Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “gradient sampling”

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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Comparative Analysis of Microbial Diversity Across Temperature Gradients in Hot Springs From Yellowstone and Iceland

Geothermal hot springs are a natural setting to study microbial adaptation to a wide range of temperatures reaching up to boiling. Temperature gradients lead to distinct microbial communities that inhabit their optimum niches. We sampled three alkaline, high temperature (80–100°C) hot springs in Yellowstone and Iceland that had cooling outflows and whose microbial communities had not been studied previously. The microbial composition in sediments and mats was determined by DNA sequencing of rRNA gene amplicons. Over three dozen phyla of Archaea and Bacteria were identified, representing over 1700 distinct organisms. We observed a significant non-linear reduction in the number of microbial taxa as the temperature increased from warm (38°C) to boiling. At high taxonomic levels, the community structure was similar between the Yellowstone and Iceland hot springs. We identified potential endemism at the genus level, especially in thermophilic phototrophs, which may have been potentially driven by distinct environmental conditions and dispersal limitations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Elemental Abundances in M31: Gradients in the Giant Stellar Stream

We analyze existing measurements of [Fe/H] and [α/Fe] for individual red giant branch (RGB) stars in the Giant Stellar Stream (GSS) of M31 to determine whether spatial abundance gradients are present. These measurements were obtained from low- (R ~ 3000) and moderate- (R ~ 6000) resolution Keck/DEIMOS spectroscopy using spectral synthesis techniques as part of the Elemental Abundances in M31 survey. From a sample of 62 RGB stars spanning the GSS at 17, 22, and 33 projected kpc, we measure a [Fe/H] gradient of -0.018 ± 0.003 dex kpc{sup -1} and negligible [α/Fe] gradient with M31-centric radius. We investigate GSS abundance patterns in the outer halo using additional [Fe/H] and [α/Fe] measurements for six RGB stars located along the stream at 45 and 58 projected kpc. These abundances provide tentative evidence that the trends in [Fe/H] and [α/Fe] beyond 40 kpc in the GSS are consistent with those within 33 kpc. We also compare the GSS abundances to 65 RGB stars located along the possibly related Southeast (SE) shelf substructure at 12 and 18 projected kpc. The abundances of the GSS and SE shelf are consistent, supporting a common origin hypothesis, although this interpretation may be complicated by the presence of [Fe/H] gradients in the GSS. We discuss the abundance patterns in the context of photometric studies from the literature and explore implications for the properties of the GSS progenitor, suggesting that the high ⟨[α/Fe]⟩ of the GSS (+0.40 ± 0.05 dex) favors a major merger scenario for its formation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Degenerate doping in B-Ga 2 O 3 Single Crystals through Hf-doping

n-type conductivity of β-Ga 2 O 3 grown from the melt is typically achieved using Sn and Si. In this paper, we experimentally and computationally investigate Hf doping of β-Ga 2 O 3 single crystals using UV–vis-NIR absorption and Hall effect measurements and hybrid functional calculations. Unintentionally-doped and Hf-doped samples with a nominal concentration of 0.5at% were grown from the melt using vertical gradient freeze and Czochralski method in mixed Ar + O 2 atmosphere. We demonstrate Hf dopants, predicted to incorporate on the octahedral GaII site as a shallow donor, achieve degenerate doping in β-Ga 2 O 3 with a measured electron concentration ~2 × 10 19 cm -3 , mobility 80–65 cm 2 V -1 s -1 , and resistivity down to 5 mΩ cm in our samples. The concentration of Hf was measured to be 1.3 × 10 19 atoms cm -3 using glow discharge mass spectroscopy on doped samples, confirming Hf to be the cause of n-type conductivity (electron concentration ~2 × 10 19 cm -3 ).

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ice nucleating particle concentrations measured by the CSU-CFDC during the AGINSGP field experiment

