Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “activation 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.

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

At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Magnetized Strongly Turbulent Corona as the Source of Neutrinos from NGC 1068

Abstract The cores of active galactic nuclei are potential accelerators of 10–100 TeV cosmic rays, in turn producing high-energy neutrinos. This picture was confirmed by the compelling evidence of a TeV neutrino signal from the nearby active galaxy NGC 1068, leaving open the question of what is the site and mechanism of cosmic-ray acceleration. One candidate is the magnetized turbulence surrounding the central supermassive black hole. Recent particle-in-cell simulations of magnetized turbulence indicate that stochastic cosmic-ray acceleration is nonresonant, in contrast to the assumptions of previous studies. We show that this has important consequences on a self-consistent theory of neutrino production in the corona, leading to a more rapid cosmic-ray acceleration than previously considered. The turbulent magnetic-field fluctuations needed to explain the neutrino signal are consistent with a magnetically powered corona. We find that strong turbulence, with turbulent magnetic energy density higher than 1% of the rest-mass energy density, naturally explains the normalization of the IceCube neutrino flux, in addition to the neutrino spectral shape. Only a fraction of the protons in the corona, which can be directly inferred from the neutrino signal, are accelerated to high energies. Thus, in this framework, the neutrino signal from NGC 1068 provides a testbed for particle acceleration in magnetized turbulence.

Fiorillo, Damiano F. G. (ORCID:0000000349279850)↗
NASA NTRS1997

Neuromuscular activation patterns during treadmill walking after space flight

Astronauts adopt a variety of neuromuscular control strategies during space flight that are appropriate for locomoting in that unique environment, but are less than optimal upon return to Earth. We report here the first systematic investigation of potential adaptations in neuromuscular activity patterns associated with postflight locomotion. Astronaut-subjects were tasked with walking on a treadmill at 6.4 km/h while fixating a visual target 30 cm away from their eyes after space flights of 8-15 days. Surface electromyography was collected from selected lower limb muscles and normalized with regard to mean amplitude and temporal relation to heel strike. In general, high correlations (more than 0.80) were found between preflight and postflight activation waveforms for each muscle and each subject: however relative activation amplitude around heel strike and toe off was changed as a result of flight. The level of muscle cocontraction and activation variability, and the relationship between the phasic characteristics of the ankle musculature in preparation for toe off also were altered by space flight. Subjects also reported oscillopsia during treadmill walking after flight. These findings indicate that, after space flight, the sensory-motor system can generate neuromuscular-activation strategies that permit treadmill walking, but subtle changes in lower-limb neuromuscular activation are present that may contribute to increased lower limb kinematic variability and oscillopsia also present during postflight walking.

Flight Experiment↗
DOE OSTI2024

Active and Transfer Learning of High-Dimensional Neural Network Potentials for Transition Metals

Classical molecular dynamics (MD) simulations represent a very popular and powerful tool for materials modeling and design. The predictive power of MD hinges on the ability of the interatomic potential to capture the underlying physics and chemistry. There have been decades of seminal work on developing interatomic potentials, albeit with a focus predominantly on capturing the properties of bulk materials. Such physics-based models, while extensively deployed for predicting the dynamics and properties of nanoscale systems over the past two decades, tend to perform poorly in predicting nanoscale potential energy surfaces (PESs) when compared to high-fidelity first-principles calculations. These limitations stem from the lack of flexibility in such models, which rely on a predefined functional form. Machine learning (ML) models and approaches have emerged as a viable alternative to capture the diverse size-dependent cluster geometries, nanoscale dynamics, and the complex nanoscale PESs, without sacrificing the bulk properties. Here, in this study, we introduce an ML workflow that combines transfer and active learning strategies to develop high-dimensional neural networks (NNs) for capturing the cluster and bulk properties for several different transition metals with applications in catalysis, microelectronics, and energy storage, to name a few. Our NN first learns the bulk PES from the high-quality physics-based models in literature and subsequently augments this learning via retraining with a higher-fidelity first-principles training data set to concurrently capture both the nanoscale and bulk PES. Our workflow departs from status-quo in its ability to learn from a sparsely sampled data set that nonetheless covers a diverse range of cluster configurations from near-equilibrium to highly nonequilibrium as well as learning strategies that iteratively improve the fingerprinting depending on model fidelity. All the developed models are rigorously tested against an extensive first-principles data set of energies and forces of cluster configurations as well as several properties of bulk configurations for 10 different transition metals. Our approach is material agnostic and provides a methodology to transfer and build upon the learnings from decades of seminal work in molecular simulations on to a new generation of ML-trained potentials to accelerate materials discovery and design.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Active chlorine and nitric oxide formation from chemical rocket plume afterburning

