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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A flexible and scalable scheme for mixing computed formation energies from different levels of theory

Abstract Computational materials discovery efforts are enabled by large databases of properties derived from high-throughput density functional theory (DFT), which now contain millions of calculations at the generalized gradient approximation (GGA) level of theory. It is now feasible to carry out high-throughput calculations using more accurate methods, such as meta-GGA DFT; however recomputing an entire database with a higher-fidelity method would not effectively leverage the enormous investment of computational resources embodied in existing (GGA) calculations. Instead, we propose here a general procedure by which higher-fidelity, low-coverage calculations (e.g., meta-GGA calculations for selected chemical systems) can be combined with lower-fidelity, high-coverage calculations (e.g., an existing database of GGA calculations) in a robust and scalable manner. We then use legacy PBE(+ U ) GGA calculations and new r 2 SCAN meta-GGA calculations from the Materials Project database to demonstrate that our scheme improves solid and aqueous phase stability predictions, and discuss practical considerations for its implementation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Scalable method for micro-CT analysis enables large scale quantitative characterization of brain lesions and implants

Anatomic evaluation is an important aspect of many studies in neuroscience; however, it often lacks information about the three-dimensional structure of the brain. Micro-CT imaging provides an excellent, nondestructive, method for the evaluation of brain structure, but current applications to neurophysiological or lesion studies require removal of the skull as well as hazardous chemicals, dehydration, or embedding, limiting their scalability and utility. Here we present a protocol using eosin in combination with bone decalcification to enhance contrast in the tissue and then employ monochromatic and propagation phase-contrast micro-CT imaging to enable the imaging of brain structure with the preservation of the surrounding skull. Instead of relying on descriptive, time-consuming, or subjective methods, we develop simple quantitative analyses to map the locations of recording electrodes and to characterize the presence and extent of hippocampal brain lesions.

3-D reconstruction↗
DOE OSTI2021

Freely scalable and reconfigurable optical hardware for deep learning

Abstract As deep neural network (DNN) models grow ever-larger, they can achieve higher accuracy and solve more complex problems. This trend has been enabled by an increase in available compute power; however, efforts to continue to scale electronic processors are impeded by the costs of communication, thermal management, power delivery and clocking. To improve scalability, we propose a digital optical neural network (DONN) with intralayer optical interconnects and reconfigurable input values. The path-length-independence of optical energy consumption enables information locality between a transmitter and a large number of arbitrarily arranged receivers, which allows greater flexibility in architecture design to circumvent scaling limitations. In a proof-of-concept experiment, we demonstrate optical multicast in the classification of 500 MNIST images with a 3-layer, fully-connected network. We also analyze the energy consumption of the DONN and find that digital optical data transfer is beneficial over electronics when the spacing of computational units is on the order of $$>10\,\upmu $$ > 10 μ m.

42 ENGINEERING↗
DOE OSTI2022

Scalable and accurate multi-GPU-based image reconstruction of large-scale ptychography data

Abstract While the advances in synchrotron light sources, together with the development of focusing optics and detectors, allow nanoscale ptychographic imaging of materials and biological specimens, the corresponding experiments can yield terabyte-scale volumes of data that can impose a heavy burden on the computing platform. Although graphics processing units (GPUs) provide high performance for such large-scale ptychography datasets, a single GPU is typically insufficient for analysis and reconstruction. Several works have considered leveraging multiple GPUs to accelerate the ptychographic reconstruction. However, most of these works utilize only the Message Passing Interface to handle the communications between GPUs. This approach poses inefficiency for a hardware configuration that has multiple GPUs in a single node, especially while reconstructing a single large projection, since it provides no optimizations to handle the heterogeneous GPU interconnections containing both low-speed (e.g., PCIe) and high-speed links (e.g., NVLink). In this paper, we provide an optimized intranode multi-GPU implementation that can efficiently solve large-scale ptychographic reconstruction problems. We focus on the maximum likelihood reconstruction problem using a conjugate gradient (CG) method for the solution and propose a novel hybrid parallelization model to address the performance bottlenecks in the CG solver. Accordingly, we have developed a tool, called PtyGer ( Pty chographic G PU(multipl e )-based r econstruction), implementing our hybrid parallelization model design. A comprehensive evaluation verifies that PtyGer can fully preserve the original algorithm’s accuracy while achieving outstanding intranode GPU scalability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Improved particle-flow event reconstruction with scalable neural networks for current and future particle detectors

