs, and deployment potential for replacing older single-pane windows. The U.S. Department of Energy's National Renewable Energy Laboratory performed several different evaluations to assess the viability of the quad-pane windows for GSA applications. Some of these assessments were performed with models, while others required onsite evaluations including time series measurements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Near-infrared absorbing acceptor with suppressed triplet exciton generation enabling high performance tandem organic solar cells

Reducing the energy loss of sub-cells is critical for high performance tandem organic solar cells, while it is limited by the severe non-radiative voltage loss via the formation of non-emissive triplet excitons. Herein, we develop an ultra-narrow bandgap acceptor BTPSeV-4F through replacement of terminal thiophene by selenophene in the central fused ring of BTPSV-4F, for constructing efficient tandem organic solar cells. The selenophene substitution further decrease the optical bandgap of BTPSV-4F to 1.17 eV and suppress the formation of triplet exciton in the BTPSV-4F-based devices. The organic solar cells with BTPSeV-4F as acceptor demonstrate a higher power conversion efficiency of 14.2% with a record high short-circuit current density of 30.1 mA cm –2 and low energy loss of 0.55 eV benefitted from the low non-radiative energy loss due to the suppression of triplet exciton formation. We also develop a high-performance medium bandgap acceptor O1-Br for front cells. By integrating the PM6:O1-Br based front cells with the PTB7-Th:BTPSeV-4F based rear cells, the tandem organic solar cell demonstrates a power conversion efficiency of 19%. The results indicate that the suppression of triplet excitons formation in the near-infrared-absorbing acceptor by molecular design is an effective way to improve the photovoltaic performance of the tandem organic solar cells.

14 SOLAR ENERGY↗
DOE OSTI2021

Dual-Solvent Li-Ion Solvation Enables High-Performance Li-Metal Batteries

Novel electrolyte designs to further enhance the lithium (Li) metal battery cyclability are highly desirable. Here, fluorinated 1,6-dimethoxyhexane (FDMH) is designed and synthesized as the solvent molecule to promote electrolyte stability with its prolonged –CF 2 – backbone. Meanwhile, 1,2-dimethoxyethane is used as a co-solvent to enable higher ionic conductivity and much reduced interfacial resistance. Combining the dual-solvent system with 1 m lithium bis(fluorosulfonyl)imide (LiFSI), high Li-metal Coulombic efficiency (99.5%) and oxidative stability (6 V) are achieved. Using this electrolyte, 20 µm Li||NMC batteries are able to retain ≈80% capacity after 250 cycles and Cu||NMC anode-free pouch cells last 120 cycles with 75% capacity retention under ≈2.1 µL mAh -1 lean electrolyte conditions. Such high performances are attributed to the anion-derived solid-electrolyte interphase, originating from the coordination of Li-ions to the highly stable FDMH and multiple anions in their solvation environments. This work demonstrates a new electrolyte design strategy that enables high-performance Li-metal batteries with multisolvent Li-ion solvation with rationally optimized molecular structure and ratio.

25 ENERGY STORAGE↗
DOE OSTI2021

High performance ionic-liquid-gated air doped diamond field-effect transistors

Here we report successful fabrication of high performance ion-gated field-effect transistors (FETs) on hydrogenated diamond surface. Investigations on the hydrogen (H)-terminated diamond by Hall effect measurements shows Hall mobility as high as ~200 cm 2 V –1 s –1 . In addition we demonstrate a rapid fabrication scheme for achieving stable high performance devices useful for determining optimal growth and fabrication conditions. We achieved H-termination using hydrogen plasma treatment with a sheet resistivity as low as ~1.3 kΩ/sq. Conductivity through the FET channel is studied as a function of bias voltage on the liquid ion-gated electrode from –3.0 to 1.5 V. Stability of the H-terminated diamond surface was studied by varying the substrate temperature up to 350 °C. It was demonstrated that the sheet resistance and carrier densities remain stable over 3 weeks in ambient air atmosphere even at substrate temperatures up to 350 °C, whereas increasing temperature beyond this limit has effected hydrogenation. This study opens new avenues for carrying out fundamental research on diamond FET devices with ease of fabrication and high throughput.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Reactive Processing of Furan‐Based Monomers via Frontal Ring‐Opening Metathesis Polymerization for High Performance Materials

