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DOE OSTI2024

How Precisely Can Individual Molecules Be Analyzed? A Case Study on Locally Quantifying Forces and Energies Using Scanning Probe Microscopy

Recent advances in scanning probe microscopy methodology have enabled the measurement of tip-sample interactions with picometer accuracy in all three spatial dimensions, thereby providing a detailed site-specific and distance-dependent picture of the related properties. This paper explores the degree of detail and accuracy that can be achieved in locally quantifying probe-molecule interaction forces and energies for adsorbed molecules. Toward this end, cobalt phthalocyanine (CoPc), a promising CO 2 reduction catalyst, was studied on Ag(111) as a model system using low-temperature, ultrahigh vacuum noncontact atomic force microscopy. Data were recorded as a function of distance from the surface, from which detailed three-dimensional maps of the molecule's interaction with the tip for normal and lateral forces as well as the tip-molecule interaction potential were constructed. The data were collected with a CO molecule at the tip apex, which enabled a detailed visualization of the atomic structure. Determination of the tip-substrate interaction as a function of distance allowed isolation of the molecule-tip interactions; when analyzing these in terms of a Lennard-Jones-type potential, the atomically resolved equilibrium interaction energies between the CO tethered to the tip and the CoPc molecule could be recovered. Interaction energies peaked at less than 160 meV, indicating a physisorption interaction. As expected, the interaction was weakest at the aromatic hydrogens around the periphery of the molecule and strongest surrounding the metal center. In conclusion, the interaction, however, did not peak directly above the Co atom but rather in pockets surrounding it.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Enabling The Next Generation of Smart Sensors in Coal Fired Power Plants using Cellular 5G Technology

Ohio University (OHIO), West Virginia University (WVU), and American Electric Power (AEP) proposed to study and report on the benefits of 5G wireless cellular technologies for coal-fired power plants. The significant advantages, cost savings, and potential of 5G wireless data communications based sensors promised to usher in a new era of reliable, inexpensive, and powerful embedded systems that had not previously been available for coal-fired power plants. The team built upon existing experience with cellular-based systems, power plant water quality sensing, and high temperature sensors developed during past projects. Principal Investigator Wilhelm had been developing cellular-based sensor data systems with a commercial partner for 10 years, pioneering innovative solar-powered devices that began with 2G technology. The lessons and knowledge gained served as a foundation to demonstrate innovations and potential impacts specific to coal fired power plants enabled by 5G technology, along with integration with existing sensors and systems.

20 FOSSIL-FUELED POWER PLANTS↗

NASA NTRS1992

Compatibility testing with anhydrous ammonia

Anhydrous ammonia has been proposed as the working fluid for a number of two-phase thermal control systems to be used in future space applications, including the Space Station Freedom and the Earth Observing Station (EOS). The compatibility of ammonia with the components in these systems is a major concern due to the corrosive nature of the fluid. Compatibility of ammonia with stainless steel and some aluminum alloys is well documented; however, data on other materials potentially suitable for aerospace use is less common. This paper documents the compatibility testing of nine materials with both gaseous and liquid ammonia. The test procedures are presented along with the resulting measurement data. Tensile strength was the only mechanical property tested that indicated a significant material incompatibility.

Steve M. Benner↗

DOE OSTI2021

Real-time Data Analytics for Condition Monitoring of Complex Industrial Systems

Modern industrial systems are now fitted with several sensors for condition monitoring. This is advantageous because these sensors can provide mass amounts of data that have the potential for aiding in tasks such as fault detection, diagnosis, and prognostics. However, the information valuable for performing these tasks is often clouded in noise and must be mined from high-dimensional data structures. Therefore, this dissertation presents a data analytics framework for performing these condition monitoring tasks using high-dimensional data. Demonstrations of this framework are detailed for challenges related to power generation systems in automobiles, power plants, and aircraft engines. These implementations leverage data collected from state-of-the-art, industry class test-rigs. Results indicate the ability of this framework to develop effective methodologies for condition monitoring of complex systems.

