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DOE OSTI2025

Mapping strain and structural heterogeneities around bubbles in amorphous ionically conductive Bi 2 O 3

While amorphous materials are often approximated to have a statistically homogeneous atomic structure, they frequently exhibit localized structural heterogeneity that challenges simplified models. This study uses 4D scanning transmission electron microscopy to investigate the strain and structural modifications around gas bubbles in amorphous Bi 2 O 3 induced by argon irradiation. We present a method for determining strain fields surrounding bubbles that can be used to measure the internal pressure of the gas. Compressive strain is observed around the cavities, with higher-order crystalline symmetries emerging near the cavity interfaces, suggesting paracrystalline ordering as a result of bubble coarsening. This ordering, along with a compressive strain gradient, indicates that gas bubbles induce significant localized changes in atomic packing. By analyzing strain fields with maximum compressive strains of 3%, we estimate a lower bound on the internal pressure of the bubbles at 2.5 GPa. These findings provide insight into the complex structural behavior of amorphous materials under stress, particularly in systems with gas inclusions, and offer new methods for probing the local atomic structure in disordered materials. Although considering structural heterogeneity in amorphous systems is non-trivial, these features have crucial impacts on material functionalities, such as mechanical strength, ionic conductivity, and electronic mobility.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Temperature-induced degradation of GaN HEMT: An in situ heating study

High-power electronics, such as GaN high electron mobility transistors (HEMTs), are expected to perform reliably in high-temperature conditions. This study aims to gain an understanding of the microscopic origin of both material and device vulnerabilities to high temperatures by real-time monitoring of the onset of structural degradation under varying temperature conditions. This is achieved by operating GaN HEMT devices in situ inside a transmission electron microscope (TEM). Electron-transparent specimens are prepared from a bulk device and heated up to 800 °C. High-resolution TEM (HRTEM), scanning TEM (STEM), energy-dispersive x-ray spectroscopy (EDS), and geometric phase analysis (GPA) are performed to evaluate crystal quality, material diffusion, and strain propagation in the sample before and after heating. Gate contact area reduction is visible from 470 °C accompanied by Ni/Au intermixing near the gate/AlGaN interface. Elevated temperatures induce significant out-of-plane lattice expansion at the SiNx/GaN/AlGaN interface, as revealed by geometry-phase GPA strain maps, while in-plane strains remain relatively consistent. Exposure to temperatures exceeding 500 °C leads to almost two orders of magnitude increase in leakage current in bulk devices in this study, which complements the results from our TEM experiment. The findings of this study offer real-time visual insights into identifying the initial location of degradation and highlight the impact of temperature on the bulk device’s structure, electrical properties, and material degradation.

36 MATERIALS SCIENCE↗

DOE OSTI2021

MBE growth and donor doping of coherent ultrawide bandgap AlGaN alloy layers on single-crystal AlN substrates

Single-crystal Aluminum Nitride (AlN) crystals enable the epitaxial growth of ultrawide bandgap Al(Ga)N alloys with drastically lower extended defect densities. Here, we report the plasma-MBE growth conditions for high Al-composition AlGaN alloys on single-crystal AlN substrates. An AlGaN growth guideline map is developed, leading to pseudomorphic Al x Ga 1–x N epitaxial layers with x ~0.6–1.0 Al contents at a growth rate of ~0.3 μm/h. These epitaxial layers exhibit atomic steps, indicating step flow epitaxial growth, and room-temperature band edge emission from ~4.5 to 5.9 eV. Growth conditions are identified in which the background impurity concentrations of O, C, Si, and H in the MBE layers are found to be very near or below detection limits. An interesting Si segregation and gettering behavior is observed at the epitaxial AlGaN/AlN heterojunction with significant implications for the formation and transport of 2D electron or hole gases. Well-controlled intentional Si doping ranging from ~2 × 10 17 to 3 × 10 19 atoms/cm 3 is obtained, with sharp dopant density transition profiles. In Si-doped Al 0.6 Ga 0.4 N epilayers, a room-temperature free electron concentration of ~3 × 10 19 /cm 3 , an electron mobility of ~27 cm 2 /V s, and an n-type resistivity of ~7.5 m Ω cm are obtained. Here, the implications of these findings on electronic and photonic devices on single-crystal AlN substrates are discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2020