Frontal ring-opening metathesis polymerization (FROMP) presents an energy-efficient approach to produce high-performance polymers, typically utilizing norbornene derivatives from Diels–Alder reactions. This study broadens the monomer repertoire for FROMP, incorporating the cycloaddition product of biosourced furan compounds and benzyne, namely 1,4-dihydro-1,4-epoxynaphthalene (HEN) derivatives. A computational screening of Diels–Alder products is conducted, selecting products with resistance to retro-Diels–Alder but also sufficient ring strain to facilitate FROMP. The experiments reveal that varying substituents both modulate the FROMP kinetics and enable the creation of thermoplastic materials characterized by different thermomechanical properties. Moreover, HEN-based crosslinkers are designed to enhance the resulting thermomechanical properties at high temperatures (>200 °C). The versatility of such materials is demonstrated through direct ink writing (DIW) to rapidly produce 3D structures without the need for printed supports. This research significantly extends the range of monomers suitable for FROMP, furthering efficient production of high-performance polymeric materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Computational evolution of high-performing unfused non-fullerene acceptors for organic solar cells

Materials optimization for organic solar cells (OSCs) is a highly active field, with many approaches using empirical experimental synthesis, computational brute force to screen a subset of chemical space, or generative machine learning methods that often require significant training sets. While these methods may find high-performing materials, they can be inefficient and time-consuming. Genetic algorithms (GAs) are an alternative approach, allowing for the “virtual synthesis” of molecules and a prediction of their “fitness” for some property, with new candidates suggested based on good characteristics of previously generated molecules. In this work, a GA is used to discover high-performing unfused non-fullerene acceptors (NFAs) based on an empirical prediction of power conversion efficiency (PCE) and provides design rules for future work. The electron-withdrawing/donating strength, as well as the sequence and symmetry, of those units are examined. The utilization of a GA over a brute-force approach resulted in speedups up to 1.8 × 10 12 . New types of units, not frequently seen in OSCs, are suggested, and in total 5426 NFAs are discovered with the GA. Of these, 1087 NFAs are predicted to have a PCE greater than 18%, which is roughly the current record efficiency. While the symmetry of the sequence showed no correlation with PCE, analysis of the sequence arrangement revealed that higher performance can be achieved with a donor core and acceptor end groups. Future NFA designs should consider this strategy as an alternative to the current A-D-A'-D-A architecture.

14 SOLAR ENERGY↗
DOE OSTI2023

Fast correlation function calculator: A high-performance pair-counting toolkit

A novel high-performance exact pair-counting toolkit called fast correlation function calculator (FCFC) is presented. With the rapid growth of modern cosmological datasets, the evaluation of correlation functions with observational and simulation catalogues has become a challenge. High-efficiency pair-counting codes are thus in great demand. We introduce different data structures and algorithms that can be used for pair-counting problems, and perform comprehensive benchmarks to identify the most efficient algorithms for real-world cosmological applications. We then describe the three levels of parallelisms used by FCFC, SIMD, OpenMP, and MPI, and run extensive tests to investigate the scalabilities. Finally, we compare the efficiency of FCFC with alternative pair-counting codes. The data structures and histogram update algorithms implemented in FCFC are shown to outperform alternative methods. FCFC does not benefit greatly from SIMD because the bottleneck of our histogram update algorithm is mainly cache latency. Nevertheless, the efficiency of FCFC scales well with the numbers of OpenMP threads and MPI processes, even though speedups may be degraded with over a few thousand threads in total. FCFC is found to be faster than most (if not all) other public pair-counting codes for modern cosmological pair-counting applications.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Accelerating Computational Materials Discovery with Machine Learning and Cloud High-Performance Computing: from Large-Scale Screening to Experimental Validation

