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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.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

NASA Tech Briefs, August 2008

Customizable Digital Receivers for Radar Two-Camera Acquisition and Tracking of a Flying Target Visual Data Analysis for Satellites A Data Type for Efficient Representation of Other Data Types Hand-Held Ultrasonic Instrument for Reading Matrix Symbols Broadband Microstrip-to-Coplanar Strip Double-Y Balun A Topographical Lidar System for Terrain-Relative Navigation Programmable Low-Voltage Circuit Breaker and Tester Electronic Switch Arrays for Managing Microbattery Arrays Topics covered include: Lower-Dark-Current, Higher-Blue-Response CMOS Imagers; Fabricating Large-Area Sheets of Single-Layer Graphene by CVD; Support for Diagnosis of Custom Computer Hardware; Providing Goal-Based Autonomy for Commanding a Spacecraft; Dynamic Method for Identifying Collected Sample Mass; Optimal Planning and Problem-Solving; Attitude-Control Algorithm for Minimizing Maneuver Execution Errors; Grants Document-Generation System; Heat-Storage Modules Containing LiNO3 3H2O and Graphite Foam; Precipitation-Strengthened, High-Temperature, High-Force Shape Memory Alloys; Improved Relief Valve Would Be Less Susceptible to Failure; Safety Modification of Cam-and-Groove Hose Coupling; Using Composite Materials in a Cryogenic Pump; Using Electronic Noses to Detect Tumors During Neurosurgery; Producing Newborn Synchronous Mammalian Cells; Smaller, Lower-Power Fast-Neutron Scintillation Detectors; Rotationally Vibrating Electric-Field Mill; Estimating Hardness from the USDC Tool-Bit Temperature Rise; Particle-Charge Spectrometer; Automated Production of Movies on a Cluster of Computers; FIDO-Class Development Rover; and Tone-Based Command of Deep Space Probes Using Ground Antennas.

Source record↗
NASA NTRS2016

Spatio-Temporal Variability of Groundwater Storage in India

Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Ground water storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent).In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

Groundwater monitoring↗
NASA NTRS2019

Numerical Investigation and Optimization of a Flushwall Injector for Scramjet Applications at Hypervelocity Flow Conditions

An investigation utilizing Reynolds-averaged simulations (RAS) was performed in order to demonstrate the use of design and analysis of computer experiments (DACE) methods in Sandia’s DAKOTA software package for surrogate modeling and optimization. These methods were applied to a flow- path fueled with an interdigitated flushwall injector suitable for scramjet applications at hyper- velocity conditions and ascending along a constant dynamic pressure flight trajectory. The flight Mach number, duct height, spanwise width, and injection angle were the design variables selected to maximize two objective functions: the thrust potential and combustion efficiency. Because the RAS of this case are computationally expensive, surrogate models are used for optimization. To build a surrogate model a RAS database is created. The sequence of the design variables comprising the database were generated using a Latin hypercube sampling (LHS) method. A methodology was also developed to automatically build geometries and generate structured grids for each design point. The ensuing RAS analysis generated the simulation database from which the two objective functions were computed using a one-dimensionalization (1D) of the three-dimensional simulation data. The data were fitted using four surrogate models: an artificial neural network (ANN), a cubic polynomial, a quadratic polynomial, and a Kriging model. Variance-based decomposition showed that both objective functions were primarily driven by changes in the duct height. Multiobjective design optimization was performed for all four surrogate models via a genetic algorithm method. Optimal solutions were obtained at the upper and lower bounds of the flight Mach number range. The Kriging model predicted an optimal solution set that exhibited high values for both objective functions. Additionally, three challenge points were selected to assess the designs on the Pareto fronts. Further sampling among the designs of the Pareto fronts may be required to lower the surrogate model errors and perform more accurate surrogate-model-based optimization.