GIS Visualization of Transportation Energy Consumption

Transportation is witnessing unprecedented transformation, where emerging technologies are disrupting the way we travel. Be it sharing economy, or micro-mobility, the landscape of urban transportation is undergoing a much-needed paradigm shift. In order to capture and model these shifts, researchers need to be agile in their studies of the current and future transportation landscape. The need for agility in turn calls for sophisticated, intuitive, and reliable means to visualize and share transportation data. Travel is inherently spatial, so methods of visualizing transportation information should also be rooted in spatial analysis. Geographic Information Systems (GIS) are the premier technological framework to analyze and display spatial data. GIS tools have been used in the past to depict flow of vehicles, and display of network conditions (speed, congestion, etc.). However, in an ever-changing technological landscape, spanning advancements in vehicle as well as information systems, depicting vehicle flows falls short of providing a comprehensive picture of the impact these advancements have on travel related energy consumption. To address this issue, this research effort presents a web-based mapping application to visualize how travel related energy flows across a city. The application is being developed by National Renewable Energy Laboratory researchers to integrate various transportation energy consumption models within a GIS schema. This has the goal of enabling rapid analysis of energy impacts of the dramatically evolving transportation environment. The application is being developed using a Python framework for ArcGIS Online. Using road network data from the City of Columbus, Ohio and traffic data from CATT Laboratory's Regional Integrated Transportation Information System, transportation energy consumption will be modeled at a macro level. The application aims to provide highly accurate data while still maintaining the flexibility needed to adapt the model when new technologies arise. The methodology presented through this effort is expected to provide insights into how light-duty vehicles use energy on a large scale based on the road network they use. The application will also provide data exports to enable sharing and collaboration. " need for agility in turn calls for sophisticated, intuitive, and reliable means to visualize and share transportation data. Travel is inherently spatial, so methods of visualizing transportation information should also be rooted in spatial analysis. Geographic Information Systems (GIS) are the premier technological framework to analyze and display spatial data. GIS tools have been used in the past to depict flow of vehicles, and display of network conditions (speed, congestion, etc.). However, in an ever-changing technological landscape, spanning advancements in vehicle as well as information systems, depicting vehicle flows falls short of providing a comprehensive picture of the impact these advancements have on travel related energy consumption. To address this issue, this research effort presents a web-based mapping application to visualize how travel related energy flows across a city. The application is being developed by National Renewable Energy Laboratory researchers to integrate various transportation energy consumption models within a GIS schema. This has the goal of enabling rapid analysis of energy impacts of the dramatically evolving transportation environment. The application is being developed using a Python framework for ArcGIS Online. Using road network data from the City of Columbus, Ohio and traffic data from CATT Laboratory's Regional Integrated Transportation Information System, transportation energy consumption will be modeled at a macro level. The application aims to provide highly accurate data while still maintaining the flexibility needed to adapt the model when new technologies arise. The methodology presented through this effort is expected to provide insights into how light-duty vehicles use energy on a large scale based on the road network they use. The application will also provide data exports to enable sharing and collaboration.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Epitaxial growth, magnetoresistance, and electronic band structure of GdSb magnetic semimetal films

