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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

National Geothermal Data System: Interactive Assessment of Geothermal Energy Potential in the U.S.

Geothermal-relevant geosciences data from all 50 states (www.stategeothermaldata.org), federal agencies, national labs, and academic centers are being digitized and linked in a distributed online network via the U.S. Department of Energy-funded National Geothermal Data System (NGDS) to foster geothermal energy exploration and development through use of interactive online ‘mashups,’data integration, and applications. Emphasis is first to make as much information as possible accessible online, with a long range goal to make data interoperable through standardized services and interchange formats. An initial set of thirty geoscience data content models is in use or under development to define a standardized interchange format: aqueous chemistry, borehole temperature data, direct use feature, drill stem test, earthquake hypocenter, fault feature, geologic contact feature, geologic unit feature, thermal/hot spring description, metadata, quaternary fault, volcanic vent description, well header feature, borehole lithology log, crustal stress, gravity, heat flow/temperature gradient, permeability, and feature descriptions data like developed geothermal systems, geologic unit geothermal properties, permeability, production data, rock alteration description, rock chemistry, and thermal conductivity. Map services are also being developed for isopach maps, aquifer temperature maps, and several states are working on geothermal resource overview maps. Content models are developed preferentially from existing community use in order to encourage widespread adoption and promulgate minimum metadata quality standards. Geoscience data and maps from other NGDS participating institutions, or “nodes” (USGS, Southern Methodist University, Boise State University Geothermal Data Coalition) are being supplemented with extensive land management and land use resources from the Western Regional Partnership (15 federal agencies and 5 Western states) to provide access to a comprehensive, holistic set of data critical to geothermal energy development. As of September 2011, we have over 34,000 records registered in the system catalog, and 234,942 data resources online, along with scores of Web services to deliver integrated data to the desktop for free downloading or online use. The data exchange mechanism is built on the U.S. Geoscience Information Network (USGIN, http://usgin.org and http://lab.usgin.org) protocols and standards developed as a partnership of the Association of American State Geologists (AASG) and U.S. Geological Survey.

15 GEOTHERMAL ENERGY↗
DOE OSTI2012

National Geothermal Data System: A Geothermal Data System for Exploration and Development

Geothermal-relevant geosciences data from all 50 states (www.stategeothermaldata.org), federal agencies, national labs, and academic centers are being digitized and linked in a distributed online network funded by the U.S. Department of Energy Geothermal Data System (GDS) to foster geothermal energy exploration and development through use of interactive online ‘mashups,’data integration, and applications. Emphasis is first to make as much information as possible accessible online, with a long range goal to make data interoperable through standardized services and interchange formats. A growing set of more than thirty geoscience data content models is in use or under development to define standardized interchange formats for: aqueous chemistry, borehole temperature data, direct use feature, drill stem test, seismic event hypocenter, fault feature, geologic contact feature, geologic unit feature, thermal/hot spring description, metadata, quaternary fault, volcanic vent description, well header feature, borehole lithology log, crustal stress, gravity, heat flow/temperature gradient, permeability, and feature description data like developed geothermal systems, geologic unit geothermal characterization, permeability, production data, rock alteration description, rock chemistry, and thermal conductivity. Map services are also being developed for isopach maps, aquifer temperature maps, and several states are working on geothermal resource overview maps. Content models are developed based on existing community datasets to encourage widespread adoption and promulgate content quality standards. Geoscience data and maps from other GDS participating institutions, or “nodes” (e.g., U.S. Geological Survey, Southern Methodist University, Oregon Institute of Technology, Stanford University, the University of Utah) are being supplemented with extensive land management and land use resources from the Western Regional Partnership (15 federal agencies and 5 Western states) to provide access to a comprehensive, holistic set of data critical to geothermal energy development. As of May 2012 , we have nearly 37,000 records registered in the system catalog, and 550,075 data resources online, along with hundreds of Web services to deliver integrated data to the desktop for free downloading or online use. The data exchange mechanism is built on the U.S. Geoscience Information Network (USGIN, http://usgin.org and http://lab.usgin.org) protocols and standards developed as a partnership of the Association of American State Geologists (AASG) and U.S. Geological Survey (USGS). Keywords Data