High-throughput computational materials discovery has promised significant acceleration of the design and discovery of new materials for many years. Despite a surge in interest and activity, the constraints imposed by large-scale computational resources present a significant bottleneck. Furthermore, examples of large-scale computational discovery carried through experimental validation remain scarce, especially for materials with product applicability. In this paper, we demonstrate how this vision became reality by first combining state-of-the-art artificial intelligence (AI) models and traditional physics-based models on cloud high performance computing (HPC) resources to quickly navigate through more than 32 million candidates and predict around half a million potentially stable materials. Focusing on solid-state electrolytes for battery applications, our discovery pipeline further identified 18 promising candidates with new compositions and rediscovered a decade’s worth of collective knowledge in the field as a byproduct. By employing around one thousand virtual machines in the cloud, this process took less than 80 hours. We then synthesized and experimentally characterized the structures and conductivities of our top candidates, the Na x Li 3-x YCl 6 (0.5 ≤ x ≤ 2.5) series, demonstrating the potential of these compounds to serve as solid electrolytes. Additional candidate materials are currently under experimental investigation that could offer more examples of the computational discovery of new phases of Li- and Na-conducting solid electrolytes. We believe this unprecedented approach of synergistically integrating AI models and cloud HPC not only accelerates materials discovery but also showcases the potency of AI-guided experimentation in unlocking transformative scientific breakthroughs with real-world applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The Installation of Direct Water-Cooling Systems to Reduce Cooling Energy Requirements for High-Performance Computing Centers

A large cluster of High-Performance Computing (HPC) equipment at the Lawrence Livermore National Laboratory in California was retrofitted with an Asetek cooling system. The Asetek system is a hybrid scheme with water-cooled cold plates on high-heat-producing components in the information technology (IT) equipment, and with the remainder of the heat being removed by conventional air-cooling systems. In order to determine energy savings of the Asetek system, data were gathered and analyzed two ways: using top-down statistical models, and bottom-up engineering models. The cluster, “Cabernet”, rejected its heat into a facilities cooling water loop which in turn rejected the heat into the same chilled water system serving the computer-room air handlers (CRAHs) that provided the air-based cooling for the room. Because the “before” and “after” cases both reject their heat into the chilled water system, the only savings is due to reduction in CRAH fan power. The top-down analysis showed a 4% overall energy savings for the data center (power usage effectiveness (PUE) —the ratio of total data center energy to IT energy— dropped from 1.60 to 1.53, lower is better); the bottom-up analysis showed a 3% overall energy savings (PUE from 1.70 to 1.66) and an 11% savings for the Cabernet system by itself (partial PUE of 1.51). Greater savings, on the order of 15-20%, would be possible if the chilled water system was not used for rejecting the heat from the Asetek system. About 37% of the heat from the Cab system was rejected to the cooling water, lower than at other installations.

Earni, Shankar↗
DOE OSTI2021

High-Performance Piezo-Electrocatalytic Sensing of Ascorbic Acid with Nanostructured Wurtzite Zinc Oxide

We report nanostructured piezoelectric semiconductors offer unprecedented opportunities for high-performance sensing in numerous catalytic processes of biomedical, pharmaceutical, and agricultural interests, leveraging piezocatalysis that enhances the catalytic efficiency with the strain-induced piezoelectric field. Here, we design and demonstrate for the first time a cost-efficient, high-performance piezo-electrocatalytic sensor for detecting L-ascorbic acid (AA), a critical chemical for many organisms, metabolic processes, and medical treatments. We prepared ZnO nanorods and nanosheets to characterize and compare their efficacy for the piezo-electrocatalysis of AA. The electrocatalytic efficacy of AA was significantly boosted by the piezoelectric polarization induced in the nanostructured semiconducting ZnO catalysts. We elucidated the charge transfer between the strained ZnO nanostructures and AA to reveal the mechanism for the related piezo-electrocatalytic process. The low-temperature synthesis of high-quality ZnO nanostructures allows the low-cost, scalable production and integration directly into wearable electrocatalytic sensors whose performance could be boosted by otherwise wasted mechanical energy from the working environment, e.g., the human-generated mechanical signals.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