Motivated by observations of extreme magnetoresistance (XMR) in bulk crystals of rare-earth monopnictide (RE-V) compounds and emerging applications in novel spintronic and plasmonic devices based on thin-film semimetals, we have investigated the electronic band structure and transport behavior of epitaxial GdSb thin films grown on III-V semiconductor surfaces. The Gd 3 + ion in GdSb has a high spin S=7/2 and no orbital angular momentum, serving as a model system for studying the effects of antiferromagnetic order and strong exchange coupling on the resulting Fermi surface and magnetotransport properties of RE-Vs. Here, we present a surface and structural characterization study mapping the optimal synthesis window of thin epitaxial GdSb films grown on III-V lattice-matched buffer layers via molecular-beam epitaxy. To determine the factors limiting XMR in RE-V thin films and provide a benchmark for band-structure predictions of topological phases of RE-Vs, the electronic band structure of GdSb thin films is studied, comparing carrier densities extracted from magnetotransport, angle-resolved photoemission spectroscopy (ARPES), and density-functional theory (DFT) calculations. ARPES shows a hole-carrier rich, topologically trivial, semimetallic band structure close to complete electron-hole compensation, with quantum confinement effects in the thin films observed through the presence of quantum-well states. DFT-predicted Fermi wave vectors are in excellent agreement with values obtained from quantum oscillations observed in magnetic field-dependent resistivity measurements. An electron-rich Hall coefficient is measured despite the higher hole-carrier density, attributed to the higher electron Hall mobility. The carrier mobilities are limited by surface and interface scattering, resulting in lower magnetoresistance than that measured for bulk crystals.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Skyrmion-skyrmionium phase separation and laning transitions via spin-orbit torque currents

Many driven binary systems can exhibit laning transitions when the two species have different mobilities, such as colloidal particles with opposite charges in electric fields. Another example is pedestrian or active-matter systems, where particles moving in opposite directions form a phase-separated state that enhances the overall mobility. In this work, we use atomistic simulations to demonstrate that mixtures of skyrmions and skyrmioniums also exhibit pattern formation and laning transitions. Skyrmions move more slowly and at a finite skyrmion Hall angle compared to skyrmioniums, which move faster and without a skyrmion Hall effect. At low drives, the system forms a partially jammed phase where the skyrmioniums are dragged by the surrounding skyrmions, resulting in a finite angle of motion for the skyrmioniums. At higher drives, the system transitions into a laned state, but unlike colloidal systems, the lanes in the skyrmion-skyrmionium mixture are tilted relative to the driving direction due to the intrinsic skyrmion Hall angle. In the laned state, the skyrmionium angle of motion is reversed when it aligns with the tilted lane structure. At even higher drives, the skyrmioniums collapse into skyrmions. Below a critical skyrmion density, both textures can move independently with few collisions, but above this density, the laning state disappears entirely, and the system transitions to a skyrmion-only state. We map out the velocity and Hall responses of the different textures and identify three distinct phases: partially jammed, laned, and skyrmion-only moving crystal states. In conclusion, we compare our results to recent observations of tilted laning phases in pedestrian flows, where chiral symmetry breaking in the particle interactions leads to similar behavior.

36 MATERIALS SCIENCE↗

DOE OSTI2023

USAID Colombia Young Leaders Workforce Training Program Action Plans: Regulatory Road Map for Distributed Energy Resource (DER) Interconnection and Interoperability

As part of the U.S. Agency for International Development (USAID)-National Renewable Energy Laboratory (NREL) Young Leaders Workforce Training Program in Colombia, participants from Colombia's Energy and Gas Regulatory Commission (CREG) leveraged their training and professional experience to develop a regulatory roadmap for the interconnection and interoperability of increasing integration of distributed energy resources (DERs). CREG was one of four teams selected by the training program development team to receive continued technical assistance and strategic advisory support from the USAID-NREL Partnership for action plan development and implementation. This case study provides an overview of the key activities and outcomes of the technical assistance provided by NREL on the CREG Action Plan, and key next steps for implementation of Colombia's DER Integration Regulatory Roadmap.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Development of Gamma Background Radiation Digital Twin with Machine Learning Algorithms: Application of Unsupervised Machine Learning to Detection of Anomalies and Nuisances in Gamma Background Radiation Environmental Screening Data

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for development of a digital twin of gamma radiation background, and for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. In one segment of work, we developed a gamma background estimation model using a Longshort term memory (LSTM) network for one-step CPS time series prediction. The LSTM model was validated with two data sets of measurements from two independent NaI detectors positioned on a mobile platform. The data sets contained background radiation only and no orphan isotope sources. The LSTM model was constructed and tested using data from one of the detectors. Performance of the LSTM model was validate through one-step prediction of CPS time series of another NaI detector without re-training. This approach allows to create a digital twin for nuclear background estimation. Using LSTM, it could be possible to detect a source through subtraction of the estimated counts from the measured background. In another segment of work, we investigated detection of gamma emitting sources in the presence of complex background using unsupervised machine learning. Spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Deployment of a double scatter system for directional detection of background neutron radiation