Peters, Benjamin↗

DOE OSTI2025

High temperature nuclear data measurements of SiC, ZrC, and MgO [Slides]

Performed temperature dependent measurements of SiC and ZrC at ARCS instrument at SNS. Performed temperature dependent measurements of SiC, ZrC, and MgO at VISION instrument at SNS. Performed initial atomistic modeling of these materials using various techniques, including machine learned potentials. Future work includes temperature dependent transmission measurements of these materials, as well as improving the machine learned potentials with more training data and different machine learned frameworks.

ARCS↗

DOE OSTI2021

An Indicator-based Approach to Sustainable Management of Natural Resources (Chapter 12)

Assessing the sustainability of natural resource management choices for agricultural and forest lands requires quantification of potential changes to a set of environmental and socioeconomic indicators selected to characterize reference scenarios relative to projected future scenarios. Correctly framing the questions with local stakeholders is a critical first step in the sustainability assessment, and the questions that can be addressed are often limited by data availability. Selecting and prioritizing indicators with stakeholders to address their needs and concerns improves the likelihood of investment in monitoring and evaluation of those indicators over time. Computational techniques for analyzing interactions between the selected indicators are inherently affected by the scales and formats of the assembled indicator datasets. Data analytics have the potential to improve understanding of the potential synergies and tradeoffs involved with meeting multiple environmental and socioeconomic goals simultaneously, but timely and appropriate indicator datasets are not always available—even in this new era of “big data.” Continued improvements in data science and data analytics are needed to broaden understanding and acceptance of problems and to provide valuable information for natural resource management. Advances in these areas will enable society to design future landscapes that meet multiple objectives, including the provisioning of agricultural and forest resources along with a variety of ecosystem services (e.g., clean water and healthy soils).

Parish, Esther↗

DOE OSTI2019

Deep Direct-Use Feasibility Study Temperature-Depth Estimates for West Virginia University, Morgantown, WV

This dataset contains data spreadsheets and figures that summarize the results of a stochastic analysis of temperatures at depth below the West Virginia University campus in Morgantown, WV. These results are extracted from a study by Smith (2019), whose results are included in a GDR submission that provides rasters and shapefiles for the Appalachian Basin states of New York, Pennsylvania, and West Virginia (GDR submission #1182). Uncertainties considered included geologic properties, thermal properties, and uncertainty from geostatistical interpolation of the surface heat flow. A Monte Carlo analysis of these uncertain properties was used to predict temperatures at depth using a 1-D heat conduction model. For the pixel corresponding to West Virginia University, a .csv file containing the 10,000 temperature-depth profiles estimated from a Monte Carlo analysis is provided. Temperatures are provided for depths from 1-5 km in 0.5 km increments. These data are summarized in a figure containing violin plots that illustrates the probability of obtaining certain temperatures at depth for Morgantown.

15 GEOTHERMAL ENERGY↗

NASA NTRS1983

User's manual for master: Modeling of aerodynamic surfaces by 3-dimensional explicit representation

A system of computer programs was developed to model general three dimensional surfaces. Surfaces are modeled as sets of parametric bicubic patches. There are also capabilities to transform coordinates, to compute mesh/surface intersection normals, and to format input data for a transonic potential flow analysis. A graphical display of surface models and intersection normals is available. There are additional capabilities to regulate point spacing on input curves and to compute surface/surface intersection curves. Input and output data formats are described; detailed suggestions are given for user input. Instructions for execution are given, and examples are shown.

