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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Towards Construction of a Novel Nanometer-Resolution MeV-STEM for Imaging Thick Frozen Biological Samples

Driven by life-science applications, a mega-electron-volt Scanning Transmission Electron Microscope (MeV-STEM) has been proposed here to image thick frozen biological samples as a conventional Transmission Electron Microscope (TEM) may not be suitable to image samples thicker than 300–500 nm and various volume electron microscopy (EM) techniques either suffering from low resolution, or low speed. The high penetration of inelastic scattering signals of MeV electrons could make the MeV-STEM an appropriate microscope for biological samples as thick as 10 μm or more with a nanoscale resolution, considering the effect of electron energy, beam broadening, and low-dose limit on resolution. The best resolution is inversely related to the sample thickness and changes from 6 nm to 24 nm when the sample thickness increases from 1 μm to 10 μm. To achieve such a resolution in STEM, the imaging electrons must be focused on the specimen with a nm size and an mrad semi-convergence angle. This requires an electron beam emittance of a few picometers, which is ~1000 times smaller than the presently achieved nm emittance, in conjunction with less than 10 -4 energy spread and 1 nA current. We numerically simulated two different approaches that are potentially applicable to build a compact MeV-STEM instrument: (1) DC (Direct Current) gun, aperture, superconducting radio-frequency (SRF) cavities, and STEM column; (2) SRF gun, aperture, SRF cavities, and STEM column. Beam dynamic simulations show promising results, which meet the needs of an MeV-STEM, a few-picometer emittance, less than 10 -4 energy spread, and 0.1–1 nA current from both options. Also, we designed a compact STEM column based on permanent quadrupole quintuplet, not only to demagnify the beam size from 1 μm at the source point to 2 nm at the specimen but also to provide the freedom of changing the magnifications at the specimen and a scanning system to raster the electron beam across the sample with a step size of 2 nm and the repetition rate of 1 MHz. This makes it possible to build a compact MeV-STEM and use it to study thick, large-volume samples in cell biology.

36 MATERIALS SCIENCE↗
DOE OSTI2023

WRF Output from 270m domain running simulation with no 3D morphology, NUDAPT 3D morphology, 100m resolution 3D morphology and 10m resolution 3D morphology

This is a group of four datasets that were run for an experiment testing the effect of the resolution and the coverage of 3D urban morphological inputs on meteorological output. This data is associated with the paper "Sensitivity of Urban Morphology to the Resolution of Urban Morphological Feature Inputs: Implications for Characterizing Urban Sustainability."

integrated multisector multiscale modeling↗
DOE OSTI2024

WRF Output from 270m domain running simulation with no 3D morphology, NUDAPT 3D morphology, 100m resolution 3D morphology and 10m resolution 3D morphology

This is a group of four datasets that were run for an experiment testing the effect of the resolution and the coverage of 3D urban morphological inputs on meteorological output. This data is associated with the paper "Sensitivity of Urban Morphology to the Resolution of Urban Morphological Feature Inputs: Implications for Characterizing Urban Sustainability."

integrated multisector multiscale modeling↗
DOE OSTI2025

Enhancing fire emissions inventories for acute health effects studies: integrating high spatial and temporal resolution data

Daily fire progression information is crucial for public health studies that examine the relationship between population-level smoke exposures and subsequent health events. Issues with remote sensing used in fire emissions inventories (FEI) lead to the possibility of missed exposures that impact the results of acute health effects studies. This paper provides a method for improving an FEI dataset with readily available information to create a more robust dataset with daily fire progression. High temporal and spatial resolution burned area information from two FEI products are combined into a single dataset, and a linear regression model fills gaps in daily fire progression. The combined dataset provides up to 71% more PM 2.5 emissions, 69% more burned area, and 367% more fire days per year than using a single source of burned area information. The FEI combination method results in improved FEI information with no gaps in daily fire emissions estimates. The combined dataset provides a functional improvement to FEI data that can be achieved with currently available data.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2023