Shenoy, Rajiv R.↗
NASA NTRS1994

Linear Algorithms for Worst Case Identification in H infinity with Applications to Flexible Structures

This paper is concerned with linear algorithms for identification in which have been studied in [9]. It is shown that the two different linear algorithms in [9] can be unified into a single one which can be further extended to nonuniformly spaced frequency response samples with exponential convergence for the noise free case. Improved upper bounds for the corresponding identification errors are derived. Applications to the identification of lightly damped systems such as flexible structures are also considered.

linear↗
NASA NTRSDate not supplied

A comparison between CERES TOA Radiative Fluxes and Airborne Radiative Flux Measurements from ARISE

Uncertainty in top-of-atmosphere (TOA) radiation fluxes observations are larger in the Arctic than in other regions. These uncertainties are due to the low sun angles and the highly reflective, anisotropic, and heterogeneous surface conditions. Quantifying, attributing, and reducing Arctic TOA radiative flux uncertainty enables a better understanding of the rapidly changing Arctic. To advance this goal, we compare the Cloud and Earth’s Radiant Energy System (CERES) TOA radiative fluxes with Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) campaign measurements collected in September 2014. We compare CERES TOA and aircraft radiative flux measurements using two complementary approaches: grid box average fluxes and instantaneously matched footprints. The grid box mean flux comparison indicates an agreement between CERES and aircraft measurements within 2σ uncertainty (calibration and inversion) in the longwave for all five grid boxes and for four-of-five grid boxes in the shortwave; shortwave and longwave mean differences are -7.9 and +2.3 Wm 2, respectively. The comparison of 36 40 instantaneously matched footprints with aircraft measurements reveals mean differences of -120.25 and -1.00.4 Wm 2 in the shortwave and longwave, respectively. To further explore the persistent negative difference in the shortwave, Wwe further quantify the effects of temporal and spatial sampling differences, angular distribution models, and scene identification to CERES-aircraft differences. Our analysis indicates that sampling differences (including scene evolution) account for an additional 1.8 and 1.7% uncertainty in the shortwave and longwave, respectively and , but indicates no bias. After accounting for this sampling uncertainty, all CERES-aircraft grid box mean fluxes agree within 2σ uncertainty. Scene identification errors due to sea ice concentration data set differences exhibit no bias in the shortwave flux difference and indicate the possibility of substantial differences in the CERES fluxes in specific cases with large spatial heterogeneity. Considering the instantaneously matched footprints, we find that the angular distribution models account may account for up to 7.3 Wm-2 of the persistent CERES-aircraft shortwave flux difference due to systematic differences in the anisotropy for sea ice partly cloudy scenes. Additional analysis using a special programmable scan model with the CERES FM2 instrument suggests a significant view zenith angle dependence of the CERES fluxes for sea ice partly cloudy scenes where shortwave fluxes systematically decrease with increasing view zenith angle; no dependence is found for other scene types. We conclude that (1) spatial heterogeneity and scene temporal evolution substantially limit our ability to use aircraft measurements to place strong constraints on CERES TOA fluxes and (2) that the representation of anisotropy in sea ice partly cloudy scenes is likely a significant factor contributing to the persistent negative CERES-aircraft shortwave flux difference in this comparison and require additional data to analysis fully quantify the potential bias.

Patrick C. Taylor↗
NASA NTRSDate not supplied

Radiative Flux Measurements from ARISE: A Comparison with CERES Top-of-Atmosphere Radiative Fluxes

Uncertainty in top-of-atmosphere (TOA) radiation fluxes observations are larger in the Arctic than in other regions. These uncertainties are due to the low sun angles and the highly reflective, anisotropic, and heterogeneous surface conditions. Quantifying, attributing, and reducing Arctic TOA radiative flux uncertainty enables a better understanding of the rapidly changing Arctic. To advance this goal, we compare the Cloud and Earth’s Radiant Energy System (CERES) TOA radiative fluxes with Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) campaign measurements collected in September 2014. We compare CERES TOA and aircraft radiative flux measurements using two complementary approaches: grid box average fluxes and instantaneously matched footprints. The grid box mean flux comparison indicates an agreement between CERES and aircraft measurements within 2 uncertainty (calibration and inversion) in the longwave for all five grid boxes and for four-of-five grid boxes in the shortwave; shortwave and longwave mean differences are -7.9 and +2.3 Wm‑2, respectively. The comparison of 36 instantaneously matched footprints with aircraft measurements reveals mean differences of -10.5 and 0.4 Wm‑2 in the shortwave and longwave, respectively. To further explore the persistent negative difference in the shortwave, we further quantify the effects of temporal and spatial sampling differences, angular distribution models, and scene identification to CERES-aircraft differences. Our analysis indicates that sampling differences (including scene evolution) account for an additional 1.8 and 1.7% uncertainty in the shortwave and longwave, respectively and indicates no bias. After accounting for this sampling uncertainty, all CERES-aircraft grid box mean fluxes agree within 2 uncertainty. Scene identification errors due to sea ice concentration data set differences exhibit no bias in the shortwave flux difference and indicate the possibility of substantial differences in the CERES fluxes in specific cases with large spatial heterogeneity. Considering the instantaneously matched footprints, we find that the angular distribution models account may account for up to ‑7.3 Wm-2 of the persistent CERES-aircraft shortwave flux difference due to systematic differences in the anisotropy for sea ice partly cloudy scenes. Additional analysis using a special scan model with the CERES FM2 instrument suggests a significant view zenith angle dependence of the CERES fluxes for sea ice partly cloudy scenes where shortwave fluxes systematically decrease with increasing view zenith angle; no dependence is found for other scene types. We conclude that (1) spatial heterogeneity and scene temporal evolution substantially limit our ability to use aircraft measurements to place strong constraints on CERES TOA fluxes and (2) that the representation of anisotropy in sea ice partly cloudy scenes is a significant factor contributing to the persistent negative CERES-aircraft shortwave flux difference in this comparison and require additional data to analysis fully quantify the potential bias.