Gibson, S. G.↗

NASA NTRS2011

Lessons Learned from Assimilating Altimeter Data into a Coupled General Circulation Model with the GMAO Augmented Ensemble Kalman Filter

Satellite altimetry measurements have provided global, evenly distributed observations of the ocean surface since 1993. However, the difficulties introduced by the presence of model biases and the requirement that data assimilation systems extrapolate the sea surface height (SSH) information to the subsurface in order to estimate the temperature, salinity and currents make it difficult to optimally exploit these measurements. This talk investigates the potential of the altimetry data assimilation once the biases are accounted for with an ad hoc bias estimation scheme. Either steady-state or state-dependent multivariate background-error covariances from an ensemble of model integrations are used to address the problem of extrapolating the information to the sub-surface. The GMAO ocean data assimilation system applied to an ensemble of coupled model instances using the GEOS-5 AGCM coupled to MOM4 is used in the investigation. To model the background error covariances, the system relies on a hybrid ensemble approach in which a small number of dynamically evolved model trajectories is augmented on the one hand with past instances of the state vector along each trajectory and, on the other, with a steady state ensemble of error estimates from a time series of short-term model forecasts. A state-dependent adaptive error-covariance localization and inflation algorithm controls how the SSH information is extrapolated to the sub-surface. A two-step predictor corrector approach is used to assimilate future information. Independent (not-assimilated) temperature and salinity observations from Argo floats are used to validate the assimilation. A two-step projection method in which the system first calculates a SSH increment and then projects this increment vertically onto the temperature, salt and current fields is found to be most effective in reconstructing the sub-surface information. The performance of the system in reconstructing the sub-surface fields is particularly impressive for temperature, but not as satisfactory for salt.

Keppenne, Christian↗

NASA NTRS2012

Multi-Angle Implementation of Atmospheric Correction for MODIS (MAIAC). Part 3: Atmospheric Correction

This paper describes the atmospheric correction (AC) component of the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC) which introduces a new way to compute parameters of the Ross-Thick Li-Sparse (RTLS) Bi-directional reflectance distribution function (BRDF), spectral surface albedo and bidirectional reflectance factors (BRF) from satellite measurements obtained by the Moderate Resolution Imaging Spectroradiometer (MODIS). MAIAC uses a time series and spatial analysis for cloud detection, aerosol retrievals and atmospheric correction. It implements a moving window of up to 16 days of MODIS data gridded to 1 km resolution in a selected projection. The RTLS parameters are computed directly by fitting the cloud-free MODIS top of atmosphere (TOA) reflectance data stored in the processing queue. The RTLS retrieval is applied when the land surface is stable or changes slowly. In case of rapid or large magnitude change (as for instance caused by disturbance), MAIAC follows the MODIS operational BRDF/albedo algorithm and uses a scaling approach where the BRDF shape is assumed stable but its magnitude is adjusted based on the latest single measurement. To assess the stability of the surface, MAIAC features a change detection algorithm which analyzes relative change of reflectance in the Red and NIR bands during the accumulation period. To adjust for the reflectance variability with the sun-observer geometry and allow comparison among different days (view geometries), the BRFs are normalized to the fixed view geometry using the RTLS model. An empirical analysis of MODIS data suggests that the RTLS inversion remains robust when the relative change of geometry-normalized reflectance stays below 15%. This first of two papers introduces the algorithm, a second, companion paper illustrates its potential by analyzing MODIS data over a tropical rainforest and assessing errors and uncertainties of MAIAC compared to conventional MODIS products.

Lyapustin, A.↗

NASA NTRS1993

Clementine 2: a Double Asteroid Flyby and Impactor Mission

Recently JPL was asked by SDIO to analyze and develop a preliminary design for a deep-space mission to fly by two near-Earth asteroids, Eros and Toutatis. As a part of this mission, JPL was also asked to assess the feasibility of deploying a probe on approach to impact Toutatis. This mission is a candidate for SDIO's Clementine 2. SDIO's motivations were to provide further demonstrations of precision, autonomous navigation for controlling the flight paths of both a spacecraft and a probe. NASA's interest in this mission is driven by the opportunity to obtain the first close-up images and other scientific measurements from a spacecraft of two important near-Earth objects. For Toutatis this is especially important since it was observed and imaged extensively just last Dec. using Earth-based radar; Clementine 2 will provide the opportunity to corroborate the radar data and validate the ultimate potential of the radar technique. Scientifically, the probe impact at Toutatis will allow the acquisition of data pertaining to the dynamic strength of surface material and data on the properties of the regolith and on stratification below the surface, and will potentially allow the measurement of thermal diffusivity between the interior and the surface. These determinations will be accomplished by means of high-resolution imagery of the impact crater and its surroundings in visible, ultraviolet, and infrared wave bands from the spacecraft flying by some 30 min. after the probe strike. In addition, if the spacecraft can be equipped with a lightweight mass spectrometer and dust analyzer, the potential also exists to measure the particle sizes and distribution and the composition of the eject a cloud. This mission is planned to be launched in Jul. 1995, with the Eros encounter on 13 Mar. 1996, and the Toutatis flyby on 4 Oct. 1996, some 440 days after launch.