The detection of special nuclear materials (SNM) requires the understanding of nuclear signatures that allow the discrimination against background. In particular, understanding neutron background characteristics such as count rates and energies and their correlations with environmental conditions and surroundings of measurement locations is important in enhancing SNM detection capabilities. The Mobile Imager of Neutrons for Emergency Responders (MINER) was deployed for 8 weeks in downtown San Francisco (CA) to study such neutron background characteristics in an urban environment. Of specific interest was the investigation of the impact of surrounding buildings on the neutron background count rates and to answer the question whether buildings act as absorber of neutrons or as sources via the so-called ship effect. MINER consists of 16 liquid scintillator detector elements and can be operated as a neutron spectrometer, as a neutron imager, or simply as a counter of fast neutrons. As expected, the neutron background rate was found to be inversely proportional to the atmospheric pressure. In the energy range where MINER is most sensitive, approximately 1–10 MeV, it was found that the shape of the detected background spectrum is similar to that of a detected fission spectrum, indicating the limited discrimination power of the neutron energy. The similarities between the detected background neutron spectrum and fission sources makes it difficult to discriminate SNM from background based solely on the energies observed. The images produced using maximum likelihood expectation maximization revealed that neutrons preferentially are coming from areas in the environment that have open sky, indicating that the surrounding buildings act as absorbers of neutrons rather than sources as expected by the ship effect. Here, the inherent properties of a neutron scatter camera limit the achievable image quality and the effective deployment to systematically map neutron background signatures due to the low count rate.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Combined Mesonet and Tracker

