Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “ENERGY DEPENDENCE”

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.

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

At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Isolation of Single Donors in ZnO

The shallow donor in zinc oxide (ZnO) is a promising semiconductor spin qubit with optical access. Single indium donors are isolated in a commercial ZnO substrate using plasma focused ion beam (PFIB) milling. Quantum emitters are identified optically by spatial and frequency filtering. The indium donor assignment is based on the optical bound exciton transition energy and magnetic dependence. The emission stability of these single donors in terms of both intensity and frequency, alongside their transition linewidths less than twice the lifetime limit, highlight the promise of single In donors as optically accessible spin qubits. Here, the optical stability of single donors after FIB fabrication is promising for optical device integration required for scalable quantum technologies based on single donors in direct band gap semiconductors.

42 ENGINEERING↗
DOE OSTI2021

Electron-Beam Corkscrew Motion in an Advanced Linear Induction Accelerator

Scorpius is a multipulse linear induction accelerator (LIA) under development for flash radiography. Because it has substantially more cells than present LIAs, higher magnetic focusing fields are needed to suppress beam breakup (BBU). Therefore, it is more susceptible to corkscrew motion of the beam, which also depends on beam energy spread and focusing magnet misalignments. For energy spread and alignment tolerances expected for Scorpius, a magnetic tune designed to suppress BBU is shown to produce corkscrew motion within the range that can be controlled through the use of steering dipoles on existing LIAs. Finally, a gap-voltage modulation scheme is shown to almost completely eliminate chromatic effects such as corkscrew.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Modeling the Low-Pressure High-Voltage Branch of the Paschen Curve for Hydrogen and Deuterium

A physical and numerical model of the Townsend discharge in molecular hydrogen and deuterium has been developed to meet the needs of designing a plasma-based switching device for power grid applications. Here, the model allows to predict the low-pressure branch of the Paschen curve for applied voltage in the range of several hundred kilovolts. In the regime of interest, electrons are in a runaway state and ionization by ions and fast neutrals sustains the discharge. It was essential to correctly account for both gas-phase and surface interactions (electron emission and electron backscattering), especially in terms of their dependence on particle energy. The model yields results consistent with prior data obtained for lower voltage. The three-species (electrons, ions, and fast neutrals) model successfully captures the essential physics of the process.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Partial densities of states from x-ray absorption and Auger electron spectroscopy: Use of core-hole memory

Ag L 3 edge x-ray absorption and L 3 −M 4,5 M 4,5 Auger electron spectra have been measured and simulated for a variety of x-ray electric-field polarization and Auger electron emission directions. The theory relies on density-functional theory, use of the Bethe–Salpeter equation, atomic multiplet theory, and a simplified model for the Auger line shape and its dependence on photon energy. We also demonstrate that partial densities of states for dT 2g , dE g , and sA g symmetry partial-wave channels at the Ag site in the solid can be deduced from the experimental measurements with only atomic theoretical input, i.e., with no solid-state theory other than assuming a Fermi edge.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Voltage waveform tailoring for high aspect ratio plasma etching of SiO 2 using Ar/CF 4 /O 2 mixtures: Consequences of ion and electron distributions on etch profiles

The quality of high aspect ratio (HAR) features etched into dielectrics for microelectronics fabrication using halogen containing low temperature plasmas strongly depends on the energy and angular distribution of the incident ions (IEAD) onto the wafer, as well as potentially that of the electrons (EEAD). Positive ions, accelerated to high energies by the sheath electric field, have narrow angular spreads and can penetrate deeply into HAR features. Electrons typically arrive at the wafer with nearly thermal energy and isotropic angular distributions and so do not directly penetrate deeply into features. These differences can lead to positive charging of the insides of the features that can slow etching rates and produce geometric defects such as twisting. In this work, we computationally investigated the plasma etching of HAR features into SiO 2 using tailored voltage waveforms in a geometrically asymmetric capacitively coupled plasma sustained in an Ar/CF 4 /O 2 mixture at 40 mTorr. The tailored waveform consisted of a sinusoidal wave and its higher harmonics with a fundamental frequency of 1 MHz. We found that some degree of control of the IEADs and EEADs is possible by adjusting the phase of higher harmonics φ through the resulting generation of electrical asymmetry and electric field reversal. However, the IEADs and EEADs cannot easily be separately controlled. The control of IEADs and EEADs is inherently linked. The highest quality feature was obtained with a phase angle φ = 0° as this value generated the largest (most negative) DC self-bias and largest electric field reversal for accelerating electrons into the feature. That said, the consequences of voltage waveform tailoring (VWT) on etched features are dominated by the change in the IEADs. Although VWT does produce EEADs with higher energy and narrower angular spread, the effect of these electrons on the feature compared to thermal electrons is not large. Finally, this smaller impact of VWT produced EEADs is attributed to thermal electrons being accelerated into the feature by electric fields produced by the positive in-feature charging.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Thermally generated spin current in the topological insulator Bi 2 Se 3