Chlorine and oxides of nitrogen (NO(x)) released into the atmosphere contribute to acid rain (ground level or low-altitude sources) and ozone depletion from the stratosphere (high-altitude sources). Rocket engines have the potential for forming or activating these pollutants in the rocket plume. For instance, H2/O2 rockets can produce thermal NO(x) in their plumes. Emphasis, in the past, has been placed on determining the impact of chlorine release on the stratosphere. To date, very little, if any, information is available to understand what contribution NO(x) emissions from ground-based engine testing and actual rocket launches have on the atmosphere. The goal of this work is to estimate the afterburning emissions from chemical rocket plumes and determine their local stratospheric impact. Our study focuses on the space shuttle rocket motors, which include both the solid rocket boosters (SRB's) and the liquid propellant main engines (SSME's). Rocket plume afterburning is modeled employing a one-dimensional model incorporating two chemical kinetic systems: chemical and thermal equilibria with overlayed nitric oxide chemical kinetics (semi equilibrium) and full finite-rate chemical kinetics. Additionally, the local atmospheric impact immediately following a launch is modeled as the emissions diffuse and chemically react in the stratosphere.

Leone, D. M.↗
DOE OSTI2021

Electrochemical Modeling of Iodide Oxidation in Metal-Halide Molten Salts

The oxidation of iodide in NaI-AlBr 3 , NaI-AlCl 3 , and NaI-GaCl 3 molten salts was analyzed using simulation software to extract relevant kinetic parameters. The experimental oxidation potentials were ordered AlCl 3 < AlBr 3 < GaCl 3 , with higher oxidation potentials correlating with softer Lewis acidity of the metal halide. An iodide oxidation and metal halide speciation model was developed and simulated to fit the electrochemical response, enabling determination of electrochemical charge transfer parameters and chemical equilibrium constants. NaI-AlBr 3 displayed the fastest electron transfer rates yet showed the lowest current densities. All salts revealed smaller than expected current densities, explained by equilibrium between various species, where some are not electrochemically active at the studied potentials. These equilibrium reactions are due to the various metal halide species, controlling the reactant concentration of iodide and the resultant current. We hypothesize the electrochemically active iodide species, present as a metal halide monomer (MX 3 I − ), is decreased dramatically from the expected concentration, sequestered as a more stable metal halide dimer species (M 2 X 6 I − ) with a higher oxidation potential. Traditional Tafel analysis of the experimental data supports the validity of the simulations. These results increase understanding of iodide oxidation in low-temperature Lewis acidic molten salts and inform task-specific molten salt design.

Lee, Rose Y. (ORCID:0000000226587220)↗
NASA NTRS2001

Use of Yohkoh SXT in Measuring the Net Current and CME Productivity of Active Regions

In our investigation of the correlation of global nonpotentiality of active regions to their CME productivity (Falconer, D.A. 2001, JGR, in press, and Falconer, Moore, & Gary, 2000, EOS 82, 20 S323), we use Yohkoh SXT images for two purposes. The first use is to help resolve the 180 degree ambiguity in the direction of the observed transverse magnetic field. Resolution of the 180 degree ambiguity is important, since the net current, one of our measures of global nonpotentiality, is derived from integrating the dot product of the transverse field around a contour (I(sub N)=(integral)BT(raised dot)dl). The ambiguity results from the observed transverse field being determined from the linear polarization, which gives the plane of the direction, but leaves a 180 degrees ambiguity. Automated methods to resolve the ambiguity ranging from the simple acute angle rule (Falconer, D.A. 2001) to the more sophisticated annealing method (Metcalf T.R. 1994). For many active regions, especially ones that are nearly potential these methods work well. But for very nonpotential active regions where the shear angle (the angle between the observed and potential transverse field) is near 90 degrees throughout large swaths along the main neutral line, both methods can resolve the ambiguity incorrectly for long segments of the neutral line. By determining from coronal images, such as those from Yohkoh/SXT, the sense of shear along the main neutral line in the active region, these cases can be identified and corrected by a modification of the acute angle rule described here. The second use of Yohkoh/SXT in this study is to check for the cusped coronal arcades of long-duration eruptive flares. This signature is an excellent proxy for CMEs, and was used by Canfield, Hudson, and McKenzie (1999 GRL V26, 6, 627-630). This work is funded by NSF through the Space Weather Program and by NASA through the Solar Physics Supporting Research and Technology Program.