Patrick C Taylor↗
NASA NTRS2024

Pre-Launch Calibration and Validation of the Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) Instrument

The Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) is a new imaging polarimeter instrument capable of sampling a single Earth target from up to 120 viewing angles, in four spectral channels, and in three linear polarization states across a 114° field of view (FOV). AirHARP is telecentric in the image space and simultaneously images three linear polarization states with no moving parts. These two aspects of the design allow for a simple and efficient quantitative calibration. Using coefficients derived at the center of the lens and the detector flatfields, we can calibrate the entire AirHARP sensor in a variety of laboratory, field, and space environments. We show that this telecentric calibration technique yields a 1σ absolute uncertainty of 0.25 % in degree of linear polarization (DOLP) in the laboratory for all channels and for pixels around the optical axis. To validate across the FOV, we compare our multi-angle reflectance and polarization data with the Research Scanning Polarimeter (RSP) over targets sampled during the NASA Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign. We use the error-normalized difference technique to estimate how well the instruments compare relative to their error models. We find that AirHARP and the RSP reasonably agree for reflectance and DOLP within 2 standard deviations of their mutual uncertainty at 550, 670, and 870 nm and over a limited set of ocean and desert scenes. This calibration technique makes the Hyper-Angular Rainbow Polarimeter (HARP) design attractive for new spaceborne climate missions: HARP CubeSat (2020–2022), HARP2 (2024–) on the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE), and beyond.

Airborne Hyper-Angular Rainbow Polarimeter↗
DOE OSTI2018

A SIMPLIFIED ENERGY MODELING APPROACH FOR BUILDINGS

This paper introduces simplified energy modeling (SEM) approaches using DOE2 and EnergyPlus and proposes a validation method for simplified energy modeling. Simplified energy modeling can allow more design teams and owners to leverage the power of energy modeling to inform their designs and lead to greater energy savings and a lower first cost because the technologies and design strategies can be thoroughly tested against models before the decisions are made. By starting a discussion on how to develop simplified energy modeling approaches and methods to validate results, we hope to increase innovation in energy modeling software while decreasing variation between modelers. Simplified modeling is not yet widely accepted because it is unclear if the simplifications reduce the accuracy of the results. By starting an industry dialogue on a testing method for these modeling approaches, we hope to aid adoption of more streamlined tools when they can be shown to provide similar accuracy to more detailed tools. This paper proposes a method to test simplified energy modeling programs against the DOE prototype buildings. It builds on the testing procedure established for simulation engines by ASHRAE Standard 140. By comparing whole building and end use results from the accepted prototype buildings to any simplified modeling approach across multiple building types and climate zones we can determine if the simplifications create unwarranted error. We will present the SEM approach and results for a case study validation for a sample building types in 16 US climate zones from two such simplified energy modeling tools.