High-Performance Computational Modeling of Strong Ground Motion for Seismic Response Analysis with Implications for High-Hazard and/or Nuclear Facilities and Critical Infrastructure at the NNSSNLV-015-19, Year 2

Presentation to be given at the FY 2020 SDRD Annual Meeting, to be held Sept. 23-24, on WebEx. There is one video also attached. This presentation is a reduced slide deck of the recently STIPped version, DOE/NV/03624--0875, presented 9-15-20 at the work in progress seminar. High-Performance Computational Modeling of Strong Ground Motion for Seismic Response Analysis with Implications for High-Hazard and/or Nuclear Facilities and Critical Infrastructure at the NNSSNLV-015-19, Year 2

58 GEOSCIENCES↗
DOE OSTI2025

Low-cost and high-performance heat exchangers for CSP

This project aimed to design and manufacture a low-cost and high-performance, particle–to–sCO 2 heat exchanger (HX) for Concentrated Solar Power (CSP) using additive manufacturing (AM). Three enabling technologies will be integrated to achieve the targeted cost and performance. The first technology is the extreme high‐speed laser materials deposition (LMD) AM process known by its German acronym EHLA that was invented at the Fraunhofer Institute for Laser Technology. The EHLA process utilizes a specially designed powder-feeding nozzle that enables a laser to melt the powder particles above the melt pool, in contrast to the conventional LMD process where the powders are melted inside the melt pool. EHLA enables much faster deposition rate than conventional LMD without the need to wait for the powders to melt. The second technology is an innovative double-helical HX geometry that can be easily fabricated using the EHLA process by rotating a rod at a high-speed to take advantage of the high EHLA deposition rate. The double-helical fins separate the hot region (the hot particle side) and the cold region (the sCO 2 side) and provide large heat transfer surface area without a large pressure drop on the sCO 2 side. The particle side will have a larger gap to facilitate the particle flow. The outer rims of the double helixes can be sealed off using the same AM process. After sealing-off, additional double helixes can be built radially on top of the first set to improve HX performance. The HX can be installed vertically for gravity-driven flow of the hot particles if necessary. The third technology is a low-cost high-temperature alumina-forming austenitic (AFA) steel TMA-6350 that has creep and oxidation resistance up to 1100 °C. These technologies together will enable high-performance and low-cost HXs for particle–to–sCO 2 for CSP.

14 SOLAR ENERGY↗
DOE OSTI2021

Development of high-performance roll-to-roll-coated gas-diffusion-electrode-based fuel cells

This study focuses on determining fabrication conditions to create high-performance roll-to-roll-coated (R2R-coated) gas-diffusion electrodes (GDEs) for proton-exchange-membrane fuel cells (PEMFCs). Here, we examine how process conditions influence the distribution of ionomer in the electrode, which is shown to be critical for high performance. Using a combination of Kelvin probe, X-ray photoelectron spectroscopy, and nano-scale X-ray computed tomography we show that formation of an ionomer-rich surface is promoted by using a higher drying rate. We show that R2R-coated GDEs have higher surface ionomer concentration than spray-coated GDEs, which enables these R2R-coated GDEs to not need an additional ionomer overlayer, as is typically the case for spray-coated GDEs. This will reduce the number of processing steps and lower material costs in a manufacturing setting. This work shows that with the appropriate selection of materials, ink formulation, and processing conditions, direct-coated GDEs are a viable pathway for fuel cell manufacturing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Aligned Conjugated Polymer Nanofiber Networks in an Elastomer Matrix for High-Performance Printed Stretchable Electronics