Falconer, D. A.↗
DOE OSTI2024

Accelerated Steam Methane Reforming by Dynamically Applied Charges

Catalyst design has traditionally focused on tuning active site properties to optimally bind reaction intermediates and balance the kinetic requirements of multiple competing chemical processes, as necessitated by the Sabatier principle. It has recently been proposed that for reactions following certain potential energy landscapes, the activity limit imposed by the Sabatier principle may be overcome by using programmed oscillations of surface electron density at the timescales of surface reactions (i.e., “catalytic resonance”). Here, we use a combination of density functional theory (DFT) simulations and transient kinetic models (TKMs) to simulate the kinetics of steam methane reforming (SMR) on Ru(211) surfaces under statically and dynamically applied charges. DFT-calculated binding energies of SMR intermediates and transition states exhibit strong sensitivity to positively applied charges and follow unique scaling relationships that deviate from linear periodic trends across transition metals. Our simulations demonstrate that applying a small positive charge to Ru dramatically enhances the steady-state turnover frequency (TOF) of SMR by up to 5 orders of magnitude above the TOF observed over neutral Ru. Thus, statically charging Ru catalysts may be an effective strategy to lower the temperature requirements for SMR. Dynamic square-wave oscillations in charge resulted in SMR catalytic resonance with an onset frequency f ∼ 106 Hz and the corresponding average TOFs exceeding the statically charged Ru surface by an additional 15%. Here, based on sensitivity analyses performed for the two end points of oscillation, we propose that dynamic TOF improvement beyond the Sabatier maximum can be expected when the system oscillates between two kinetic regimes that are uniquely controlled by distinct elementary steps.

Catalysts↗
NASA NTRS1980

Fuel conservation through active control of rotor clearances

Under the NASA-sponsored Energy Efficient Engine (EEE) Project, technology is being developed which will significantly reduce the fuel consumption of turbofan engines for subsonic transport aircraft. One technology concept being pursued is active control of rotor tip clearances. Attention is given to rotor tip clearance considerations and an overview of preliminary study results as well as the General Electric EEE clearance control approach is presented. Finally, potential fuel savings with active control of rotor clearances for a typical EEE mission are predicted.

Beitler, R. S.↗
DOE OSTI2026

Unlocking plant-microbial interactions in deep Mollisols in the Midwestern US: Linking depth gradients in roots, microbial activity, and soil carbon in agroecosystems

Deep-rooted plants may build soil carbon (C) stocks, but most research has focused on shallow soils, leaving gaps in our understanding of how shifts in the balance between decomposition and C inputs drive soil C accumulation with depth. Thus, our objectives were to: (1) link depth gradients in root biomass with microbial activity and soil C stocks down to 1 m, and (2) examine the potential of simple C inputs to prime soil C across depths. To this end, we dug 5 quantitative soil pits in Argiudolls under mature perennial miscanthus plots in the SoyFACE Farm (Champaign-Urbana, IL). We added 13 C labeled glucose to our soils to determine the fate of simple C inputs with depth. We found that fine root biomass, total soil C, mineral-associated organic C (MAOC), particulate organic C (POC), and microbial activity (as measured by potential enzyme activity) declined with depth. POC declined more rapidly than MAOC, resulting in an increase in the ratio of MAOC-to-POC. Root biomass, enzyme activity (either acid phosphatase or n-acetyl-glucosaminadase) activity, and microbial respiration explained 74% and 38% of the variability in soil total C and MAOC, respectively, while POC was dependent on root biomass and microbial respiration (47%). Although the incorporation of simple 13 C inputs into MAOC was similar across depths, these inputs led to greater net MAOC losses in shallow soils than in deeper soils between 50 and 100 cm. The divergent impact of simple C inputs across depths may suggest that MAOC in shallow soils is more susceptible to priming losses, while C inputs into deep soils may instead be more persistent. Collectively, our results suggest that depth gradients in soil C stocks represents a balance between inputs, decomposition, and microbial necromass production and that increases in root C inputs by deep-rooted plants may have the potential to build stable MAOC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

BONCAT-FACS-Seq reveals the active fraction of a biocrust community undergoing a wet-up event