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

On coarse projective integration for atomic deposition in amorphous systems

Direct molecular dynamics simulation of atomic deposition under realistic conditions is notoriously challenging because of the wide range of time scales that must be captured. Numerous simulation approaches have been proposed to address the problem, often requiring a compromise between model fidelity, algorithmic complexity, and computational efficiency. Coarse projective integration, an example application of the “equation-free” framework, offers an attractive balance between these constraints. Here, periodically applied, short atomistic simulations are employed to compute time derivatives of slowly evolving coarse variables that are then used to numerically integrate differential equations over relatively large time intervals. A key obstacle to the application of this technique in realistic settings is the “lifting” operation in which a valid atomistic configuration is recreated from knowledge of the coarse variables. Using Ge deposition on amorphous SiO{sub 2} substrates as an example application, we present a scheme for lifting realistic atomistic configurations comprised of collections of Ge islands on amorphous SiO{sub 2} using only a few measures of the island size distribution. The approach is shown to provide accurate initial configurations to restart molecular dynamics simulations at arbitrary points in time, enabling the application of coarse projective integration for this morphologically complex system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Plug and Play Solar Power: Simplifying the Integration of Solar Energy in Hybrid Applications; Cooperative Research and Development Final Report, CRADA Number CRD-13-523

The Commonwealth Scientific and Industrial Research Organisation (CSIRO) is Australia's national science agency. CSIRO received funding from the Australian Solar Institute (ASI) for the United States-Australia Solar Energy Collaboration (USASEC) project 1-USO032 Plug and Play Solar Power: Simplifying the Integration of Solar Energy in Hybrid Applications (Broader Project). The Australian Solar Institute (ASI) operated from August 2009 to December 2012 before being merged into the Australian Renewable Energy Agency (ARENA). The Broader Project sought to simplify the integration, accelerate the deployment, and lower the cost of solar energy in hybrid distributed generation applications by creating plug and play solar technology. CSIRO worked with the National Renewable Energy Laboratory (NREL) as set out in a Joint Work Statement to review communications protocols relevant to plug-and-play technology and perform prototype testing in its Energy System Integration Facility (ESIF). For the avoidance of doubt, this CRADA did not cover the whole of the Broader Project and only related to the work described in the Joint Work Statement, which was carried out by NREL.

14 SOLAR ENERGY↗
DOE OSTI2016

Parallel stitching of 2D materials

Diverse parallel stitched 2D heterostructures, including metal–semiconductor, semiconductor–semiconductor, and insulator–semiconductor, are synthesized directly through selective “sowing” of aromatic molecules as the seeds in the chemical vapor deposition (CVD) method. Lastly, the methodology enables the large-scale fabrication of lateral heterostructures, which offers tremendous potential for its application in integrated circuits.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

All-Glass Metasurfaces for Ultra-Broadband and Large Acceptance Angle Antireflectivity: from Ultraviolet to Mid-Infrared

For many optics technologies, such as display screens, solar cells, laser systems, and eyeglasses, antireflective (AR) coatings are well integrated; these applications frequently benefit from the ability to function as broadband AR. Here, in this work, all-glass metasurfaces are reported on, exhibiting a measured reflectance of 0.18% ± 0.23% per interface, averaged across wavelengths spanning from 350 nm (ultraviolet) to 2350 nm (mid-infrared); to the best of knowledge, this is the first-ever demonstration of an AR layer capable of this. Furthermore, acceptance angles up to 100° (angle of incidence = ±50°) results in % R < 0.6% per interface over the band 350–1300 nm for P-polarization and S-polarization, with wavelength averaged reflectance values 0.04% ± 0.05% and 0.11% ± 0.15%, respectively – another technological first. The process advancements presented here allow for reflectance suppression over a broad range of wavelengths, angles, and polarizations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

2D Exotic Optical Lattice via a Digital‐Coding Circular Airy Beam

Optical lattices have been widely used from classical to quantum physics. The tunable and scalable fabrication of lattices would be of great significance in lattice‐based multipartite applications. This work demonstrates first that a circular Airy beam (CAB), which has the peculiar properties of self‐healing and abrupt autofocusing, can be used to generate two‐dimensional (2D) optical lattices in propagation when encoded by a programmable spatial mask, resulting in the formation of large‐scale and tunable optical lattices with both axis and axial symmetry, and even high‐orbital kaleidoscope shapes. The efficient diffraction of CAB during the spatial crosstalk with the mask enables the realization of tunable lattices with rich periodicity and complexity. The study shows a flexible method to manipulate lattices with large‐scale and versatile structures for potential applications in integrated and scalable optical and photonic devices.