Abstract Efficient and accurate algorithms are necessary to reconstruct particles in the highly granular detectors anticipated at the High-Luminosity Large Hadron Collider and the Future Circular Collider. We study scalable machine learning models for event reconstruction in electron-positron collisions based on a full detector simulation. Particle-flow reconstruction can be formulated as a supervised learning task using tracks and calorimeter clusters. We compare a graph neural network and kernel-based transformer and demonstrate that we can avoid quadratic operations while achieving realistic reconstruction. We show that hyperparameter tuning significantly improves the performance of the models. The best graph neural network model shows improvement in the jet transverse momentum resolution by up to 50% compared to the rule-based algorithm. The resulting model is portable across Nvidia, AMD and Habana hardware. Accurate and fast machine-learning based reconstruction can significantly improve future measurements at colliders.

Physics↗
DOE OSTI2014

Ultra-High Performance, High-Temperature Superconducting Wires via Cost-effective, Scalable, Co-evaporation Process

Long-length, high-temperature superconducting (HTS) wires capable of carrying high critical current, Ic, are required for a wide range of applications. Here, we report extremely high performance HTS wires based on 5 m thick SmBa2Cu3O7- (SmBCO) single layer films on textured metallic templates. SmBCO layer wires over 20 meters long were deposited by a cost-effective, scalable co-evaporation process using a batch-type drum in a dual chamber. All deposition parameters influencing the composition, phase, and texture of the films were optimized via a unique combinatorial method that is broadly applicable for co-evaporation of other promising complex materials containing several cations. Thick SmBCO layers deposited under optimized conditions exhibit excellent cube-on-cube epitaxy. Such excellent structural epitaxy over the entire thickness results in exceptionally high Ic performance, with average Ic over 1000 A/cm for the entire 22 meter long wire and maximum Ic over 1,500 A/cm for a short 12 cm long tape. The Ic values reported in this work are the highest values ever reported from any lengths of cuprate-based HTS wire or conductor.

Kim, Dr. Hosup↗
DOE OSTI2016

Scalable fabrication of micron-scale graphene nanomeshes for high-performance supercapacitor applications

Graphene nanomeshes (GNMs) with nanoscale periodic or quasi-periodic nanoholes have attracted considerable interest because of unique features such as their open energy band gap, enlarged specific surface area, and high optical transmittance. These features are useful for applications in semiconducting devices, photocatalysis, sensors, and energy-related systems. We report on the facile and scalable preparation of multifunctional micron-scale GNMs with high-density of nanoperforations by catalytic carbon gasification. The catalytic carbon gasification process induces selective decomposition on the graphene adjacent to the metal catalyst, thus forming nanoperforations. Furthermore, the pore size, pore density distribution, and neck size of the GNMs can be controlled by adjusting the size and fraction of the metal oxide on graphene. The fabricated GNM electrodes exhibit superior electrochemical properties for supercapacitor (ultracapacitor) applications, including exceptionally high capacitance (253 F g -1 at 1 A g -1 ) and high rate capability (212 F g -1 at 100 A g -1 ) with excellent cycle stability (91% of the initial capacitance after 50 000 charge/discharge cycles). Moreover, the edge-enriched structure of GNMs plays an important role in achieving edge-selected and high-level nitrogen doping.

25 ENERGY STORAGE↗
DOE OSTI2015

Scalable synthesis of Na3V2(PO4)(3)/C porous hollow spheres as a cathode for Na-ion batteries