Charge trapping correction and energy performance of the Majorana Demonstrator

P-type point contact (PPC) high-purity germanium detectors are an important technology in astroparticle and nuclear physics due to their superb energy resolution, low noise, and pulse shape discrimination capabilities. Analysis of data from the Majorana Demonstrator, a neutrinoless double-β decay experiment deploying PPC detectors enriched in 76 Ge, has led to several novel improvements in the analysis of PPC signals. Here, in this work we discuss charge trapping in PPC detectors and its effect on energy resolution. Small dislocations or impurities in the crystal lattice result in trapping of charge carriers from an ionization event of interest, attenuating the signal, and degrading the measured energy. We present a modified digital pole-zero correction to the signal energy estimation that counters the effects of charge trapping and improves the energy resolution of the Majorana Demonstrator by approximately 30 % to around 2.4 keV full width at half-maximum at 2039 keV, the 76 Ge Q value. An alternative approach achieving similar resolution enhancement is also presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Spatially Local Surrogate Modeling of Subgrid-Scale Effects in Idealized Atmospheric Flows: A Deep Learned Approach Using High-Resolution Simulation Data

Abstract We introduce a machine learned surrogate model from high-resolution simulation data to capture the subgrid-scale effects in dry, stratified atmospheric flows. We use deep neural networks (NNs) to model the spatially local state differences between a coarse-resolution simulation and a high-resolution simulation. The setup enables the capture of both dissipative and antidissipative effects in the state differences. The NN model is able to accurately capture the state differences in offline tests outside the training regime. In online tests intended for production use, the NN-coupled coarse simulation has higher accuracy over a significant period of time compared to the coarse-resolution simulation without any correction. We provide evidence of the capability of the NN model to accurately capture high-gradient regions in the flow field. With the accumulation of the errors, the NN-coupled simulation becomes computationally unstable after approximately 90 coarse simulation time steps. Insights gained from these surrogate models further pave the way for formulating stable, complex, physics-based spatially local NN models which are driven by traditional subgrid-scale turbulence closure models. Significance Statement Flows in the atmosphere are highly chaotic and turbulent, comprising flow structures of broad scales. For effective computational modeling of atmospheric flows, the effects of the small- and large-scale structures need to be captured by the simulations. Capturing the small-scale structures requires fine-resolution simulations. Even with the current state-of-the-art supercomputers, it can be prohibitively expensive to simulate these flows when computed for the entire earth over climate time scales. Thus, it is necessary to focus on the larger-scale structures using a coarse-resolution simulation while capturing the effects of the smaller-scale structures using some parameterization (approximation) scheme and incorporating it into the coarse-resolution simulation. We use machine learning to model the effects of the small-scale structures (subgrid-scale effects) in atmospheric flows. Data from a fine-resolution simulation is used to compute the missing subgrid-scale effects in coarse-resolution simulations. We then use machine learning models to approximate these differences between the coarse- and fine-resolution simulations. We see improved accuracy for the coarse-resolution simulations when corrected using these machine learned models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Global Dust Cycle and Direct Radiative Effect in E3SM Version 1: Impact of Increasing Model Resolution