We present measurements of thermally generated transverse spin currents in the topological insulator Bi2Se3, thereby completing measurements of interconversions among the full triad of thermal gradients, charge currents, and spin currents. We accomplish this by comparing the spin Nernst magneto-thermopower to the spin Hall magnetoresistance for bilayers of Bi 2 Se 3 /CoFeB. We find that Bi 2 Se 3 does generate substantial thermally driven spin currents. A lower bound for the ratio of spin current density to thermal gradient is $\frac{J_{s}}{∇_{x}T}$ = (4.9 ± 0.9) × 10 6 ($\frac{ℏ}{2e}$) $\frac{A m^{-2}}{K μm^{-1}}$, and a lower bound for the magnitude of the spin Nernst ratio is -0.61 ± 0.11. The spin Nernst ratio for Bi 2 Se 3 is the largest among all materials measured to date, two to three times larger compared to previous measurements for the heavy metals Pt and W. Strong thermally generated spin currents in Bi 2 Se 3 can be understood via Mott relations to be due to an overall large spin Hall conductivity and its dependence on electron energy.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Landau-phonon polaritons in Dirac heterostructures

Polaritons are light-matter quasiparticles that govern the optical response of quantum materials at the nanoscale, enabling on-chip communication and local sensing. Here, we report Landau-phonon polaritons (LPPs) in magnetized charge-neutral graphene encapsulated in hexagonal boron nitride (hBN). These quasiparticles emerge from the interaction of Dirac magnetoexciton modes in graphene with the hyperbolic phonon polariton modes in hBN. Using infrared magneto-nanoscopy, we reveal the ability to completely halt the LPP propagation in real space at quantized magnetic fields, defying the conventional optical selection rules. The LPP-based nanoscopy also tells apart two fundamental many-body phenomena: the Fermi velocity renormalization and field-dependent magnetoexciton binding energies. Our results highlight the potential of magnetically tuned Dirac heterostructures for precise nanoscale control and sensing of light-matter interaction.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Grand Challenges in the Science of Wind Energy

The energy system of the future that depends on 80% or more renewable energy will put new demands on the wind systems that support it. There are significant areas of scientific uncertainly that need to be addressed to enable the innovation required for success. This presentation, based on a 2019 article in Science, lays out those areas of scientific challenges and proposes an integrated wind energy discipline that encompasses the needed research.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2024

A study of nuclear structure of light nuclei at the electron–ion collider

Understanding the substructure of atomic nuclei, particularly the clustering of nucleons inside them, is essential for comprehending nuclear dynamics. Various cluster configurations can emerge depending on excitation energy, the number and types of core clusters, and the presence of excess neutrons. Despite the prevalence of tightly bound cluster formations in low-lying states, understanding the correlation between clusters and their formation mechanisms remains incomplete. This exploring study investigates nuclear clustering at the electron–ion collider (EIC) using simulations based on the modified BeAGLE model. By simulating collisions involving e+ 9 Be, e+ 12 C, and e+ 16 O nuclei, we find that the average energy of particles and the system size ratios of particles at forward rapidity exhibit sensitivity to alpha clustering and its various configurations. These findings offer valuable insights into the dynamics of nuclear clustering and its implications for future studies at the EIC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Evidence of Mixed Scaling for Mean Profile Similarity in the Stable Atmospheric Surface Layer

A new mixed scaling parameter Z = z/(Lh)1/2 is proposed for similarity in the stable atmospheric surface layer, where z is the height, L is the Obukhov length, and h is the boundary layer depth. In comparison with the parameter ζ = z/L from Monin–Obukhov similarity theory (MOST), the new parameter Z leads to improved mean profile similarity for wind speed and air temperature in large-eddy simulations. It also yields the same linear similarity relation for CASES-99 field measurements, including in the strongly stable (but still turbulent) regime where large deviations from MOST are observed. Results further suggest that similarity for turbulent energy dissipation rate depends on both Z and ζ. The proposed mixed scaling of Z and relevance of h can be explained by physical arguments related to the limit of z-less stratification that is reached asymptotically above the surface layer. The presented evidence and fitted similarity relations are promising, but the results and arguments are limited to a small sample of idealized stationary stable boundary layers. Here, corroboration is needed from independent datasets and analyses, including for complex and transient conditions not tested here.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A miniaturized feedstocks-to-fuels pipeline for screening the efficiency of deconstruction and microbial conversion of lignocellulosic biomass