Na3V2(PO4)(3) (NVP) has been considered as a very promising cathode material for sodium-ion batteries (SIBs) due to its typical NASICON structure, which provides an open and three dimensional (3D) framework for Na+ migration. However, the low electronic conductivity of NVP limits its rate capability and cycling ability. In this study, carbon coated hollow structured NVP/C composites are synthesized via a template-free and scalable ultrasonic spray pyrolysis process, where the carbon coated NVP particles are uniformly decorated on the inner and outer surfaces of the porous hollow carbon spheres. When evaluated as a cathode material for SIBs, the unique NVP/C porous hollow sphere cathode delivers an initial discharge capacity of 99.2 mA h g(-1) and retains 89.3 mA h g(-1) after 300 charge/discharge cycles with a very low degradation rate of 0.035% per cycle. For comparison, the NVP/C composite, prepared by the traditional sol-gel method, delivers a lower initial discharge capacity of 97.4 mA h g(-1) and decreases significantly to 71.5 mA h g(-1) after 300 cycles. The superior electrochemical performance of NVP/C porous hollow spheres is attributed to their unique porous, hollow and spherical structures, as well as the carbon-coating layer, which provides a high contact area between electrode/electrolyte, high electronic conductivity, and high mechanical strength.

Mao, JF↗
DOE OSTI2017

Fabrication and optical characterization of polystyrene opal templates for the synthesis of scalable, nanoporous (photo)electrocatalytic materials by electrodeposition

Finding solutions to improve the performance of semiconductor light absorbers and catalyst materials remains an outstanding issue that prevents the realization of solar fuel generators. Nanostructuring approaches of photoelectrocatalytic materials have the potential to reduce bulk recombination and improve electron-hole pair separation in semiconductor light absorbers, as well as to increase the active surface area and influence the activity in catalytic systems. Herein, we propose a versatile approach for the synthesis of reproducible, highly homogeneous, large scale nanoporous (photo)electrocatalytic materials for artificial photosynthesis. By identifying and carefully analyzing critical parameters for forming opal templates from solutions of colloidal polystyrene beads (PS), we are able to reproducibly fabricate large area ( > cm 2 ) PS films with high optical quality over a wide diameter range (170-600 nm). Using these PS bead opal films as templates, we demonstrate that electrodeposition is a suitable bottom-up infilling technique to produce scalable, homogeneous, and highly ordered nanoporous (photo)electrocatalytic materials, namely Cu 2 O, BiVO 4 , CuBi 2 O 4 , and Cu. Here, we provide morphological, structural, and optical characterization of the resulting opal replicas. Finally, we demonstrate preliminary integration of the Cu 2 O inverse opal film into a working photocathode under CO 2 reduction conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Facile and scalable dry surface doping technique to enhance the electrochemical performance of LiNi 0.64 Mn 0.2 Co 0.16 O 2 cathode materials

Lithium nickel manganese cobalt oxide (NMC) is one of the dominant cathode materials in lithium-ion batteries. In this study a simple, efficient and scalable surface doping technique is successfully demonstrated, which can be readily used in mass production of cathode materials. For the first time neodymium oxide (Nd 2 O 3 ) has been employed as the surface doping agent. The Nd-doped NMC shows greatly improved cycling and rate performance, and the enhanced cycling stability has been demonstrated in full pouch cells, with a 17.5% increase in capacity retention after 300 cycles. Fewer cracks have been observed in the doped NMC after cycling, and in situ X-ray diffraction reveals the suppressed lattice collapse by Nd doping. Greatly suppressed surface phase change has been confirmed by HR-TEM and EELS. The result suggests great promise in using this dry doping technique to enhance the electrochemical performance of NMC cathodes.

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

Scalable open-air deposition of compact ETL TiO x on perovskite for fullerene-free solar cells

We report a scalable, low-temperature TiO x electron transport layer (ETL) produced directly on top of perovskite in an inverted architecture device by an open-air chemical vapor deposition (OA-CVD) process. The OA-CVD pyrolysis of a titanium ethoxide precursor forms a fully inorganic, conformal, and compact TiO x film. The resultant film is mechanically robust and exhibits a fracture toughness 30-fold higher than commonly used fullerene-based ETL films. The TiO x is an effective barrier layer against environmental degradation—unencapsulated devices with the TiO x ETL retain 60% of their initial efficiency after 1000 hours in ambient aging conditions—compared to devices with a fullerene ETL which were inoperable after 144 hours. Inverted architecture devices with an optimized TiO x ETL thickness of 70 nm exhibited high open-circuit voltages of 1.08 V. We comment on the photocatalytic properties of TiO x and the influence of an amorphous film on maximum power point stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