Title: Combined Mesonet and Trackers (UNL Mobile Mesonets) Authors University of Nebraska PI: Adam Houston, UNL Professor (ahouston2@unl.edu) Mailing Address: 126 Bessey Hall P.O. Box 880340 Lincoln, NE 68588-0340 CoMeT Overview The University of Nebraska-Lincoln operates three Combined Mesonet and Tracker (CoMeTs). CoMeTs are Ford Explorers (model years 2015, 2017, and 2019) with forward-mounted suites of meteorological sensors and dual moonroofs, combining the capability of a mobile mesonet to collect near-surface observations with the capability of an unmanned aircraft systems (UAS) tracker vehicle, which enables an observer in the second row of seats to see the aircraft and maintain compliance with Federal Aviation Administration policies on UAS operation. The CoMeTs collect observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155A, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, and vehicle heading using a KVH Industries C-100 fluxgate compass (Barbieri et al. 2019). The HMP155A and 109SS-L thermistor are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). This list of sensors is also included in the CoMeT data file metadata. Manufacturer specifications for these instruments are given in Table 1 of Hanft and Houston (2018). The reported measured quantities are summarized below.CoMeT-3 was funded through an equipment allocation included in the NSF TORUS award (AGS-1824649). Instrument Description The specific sensors included on each CoMeT are summarized in the table at the end of this section. In general each CoMeT collects observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210 barometer with a Gill pressure port, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, position using a Garmin 19x HVS receiver, and vehicle heading using a KVH Industries C-100 fluxgate compass. The HMP155 and 109SS are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). Fast temperature and corrected RH measurements (using sensors housed within the U-tube) have a time constant of 10-12 s based on data collected across a temperature and RH shock during the CLOUD-MAP 2017 calibration/validation tests on June 26, 2017. Vehicle speed was < 10 kts for this test. CoMeT-1 CoMeT-2 CoMeT-3 Slow Temperature Slow RH Vaisala HMP155A-L20-PT Part #: 22280-7 Vaisala HMP155E Part #: E1AA11A0B1A1A0A Vaisala HMP155E Part #: E1AA11A0B1A1A0A Fast temperature Campbell Scientific 109SS-L20-PT Part #: 21448-3 Campbell Scientific 109SS-L12-PW Part #: 21448-109 Campbell Scientific 109SS-L12-PW Part #: 21448-150 Pressure Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Wind RM Young 05103-L20-PT Part #: 18435-310 RM Young 05103-L20-PW Part #: 18435-244 RM Young 05103-L20-PW Part #: 18435-244 GPS Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Compass KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 Logger Campbell Scientific CR6-NA-XT-SW Part #: 28385-9 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Data Collection and Real-Time Processing The reported measured quantities are summarized in the table below. Quantity Units Source Epoch time Seconds GPS Latitude and longitude Degrees GPS Altitude m GPS Pressure hPa PTB210 Temperature (fast) deg C 109SS-L Temperature (slow) deg C HMP155 RH (slow) % HMP155 Vehicle speed m/s GPS Vehicle heading deg C-100 and GPS In addition to the measured variables, several derived variables are calculated. Corrected/fast relative humidity (%) Relative humidity is adjusted to the fast temperature following Richardson et al. (1998) and Houston et al. (2016). Water vapor mixing ratio (g/kg) Dew point temperature (°C) Potential temperature (Kelvin) Virtual potential temperature (Kelvin) Equivalent potential temperature (Kelvin) Regular intercomparisons between all three CoMeTs were performed during TORUS 2019. Comparisons were also conducted between CoMeT-1 and CoMeT-2 during LAPSE-RATE (2018) on 14 July. In these intercomparisons, the vehicles were parked adjacent to each other aligned perpendicular to (and facing into) the wind. To minimize engine heating effects, intercomparisons were only conducted when the wind speed was >10 kts. Data Format Original data files for each deployment are saved as text files and then converted to NetCDF. NetCDF versions have units that are CF compliant and may not match the original units in the txt files. The naming convention for the NetCDF files is as follows: UNL.CoMeT3.{deployment date YYYYMMDD}.{start time of observation collection in UTC HHMM}.L2.{post-processing codes}.cdf example: UNL.CoMeT3.20190627.1931.L2.g1.f1.cdf Post-processing codes are included to track modifications to the raw data. These codes are closely connected to error flags associated with each record. Each letter corresponds to a particular instrument: g: GPS p: Barometer tf: Fast temperature ts: Slow temperature rh: Relative humidity f: Compass w: Wind monitor a: All instruments Each number corresponds to a particular post-processing action described more below. Measured and derived variables are included in the following table. Variable Heading Standard Name Units time Time seconds since 00:00:00, 01-01-1970 Alt Altitude meters lat Latitude degrees north lon Longitude degrees east fast_temp Air Temperature kelvin slow_temp Air Temperature kelvin pressure Air Pressure pascals logger_RH Relative Humidity percent calc_corr_RH Relative Humidity percent wind_speed Wind Speed meters per second wind_dir Wind From Direction degrees vehicle_dir Vehicle Direction degrees dewpoint Dew Point Temperature kelvin mixing_ratio Humidity Mixing Ratio g/g theta Air Potential Temperature kelvin theta_v Virtual Potential Temperature kelvin theta_e Equivalent Potential Temperature Kelvin error_flag The error_flag variable is a string that matches the post-processing codes listed above. All instruments will have an associated code, but will have a “0” if the datum is unchanged from the initial processed value. Error Codes The following table summarizes the error codes for data collected before 2020: Error Code Relevant CoMeT Description g1 1,2,3 Exact correction. GPS position and time reprocessed from raw data g2 1 As far as we can tell this is an exact correction to an error in the GPS time. During the correct time periods the time suddenly went backwards ~250s and stayed at this offset for 750s when it corrected itself. The offset was applied to the “time warp” period. p1 2 Approximate correction. Hole in the pressure tube connecting the pressure port to the barometer. Resulted in erroneously low air pressure measurements when the vehicle was in motion. Derived variables recalculated (dew point temperature [e depends on qv and p], water vapor mixing ratio, potential temperature, virtual potential temperature, equivalent potential temperature) a1 3 Exact correction. Missing data reprocessed from raw data a2 1 Bug fix to bias correction for ts1, ts2, and rh1: water vapor mixing ratio was off by a factor of 10 and virtual potential temperature was wrong because of this. f1 3 No correction, missing data. Fluxgate compass inoperable. Wind speed and direction calculated using GPS-derived vehicle heading instead. rh1 1 Approximate correction. Constant bias of +1.7% removed from relative humidity. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts1 1 Approximate correction. Constant bias of +0.6 K removed from slow temperature. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts2 1 Approximate correction. Constant bias of +1.0 K removed. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) References Bolton, D., 1980: The Computation of Equivalent Potential Temperature. Mon. Wea. Rev., 108, 1046–1053, https://doi.org/10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2. Hanft, W., and A. L. Houston, 2018: An Observational and Modeling Study of Mesoscale Air Masses with High Theta-E. Mon. Wea. Rev., 146, 2503–2524, https://doi.org/10.1175/MWR-D-17-0389.1.Wexler Houston, A. L., R. J. Laurence III, T. W. Nichols, S. Waugh, B. Argrow, and C. L. Ziegler, 2016: Intercomparison of unmanned aircraft-borne and mobile mesonet atmospheric sensors. Journal of Atmospheric and Oceanic Technology. 33, 1569-1582, doi: 10.1175/JTECH-D-15-0178.1. Lowe, P. R., 1977: An Approximating Polynomial for the Computation of Saturation Vapor Pressure. J. Applied Meteorology, 16, 100–103. Richardson, S. J., S. E. Frederickson, F. V. Brock, and J. A. Brotzge, 1998: Combination temperature and relative humidity probes: Avoiding large air temperature errors and associated relative humidity errors. Preprints, 10th Symp. On Meteorological Observations and Instrumentation, Phoenix, AZ, Amer. Meteor. Soc., 278–283. Waugh, S., and S. E. Frederickson, 2010: An improved aspirated temperature system for mobile meteorological observations, especially in severe weather. 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., P5.2. [Available online at https://ams.confex.com/ams/25SLS/techprogram/paper_176205.htm.]