Quantification of dust aerosols in Earth System Models (ESMs) has important implications for water cycle and biogeochemistry studies. This study examines the global life cycle and direct radiative effects (DREs) of dust in the U.S. Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1), and the impact of increasing model resolution both horizontally and vertically. The default 1° E3SMv1 captures the spatial and temporal variability in the observed dust aerosol optical depth (DAOD) reasonably well, but overpredicts dust absorption in the shortwave (SW). Simulations underestimate the dust vertical and long-range transport, compared with the satellite dust extinction profiles. After updating dust refractive indices and correcting for a bias in partitioning size-segregated emissions, both SW cooling and longwave (LW) warming of dust simulated by E3SMv1 are increased and agree better with other recent studies. The estimated net dust DRE of –0.42 Wm –2 represents a stronger cooling effect than the observationally based estimate –0.2 Wm –2 (–0.48 to +0.2), due to a smaller LW warming. Constrained by a global mean DAOD, model sensitivity studies of increasing horizontal and vertical resolution show strong influences on the simulated global dust burden and lifetime primarily through the change of dust dry deposition rate; there are also remarkable differences in simulated spatial distributions of DAOD, DRE, and deposition fluxes. Thus, constraining the global DAOD is insufficient for accurate representation of dust climate effects, especially in transitioning to higher- or variable-resolution ESMs. Better observational constraints of dust vertical profiles, dry deposition, size, and LW properties are needed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Measurement of $\nu_\mu$ CC Interactions With Two-Proton Final State in MINERvA

This dissertation presents a measurement of charged–current (CC) muon–neutrino interactions with exactly two protons and no pions in the final state (CC~$2p\,0\pi$), using data collected by the MINERvA detector in the NuMI medium–energy beam at Fermilab. Such two–proton topologies are a sensitive probe of nuclear dynamics in the few–GeV regime, including multi–nucleon correlations (npnh, notably $2p2h$) and intranuclear final–state interactions (FSI) such as pion absorption and nucleon rescattering. A precise experimental characterization of these processes is essential both for neutrino–interaction theory and for reducing systematic uncertainties in oscillation experiments that rely on accurate modeling of neutrino–nucleus interactions. Events are selected by requiring a $\nu_\mu$ CC interaction with a reconstructed $\mu^-$ and two proton tracks originating from a common vertex in MINERvA’s finely segmented scintillator tracker, with no reconstructed mesons. Muon charge and momentum are constrained by matching to the MINOS Near Detector, while proton identification exploits energy–loss profiles and stopping–proton features. Backgrounds from pion–producing channels that enter the signal region through FSI or reconstruction effects are constrained with data–driven sidebands (Michel–electron and isolated–cluster “blob” samples) and tuned via a simultaneous fit across signal and sideband regions. To correct detector resolution and acceptance effects, the analysis employs iterative Bayesian unfolding with extensive validation: statistical pseudo–experiments, and robustness checks against generator systematic “universes” and additional strong shape warps. Single–differential cross sections are reported for three observables tailored to the two–proton final state: the opening–angle cosine $\cos\!\left(\theta_{pp}\right)$, the leading–proton momentum, and the subleading–proton momentum. Systematic uncertainties include contributions from neutrino flux, interaction modeling (e.g., npnh and resonance parameters, pion FSI), and detector response (calibration, reconstruction efficiencies). The resulting distributions provide targeted constraints on the interplay of multi–nucleon dynamics and FSI that shape CC~$2p\,0\pi$ final states on hydrocarbon. Comparisons to modern GENIE–based simulations highlight kinematic regions where model components require refinement. These measurements thus inform generator tuning and improve the reliability of neutrino–energy reconstruction strategies for current and future long–baseline oscillation programs.

Syrotenko, Vladyslav S. [Tufts U.]↗
DOE OSTI2021

Efficacy of a portable, moderate-resolution, fast-scanning differential mobility analyzer for ambient aerosol size distribution measurements