Energy Modeling, 90.1 Appendix G, Asset Score Tool↗
DOE OSTI2026

SPT-3G D1: Maps of the millimeter-wave sky from 2019 and 2020 observations of the SPT-3G Main field

Maps of the sky in millimeter wavelengths contain rich information on cosmology through anisotropies of the cosmic microwave background (CMB). Creating multifrequency sky maps of anisotropies in the $I$, $Q$, and $U$ Stokes parameters is one of the first steps of CMB cosmology analyses. In this work, we describe the production and validation of a set of sky maps from the South Pole Telescope's third-generation camera, SPT-3G. The maps are from data taken in frequency bands centered at 95, 150, and 220 GHz and taken during the first two years, 2019 and 2020, of the SPT-3G Main survey, which covers $4\%$ of the sky. We applied high-pass filters to time series of individual detectors and binned the filtered time series samples into map pixels. After that, we calibrated and cleaned the maps to reduce known systematic errors. In addition, we searched for other systematic errors through null tests and mitigated a significant systematic error detected therein. The white noise levels of the full-depth maps of the $I$ Stokes parameter are $5.4$, $4.4$, and $16.2$$\mathrm{μK}$-$\mathrm{arcmin}$ in the 95, 150, and 220 GHz bands, respectively, and $8.4$, $6.6$, and $25.8$$\mathrm{μK}$-$\mathrm{arcmin}$ for $Q/U$. These maps are the deepest to date used for measurements of mid-to-high-$\ell$ primary temperature and $E$-mode polarization CMB anisotropies, and reconstructions of the CMB gravitational lensing potential. We make these maps and supporting data products publicly accessible.

Quan, W. [Argonne (main); Chicago U., EFI; Chicago↗
DOE OSTI2025

Greedy emulators for nuclear two-body scattering

Applications of reduced basis method emulators are increasing in low-energy nuclear physics because they enable fast and accurate sampling of high-fidelity calculations, enabling robust uncertainty quantification. Here, in this paper, we develop, implement, and test two model-driven emulators based on the (Petrov-)Galerkin projection using the prototypical test case of two-body scattering with the Minnesota potential and a more realistic local chiral potential. The high-fidelity scattering equations are solved with the matrix Numerov method, a reformulation of the popular Numerov recurrence relation for solving special second-order differential equations as a linear system of coupled equations. A novel error estimator based on reduced-space residuals is applied to an active learning approach (a greedy algorithm) to choosing training samples (“snapshots”) for the emulator and contrasted with a proper orthogonal decomposition (POD) approach. Both approaches allow for computationally efficient offline-online decompositions, but the greedy approach requires many fewer snapshot calculations. These developments set the groundwork for emulating scattering observables based on chiral nucleon-nucleon and three-nucleon interactions and optical models, where computational speed-ups are necessary for Bayesian uncertainty quantification. Our emulators and error estimators are widely applicable to linear systems.

Bayesian methods↗
DOE OSTI2024

Extending the computational reach of a superconducting qutrit processor

Quantum computing with qudits is an emerging approach that exploits a larger, more connected computational space, providing advantages for many applications, including quantum simulation and quantum error correction. Nonetheless, qudits are typically afflicted by more complex errors and suffer greater noise sensitivity which renders their scaling difficult. In this work, we introduce techniques to tailor arbitrary qudit Markovian noise to stochastic Weyl–Heisenberg channels and mitigate noise that commutes with our Clifford and universal two-qudit gate in generic qudit circuits. We experimentally demonstrate these methods on a superconducting transmon qutrit processor, and benchmark their effectiveness for multipartite qutrit entanglement and random circuit sampling, obtaining up to 3× improvement in our results. To the best of our knowledge, this constitutes the first-ever error mitigation experiment performed on qutrits. Our work shows that despite the intrinsic complexity of manipulating higher-dimensional quantum systems, noise tailoring and error mitigation can significantly extend the computational reach of today’s qudit processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Investigation of observational error sources in multi-Doppler-radar three-dimensional variational vertical air motion retrievals

Abstract. Multi-Doppler-radar network observations have been used in different configurations over the last several decades to conduct three-dimensional wind retrievals in mesoscale convective systems. Here, the impacts of the selected radar volume coverage pattern (VCP), the sampling time for the VCP, the number of radars used, and the added value of advection correction on the retrieval of the vertical air motion in the upper part of convective clouds are examined using the Weather Research and Forecasting (WRF) model simulation, the Cloud Resolving Model Radar SIMulator (CR-SIM), and a three-dimensional variational multi-Doppler-radar retrieval technique. Comparisons between the model truth (i.e., WRF kinematic fields) and updraft properties (updraft fraction, updraft magnitude, and mass flux) retrieved from the CR-SIM-generated multi-Doppler-radar field are used to investigate these impacts. The findings are that (1) the VCP elevation strategy and sampling time have a significant effect on the retrieved updraft properties above 6  km in altitude; (2) 2  min or shorter VCPs have small impacts on the retrievals, and the errors are comparable to retrievals using a snapshot cloud field; (3) increasing the density of elevation angles in the VCP appears to be more effective to reduce the uncertainty than an addition of data from one more radar, if the VCP is performed in 2  min ; and (4) the use of dense elevation angles combined with an advection correction applied to the 2  min VCPs can effectively improve the updraft retrievals, but for longer VCP sampling periods (5  min ) the value of advection correction is challenging. This study highlights several limiting factors in the retrieval of upper-level vertical velocity from multi-Doppler-radar networks and suggests that the use of rapid-scan radars can substantially improve the quality of wind retrievals if conducted in a limited spatial domain.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Machine‐learning‐based construction of barrier functions and models for safe model predictive control