Real-time, immersion mode ambient ice nucleating particle (INP) concentrations were measured at ARM&rsquo;s Southern Great Plains (SGP) site during the AGINSGP field experiment using a continuous flow diffusion chamber (CFDC) from Colorado State University (CSU). The CSU-CFDC is an ice-thermal gradient diffusion chamber that optically detects the freezing of single aerosol particles (Rogers 1988; Rogers et al. 2001; and Eidhammer et al. 2010). The instrument was located in the guest instrument facility (GIF) and measured INP concentrations from April 8th to April 29th. Air was drawn into the GIF through custom aluminum stack inlets (6&rdquo; inner diameter) attached vertically to the outer GIF wall and the GIF outside platform. A blower pulled air through the stacks at a velocity of 1 m/s. Aerosol instruments subsampled via wall ports, through either 3/8&rdquo; or 1/4" copper lines, depending on sample flow of the instrument. Rogers, D. C., Development of a continuous flow thermal gradient diffusion chamber for ice nucleation studies, Atmospheric Research, 22(2), 149-181, doi:10.1016/0169-8095(88)90005-1, 1988. Rogers, D. C., P. J. DeMott, S. M. Kreidenweis and Y. Chen, A continuous flow diffusion chamber for airborne measurements of ice nuclei, J. Atmos. Oceanic Technol., 18, 725-741, doi:10.1175/1520-0426(2001)018<0725:ACFDCF>2.0.CO;2, 2001. Eidhammer, T., DeMott, P. J., Prenni, A. J., Petters, M. D., Twohy, C. H., Rogers, D. C., Stith, J., Heymsfield, A., Wang, Z., Haimov, S., French, J., Pratt, K., Prather, K., Murphy, S., Seinfeld, J., Subramanian, R., and Kreidenweis, S. M., Ice initiation by aerosol particles: Measured and predicted ice nuclei concentrations versus measured ice crystal concentrations in an orographic wave cloud, J. Atmos. Sci., 67, 2417-2436, doi:10.1175/2010JAS3266.1, 2010

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Degradation Reduces Microbial Richness and Alters Microbial Functions in an Australian Peatland

Abstract Peatland ecosystems cover only 3% of the world’s land area; however, they store one-third of the global soil carbon (C). Microbial communities are the main drivers of C decomposition in peatlands, yet we have limited knowledge of their structure and function. While the microbial communities in the Northern Hemisphere peatlands are well documented, we have limited understanding of microbial community composition and function in the Southern Hemisphere peatlands, especially in Australia. We investigated the vertical stratification of prokaryote and fungal communities from Wellington Plains peatland in the Australian Alps. Within the peatland complex, bog peat was sampled from the intact peatland and dried peat from the degraded peatland along a vertical soil depth gradient (i.e., acrotelm, mesotelm, and catotelm). We analyzed the prokaryote and fungal community structure, predicted functional profiles of prokaryotes using PICRUSt, and assigned soil fungal guilds using FUNGuild. We found that the structure and function of prokaryotes were vertically stratified in the intact bog. Soil carbon, manganese, nitrogen, lead, and sodium content best explained the prokaryote composition. Prokaryote richness was significantly higher in the intact bog acrotelm compared to degraded bog acrotelm. Fungal composition remained similar across the soil depth gradient; however, there was a considerable increase in saprotroph abundance and decrease in endophyte abundance along the vertical soil depth gradient. The abundance of saprotrophs and plant pathogens was two-fold higher in the degraded bog acrotelm. Soil manganese and nitrogen content, electrical conductivity, and water table level (cm) best explained the fungal composition. Our results demonstrate that both fungal and prokaryote communities are shaped by soil abiotic factors and that peatland degradation reduces microbial richness and alters microbial functions. Thus, current and future changes to the environmental conditions in these peatlands may lead to altered microbial community structures and associated functions which may have implications for broader ecosystem function changes in peatlands.

Environmental Sciences & Ecology↗
DOE OSTI2023

Tailoring material microstructure and property in wire-laser directed energy deposition through a wiggle deposition strategy

Developing effective strategies to directly control material microstructure, property, and anisotropy is an active research area in metal additive manufacturing. This work develops a wiggle deposition pattern for wire-laser directed energy deposition (DED) of 316L stainless steel (SS) to modify the solidification texture, particularly in the building direction, in as-deposited samples. Through multi-physics simulation, operando near-infrared imaging, and synchrotron x-ray characterization, it is found that the wiggle deposition strategy induces highly dynamic melt flow and oscillating thermal gradient in the melt pool, which is responsible for the variation of preferable grain growth direction and crystallographic texture in the sample. The specific texture reduces the anisotropy in the tensile strength of as-printed 316L SS samples cut along different directions. Also, it largely increases the ductility along the build direction. Crystal plasticity simulation is performed to correlate the sample texture with mechanical property. In conclusion, this work offers a unique approach for tailoring local properties through the control of melt pool instability by applying different tool paths.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Synthesis of cobalt grown from Co-S eutectic in high magnetic fields

