SEARCH · Engineering Papers

Results for “deep potential”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,495 records · Page 83

All sources NASA NTRS DOE OSTI

DOE OSTI2013

Geochemical Implications of Gas Leakage Associated with Geologic CO2 Storage - A Qualitative Review

Leakage from deep storage reservoirs is considered the major risk factor associated with geologic sequestration of CO2. Different schools of thought exist concerning the potential implications of such leakage for near-surface environments. We reviewed the current literature on how CO2 leakage (from storage reservoirs) would likely impact the geochemistry of overlying potable aquifers. Results from experimental and modeling studies point to the potential for both beneficial (e.g. contaminant immobilization) and deleterious (e.g. contaminant mobilization) consequences of CO2 intrusion into potable groundwater. However, there are significant discrepancies between studies particularly concerning, what contaminants are of concern and the geochemical processes involved. These discrepancies reflected the lack of a consensus on CO2-induced changes in subsurface geochemical processes and subsequent effects on groundwater chemistry. The development of consistent experimental protocols and the identification of pertinent factors driving CO2-induced geochemical changes in the subsurface were identified as key research needs. Geochemical modeling was used to systematically highlight why a standardization of experimental protocols and the consideration of experimental factors such as gas leakage rates, redox status and the influence of co-transported gases are pertinent. The role of analog studies, reactions occurring in the vadose zone, and the influence of organic contaminants are also discussed.

basalts↗

DOE OSTI2014

Surface defect states in MBE-grown CdTe layers

Semiconductor surface plays an important role in the technology of semiconductor devices. In the present work we report results of our deep-level transient spectroscopy (DLTS) investigations of surface defect states in nitrogen doped p-type CdTe layers grown by the molecular-beam epitaxy technique. We observed a deep-level trap associated with surface states, with the activation energy for hole emission of 0.33 eV. DLTS peak position in the spectra for this trap, and its ionization energy, strongly depend on the electric field. Our measurements allow to determine a mechanism responsible for the enhancement of hole emission rate from the traps as the phonon-assisted tunnel effect. Density of surface defect states significantly decreased as a result of passivation in ammonium sulfide. Capacitance-voltage measurements confirmed the results obtained by the DLTS technique.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

PAC in DESI. II. Galaxy-halo connection into the $10^{6}{\rm M}_{\odot}$ frontier

Understanding dwarf galaxy formation is crucial for testing dark matter models and reionization physics. However, constructing stellar-mass complete spectroscopic samples at low masses is increasingly difficult, and the potential existence of a local void complicates studies in an average environment. The Photometric object Around Cosmic webs (PAC) method, which combines deep photometric and spectroscopic data to measure the excess surface density $\bar{n}_2w_{\rm{p}}(r_{\rm{p}})$ of photometric objects around spectroscopic tracers, offers a promising path forward. We model 349 $\bar{n}_2w_{\rm{p}}(r_{\rm{p}})$ measurements from DESI Y1 BGS and DECaLS, reaching $M_*=10^{6.4}\,{\rm M}_{\odot}$, using a stellar mass-halo mass relation (SHMR)-based subhalo abundance matching framework applied to two high-resolution $N$-body simulations from the Jiutian suite. The resulting SHMR is constrained down to $M_{\rm h}\simeq10^{8.0}\,h^{-1}{\rm M}_{\odot}$, revealing a clear upturn at $\sim10^{10.0}\,h^{-1}{\rm M}_{\odot}$ toward lower masses, indicating rising star-formation efficiency (SFE) in small haloes. This feature persists under extensions of the model that allow mass-dependent scatter, reionization-induced suppression of the halo occupation fraction, galaxy assembly bias, and alternative cosmologies. Combining with the results from Paper I, we find that central red galaxies dominate the low-mass regime. Our results motivate a hypothesis in which SFE is significantly higher than previously thought prior to reionization, enabling relatively massive galaxies to form in small haloes. These systems are subsequently quenched by the UV background, producing the central red dwarf galaxies observed. Finally, we obtain $3σ$ and $5σ$ upper mass bounds of $10^{8.80}\,h^{-1}{\rm M}_{\odot}$ and $10^{10.24}\,h^{-1}{\rm M}_{\odot}$ on the smallest haloes required to exist.