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

A formaldehyde and nitrogen dioxide toxics monitor for environmental justice

DOE’s Integrated Field Laboratories (IFLs) require a vast array of measurements to measure urban air quality. Nitrogen dioxide (NO2) and formaldehyde (HCHO) are ubiquitous pollutants with numerous sources, most notably vehicle exhaust. High-spatial density measurements are critical to understanding how certain neighborhoods are more adversely impacted by pollutants. This report describes the results of a Phase I SBIR project to develop and demonstrate a rapid, affordable, low-power monitor to provide high spatial resolution mobile measurements of formaldehyde and nitrogen dioxide at street-level, where people live and walk. The spatial density will be achieved via rapid measurements on a mobile platform. This sensor will quantify spatial disparities in cities of the toxics, HCHO and NO2, as well as carbon monoxide and carbon dioxide for better source identification. These species are detected in the mid infrared by laser absorption spectroscopy, and fiberoptics are used. Tasks accomplished include identification and testing of the appropriate spectroscopic regions; coupling of laser light into a fiberoptic system; development of software to control miniature electronics to scan and control two lasers simultaneously; coupling of the mid infrared fiber into a multipass cell for enhanced pathlength and sensitivity; characterization of sources of instrument noise; and design work for a Phase II prototype.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Use of the Manuela 3D/Radiation Scanning Tool at Nuclear Facilities - 20437