Determining which microorganisms are active within soil communities remains a major technical endeavor in microbial ecology research. One promising method to accomplish this is coupling bioorthogonal non-canonical amino acid tagging (BONCAT) with fluorescence activated cell sorting (FACS) which sorts cells based on whether or not they are producing new proteins. Combined with shotgun metagenomic sequencing (Seq), we apply this method to profile the diversity and potential functional capabilities of both active and inactive microorganisms in a biocrust community after being resuscitated by a simulated rain event. We find that BONCAT-FACS-Seq is capable of discerning the pools of active and inactive microorganisms, especially within hours of applying the BONCAT probe. The active and inactive components of the biocrust community differed in species richness and composition at both 4 and 21 h after the wetting event. The active fraction of the biocrust community is marked by taxa commonly observed in other biocrust communities, many of which play important roles in species interactions and nutrient transformations. Among these, 11 families within the Firmicutes are enriched in the active fraction, supporting previous reports indicating that the Firmicutes are key early responders to biocrust wetting. We highlight the apparent inactivity of many Actinobacteria and Proteobacteria through 21 h after wetting, and note that members of the Chitinophagaceae, enriched in the active fraction, may play important ecological roles following wetting. Based on the enrichment of COGs in the active fraction, predation by phage and other bacterial members, as well as scavenging and recycling of labile nutrients, appear to be important ecological processes soon after wetting. To our knowledge, this is the first time BONCAT-FACS-Seq has been applied to biocrust samples, and therefore we discuss the potential advantages and shortcomings of coupling metagenomics to BONCAT to intact soil communities such as biocrust. In all, by pairing BONCAT-FACS and metagenomics, we are capable of highlighting the taxa and potential functions that typifies the microbes actively responding to a rain event.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

High-temperature nanoindentation creep studies on castable and sintered nanostructured low-activation ferritic-martensitic alloys

In this article, we present the creep characteristics of two reduced activation ferritic-martensitic steels of identical starting compositions formed by different fabrication routes: a nanostructured ferritic alloy commonly referred to as a castable nanostructured alloy (CNA) and a sintered nanostructured alloy (SNA) variant. Through a series of nanoindentation experiments spanning a temperature range of 25 °C to 650 °C, with a maximum load of 100 mN, we find creep behaviors in the cast and sintered materials to be remarkably similar. The creep stress exponent (n) for CNA and SNA were found to be in the range of 8–35 and the activation volume was ∼14–42b 3 , underscoring a dominance of dislocation-mediated mechanisms in both alloys. Notably, we observed a decline in the creep stress exponent with increasing temperature, attributable to the heightened influence of thermally activated dislocations. This phenomenon suggests a potential transition in the deformation mechanism towards a thermally activated dislocation climb process, significantly impacting the observed creep behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Near-Zero Power MOF-Based Sensors for NO 2 Detection

Detection and capture of toxic nitrogen oxides (NO x ) is important for emissions control of exhaust gases and general public health. The ability to directly electrically detect trace (0.5–5 ppm) NO 2 by a metal–organic framework (MOF)-74-based sensor at relatively low temperatures (50 °C) is demonstrated via changes in electrical properties of M-MOF-74, M = Co, Mg, Ni. The magnitude of the change is ordered Ni > Co > Mg and explained by each variant's NO 2 adsorption capacity and specific chemical interaction. Ni-MOF-74 provides the highest sensitivity to NO 2 ; a 725× decrease in resistance at 5 ppm NO2 and detection limit <0.5 ppm, levels relevant for industry and public health. Furthermore, the Ni-MOF-74-based sensor is selective to NO 2 over N 2 , SO 2 , and air. Linking this fundamental research with future technologies, the high impedance of MOF-74 enables applications requiring a near-zero power sensor or dosimeter, with the active material drawing <15 pW for a macroscale device 35 mm 2 with 0.8 mg MOF-74. Finally, this represents a 10 4 –10 6 × decrease in power consumption compared to other MOF sensors and demonstrates the potential for MOFs as active components for long-lived, near-zero power chemical sensors in smart industrial systems and the internet of things.

47 OTHER INSTRUMENTATION↗
NASA NTRS1971

The magnetic field structure in the active solar corona.

The structure of the magnetic field of the active solar corona is discussed with reference to optical and radio observations of the solar atmosphere. Eclipse observations provide evidence of fine scale structures in the solar atmosphere that appear to relate to the coronal magnetic field. The coronal magnetic field used for comparison is calculated from potential theory; the influence of solar activity upon the potential theory field is discussed with reference to observations of the Faraday rotation of a microwave signal from Pioneer 6 as it was occulted by the solar atmosphere. Evidence has been found suggesting the existence of expanding magnetic bottles located at 10 solar radii above flaring active regions. The dynamics of these events is discussed. It is further suggested that these magnetic bottles are an important component in the solar corona.