Xu, Kun [Pennsylvania U.; Durham U., ICC; Tsung-Da↗

DOE OSTI2021

Deep learning of accurate force field of ferroelectric HfO 2

The discovery of ferroelectricity in HfO 2 -based thin films opens up new opportunities for using this silicon-compatible ferroelectric to realize low-power logic circuits and high-density nonvolatile memories. The functional performances of ferroelectrics are intimately related to their dynamic responses to external stimuli such as electric fields at finite temperatures. Molecular dynamics is an ideal technique for investigating dynamical processes on large length and time scales, though its applications to new materials are often hindered by the limited availability and accuracy of classical force fields. Here we present a deep neural network–based interatomic force field of HfO 2 learned from ab initio data using a concurrent learning procedure. The model potential is able to predict structural properties such as elastic constants, equation of states, phonon dispersion relationships, and phase transition barriers of various hafnia polymorphs with accuracy comparable with density functional theory calculations. Here, the validity of this model potential is further confirmed by the reproduction of experimental sequences of temperature-driven ferroelectric-paraelectric phase transitions of HfO 2 with isobaric-isothermal ensemble molecular dynamics simulations. We suggest a general approach to extend the model potential of HfO 2 to related material systems including dopants and defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2013

The Sivers effect and the Single Spin Asymmetry A_N in p(transv. pol.) p --> h X processes

The single spin asymmetry A_N, for large P_T single inclusive particle production in p(transv. pol.) p collisions, is considered within a generalised parton model and a transverse momentum dependent factorisation scheme. The focus is on the Sivers effect and the study of its potential contribution to A_N, based on a careful analysis of the Sivers functions extracted from azimuthal asymmetries in semi-inclusive deep inelastic scattering processes. It is found that such Sivers functions could explain most features of the A_N data, including some recent STAR results which show the persistence of a non zero A_N up to surprisingly large P_T values.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

Development of GaInP Solar Cells Grown by Hydride Vapor Phase Epitaxy

We demonstrate the growth of homojunction GaInP solar cells by dynamic hydride vapor phase epitaxy for the first time. Simple unpassivated n-on-p structures grown in an inverted configuration with gold back reflectors were analyzed. Short wavelength performance varied strongly with emitter thickness, since collection in the emitter was limited by the lack of surface passivation. Collection in the base increased strongly with decreasing doping density, in the range 1 x 10 16 - 5 x 10 17 cm -3 . Optical modeling indicated that, in our best device, doped ~1 x 10 16 cm -3 , almost 94% of photons that passed through the emitter were collected. Modeling also indicated that the majority of collection occurs in the depletion region with this design, suggesting that nonradiative recombination there might limit device performance. In agreement with this observation, the experimental dark J-V curve exhibited an ideality factor near n = 2. Thus, limitation of deep level carrier traps in the material is a path to improved performance. Preliminary experiments indicate that a reduced V/III ratio, which potentially affects the density of these presumed traps, improves cell performance. With reduced V/III ratio, we demonstrate a ~13% efficient GaInP cell measured under the 1-sun AM1.5G spectrum. In conclusion, this cell had an antireflective coating, but no front surface passivation.

14 SOLAR ENERGY↗

DOE OSTI2018

Avoiding Pitfalls in the Determination of Reliable Electrochemical Kinetics Parameters for the Cu 2+ → Cu 1+ Reduction Reaction in Deep Eutectic Solvents

Deep eutectic solvents (DES), on account of their low-cost, non-flammability and electrochemical stability, are attracting attention for their potential use in applications such as electrodeposition and energy storage. In these applications, knowledge of the transport and electrochemical kinetics properties of DES is critically important. To date, attempts to measure the kinetics parameters of the Cu 2+ + e ⇌ Cu 1+ reaction in ethaline DES have yielded a cathodic charge transfer coefficient (α) in the range of 0.2–0.3 suggesting an unexpected asymmetric polarization behavior. In the present work, we pursued a comprehensive study of the kinetics and transport properties of the aforementioned reaction. Using steady-state and transient polarization measurements on RDE and microelectrodes combined with diffusion-reaction modeling, we demonstrate that the Cu 2+ /Cu 1+ transition exhibits a charge transfer coefficient in the range of 0.49–0.54 and an exchange current density in the range 1.72–1.88 mA/cm 2 . Recommendations are provided for avoiding pitfalls in kinetics analysis of highly resistive DES electrolytes. These recommendations include the application of accurate $IR_Ω$ correction and the use of electrode configurations where the secondary current distribution is relatively uniform.