Abstract. Ambient aerosol size distributions obtained with a compact scanning mobility analyzer, the “Spider” differential mobility analyzer (DMA), are compared to those obtained with a conventional mobility analyzer, with specific attention to the effect of mobility resolution on the measured size distribution parameters. The Spider is a 12 cm diameter radial differential mobility analyzer that spans the 10–500 nm size range with 30 s mobility scans. It achieves its compact size by operating at a nominal mobility resolution R=3 (sheath flow = 0.9 L min−1; aerosol flow = 0.3 L min−1) in place of the higher ratio of sheath flow to aerosol flow commonly used. The question addressed here is whether the lower resolution is sufficient to capture key characteristics of ambient aerosol size distributions. The Spider, operated at R=3 with 30 s up- and downscans, was co-located with a TSI 3081 long-column mobility analyzer, operated at R=10 with a 360 s sampling duty cycle. Ambient aerosol data were collected over 26 consecutive days of continuous operation, in Pasadena, CA. Over the 17–500 nm size range, the two instruments exhibit excellent correlation in the total particle number concentrations and geometric mean diameters, with regression slopes of 1.13 and 1.00, respectively. Our results suggest that particle sizing at a lower resolution than typically employed may be sufficient to obtain key properties of ambient size distributions, at least for these two moments of the size distribution. Moreover, it enables better counting statistics, as the wider transfer function for a given aerosol flow rate results in a higher counting rate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Super Resolution Digital Image Correlation (SR-DIC): an Alternative to Image Stitching at High Magnifications

Abstract Background High-resolution Digital Image Correlation (DIC) measurements have previously been produced by stitching of neighboring images, which often requires short working distances. Separately, the image processing community has developed super resolution (SR) imaging techniques, which improve resolution by combining multiple overlapping images. Objective This work investigates the novel pairing of super resolution with digital image correlation, as an alternative method to produce high-resolution full-field strain measurements. Methods First, an image reconstruction test is performed, comparing the ability of three previously published SR algorithms to replicate a high-resolution image. Second, an applied translation is compared against DIC measurement using both low- and super-resolution images. Third, a ring sample is mechanically deformed and DIC strain measurements from low- and super-resolution images are compared. Results SR measurements show improvements compared to low-resolution images, although they do not perfectly replicate the high-resolution image. SR-DIC demonstrates reduced error and improved confidence in measuring rigid body translation when compared to low resolution alternatives, and it also shows improvement in spatial resolution for strain measurements of ring deformation. Conclusions Super resolution imaging can be effectively paired with Digital Image Correlation, offering improved spatial resolution, reduced error, and increased measurement confidence.

Hansen, R. S.↗
DOE OSTI2022

The Impact of Resolution on Double-detonation Models for Type Ia Supernovae

Abstract Thermonuclear supernovae are the result of the violent unbinding of a white dwarf (WD), but the precise nature of the explosion mechanism(s) is a matter of active debate. To this end, several specific scenarios have been proposed to explain the observable traits of Type Ia supernovae. A promising pathway is the double-detonation scenario, where a WD accretes a shell of helium-rich material from a companion and a detonation in the resulting helium shell is the primary cause of the explosion. Through a set of two-dimensional grid-based simulations of this scenario we clearly distinguish three phases of evolution: external helium-rich detonation, core compressive heating, and a final core carbon burn. Though final disruption of the whole system is achieved at all resolutions, only models with minimum resolutions of 4 km and better exhibit all three phases. Particularly, core compression detonation is only observed for higher resolutions, producing qualitatively different nucleosynthetic outcomes. We identify the effect of finer spatial resolution on the mixing of hot silicon at the interface between the detonating helium layer and the underlying C/O WD as a primary driver of these dynamic differences.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Stability and convergence of nuclear detonations in white dwarf collisions

We investigate the numerical stability of thermonuclear detonations in 1D accelerated reactive shocks and 2D binary collisions of equal-mass magnetized and unmagnetized white dwarf stars. To achieve high resolution at initiation sites, we devised geometric gridding and mesh velocity strategies specially adapted to the unique requirements of head-on collisional geometries, scenarios in which one expects maximum production of iron-group products. We study the effects of grid resolution and the limiting of temperature, energy, and reactants for different stellar masses, separations, magnetic fields, inigenerationtial compositions, detonation mechanisms, and limiter parameters across a range of cell sizes from 1 to 100 km. Our results set bounds on the parameter space of limiter amplitudes for which both temperature- and energy-limiting procedures yield consistent and monotonically convergent solutions. Within these bounds, we find that grid resolutions of 5 km or better are necessary for uncertainties in total released energy and iron-group products to drop below 10%. Intermediate-mass products (e.g., calcium) exhibit similar convergence trends but with somewhat greater uncertainty. These conclusions apply equally to pure C/O white dwarfs, multispecies compositions (including helium shells), magnetized and unmagnetized cores, and either single or multiple detonation scenarios.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Effects of Atmosphere and Ocean Horizontal Model Resolution on Tropical Cyclone and Upper-Ocean Response Forecasts in Four Major Hurricanes