Sun, Peisheng↗
DOE OSTI2024

TiN‐Au/HfO 2 ‐Au Multilayer Thin Films with Tunable Hyperbolic Optical Response

Abstract Hyperbolic metamaterials (HMM) possess significant anisotropic physical properties and tunability and thus find many applications in integrated photonic devices. HMMs consisting of metal and dielectric phases in either multilayer or vertically aligned nanocomposites (VAN) form are demonstrated with different hyperbolic properties. Herein, self‐assembled HfO 2 ‐Au/TiN‐Au multilayer thin films, combining both the multilayer and VAN designs, are demonstrated. Specifically, Au nanopillars embedded in HfO 2 and TiN layers forming the alternative layers of HfO 2 ‐Au VAN and TiN‐Au VAN. The HfO 2 and TiN layer thickness is carefully controlled by varying laser pulses during pulsed laser deposition (PLD). Interestingly, tunable anisotropic physical properties can be achieved by adjusting the bi‐layer thickness and the number of the bi‐layers. Type II optical hyperbolic dispersion can be obtained from high layer thickness structure (e.g., 20 nm), while it can be transformed into Type I optical hyperbolic dispersion by reducing the thickness to a proper value (e.g., 4 nm). This new nanoscale hybrid metamaterial structure with the three‐phase VAN design shows great potential for tailorable optical components in future integrated devices.

Chemistry↗
DOE OSTI2019

Ecosystem services of poplar at long-term phytoremediation sites in the Midwest and Southeast, United States

Short rotation woody crops (SRWCs) including Populus species and their hybrids (i.e., poplars) are ideal for incorporating biomass production with phytotechnologies such as phytoremediation. To integrate these applications, 15 poplar plantings from nine long-term phytoremediation installations were sampled from 2012 to 2013 in the Midwest (Illinois, Iowa, Wisconsin) and Southeast (Alabama, Florida, North Carolina) United States. In this review, we report summary results of this sampling and how performance at each site compared with comparable phytoremediation systems in the literature. We review significant genotypic differences from each planting within the context of provisioning (i.e., biomass production) and regulating (i.e., carbon sequestration) ecosystem services and how they relate to the need for a cleaner environment during times of accelerated ecological degradation. Overall, the contaminated poplar sites provided these ecosystem services comparable to noncontaminated poplar sites used for bioenergy and biofuels feedstock production. For example, phytoremediation trees at the Midwestern sites had biomass values ranging from 4.4 to 15.5 Mg ha –1 y –1 , which was 20% less relative to bioenergy trees (p = .0938). Results were similar for diameter and carbon, with some genotype x environment interactions resulting in phytoremediation trees exhibiting substantially greater growth and productivity (i.e., +131% at one site). As illustrated in the current review, phytoremediation success can be increased with the identification and deployment of genotypes tailored to grow well and tolerate a broad diversity of contaminants (generalists) (i.e., 'DN34', 'NM6', '7300501') versus those that significantly outperform their counterparts under unique site conditions (specialists) (i.e., '220-5', '51-5', 'S13C20').

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Melt Pool and Heat Treatment Optimization for the Fabrication of High-Strength and High-Toughness Additively Manufactured 4340 Steel

Additively manufactured (AM) components offer superior design flexibility compared to their conventionally manufactured counterparts, and optimizing processing parameters is key to achieving high-quality depositions with desirable and predictable mechanical properties. This study was focused on 4340 steel fabricated using laser powder bed fusion (LPBF), and 42 laser power and scan speed combinations have been systematically investigated to determine an optimized melt pool geometry that would ensure fully-dense parts. The AM material was compared with a wrought 4340 equivalent and studied in two customized heat treated conditions, optimized for strength and toughness, respectively. The microstructures of the as-fabricated and heat treated AM and wrought materials were characterized to assess differences introduced by the layer-by-layer fabrication process and subsequent heat treatment. Tensile properties of both materials were also evaluated and demonstrate that the AM materials offer equal or superior properties compared to the wrought equivalents. Differences in fracture surface morphologies indicate the distinct failure mechanisms associated with the materials’ characteristic microstructures, and the role of inclusions in the failures was studied to elucidate these differences. Complementary to the experimental investigations, the dataset was leveraged to make recommendations for future design of experiments to optimize AM build parameters in other material systems. A statistical Monte Carlo analysis was used to predict the interpolation error produced using reduced datasets and to enable informed processing parameters selection. These findings are discussed to make recommendations for the use of AM materials for high-integrity structural applications.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Characterization of fatigue crack growth behavior in LENS fabricated Ti-6Al-4V using high-energy synchrotron x-ray microtomography

Laser Engineered Net Shaping (LENS) is an additive manufacturing technique that belongs to the ASTM standardized directed energy deposition category. To date, very limited work has been conducted towards understanding the fatigue crack growth behavior of LENS fabricated materials, which hinders the widespread adoption of this technology for high-integrity structural applications. In this study, the propagation of a 20 μm initial crack in LENS fabricated Ti-6Al-4V was captured in-situ, using high-energy synchrotron x-ray microtomography. Fatigue crack growth (FCG) data were then determined from 2D and 3D tomography reconstructions, as well as from fracture surface striation measurements using SEM. The generated data were compared to those obtained from conventional FCG tests that used compliance and direct current potential drop (DCPD) techniques to measure long and small crack growth. In conclusion, the observed agreement demonstrates that x-ray microtomography and fractographic analysis using SEM can be successfully combined to study the propagation behavior of fatigue cracks.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Benchmarking of massively parallel phase-field codes for directional solidification