Conjugated polymer films are promising in wearable X-ray detection. However, achieving optimal film microstructure possessing good electrical and detection performance under large deformation via scalable printing remains challenging. Herein, we report bar-coated high-performance stretchable films based on a conjugated polymer P(TDPP-Se) and elastomer SEBS blend by optimizing the solution-processing conditions. The moderate preaggregation in solution and prolonged growth dynamics from a solvent mixture with limited dissolving capacity is critical to forming aligned P(TDPP-Se) chains/crystalline nanofibers in the SEBS phase with enhanced π–π stacking for charge transport and stress dissipation. The film shows a large elongation at break of >400% and high mobilities of 5.29 cm 2 V –1 s –1 at 0% strain and 1.66 cm 2 V –1 s –1 over 500 stretch–release cycles at 50% strain, enabling good X-ray imaging with a high sensitivity of 1501.52 μC Gy air –1 cm –2 . Finally, our work provides a morphology control strategy toward high-performance conjugated polymer film-based stretchable electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Potential high-performance magnet materials: Co- and Al-alloyed Sm 2 Fe 17

Sm 2 Fe 17 has long been known as a potential high-performance magnet whose deficiencies—planar anisotropy and lower-than-optimal T c —can be remedied by nitrogen addition, but which presents synthesis difficulties. In this work, we apply first-principles calculations to search for alternative low-cost, high-performance permanent magnets in this family, by exploring simultaneous Fe and Al substitution. Specifically, the goal is to improve properties of Sm 2 Fe 14 Al 3 easy-plane magnet at the stoichiometric composition. Density functional theory calculations were executed for three series of compounds, i.e., Sm 2 (Fe 1-x Co x ) 14 Al 3 , Sm 2 (Fe 1-x Co x ) 15 Al 2 , and Sm 2 (Fe 1-x Cox) 16 Al. We find that substitution of Fe with 12–18 of Co in % Sm 2 Fe 14 Al 3 modifies the magnetic anisotropy type from easy plane to easy axis with a substantial anisotropy of 7.1 MJ/m 3 . We also demonstrate that the largest part of magnetic anisotropy is introduced by 4f Sm atom electrons. Thus the rotation of magnetic moment orientation from $\langle$$1\bar10$$\rangle$ to $\langle$111$\rangle$ is followed by an increase of the occupied 4f state number and, as a result, the orbital part of the magnetic moment of one of the Sm atoms. This increase of the occupied 4f state number at an energy ~ -4.3 eV results in a significant reduction of band structure energy. The substitution of Fe by Co does not significantly reduce the magnetization of the compound and keeps it slightly above 1 T. This combination of magnetic anisotropy and magnetization makes the compound a promising candidate for a permanent magnet.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Synthesis of Manganese Hydroxide Nanowire Arrays for a High-Performance Zinc-Ion Battery

The morphology, microstructure as well as the orientation of cathodic materials are the key issues when preparing high-performance aqueous zinc-ion batteries (ZIBs). In this paper, binder-free electrode Mn(OH)2 nanowire arrays were facilely synthesized via electrodeposition. The nanowires were aligned vertically on a carbon cloth. The as-prepared Mn(OH)2 nanowire arrays were used as cathode to fabricate rechargeable ZIBs. The vertically aligned configuration is beneficial to electron transport and the free space between the nanowires can provide more ion-diffusion pathways. As a result, Mn(OH)2 nanowire arrays yield a high specific capacitance of 146.3 Ma h g−1 at a current density of 0.5 A g−1. They also demonstrates ultra-high diffusion coefficients of 4.5 × 10−8~1.0 × 10−9 cm2 s−1 during charging and 1.0 × 10−9~2.7 × 10−11 cm−2 s−1 during discharging processes, which are one or two orders of magnitude higher than what is reported in the studies. Furthermore, the rechargeable Zn//Mn(OH)2 battery presents a good capacity retention of 61.1% of the initial value after 400 cycles. This study opens a new avenue to boost the electrochemical kinetics for high-performance aqueous ZIBs.

25 ENERGY STORAGE↗