Samples of Co were grown directly in the ferromagnetic state under equilibrium conditions using a cobalt sulfide flux. Magnetic fields up to 9 T were applied during growth, and isolated Co products exhibit progressively elongated morphologies, from cubes to rectangular rods to needle-like tendrils with poorly-defined facets. The degree of elongation of the major axis was found to correlate with magnetic field direction, strength, and gradient. Two-dimensional X-ray diffraction data indicate some level of polycrystalline-like samples, and quantitative analyses (Le Bail and Rietveld) of the one-dimensional data confirm the presence of hcp and fcc phases. The magnetic responses indicate a partial alignment of the magnetic easy-axis of the hcp phase along the magnetic field present during growth.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Vapor-Phase Intercalation of Cesium into Black Phosphorous

Cesium vapors were charged into black phosphorous (BP) flakes at varied times and at a temperature gradient of 150 °C. The X-ray diffraction (XRD) measurements of these samples suggest a reduction in the strength of van der Waal interactions between BP layers leading to the loss of coherence of out-of-plane peaks. At the same time, the three main Raman modes of BP (A g 1 , B 2 g , and A g 2 ) steadily redshifted as exposure times were increased, with modes B 2 g and A g 2 shifting faster than A g 1 . After initial rapid downshifts of active BP phonon modes, this intercalation strategy showed its limits following prolonged exposure times. Saturation of BP flakes by Cs vapors ensued and the kinetics was fitted with an exponential decay function. Furthermore, the thermoelectric power (TEP) of cesiated BP exhibited an inversion in sign from positive to negative around 400 K, lending credence to the transformation of as-prepared BP which is a p-type semiconductor to an n-type equivalent due to Cs atom intercalation driven shifting of the Fermi level toward the conduction band of BP and the donation of electrons from Cs. Furthermore, density functional theory (DFT) calculations were used to delve deeper into understanding Cs intercalation on the structural evolution of BP.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Soil carbon storage capacity of drylands under altered fire regimes

The determinants of fire-driven changes in soil organic carbon (SOC) across broad environmental gradients remains unclear, especially in global drylands. Here we combined datasets and field sampling of fire-manipulation experiments to evaluate where and why fire changes SOC and compared our statistical model to simulations from ecosystem models. Drier ecosystems experienced larger relative changes in SOC than humid ecosystems—in some cases exceeding losses from plant biomass pools—primarily explained by high fire-driven declines in tree biomass inputs in dry ecosystems. Many ecosystem models underestimated the SOC changes in drier ecosystems. Upscaling our statistical model predicted that soils in savannah–grassland regions may have gained 0.64 PgC due to net-declines in burned area over the past approximately two decades. Consequently, ongoing declines in fire frequencies have probably created an extensive carbon sink in the soils of global drylands that may have been underestimated by ecosystem models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A synthesis of bacterial and archaeal phenotypic trait data

A synthesis of phenotypic and quantitative genomic traits is provided for bacteria and archaea, in the form of a scripted, reproducible workflow that standardizes and merges 26 sources. The resulting unified dataset covers 14 phenotypic traits, 5 quantitative genomic traits, and 4 environmental characteristics for approximately 170,000 strain-level and 15,000 species-aggregated records. It spans all habitats including soils, marine and fresh waters and sediments, host-associated and thermal. Trait data can find use in clarifying major dimensions of ecological strategy variation across species. They can also be used in conjunction with species and abundance sampling to characterize trait mixtures in communities and responses of traits along environmental gradients.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Ab initio molecular dynamics on quantum computers

Ab initio molecular dynamics (AIMD) is a valuable technique for studying molecules and materials at finite temperatures where the nuclei evolve on potential energy surfaces obtained from accurate electronic structure calculations. In this work, we present an approach to running AIMD simulations on noisy intermediate-scale quantum (NISQ)-era quantum computers. The electronic energies are calculated on a quantum computer using the variational quantum eigensolver (VQE) method. Algorithms for computation of analytical gradients entirely on a quantum computer require quantum fault-tolerant hardware, which is beyond NISQ-era. Therefore, we compute the energy gradients numerically using finite differences, the Hellmann-Feynman theorem, and a correlated sampling technique. This method only requires additional classical calculations of electron integrals for each degree of freedom without any additional computations on a quantum computer beyond the initial VQE run. As a proof of concept, AIMD simulations are demonstrated for the H-2 molecule on IBM quantum devices. In addition, we demonstrate the validity of the method for larger molecules using full configuration interaction wave functions. As quantum hardware and noise mitigation techniques continue to improve, the method can be utilized for studying larger molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Wavefront shaping with a Hadamard basis for scattering soil imaging