Boain, R. J.↗

DOE OSTI2019

A preliminary study of the gas hydrate stability zone in a gas hydrate potential region of China

Abstract Due to its significance for gas hydrate accumulation, the gas hydrate stability zone (GHSZ) is an essential condition for successful gas hydrate exploration and is usually controlled by three main factors: gas components, geothermal gradient, and permafrost thickness. Based on the core and conventional log data of gas hydrate potential region, the CSMHYD program was adopted to simulate the influences of above three factors on the thickness of the GHSZ. When the gas components of the gas hydrate were CH 4 , C 2 H 6 , and C 3 H 8 , with the CH 4 percentage ranging from 50% to 100%, the average GHSZ thickness can reach 1000 m according to the forward simulation results. When the gas hydrate was composed of CH 4 and one of C 2 H 6 , C 3 H 8 , H 2 S, and CO 2 , the influence order of the above four gases on the thickness of GHSZ is as follows: H 2 S ＞ C 2 H 6 ＞ C 3 H 8 ＞ CO 2 . Under the gas components of 90% CH 4 , 5% C 2 H 6, and 5% C 3 H 8 , the thickness of GHSZ decreased rapidly as the geothermal gradient increased following an exponential relation with a correlation of 99.92% and increased slowly as permafrost thickness increased following a linear relation with a correlation of 99.9%. In addition, the thickness of a gas hydrate favorable reservoir was determined by comprehensive log methods as 500 m. We conclude that a reservoir within 500 m below the permafrost layer is favorable for gas hydrate reservoir formation.

Xiao, Kun↗

DOE OSTI2022

Monitoring and flaw detection during wire-based directed energy deposition using in-situ acoustic sensing and wavelet graph signal analysis

The goal of this work is to detect flaw formation in the wire-based directed energy deposition (W-DED) process using in-situ sensor data. The W-DED studied in this work is analogous to metal inert gas electric arc welding. The adoption of W-DED in industry is limited because the process is susceptible to stochastic and environmental disturbances that cause instabilities in the electric arc, eventually leading to flaw formation, such as porosity and suboptimal geometric integrity. Moreover, due to the large size of W-DED parts, it is difficult to detect flaws post-process using non-destructive techniques, such as X-ray computed tomography. Accordingly, the objective of this work is to detect flaw formation in W-DED parts using data acquired from an acoustic (sound) sensor installed near the electric arc. To realize this objective, we develop and apply a novel wavelet integrated graph theory approach. The approach extracts a single feature called graph Laplacian Fiedler number from the noise-contaminated acoustic sensor data, which is subsequently tracked in a statistical control chart. Using this approach, the onset of various types of flaws are detected with a false alarm rate less-than 2%. This work demonstrates the potential of using advanced data analytics for in-situ monitoring of W-DED.

42 ENGINEERING↗

NASA NTRS1981

Treatment of conical and nonconical supersonic flows by an implicit marching scheme applied to the full potential equation

An aerodynamic prediction technique based on the full potential equation in conservation form is developed for the treatment of supersonic flows. This technique bridges the gap between simplistic linear theory methods and complex Euler solvers. A novel local density linearization concept and a second order accurate retarded density scheme, both producing the correct artificial viscosity, are introduced in developing an implicit marching scheme for solving the scalar potential. Results for conical flows over delta wings and a wing-body combination and for non-conical flows over bodies of revolution at angles of attack are compared with Euler and nonconservative full potential calculations and experimental data. The present formulation requires an order of magnitude less computer time and significantly less computer memory over Euler codes and exhibits a considerable improvement in computational efficiency and generality over an existing nonconservative full potential code.