25 ENERGY STORAGE↗

DOE OSTI2019

Targeted Mineral Carbonation to Enhance Wellbore Integrity [Final Report]

This project evaluated the potential to deploy targeted carbonation reactions to the leading edge of leaking CO 2 ganglion as a strategy for mitigating leakage from deep CO 2 injection sites. Tasks that were performed for this objective included (i) Maintaining and revising the project management and planning; (ii) Developing novel stimuli-responsive materials that release mineral silicates only below a target temperature; (iii) Imaging of subsamples from targeted carbonation demonstration experiments in porous media and fractured wellborn-zone environments; and (iv) Building models to best fit the experiment results and confirm the hypothesis driving this work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Targeted Mineral Carbonation to Enhance Wellbore Integrity

42 ENGINEERING↗

DOE OSTI2022

Exploration of Quantum Machine Learning and AI Accelerators for Fusion Science

The dawn of the noisy intermediate-scale quantum (NISQ) era sparked rapid development in variational quantum algorithms. These algorithms, utilizing parameterized quantum circuit optimized by classical computers with feedback, are practical under the constraints of the current hardware and can potentially show quantum advantage. In recent years, these variational circuit are applied to neural networks, hoping to boost the triumphant success of deep learning. We simulate various of quantum-classical hybrid neural networks applied to scientific tasks, and seek to understand their capabilities and limitations. Specifically, we devise quantum convolutional layers and apply them to deep neural networks used for predicting plasma disruption in fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Resolving Issues Regarding Disposal of Safeguarded Nuclear Materials: Concepts for Near Surface and Intermediate Depth Disposal sites

This document presents two case studies on nuclear waste disposal to explore the safeguards challenges and potential solutions present under each scenario. Both involve the disposal of nuclear materials, either for waste containing safeguarded nuclear materials or waste where safeguards on the nuclear materials have been previously terminated. The first case study is that of a low-level waste (LLW) repository that is situated near the surface. This facility will accept safeguarded nuclear materials for disposal. Examples of this type of activity are rare, but the potential for more facilities of this type is very possible as States become more comfortable with considering safeguards measures in perpetuity on deep geological repositories. The second study extends this to the case of terminated wastes at an intermediate depth disposal site. In this case, the reasons why terminated nuclear materials could be found in these disposal facilities and how obligations under the Comprehensive Safeguards Agreement (CSA) and Additional Protocol (AP) are met when the disposed waste items are intermediate level waste (ILW) or high-level waste (HLW).

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2014

Assessment of the Deepwater Horizon oil spill impact on Gulf coast microbial communities

One of the major environmental concerns of the Deepwater Horizon oil spill in the Gulf of Mexico was the ecological impact of the oil that reached shorelines of the Gulf Coast. Here we investigated the impact of the oil on the microbial composition in beach samples collected in June 2010 along a heavily impacted shoreline near Grand Isle, Louisiana. Successional changes in the microbial community structure due to the oil contamination were determined by deep sequencing of 16S rRNA genes. Metatranscriptomics was used to determine expression of functional genes involved in hydrocarbon degradation processes. In addition, potential hydrocarbon-degrading Bacteria were obtained in culture. The 16S data revealed that highly contaminated samples had higher abundances of Alpha- and Gammaproteobacteria sequences. Successional changes in these classes were observed over time, during which the oil was partially degraded. The metatranscriptome data revealed that PAH, n-alkane, and toluene degradation genes were expressed in the contaminated samples, with high homology to genes from Alteromonadales, Rhodobacterales, and Pseudomonales. Notably, Marinobacter (Gammaproteobacteria) had the highest representation of expressed genes in the samples. A Marinobacter isolated from this beach was shown to have potential for transformation of hydrocarbons in incubation experiments with oil obtained from the Mississippi Canyon Block 252 (MC252) well; collected during the Deepwater Horizon spill. The combined data revealed a response of the beach microbial community to oil contaminants, including prevalence of Bacteria endowed with the functional capacity to degrade oil.