Here, soil is a scattering medium that inhibits imaging of plant-microbial-mineral interactions that are essential to plant health and soil carbon sequestration. However, optical imaging in the complex medium of soil has been stymied by the seemingly intractable problems of scattering and contrast. Here, we develop a wavefront shaping method based on adaptive stochastic parallel gradient descent optimization with a Hadamard basis to focus light through soil mineral samples. Our approach allows a sparse representation of the wavefront with reduced dimensionality for the optimization. We further divide the used Hadamard basis set into subsets and optimize a certain subset at once. Simulation and experimental optimization results demonstrate our method has an approximately seven times higher convergence rate and overall better performance compared to that with optimizing all pixels at once. The proposed method can benefit other high-dimensional optimization problems in adaptive optics and wavefront shaping.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Dissolved oxygen sensor in an automated hyporheic sampling system reveals biogeochemical dynamics

Many river corridor systems frequently experience rapid variations in river stage height, hydraulic head gradients, and residence times. The integrated hydrology and biogeochemistry of such systems is challenging to study, particularly in their associated hyporheic zones. Here we present an automated system to facilitate 4-dimensional study of dynamic hyporheic zones. It is based on combining real-time in-situ and ex-situ measurements from sensor/sampling locations distributed in 3-dimensions. A novel dissolved oxygen (DO) sensor was integrated into the system during a small scale study. We measured several biogeochemical and hydrologic parameters at three subsurface depths in the riverbed of the Columbia River in Washington State, USA, a dynamic hydropeaked river corridor system. During the study, episodes of significant DO variations (~+/- 4 mg/l) were observed, with minor variation in other parameters (e.g., <~+/-0.15 mg/l NO 3 ). DO concentrations were related to hydraulic head gradients, showing both hysteretic and non-hysteretic relationships with abrupt (hours) transitions between the two types of relationships. The observed relationships provide a number of hypotheses related to the integrated hydrology and biogeochemistry of dynamic hyporheic zones. We suggest that preliminary high-frequency monitoring is advantageous in guiding the design of long term monitoring campaigns. The study also demonstrated the importance of measuring multiple parameters in parallel, where the DO sensor provided the key signal for identifying/detecting transient phenomena.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Solute chemistry for streams draining geomorphic features and varying land cover gradients in the East River watershed, Colorado

This dataset contains solute chemistry data and GPS coordinates for surface water samples collected in the East River watershed in the Elk and West Elk Ranges of Colorado from August 3rd through August 11th, 2022. Samples were collected from streams and groundwater seeps as part of a comprehensive analysis within the watershed of how different geomorphic features (such as landslides and rock glaciers) along with variations in land cover (such as the presence of vegetation) affect stream water quality in this Rocky Mountain headwater environment. This dataset includes concentrations of the following in a single csv file: fluoride, chloride, sulfate, nitrate, calcium, potassium, magnesium, sodium, silicon, and total organic carbon (TOC). All concentrations are reported in mg/L. The sulfate data in this version have been updated to account for an earlier ion chromatograph instrument method error whereby sulfate and bromide peaks overlapped in calibration solution samples, biasing calculated sulfate concentrations low by 30-50%. Sulfate data reported herein are from a re-run of the samples performed in December 2024 using a corrected instrument method. All samples were stored under refrigerated conditions and filtered on initial collection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Root‐Pore Interactions, the Underestimated Driver for Rhizosphere Structure and Rhizosheath Development

Physical characteristics of rhizosphere and rhizosheath, that is, root-adhering soil, are crucial for plant performance. Yet, the drivers of the rhizosphere's structural properties and their relationships with rhizosheath development remain unclear. We used X-ray computed micro-tomography (i) to explore two drivers of rhizosphere porosity: root-induced changes vs. preferential root growth into soil with certain pore characteristics and (ii) to estimate their contributions to rhizosphere macroporosity gradients and rhizosheath formation. Rhizosheath development was assessed in relation to rhizosphere macroporosity and rhizodeposition after ¹⁴C labeling. Our results confirmed that both root-induced changes and growth preferences shape rhizosphere structure, with their relative significance depending on the inherent macropore availability. In intact soils, growth preferences were the dominant factor, while in sieved soils the root-induced changes became equally important. Rhizosheath formation was associated with roots compacting their surrounding and releasing carbon. However, no correlation was found between rhizosheath formation and the actual rhizosphere, that is, the volume of soil adjacent to the roots. The study offers new process-level understanding of rhizosphere porosity gradients, while emphasizing caution in interpreting root growth data from sieved soil studies. Similarly, traditional destructively sampled rhizosheath may not fully capture the true characteristics of the actual rhizosphere, underscoring importance of intact-soil analyses.