We present a detailed benchmark comparing two state-of-the-art phase-field implementations for simulating alloy solidification under experimentally relevant conditions. The study investigates the directional solidification of Al-3wt%Cu under high-velocity solidification conditions and SCN-0.46wt% camphor under microgravity conditions from National Aeronautics and Space Administration (NASA) DECLIC-DSI-R experiments. Both codes, one employing finite-difference discretization with uniform mesh and GPU-acceleration (GPU-PF) and the other one employing finite-element discretization with adaptive-mesh and CPU-parallelization (PRISMS-PF), solve the same quantitative phase-field formulation that incorporates an anti-trapping current for the solidification of dilute alloys. We evaluate the predictions of each code for dendritic morphology, primary spacing, and tip dynamics in both 2D and 3D, as well as their numerical convergence and computational performance. While existing benchmark problems have primarily focused on simplified or small-scale simulations, they do not reflect the computational and modeling challenges posed by employing experimentally relevant time and length scales. Our results provide a practical framework for assessing phase-field code performance as well as validating and facilitating their application in integrated computational materials engineering (ICME) workflows that require integration with realistic experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Impact of low-chemical storage pretreatment of loblolly pine bark on biochar from microwave pyrolysis

Forest product residues such as bark represent a low-cost, abundant feedstock for bioenergy, but their high ash and alkali and alkaline earth metal (AAEM) content limit thermochemical conversion efficiency. This study evaluates the use of low-severity chemical pretreatments during anaerobic storage to improve the performance of microwave pyrolysis for loblolly pine bark. Bark was treated with dilute sulfuric acid (0.1% and 1%, w/w) or sodium hydroxide (4%, w/w) and incubated anaerobically for one or two weeks to simulate in-pile biorefinery storage. The most effective treatment—1% H2SO4 for two weeks—reduced AAEM content by 35.7% and increased bio-oil yield by 11% compared to untreated controls, while also reducing pyrolysis gas production. In contrast, alkali treatment did not reduce AAEM levels and led to decreased bio-oil yields with increased gas formation. Although biochar yields were relatively stable across treatments, their physicochemical characteristics varied significantly. Acid-treated bark yielded biochars with higher carbon content, lower O/C and H/C ratios, greater surface area, and enhanced heating values. These improvements suggest that chemical pretreatment during storage can tailor biochar quality for specific end uses. Biochars produced under optimized conditions exhibited properties suitable for soil amendment, carbon sequestration, and solid fuel applications. This integrated approach—combining storage, mild chemical conditioning, and microwave pyrolysis—provides a viable pathway to enhance the value and sustainability of bark-derived bioenergy products.

09 - BIOMASS FUELS↗
DOE OSTI2025

Multi-head physics-informed neural networks for learning functional priors and uncertainty quantification

In numerous applications, the integration of prior knowledge and historical information is essential, particularly for tasks requiring the solution of ordinary or partial differential equations (ODEs/PDEs) in data-sparse or noisy environments. For instance, achieving accurate solutions to time-dependent PDEs with limited initial condition measurements necessitates an effective strategy for embedding prior knowledge. Hard-parameter sharing architectures in neural networks (NNs) have demonstrated success in both traditional and scientific machine learning domains, facilitating the learning of informative representations. Here, in this study, we introduce a novel, yet efficient, method to enhance physics-informed neural networks (PINNs) by incorporating a multi-head structure that enables the learning of functional priors from both empirical data and governing physical laws. This prior information can then be used to address data sparsity and high-level noise in solving ODE/PDE problems with uncertainty quantification (UQ). The approach, termed Multi-Head PINN (MH-PINN), consists of a shared body NN and multiple head NNs, each corresponding to an individual PINN instance. Our framework for functional prior learning is carried out in two stages: (1) training the MH-PINNs to develop a shared body NN alongside multiple head NNs, and (2) employing these trained head NNs to estimate a prior distribution through a normalizing flow-based density estimator. The learned functional prior can then be applied as a regularization mechanism in deterministic contexts or as an informative prior within a Bayesian inference framework, aiding in the resolution of subsequent ODE/PDE tasks. We evaluate the efficacy of MH-PINNs across five benchmark problems, including a high-dimensional parametric PDE, all characterized by data sparsity or substantial noise levels. Our findings reveal that MH-PINNs deliver accurate solutions and robust UQ, demonstrating adaptability across a range of complex and challenging scenarios.

Bayesian inference↗