Schatten, K. H.↗
DOE OSTI2023

Rapid Polyolefin Hydrogenolysis by a Single‐Site Organo‐Tantalum Catalyst on a Super‐Acidic Support: Structure and Mechanism

Abstract The novel electrophilic organo‐tantalum catalyst AlS/TaNp x ( 1 ) (Np=neopentyl) is prepared by chemisorption of the alkylidene Np 3 Ta=CH t Bu onto highly Brønsted acidic sulfated alumina (AlS). The proposed catalyst structure is supported by EXAFS, XANES, ICP, DRIFTS, elemental analysis, and SSNMR measurements and is in good agreement with DFT analysis. Catalyst 1 is highly effective for the hydrogenolysis of diverse linear and branched hydrocarbons, ranging from C2 to polyolefins. To the best of our knowledge, 1 exhibits one of the highest polyolefin hydrogenolysis activities (9,800 (CH 2 units) ⋅ mol(Ta) −1 ⋅ h −1 at 200 °C/17 atm H 2 ) reported to date in the peer‐reviewed literature. Unlike the AlS/ZrNp 2 analog, the Ta catalyst is more thermally stable and offers multiple potential C−C bond activation pathways. For hydrogenolysis, AlS/TaNp x is effective for a wide variety of pre‐ and post‐consumer polyolefin plastics and is not significantly deactivated by standard polyolefin additives at typical industrial concentrations.

Lai, Qingheng↗
DOE OSTI2023

AL4GAP: Active learning workflow for generating DFT-SCAN accurate machine-learning potentials for combinatorial molten salt mixtures

Machine learning interatomic potentials have emerged as a powerful tool for bypassing the spatiotemporal limitations of ab initio simulations, but major challenges remain in their efficient parameterization. We present AL4GAP, an ensemble active learning software workflow for generating multicomposition Gaussian approximation potentials (GAP) for arbitrary molten salt mixtures. The workflow capabilities include: (1) setting up user-defined combinatorial chemical spaces of charge neutral mixtures of arbitrary molten mixtures spanning 11 cations (Li, Na, K, Rb, Cs, Mg, Ca, Sr, Ba and two heavy species, Nd, and Th) and 4 anions (F, Cl, Br, and I), (2) configurational sampling using low-cost empirical parameterizations, (3) active learning for down-selecting configurational samples for single point density functional theory calculations at the level of Strongly Constrained and Appropriately Normed (SCAN) exchange-correlation functional, and (4) Bayesian optimization for hyperparameter tuning of two-body and many-body GAP models. Here, we apply the AL4GAP workflow to showcase high throughput generation of five independent GAP models for multicomposition binary-mixture melts, each of increasing complexity with respect to charge valency and electronic structure, namely: LiCl–KCl, NaCl–CaCl 2 , KCl–NdCl 3 , CaCl 2 –NdCl 3 , and KCl–ThCl 4 . Our results indicate that GAP models can accurately predict structure for diverse molten salt mixture with density functional theory (DFT)-SCAN accuracy, capturing the intermediate range ordering characteristic of the multivalent cationic melts.

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

Rapid Polyolefin Hydrogenolysis by a Single‐Site Organo‐Tantalum Catalyst on a Super‐Acidic Support: Structure and Mechanism

The novel electrophilic organo-tantalum catalyst AlS/TaNp x (1) (Np=neopentyl) is prepared by chemisorption of the alkylidene Np 3 Ta=CH t Bu onto highly Brønsted acidic sulfated alumina (AlS). Here, the proposed catalyst structure is supported by EXAFS, XANES, ICP, DRIFTS, elemental analysis, and SSNMR measurements and is in good agreement with DFT analysis. Catalyst 1 is highly effective for the hydrogenolysis of diverse linear and branched hydrocarbons, ranging from C2 to polyolefins. To the best of our knowledge, 1 exhibits one of the highest polyolefin hydrogenolysis activities (9,800 (CH 2 units) ⋅ mol(Ta) −1 ⋅ h −1 at 200 °C/17 atm H 2 ) reported to date in the peer-reviewed literature. Unlike the AlS/ZrNp 2 analog, the Ta catalyst is more thermally stable and offers multiple potential C−C bond activation pathways. For hydrogenolysis, AlS/TaNp x is effective for a wide variety of pre- and post-consumer polyolefin plastics and is not significantly deactivated by standard polyolefin additives at typical industrial concentrations.

03 NATURAL GAS↗