A coupled atmosphere–ocean model is necessary for tropical cyclone (TC) prediction to accurately characterize ocean feedback on atmospheric processes within the TC environment. Here, the ECMWF coupled global model is run at horizontal resolutions from 9 to 1.4 km in the atmosphere, as well as 25 and 8 km in the ocean, to identify how resolution impacts forecast accuracy of four observed major TCs in the Atlantic: Irma, Florence, Teddy, and Ida. Most of the resolutions used here are unprecedented for global models. GOES-16 and synthetic aperture radar (SAR) satellite images and best track data are used for atmospheric validation. Salinity and temperature observations from Air-Launched Autonomous Micro-Observer (ALAMO) floats are used to validate modeled upper-ocean response, including mixed layer deepening, sea surface cooling, and near-inertial waves in the wakes of TCs. Increasing atmospheric resolution leads to more realistic TC structure and stronger winds, significantly improving TC intensity forecasts and modestly improving track errors. Ocean resolution impacts the upper-ocean response but does not influence atmospheric forecasts for the fast-moving TCs considered here. Stronger mixing, sea surface cooling, and near-inertial oscillations are found for both higher atmosphere and ocean resolutions, provided the initial upper-ocean state is the same for the two ocean resolutions. Whether this agrees better with the ALAMO observations also depends on the realism of the initial upper-ocean state in the model, emphasizing the importance of ocean initialization for the accurate upper-ocean response. Overall, the model at all resolutions correctly predicts stronger mixing, surface cooling, and near-inertial oscillation amplitudes to the right of a TC center, as observed by ALAMO floats.

Atmosphere-ocean interaction↗
DOE OSTI2022

A New Search for Low-mass Dark Matter and an Examination and Reduction of the Uncertainty due to the Photoelectric Absorption Cross Section using a Cryogenic Silicon Detector with Single-charge Sensitivity

Many astrophysical observations point to the abundant existence of dark matter (DM) in the universe composed of particles beyond the Standard Model. However despite numerous experiments using different techniques, DM particles have yet to be directly observed. The Super Cryogenic Dark Matter Search (SuperCDMS) SNOLAB experiment will employ silicon and germanium crystal detectors operated at temperatures as low as 15~mK to probe DM interactions using phonon and ionization signals. Recently, R\&D; facilities have developed gram-sized high-voltage eV-scale (HVeV) silicon detectors that achieve single-electron-hole-pair resolution. By probing effective DM-electron interactions, these devices can be used for searches of low-mass DM candidates.This dissertation presents a DM search experiment known as HVeV Run~2 that employs a second-generation HVeV detector operated in an above-ground laboratory at Northwestern University (IL, USA). Energy spectra are obtained from a blind analysis with 0.39 and 1.2\,g-days of exposure with the detector biased at 60 and 100\,V, respectively. The 0.93~gram detector achieves a 3\,eV phonon energy resolution, corresponding to a world-leading charge resolution of 3\,\% of a single electron-hole pair for a detector bias of 100\,V. With charge carrier trapping and impact ionization effects incorporated into the DM signal models, the resulting exclusion limits are reported for inelastic DM-electron scattering for DM masses from 0.5--$10^{4}$\,MeV$/c^{2}$; in the mass range from 1.2--50\,eV$/c^{2}$ the limits for dark photon and axion-like particle absorption are reported.Several DM search experiments, including HVeV Run~2, are sensitive to low-mass DM candidates that rely on the temperature-dependent photoelectric absorption cross section of silicon. However discrepancies in the underlying literature data result in dominating systematic uncertainties on the DM exclusion limits. In order to reduce these systematic uncertainties, this dissertation presents a novel method of making a direct, low-temperature measurement of the photoelectric absorption cross section of silicon at energies near the band gap (1.2--2.8\,eV).