Shankar, V.↗

NASA NTRS1985

The Use of Linear Feature Detection to Investigate Thematic Mapper Data Performance and Processing

The geometric and radiometric characteristics of thematic mapper data through analysis of linear features in the data are investigated. The particular aspects considered are: (1) thematic mapper ground IFUV; (2) radiometric contrast between linear features and background; (3) precision of system geometric correction; (4) band-to-band registration; and (5) potential utility of TM data for linear feature detection especially as compared to MSS data. It is shown that TM data may be used to estimate TM pixel size illustrate band: band mis-registration.

Gurney, C. M.↗

NASA NTRS2014

Analysis of Inter-Moss Loops in the Solar Region with IRIS and SDO AIA: Automatic Event Detection and Characterization

The Interface Region Imaging Spectrograph (IRIS), launched in the summer of 2013, is designed specifically to observe and investigate the transition region and adjacent layers of the solar atmosphere, obtaining images in high spatial, temporal, and spectral resolution. Our particular work is focused on the evolution of inter-moss loops, which have been detected in the lower corona by the Atmospheric Imaging Assembly (AIA) and the High-Resolution Coronal Imager (Hi- C), but are known to have foot points below the transition region. With the high-resolution capabilities of IRIS and its Si IV pass band, which measures activity in the upper chromosphere, we can study these magnetic loops in detail and compare their characteristic length and time scales to those obtained from several AIA image sets, particularly the 171, 193, and 211 pass bands. By comparing the results between these four data sets, one can potentially establish a measure of the ionization equilibrium for the location in question. To explore this idea, we found a large, sit-and-stare observation within the IRIS database that fit our specifications. This data set contained a number of well-defined inter-moss loops (by visual inspection) with a cadence less than or equal to that of AIA (approximately 12 seconds). This particular data set was recorded on October 23, 2013 at 07:09:30, lasting for 3219 seconds with a field of view of 120.6 by 128.1 arcseconds, centered on -53.9 by 59.1 arcseconds from disk center. For ease of comparison, the AIA data has been interpolated to match the IRIS cadence and resolution. In the main portion of the poster, we demonstrate the detection of events, the information collected, and the immediate results to the right, showing the progress of an event with green as the start, blue as the peak, and red as the end. Below here, we demonstrate how pixels are combined to form groups. The 3D results are shown to the right.

event detection↗

NASA NTRS2016

Analysis of Inter-Moss Loops in the Solar Region with IRIS and SDO AIA: Automatic Event Detection and Characterization

IRIS↗

NASA NTRS1987

Three-dimensional analysis of potential vorticity associated with tropopause folds and observed variations of ozone and carbon monoxide

The usability and reliability of potential vorticity as a meteorological stratospheric tracer are evaluated. The concept of potential vorticity conservation during transport in which stratospheric and tropospheric air are mixing is tested. Aircraft data collected on April 20, 1984 in the western and southwestern U.S. are analyzed in order to derive potential vorticity data; vertical cross sections of constant-pressure data and temperature and wind speed gradients are examined. The tropopause fold observed during the April 20, 1984 aircraft flights is described. The potential vorticity, ozone mixing ratio, and carbon monoxide mixing ratio are compared; a positive correlation between potential vorticity and the ozone mixing ratio and a negative correlation between the potential vorticity and the carbon monoxide mixing ratio are detected. The data support the concepts of the conservation of potential vorticity, the entrainment and mixing of tropospheric air across the boundaries of the fold, and the applicability of potential vorticity as a stratospheric tracer.

Danielsen, Edwin F.↗