Licensees, facility operators and decommissioning contractors have a need for comprehensive, accurate and precise radiological and topographical data to plan and execute safe and efficient Decontamination and Decommissioning (D and D) projects. Traditional approaches rely greatly upon labor and administratively intensive data collection methods that require considerable time and effort to glean the relevant data to plan and perform work in a radiological work area. Orano Decommissioning Services has developed and utilized at French nuclear facilities a lightweight portable scanning instrument called MANUELA (Mobile Apparatus for Nuclear Expertise Localization Assistance). Recently Orano conducted demonstrations at two United States nuclear facilities using MANUELA that may prove useful in areas of the fuel cycle including: - ALARA (As Low As Reasonably Achievable) planning during facility operations; - Scoping and site characterization during the D and D planning phase; - Remedial action support during active decommissioning work; - Radiation and modeling planning for plant modifications; - Support Final Status Survey and demonstration of 'end state' compliance for license termination. MANUELA is currently being evaluated for use during decommissioning of nuclear facilities and could aide in demonstrating compliance with end state criteria after decommissioning. Of particular interest are decommissioning projects planned for various sites across the United States. Most of these sites present unique challenges and opportunities to safely and efficiently decommission in a regulatory compliant manner. The two demonstration site's current conditions of relatively low radiation levels inside containment proved to be ideal platforms to deploy the MANUELA instrument for evaluation of the complex geometries typically found in a nuclear facility. The MANUELA instrument was able to precisely identify local hot spots of the reactor system's primary equipment and was able to simultaneously overlay the dose information onto the scanned 3D images. Using data like this, a licensee would be able to make informed technical and personnel decisions on methods to remediate, shield or properly dispose of the radioactive source term. MANUELA can be used throughout the decommissioning process to validate progress and continue to refine the work activities to optimize the efforts of the crew which reduces downtime waiting for survey results, whereas traditional survey methodology relies on a physical survey to be performed and the data transcribed onto survey maps that are only two dimensional. The traditional format tends to be inaccurate and difficult to interpret the precise location(s) of hot spots or generalized dose rates. The resultant scan also allows the user to know the exact extent of the survey versus transposing information onto a map with only a portion of the map area scanned. MANUELA also compiles all of the relevant survey data into a downloadable table format which includes the measurement identification number, time stamp, point space location on the XYZ plane, and the dose rate value. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Removable, Sequestration Coatings for Mitigating Hazardous Contaminants Related to Deactivation and Decommissioning Activities

This project is a collaborative effort between InnoSense LLC (ISL) and Oak Ridge National Laboratory (ORNL) aimed at mitigating the mercury (Hg) contamination problem at the Y-12 National Security Complex (NSC). The report summarizes the research and technology development work of the Phase IIB Project, led by Dr. Uma Sampathkumaran at ISL for the period of July 31, 2017–October 31, 2021. The Y-12 site cleanup includes technologies for safe and cost-effective facility demolition, soil remediation, and on-site treatment and disposal of mercury bearing wastes. One of the technology demonstration goals was a reactive strippable coating for targeted pre-demolition and de-contamination to limit Hg mobilization and the volume of debris requiring treatment for disposal. Toward this, ISL has developed a water-based reactive strippable coating (Trap & See-Hg™) to sequester elemental Hg(0) and mercuric Hg(II) species in the coating. The coating provides multiple benefits including (1) Hg vapor suppression, (2) sealing in the hazardous contaminants, (3) visually locating the contaminant through color changes, and (4) remediating the contaminated surfaces upon coating removal. Through collaboration between ORNL and ISL in Phase II work, the team successfully demonstrated the Trap & See-Hg technology to (1) visually locate the presence of Hg on concrete, soil and drywall surfaces, (2) effectively sequester all mercury species (elemental, soluble and insoluble Hg) from lab-generated and ex-situ soil and brick/rubble samples collected from the Y 12 site with 80 to 95% efficiency to capture/reduce Hg vapor concentration, (3) be applied by manual and robotic spray applicators and cure at room ambient, (4) remain a cohesive and peelable coating upon drying, and (5) sequester Hg0 from walls in the alpha-2 building basement at Y-12 during a small scale in-situ field trial. In Phase IIB, ISL’s effort was focused on refining the coating formulations with additives containing passive and reactive sorbents, colorimetric indicator, and thixotropic agents to achieve the desired performance. The paints were then evaluated at ORNL for applicability to metal and concrete surfaces of different sizes and shapes, and soil rubble, Hg-sorption capacity and achieving sag-free coating on surfaces when applied by a manual spray applicator. Ambient cure of the coating resulted in a dry thickness of 16–20 mil. The coatings were removed from smooth or rough surfaces with low to moderate force. Both lab-generated Hg-contaminated samples and soil and brick/rubble samples containing a range of Hg concentrations (collected from the Y-12 site by UCOR) were used in this project. Optimized formulations were applied to these samples and evaluated for ability to suppress Hg vapors, sequester Hg 0 and Hg(II) species and color mapping of mercury species on the test surface. The ORNL team initially identified three to four potential sites at Y-12 and ORNL for potential demonstration. However, the pandemic closed any possible avenues for on-site demonstration of the robotic spray applicator. The metal and concrete samples with low to high Hg content provided by UCOR from an ongoing demolition were subsequently used for ex-situ sample characterization and analysis at ORNL over a period of 25 days. The coatings suppressed Hg vapors with an efficiency of 95–99% from heavily contaminated metal and 60% from concrete substrate. Analysis of total Hg in the peeled paints indicates sorption capacities ranging from 12 µg Hg/g of paint from concrete to 1.2 mg Hg/g of paint from the metal substrates while peeled paints from soil samples could capture a total Hg from 2.3 mg Hg/g to 66 mg/g paint. Toxicity characteristic leaching procedure (TCLP) tests recovered total mercury leached at 0.15±0.0008 µg/L for concrete to 126.81±0.67 µg/L and 377.25±5.67 µg/L for the two metal substrates, to allow for informed decisions on downstream disposal considerations. Together, this Phase IIB demonstrated the potential value of the Trap & See-Hg for Hg uptake, vapor suppression, and color mapping, and may thus be used to enhance worker safety during site cleanup, facility demolition, and downstream waste disposal at Y-12 NSC.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Low-Flow Marine Hydrokinetic Turbine for Small Autonomous Unmanned Mobile Recharge Stations