16S rRNA gene↗

DOE OSTI2020

Effect of Computational Schemes on Coupled Flow and Geo-Mechanical Modeling of CO 2 Leakage through a Compromised Well

Carbon capture, utilization, and storage (CCUS) describes a set of technically viable processes to separate carbon dioxide (CO 2 ) from industrial byproduct streams and inject it into deep geologic formations for long-term storage. Legacy wells located within the spatial domain of new injection and production activities represent potential pathways for fluids (i.e., CO 2 and aqueous phase) to leak through compromised components (e.g., through fractures or micro-annulus pathways). The finite element (FE) method is a well-established numerical approach to simulate the coupling between multi-phase fluid flow and solid phase deformation interactions that occur in a compromised well system. We assumed the spatial domain consists of a three-phases system: a solid, liquid, and gas phase. For flow in the two fluids phases, we considered two sets of primary variables: the first considering capillary pressure and gas pressure (PP) scheme, and the second considering liquid pressure and gas saturation (PS) scheme. Fluid phases were coupled with the solid phase using the full coupling (i.e., monolithic coupling) and iterative coupling (i.e., sequential coupling) approaches. The challenge of achieving numerical stability in the coupled formulation in heterogeneous media was addressed using the mass lumping and the upwinding techniques. Numerical results were compared with three benchmark problems to assess the performance of coupled FE solutions: 1D Terzaghi’s consolidation, Liakopoulos experiments, and the Kueper and Frind experiments. We found good agreement between our results and the three benchmark problems. For the Kueper and Frind test, the PP scheme successfully captured the observed experimental response of the non-aqueous phase infiltration, in contrast to the PS scheme. These exercises demonstrate the importance of fluid phase primary variable selection for heterogeneous porous media. We then applied the developed model to the hypothetical case of leakage along a compromised well representing a heterogeneous media. Considering the mass lumping and the upwinding techniques, both the monotonic and the sequential coupling provided identical results, but mass lumping was needed to avoid numerical instabilities in the sequential coupling. Additionally, in the monolithic coupling, the magnitude of primary variables in the coupled solution without mass lumping and the upwinding is higher, which is essential for the risk-based analyses.

deformation flow↗

DOE OSTI2024

Missing Wedge Completion via Unsupervised Learning with Coordinate Networks

Cryogenic electron tomography (cryoET) is a powerful tool in structural biology, enabling detailed 3D imaging of biological specimens at a resolution of nanometers. Despite its potential, cryoET faces challenges such as the missing wedge problem, which limits reconstruction quality due to incomplete data collection angles. Recently, supervised deep learning methods leveraging convolutional neural networks (CNNs) have considerably addressed this issue; however, their pretraining requirements render them susceptible to inaccuracies and artifacts, particularly when representative training data is scarce. To overcome these limitations, we introduce a proof-of-concept unsupervised learning approach using coordinate networks (CNs) that optimizes network weights directly against input projections. This eliminates the need for pretraining, reducing reconstruction runtime by 3–20× compared to supervised methods. Our in silico results show improved shape completion and reduction of missing wedge artifacts, assessed through several voxel-based image quality metrics in real space and a novel directional Fourier Shell Correlation (FSC) metric. Our study illuminates benefits and considerations of both supervised and unsupervised approaches, guiding the development of improved reconstruction strategies.