Sustainably grown biomass is a promising alternative to produce fuels and chemicals and reduce the dependency on fossil energy sources. However, the efficient conversion of lignocellulosic biomass into biofuels and bioproducts often requires extensive testing of components and reaction conditions used in the pretreatment, saccharification, and bioconversion steps. This restriction can result in a significant and unwieldy number of combinations of biomass types, solvents, microbial strains, and operational parameters that need to be characterized, turning these efforts into a daunting and time-consuming task. Here we developed a high-throughput feedstocks-to-fuels screening platform to address these challenges. The result is a miniaturized semi-automated platform that leverages the capabilities of a solid handling robot, a liquid handling robot, analytical instruments, and a centralized data repository, adapted to operate as an ionic-liquid-based biomass conversion pipeline. The pipeline was tested by using sorghum as feedstock, the biocompatible ionic liquid cholinium phosphate as pretreatment solvent, a “one-pot” process configuration that does not require ionic liquid removal after pretreatment, and an engineered strain of the yeast Rhodosporidium toruloides that produces the jet-fuel precursor bisabolene as a conversion microbe. By the simultaneous processing of 48 samples, we show that this configuration and reaction conditions result in sugar yields (~70%) and bisabolene titers (~1500 mg/L) that are comparable to the efficiencies observed at larger scales but require only a fraction of the time. We expect that this Feedstocks-to-Fuels pipeline will become an effective tool to screen thousands of bioenergy crop and feedstock samples and assist process optimization efforts and the development of predictive deconstruction approaches.

09 BIOMASS FUELS↗
DOE OSTI2021

Dose-Rate Effects of Protons and Light Ions for DNA Damage Induction, Survival and Transformation in Apparently Normal Primary Human Fibroblasts

In this work, we report on effects of low-dose exposures of accelerated protons delivered at high-dose rate (HDR) or a simulated solar-particle event (SPE) like low-dose rate (LDR) on immediate DNA damage induction and processing, survival and in vitro transformation of low passage NFF28 apparently normal primary human fibroblasts. Cultures were exposed to 50, 100 and 1,000 MeV monoenergetic protons in the Bragg entrance/plateau region and cesium-137 γ rays at 20 Gy/h (HDR) or 1 Gy/h (LDR). DNA double-strand breaks (DSB) and clustered DNA damages (containing oxypurines and abasic sites) were measured using transverse alternating gel electrophoresis (TAFE) and immunocytochemical detection/scoring of colocalized γ-H2AX pS139/53BP1 foci, with their induction being linear energy transfer (LET) dependent and dose-rate sparing observed for the different damage classes. Relative biological effectiveness (RBE) values for cell survival after proton irradiation at both dose-rates ranged from 0.61–0.73. Transformation RBE values were dose-rate dependent, ranging from ~1.8–3.1 and ~0.6–1.0 at low doses (≤30 cGy) for HDR and LDR irradiations, respectively. However peak transformation frequencies were significantly higher (1.3–7.3-fold) for higher doses of 0.5–1 Gy delivered at SPE-like LDR. Cell survival and transformation frequencies measured after low-dose 500 MeV/n He-4, 290 MeV/n C-12 and 600 MeV/n Si-28 ion irradiations also showed an inverse dose-rate effect for transformation at SPE-like LDR. This work demonstrates the existence of inverse dose-rate effects for proton and light-ion-induced postirradiation cell survival and in vitro transformation for space mission-relevant doses and dose rates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Joint optimal scheduling for electric vehicle battery swapping-charging system based on wind farms

Insufficiencies in charging facilities limit the broad application of electric vehicles (EVs). In addition, EV can hardly represent a green option if its electricity primarily depends on fossil energy. Considering these two problems, this paper studies a battery swapping-charging system based on wind farms (hereinafter referred to as W-BSCS). In a W-BSCS, the wind farms not only supply electricity to the power grid but also cooperate with a centralized charge station (CCS), which can centrally charge EV batteries and then distribute them to multiple battery swapping stations (BSSs). The operational framework of the W-BSCS is analyzed, and some preprocessing technologies are developed to reduce complexity in modeling. Then, a joint optimal scheduling model involving a wind power generation plan, battery swapping demand, battery charging and discharging, and a vehicle routing problem (VRP) is established. Then a heuristic method based on the exhaustive search and the Genetic Algorithm is employed to solve the formulated NP-hard problem. Numerical results verify the effectiveness of the joint optimal scheduling model, and they also show that the W-BSCS has great potential to promote EVs and wind power.