Wilson, Matthew James↗
DOE OSTI2021

Effect of natural gamma background radiation on portal monitor radioisotope unmixing

It is well known that national security relies on several layers of protection. One of the most important is the traffic control at borders and ports that exploits Radiation Portal Monitors (RPMs) to detect and deter potential smuggling attempts. Most portal monitors rely on plastic scintillators to detect gamma rays. Despite their poor energy resolution, their cost effectiveness and the possibility of growing them in large sizes make them the gamma-ray detector of choice in RPMs. Unmixing algorithms applied to organic scintillator spectra can be used to reliably identify the bare and unshielded radionuclides that triggered an alarm, even with fewer than 1000 detected counts and in the presence of two or three nuclides at the same time. In this work, we experimentally studied the robustness of a state-of-the-art unmixing algorithm to different radiation background spectra, due to varying atmospheric conditions, in the 16 °C to 28 °C temperature range. In the presence of background, the algorithm is able to identify the nuclides present in unknown radionuclide mixtures of three nuclides, when at least 1000 counts from the sources are detected. With fewer counts available, we found larger differences of approximately 35.9% between estimated nuclide fractions and actual ones. In these low count rate regimes, the uncertainty associated by our algorithm with the identified fractions could be an additional valuable tool to determine whether the identification is reliable or a longer measurement to increase the signal-to-noise ratio is needed. Moreover, the algorithm identification performances are consistent throughout different data sets, with negligible differences in the presence of background types of different intensity and spectral shape.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Solving disorder in (3D) real space: a comparative study of the three-dimensional difference pair distribution function and atomic resolution holography reconstructions

The quantitative analysis of local ordering principles in disordered crystalline systems has gained much attention over the past few years, as it is often considered crucial for optimizing material functionality. This development has been driven by significant advancements in computational and experimental methods, which have led to the establishment and widespread use of various analytical techniques. In this study, we perform model calculations to compare the effectiveness of atomic resolution holography and three-dimensional difference pair distribution function analysis (3D-ΔPDF). Using Cu 3 Au as a model system, we demonstrate an approach to derive local order parameters quantitatively and show that both techniques are well suited to quantifying chemical short-range order correlations and local bond-distance variations. By evaluating the strengths and limitations of both techniques, we advocate for their combined use to solve complex short-range order problems accurately.

3D-ΔPDF↗
DOE OSTI2021

Sub-Sampled Imaging for STEM: Maximising Image Speed, Resolution and Precision Through Reconstruction Parameter Refinement

Sub-sampling during image acquisition in scanning transmission electron microscopy (STEM) has been shown to provide a means to increase the overall speed of acquisition while at the same time providing an efficient means to control the dose, dose rate and dose overlap delivered to the sample. In this paper, we discuss specifically the parameters used to reconstruct sub-sampled images and highlight their effect on inpainting using the beta-process factor analysis (BPFA) methodology. The selection of the main control parameters can have a significant effect on the resolution, precision and sensitivity of the final inpainted images, and here we demonstrate a method by which these parameters can be optimised for any image in STEM. As part of this paper, we also provide a link to open source code and a tutorial on its use, whereby these parameters can be tested for any datasets. When coupled with the hardware necessary to rapidly sub-sample images in STEM, this approach can have significant implications for imaging beam sensitive materials and dynamic processes.

47 OTHER INSTRUMENTATION↗