macroporosity gradients↗
DOE OSTI2020

A Dynamic Amplitude-Correcting Gradient Estimation Technique to Align X-ray Focusing Optics

High-brightness X-rays, as produced at synchrotrons and X-ray free electron laser (XFEL) facilities, are used to characterize materials in a variety of scientific experiments. In most cases, effective use of the high-energy light requires precisely-aligned focusing optics; one example being a compound refractive lens (CRL). To align a CRL, the position and rotation must be optimized along four axes. In practice, this is a labor-intensive, time-consuming manual process that can monopolize scarce experimental time at the necessary X-ray facilities. Models of the expected Xray transmission function suggest that this task can be automated; however, the temporally-varying intensity at X-ray free electron laser facilities preclude the direct use of standard implementations of optimization solvers such as steepest descent algorithms. In this paper, we propose a novel technique to estimate the gradient of noisy functions with temporally-varying amplitudes. We construct this dynamicamplitude correction by systematically sampling a fixed central location within the standard finite difference stencil, accounting for the observed changes in time, and normalizing the difference quotients against those fluctuations. In addition to a rigorous error analysis of the sampling technique, we demonstrate its efficacy in stochastic descent optimization methods. Further, we demonstrate how this approach may be implemented to optimize X-ray focusing optics at synchrotrons or XFEL facilities

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker–Planck Equations

The Fokker-Planck (FP) equation is a foundational partial differential equation (PDE) in stochastic processes involving Brownian motions. However, the curse of dimensionality (CoD) poses a formidable challenge when dealing with high-dimensional FP equations. Although Monte Carlo simulation and (vanilla) Physics-Informed Neural Networks (PINNs) have shown the potential to tackle CoD, both methods exhibit significant numerical errors in high dimensions when dealing with the probability density function (PDF) associated with Brownian motion. The point-wise PDF values tend to decrease exponentially as dimensionality increases, surpassing the precision of numerical simulations and resulting in substantial errors. In addition, due to its massive sampling, Monte Carlo fails to offer fast sampling. Modeling the logarithm likelihood (LL) via vanilla PINNs transforms the FP equation into a notoriously difficult Hamilton-Jacobi-Bellman (HJB) equation, which is impractical for PINN learning, whose error grows rapidly with dimension. To this end, we propose a novel approach utilizing a score-based solver to fit the score function in stochastic differential equations (SDEs). The score function, defined as the gradient of the LL, plays a fundamental role in inferring LL and PDF and enables fast SDE sampling, offering an effective means to overcome the CoD. Three fitting methods, Score Matching (SM), Sliced Score Matching (SSM), and Score-PINN, are introduced, each contributing unique advantages in computational complexity, accuracy, and generality. The proposed score-based SDE solver operates in two stages: first, employing score matching or Score-PINN to acquire the score function; and second, solving the LL via an ordinary differential equation (ODE) using the obtained score function. Comparative evaluations across these methods showcase varying trade-offs. The proposed methodology is evaluated across diverse SDEs, including anisotropic Ornstein-Uhlenbeck processes, geometric Brownian motion, and Brownian motion with varying eigenspace. We also test various distributions, including Gaussian, Log-normal, Laplace, and Cauchy distributions. The numerical results demonstrate the score-based SDE solver’s stability, speed, and performance across different experimental settings, solidifying its potential as a solution to CoD for high-dimensional FP equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Resource frugal optimizer for quantum machine learning

Quantum-enhanced data science, also known as quantum machine learning (QML), is of growing interest as an application of near-term quantum computers. Variational QML algorithms have the potential to solve practical problems on real hardware, particularly when involving quantum data. However, training these algorithms can be challenging and calls for tailored optimization procedures. Specifically, QML applications can require a large shot-count overhead due to the large datasets involved. In this work, we advocate for simultaneous random sampling over both the dataset as well as the measurement operators that define the loss function. We consider a highly general loss function that encompasses many QML applications, and we show how to construct an unbiased estimator of its gradient. This allows us to propose a shot-frugal gradient descent optimizer called Refoqus (REsource Frugal Optimizer for QUantum Stochastic gradient descent). Our numerics indicate that Refoqus can save several orders of magnitude in shot cost, even relative to optimizers that sample over measurement operators alone.

97 MATHEMATICS AND COMPUTING↗