42 ENGINEERING↗

DOE OSTI2022

Low Pathogenicity H7N3 Avian Influenza Viruses Have Higher Within-Host Genetic Diversity Than a Closely Related High Pathogenicity H7N3 Virus in Infected Turkeys and Chickens

Within-host viral diversity offers a view into the early stages of viral evolution occurring after a virus infects a host. In recent years, advances in deep sequencing have allowed for routine identification of low-frequency variants, which are important sources of viral genetic diversity and can potentially emerge as a major virus population under certain conditions. We examined within-host viral diversity in turkeys and chickens experimentally infected with closely related H7N3 avian influenza viruses (AIVs), specifically one high pathogenicity AIV (HPAIV) and two low pathogenicity AIV (LPAIVs) with different neuraminidase protein stalk lengths. Consistent with the high mutation rates of AIVs, an abundance of intra-host single nucleotide variants (iSNVs) at low frequencies of 2–10% was observed in all samples collected. Furthermore, a small number of common iSNVs were observed between turkeys and chickens, and between directly inoculated and contact-exposed birds. Notably, the LPAIVs have significantly higher iSNV diversities and frequencies of nonsynonymous changes than the HPAIV in both turkeys and chickens. These findings highlight the dynamics of AIV populations within hosts and the potential impact of genetic changes, including mutations in the hemagglutinin gene that confers the high pathogenicity pathotype, on AIV virus populations and evolution.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Genomic comparisons of a bacterial lineage that inhabits both marine and terrestrial deep subsurface systems

It is generally accepted that diverse, poorly characterized microorganisms reside deep within Earth’s crust. One such lineage of deep subsurface-dwelling bacteria is an uncultivated member of the Firmicutes phylum that can dominate molecular surveys from both marine and continental rock fracture fluids, sometimes forming the sole member of a single-species microbiome. Here, we reconstructed a genome from basalt-hosted fluids of the deep subseafloor along the eastern Juan de Fuca Ridge flank and used a phylogenomic analysis to show that, despite vast differences in geographic origin and habitat, it forms a monophyletic clade with the terrestrial deep subsurface genome of “ Candidatus Desulforudis audaxviator” MP104C. While a limited number of differences were observed between the marine genome of “ Candidatus Desulfopertinax cowenii” modA32 and its terrestrial relative that may be of potential adaptive importance, here it is revealed that the two are remarkably similar thermophiles possessing the genetic capacity for motility, sporulation, hydrogenotrophy, chemoorganotrophy, dissimilatory sulfate reduction, and the ability to fix inorganic carbon via the Wood-Ljungdahl pathway for chemoautotrophic growth. Finally, our results provide insights into the genetic repertoire within marine and terrestrial members of a bacterial lineage that is widespread in the global deep subsurface biosphere, and provides a natural means to investigate adaptations specific to these two environments.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1990

Initial results on fault diagnosis of DSN antenna control assemblies using pattern recognition techniques

Initial results obtained from an investigation using pattern recognition techniques for identifying fault modes in the Deep Space Network (DSN) 70 m antenna control loops are described. The overall background to the problem is described, the motivation and potential benefits of this approach are outlined. In particular, an experiment is described in which fault modes were introduced into a state-space simulation of the antenna control loops. By training a multilayer feed-forward neural network on the simulated sensor output, classification rates of over 95 percent were achieved with a false alarm rate of zero on unseen tests data. It concludes that although the neural classifier has certain practical limitations at present, it also has considerable potential for problems of this nature.

Smyth, P.↗

NASA NTRS1994

A simplified Integer Cosine Transform and its application in image compression

A simplified version of the integer cosine transform (ICT) is described. For practical reasons, the transform is considered jointly with the quantization of its coefficients. It differs from conventional ICT algorithms in that the combined factors for normalization and quantization are approximated by powers of two. In conventional algorithms, the normalization/quantization stage typically requires as many integer divisions as the number of transform coefficients. By restricting the factors to powers of two, these divisions can be performed by variable shifts in the binary representation of the coefficients, with speed and cost advantages to the hardware implementation of the algorithm. The error introduced by the factor approximations is compensated for in the inverse ICT operation, executed with floating point precision. The simplified ICT algorithm has potential applications in image-compression systems with disparate cost and speed requirements in the encoder and decoder ends. For example, in deep space image telemetry, the image processors on board the spacecraft could take advantage of the simplified, faster encoding operation, which would be adjusted on the ground, with high-precision arithmetic. A dual application is found in compressed video broadcasting. Here, a fast, high-performance processor at the transmitter would precompensate for the factor approximations in the inverse ICT operation, to be performed in real time, at a large number of low-cost receivers.

Costa, M.↗