Abstract In this paper, we propose a control Lyapunov‐barrier function‐based model predictive control method utilizing a feed‐forward neural network specified control barrier function (CBF) and a recurrent neural network (RNN) predictive model to stabilize nonlinear processes with input constraints, and to guarantee that safety requirements are met for all times. The nonlinear system is first modeled using RNN techniques, and a CBF is characterized by constructing a feed‐forward neural network (FNN) model with unique structures and properties. The FNN model for the CBF is trained based on data samples collected from safe and unsafe operating regions, and the resulting FNN model is verified to demonstrate that the safety properties of the CBF are satisfied. Given sufficiently small bounded modeling errors for both the FNN and the RNN models, the proposed control system is able to guarantee closed‐loop stability while preventing the closed‐loop states from entering unsafe regions in state‐space under sample‐and‐hold control action implementation. We provide the theoretical analysis for bounded unsafe sets in state‐space, and demonstrate the effectiveness of the proposed control strategy using a nonlinear chemical process example with a bounded unsafe region.

Chen, Scarlett↗
DOE OSTI2017

Individual phase constitutive properties of a TRIP-assisted QP980 steel from a combined synchrotron X-ray diffraction and crystal plasticity approach

Microstructure-based constitutive models for multiphase steels require accurate constitutive properties of the individual phases for component forming and performance simulations. We address this requirement with a combined experimental/theoretical methodology which determines the critical resolved shear stresses and hardening parameters of the constituent phases in QP980, a TRIP assisted steel subject to a two-step quenching and partitioning heat treatment. High energy X-Ray diffraction (HEXRD) from a synchrotron source provided the average lattice strains of the ferrite, martensite, and austenite phases from the measured volume during in situ tensile deformation. The HEXRD data was then input to a computationally efficient, elastic-plastic self-consistent (EPSC) crystal plasticity model which estimated the constitutive parameters of different slip systems for the three phases via a trial-and-error approach. The EPSC-estimated parameters are then input to a finite element crystal plasticity (CPFE) model representing the QP980 tensile sample. The predicted lattice strains and global stress versus strain curves are found to be 8% lower that the EPSC model predicted values and from the HEXRD measurements, respectively. This discrepancy, which is attributed to the stiff secant assumption in the EPSC formulation, is resolved with a second step in which CPFE is used to iteratively refine the EPSC-estimated parameters. Remarkably close agreement is obtained between the theoretically-predicted and experimentally derived flow curve for the QP980 material.

Hu, X. H. (ORCID:0000000277355091)↗
DOE OSTI2024

Momentum power spectrum of SDSS galaxies by massE cosmic ruler: 2.1×improvement in measure of growth rate

ABSTRACT Peculiar motion of galaxies probes the structure growth in the universe. In this study, we employ the galaxy stellar mass-binding energy (massE) relation with only two nuisance parameters to build the largest peculiar-velocity (PV) catalogue to date, consisting of 229 890 ellipticals from the main galaxy sample (MGS) of the Sloan Digital Sky Survey (SDSS). We quantify the distribution of the massE-based distances in individual narrow redshift bins (dz = 0.005), and then estimate the PV of each galaxy based on its offset from the Gaussian mean of the distribution. As demonstrated with the Uchuu-SDSS mock data, the derived PV and momentum power spectra are insensitive to accurate calibration of the massE relation itself, enabling measurements out to a redshift of 0.2, well beyond the current limit of z = 0.1 using other galaxy scaling laws. We then measure the momentum power spectrum and demonstrate that it remains almost unchanged if varying significantly the redshift bin size within which the distance is measured, as well as the intercept and slope of the massE relation, respectively. By fitting the spectra using the perturbation theory model with four free parameters, fσ8 is constrained to fσ8 = 0.459$^{+0.068}_{-0.069}$ over Δz = 0.02–0.2, 0.416$^{+0.074}_{-0.076}$ over Δz = 0.02–0.1, and 0.526$^{+0.133}_{-0.148}$ over Δz = 0.1–0.2. The error of fσ8 is 2.1 times smaller than that by the redshift space distortion (RSD) of the same sample. A Fisher matrix forecast illustrates that the constraint on fσ8 from the massE-based PV can potentially exceed that from the stage-IV RSD in late universe (z<0.5).