A prototype low-flow marine current turbine for deployment from a small unmanned mobile floating platform has been developed for autonomously seeking and harnessing tidal/coastal currents. The support platform is an unmanned surface vehicle (USV), in the form of a catamaran with two electric outboard motors and with capabilities for autonomous navigation. The USV utilized is a WAM-V 16 vehicle that has been developed separately with support from the Office of Naval Research (ONR) [1]. The marine current turbine is based on a freestream waterwheel (FSWW), also known as an undershot waterwheel (FSWW), mounted on the stern of the USV. The concept of operation involves the USV autonomously navigating to a designated marine current resource. Upon arrival, the USV anchors itself, aligns with the current, and deploys the FSWW turbine using a custom cable-lift mechanism. The turbine harnesses the local current, and an onboard power-take-off (PTO) device converts the mechanical energy into electricity, which is stored in an onboard battery bank. When energy harvesting is completed, the turbine and the anchor are retrieved and the USV navigates to a selected location. These unmanned at-sea platforms can provide power to other unmanned maritime systems. Specifically, in this project, the power generated onboard can be used to charge aerial drones via a custom flight deck that has been developed for the USV. The recharging capabilities offered by a fleet of such strategically placed recharging stations can significantly benefit aerial drones operating in the maritime domain by eliminating the need to travel back and forth to land or ship based charging stations. The project has resulted in the development of subcomponents, including the FSWW turbine, a novel PTO, an automated anchoring system for the USV, an automated turbine deployment system, and a flight deck with capabilities onboard the USV for landing, direct-contact charging and takeoff of aerial drones. The design and development of these subsystems have culminated in the overall prototype marine hydrokinetic platform (MHK Platform, Fig. 1). Comprehensive lab and field testing have been conducted to validate the functionality and performance of the platform and its components. The project demonstrates the potential for autonomous, unmanned systems to harness renewable energy from marine currents, and provide sustainable power solutions for maritime applications such as coastal surveillance and environmental monitoring; shoreline mapping; search and rescue; oceanographic research; inspection and maintenance of offshore energy installations like wind turbines and oil rigs; oil spill response; maritime disaster response; and aerial surveys, as well as facilitation of data transfer drones and shore stations.

16 TIDAL AND WAVE POWER↗