17 WIND ENERGY↗
DOE OSTI2021

Estimates of Damped Energy Spread and Emittance in a Two Energy Storage Ring Cooler

In this paper we provide estimates of the damped energy spread and emittance in a two-energy storage ring cooler. Two energy storage rings have two loops at markedly different energies, one at low energy and the other at high energy. In a cooling application the low energy ring has a cooling section to cool the ion beam and the high energy ring may have a wiggler section to enhance the damping effect on electron beam. The linear optics in the cooling section is designed to attain the maximum cooling of ion beams. Similarly, the linear optics in the wiggler section is designed to attained the required equilibrium emittance and energy spread. Hence, the radiation events in these two rings are different and independent. Since the values of damped energy spread and emittance depend on a range of parameters related to lattice design and rings energies, we present analytical calculations along with simulation results to estimate the values of damped energy spread and emittance in a two energy storage ring cooler.

Dhital, B.↗
DOE OSTI2022

Boson Fermion Nucleus Explanation for Fission Fragment Anisotropy: Monograph #13

Since 1952, anisotropy has been observed in the paths of fission fragments following the assimilation of an incident neutron or photon in the nucleus. Fission fragment flux favors certain angles relative to the path of the incident particle, constituting anisotropy. The amount of anisotropy is dependent on the energy of the incident particle. Fission fragment anisotropy can be explained by the disruption of nuclear structure combined with the requirement of a specific rotational orientation in theta and phi of that structure relative to the incident neutron or photon flux. A specific and limited area in the nucleus can assimilate the incident particle and induce upset within the structure, followed by scission and fission of the nucleus. The orientation and nature of the structure upset dictates fission fragment trajectory and is responsible for fission fragment anisotropy. This concept can be explained and supported by the theory of boson fermion nucleus (BFN) structure.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Integrating Machine Learning into a Methodology for Early Detection of Wellbore Failure [Slides]

Approximately 93% of US total energy supply is dependent on wellbores in some form. The industry will drill more wells in next ten years than in the last 100 years (King, 2014). Global well population is around 1.8 million of which approximately 35% has some signs of leakage (i.e. sustained casing pressure). Around 5% of offshore oil and gas wells “fail” early, more with age and most with maturity. 8.9% of “shale gas” wells in the Marcellus play have experienced failure (120 out of 1,346 wells drilled in 2012) (Ingraffea et al., 2014). Current methods for identifying wells that are at highest priority for increased monitoring and/or at highest risk for failure consists of “hand” analysis of multi-arm caliper (MAC) well logging data and geomechanical models. Machine learning (ML) methods are of interest to explore feasibility for increasing analysis efficiency and/or enhanced detection of precursors to failure (e.g. deformations). MAC datasets used to train ML algorithms and preliminary tests were run for “predicting” casing collar locations and performed above 90% in classification and identifying of casing collar locations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Integrating Machine Learning into a Methodology for Early Detection of Wellbore Failure [Slides]

Approximately 93% of US total energy supply is dependent on wellbores in some form. The industry will drill more wells in next ten years than in the last 100 years (King, 2014). Global well population is around 1.8 million of which approximately 35% has some signs of leakage (i.e. sustained casing pressure). Around 5% of offshore oil and gas wells “fail” early, more with age and most with maturity. 8.9% of “shale gas” wells in the Marcellus play have experienced failure (120 out of 1,346 wells drilled in 2012) (Ingraffea et al., 2014). Current methods for identifying wells that are at highest priority for increased monitoring and/or at highest risk for failure consists of “hand” analysis of multi-arm caliper (MAC) well logging data and geomechanical models. Machine learning (ML) methods are of interest to explore feasibility for increasing analysis efficiency and/or enhanced detection of precursors to failure (e.g. deformations). MAC datasets used to train ML algorithms and preliminary tests were run for “predicting” casing collar locations and performed above 90% in classification and identifying of casing collar locations.

54 ENVIRONMENTAL SCIENCES↗