Shi, Yong (ORCID:0000000286146275)↗
DOE OSTI2020

National population mapping from sparse survey data: A hierarchical Bayesian modeling framework to account for uncertainty

Population estimates are critical for government services, development projects, and public health campaigns. Such data are typically obtained through a national population and housing census. However, population estimates can quickly become inaccurate in localized areas, particularly where migration or displacement has occurred. Some conflict-affected and resource-poor countries have not conducted a census in over 10 y. We developed a hierarchical Bayesian model to estimate population numbers in small areas based on enumeration data from sample areas and nationwide information about administrative boundaries, building locations, settlement types, and other factors related to population density. We demonstrated this model by estimating population sizes in every 10- m grid cell in Nigeria with national coverage. These gridded population estimates and areal population totals derived from them are accompanied by estimates of uncertainty based on Bayesian posterior probabilities. The model had an overall error rate of 67 people per hectare (mean of absolute residuals) or 43% (using scaled residuals) for predictions in out-of-sample survey areas (approximately 3 ha each), with increased precision expected for aggregated population totals in larger areas. This statistical approach represents a significant step toward estimating populations at high resolution with national coverage in the absence of a complete and recent census, while also providing reliable estimates of uncertainty to support informed decision making.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Challenges in solving structures from radiation-damaged tomograms of protein nanocrystals assessed by simulation

Structure-determination methods are needed to resolve the atomic details that underlie protein function. X-ray crystallography has provided most of our knowledge of protein structure, but is constrained by the need for large, well ordered crystals and the loss of phase information. The rapidly developing methods of serial femtosecond crystallography, micro-electron diffraction and single-particle reconstruction circumvent the first of these limitations by enabling data collection from nanocrystals or purified proteins. However, the first two methods also suffer from the phase problem, while many proteins fall below the molecular-weight threshold required for single-particle reconstruction. Cryo-electron tomography of protein nanocrystals has the potential to overcome these obstacles of mainstream structure-determination methods. Here, a data-processing scheme is presented that combines routines from X-ray crystallography and new algorithms that have been developed to solve structures from tomograms of nanocrystals. This pipeline handles image-processing challenges specific to tomographic sampling of periodic specimens and is validated using simulated crystals. The tolerance of this workflow to the effects of radiation damage is also assessed. The simulations indicate a trade-off between a wider tilt range to facilitate merging data from multiple tomograms and a smaller tilt increment to improve phase accuracy. Since phase errors, but not merging errors, can be overcome with additional data sets, these results recommend distributing the dose over a wide angular range rather than using a finer sampling interval to solve the protein structure.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1994

Neutral ion sources in precision manufacturing

Ion figuring of optical components is a relatively new technology that can alleviate some of the problems associated with traditional contact polishing. Because the technique is non contacting, edge distortions and rib structure print through do not occur. This initial investigation was aimed at determining the effect of ion figuring on surface roughness of previously polished or ductile ground ceramic optical samples. This is the first step in research directed toward the combination of a pre-finishing process (ductile grinding or polishing) with ion figuring to produce finished ceramic mirrors. The second phase of the project is focusing on the development of mathematical algorithms that will deconvolve the ion beam profile from the surface figure errors so that these errors can be successfully removed from the optical components. In the initial phase of the project, multiple, chemical vapor deposited silicon carbide (CVD SiC) samples were polished or ductile ground to specular or near-specular roughness. These samples were then characterized to determine topographic surface information. The surface evaluation consisted of stylus profilometry, interferometry, and optical and scanning electron microscopy. The surfaces, were ion machined to depths from 0-5 microns. The finished surfaces were characterized to evaluate the effects of the ion machining process with respect to the previous processing methods and the pre-existing subsurface damage. The development of the control algorithms for figuring optical components has been completed. These algorithms have been validated with simulations and future experiments have been planned to verify the methods. This paper will present the results of the initial surface finish experiments and the control algorithms simulations.

Fawcett, Steven C.↗