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DOE OSTI2021

Version 2 - Tidal Energy Resource Characterization, Velocity and Turbulence Measurements, Cook Inlet, AK, 2021

Version 2 of MHKDR submission #475, which also contains the metadata for these measurements. Files here are stored in netCDF4 format, which can be read in Python using the "netcdf4" or "xarray" packages or in MATLAB using the "ncread()" function. Changes are as follows: MWM1 (mid-water mooring 1) ADV - Time length of data now ends when bottom track data is lost - Improved filtering and quality control of bottom track measurements - improved motion correction of velocity - Improved Doppler noise subtraction - improved velocity, turbulent kinetic energy (TKE), Reynolds stress, time interval (TI), and dissipation rate estimations MWM1 Down-Looking ADCP - Improved filtering and quality control of bottom track measurements - improved motion correction of velocity - Improved Doppler noise subtraction - improved TI and dissipation rate estimations - Removed TKE calculations - accuracy could not be verified MWM1 Up-Looking ADCP - Improved Doppler noise subtraction - improved TI and dissipation rate estimations - Removed TKE calculations - accuracy could not be verified - Velocity unchanged MWM2 ADV - Removes data after instrument was hit by debris - Improved filtering and quality control of bottom track measurements - improved motion correction of velocity - Improved Doppler noise subtraction - improved velocity, TKE, Reynolds stress, TI, and dissipation rate estimations MWM2 Down-Looking ADCP - Improved filtering and quality control of bottom track measurements - improved motion correction of velocity - Improved Doppler noise subtraction - improved TI and dissipation rate estimations - Removed TKE calculations - accuracy could not be verified MWM2 Up-Looking ADCP - Improved filtering and quality control of bottom track measurements - improved motion correction of velocity - Improved Doppler noise subtraction - improved TI and dissipation rate estimations - Removed TKE calculations - accuracy could not be verified THEOM (bottom lander) ADV - Improved Doppler noise subtraction - improved TKE, Reynolds stress, TI, and dissipation rate estimations - Velocity unchanged THEOM ADCP (up-looking) - Improved Doppler noise subtraction - improved TKE, TI, and dissipation rate estimations - Removed vertical TKE component (w'w' bar) - Velocity unchanged

16 TIDAL AND WAVE POWER↗

DOE OSTI2021

Raw Data published in PeerJ, 2021 for Crested Butte decomposition field study 2017-2019.

This data package contains text files that describe geochemical measurements collected from 2017-2019 during isolated conifer needle decomposition field studies in Crested Butte, Colorado. The geochemical measurements were collected across three elevations (2,800–3,500 m) ranging from montane to subalpine ecoregions. The data sets within include total carbon and nitrogen content and fourier-transform infrared spectroscopy (FTIR) results for the initial needles collected in 2016 and after decomposition in 2019. Data collection results from August 2020 are also included from when the experimental plots were removed to understand final concentrations of soil extractable carbon and nitrogen content as well as mass balances from litter bag deployments. Soil porewater results are also provided from 2017-2019 for DOC, TN, UV254, and specific UV absorbance (SUVA) analyses at 15 cm soil depth. Gas flux raw data provides CO2, CH4, N2O, and NH3 measurements above needle decomposition over the three study years. Finally, soil samples for microbial DNA extractions were collected from the upper soil depth. This raw data is available in the NCBI SRA database under SRA accession numbers PRJNA605259 and PRJNA715914. These data sets were generated to investigate the isolated decomposition of spruce and lodgepole conifer needles. The goal of this work was to determine the roles of elevation, soil type, seasonal changes in soil moisture, and snowmelt timing on litter decomposition processes. Results from this work are detailed in the reference paper "Effect of elevation, season and accelerated snowmelt on biogeochemical processes during isolated conifer needle litter decomposition. DOI: 10.7717/peerj.11926."

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

WHONDRS Surface Water and Sediment Non-Purgeable Organic Carbon and FTICR-MS across Glacial Features in Svalbard 2021 (v3)

This dataset supports a broader study examining land-atmosphere gas exchange associated with permafrost and glaciers in Svalbard. The dataset provides geochemistry and organic matter characterization data generated from surface water and sediment. Samples were collected from 8 spatially diverse sites across central Svalbard and also from a more comprehensive temporal and spatial study within one glacial catchment area throughout one summer melt season. Related data were collected and will be published separately in collaboration with Yde and Kleber.This data package was originally published in September 2022. It was updated in March 2023 (v2; new and modified files), and July 2025 (v3; modified files). See the change history section in the readme for details.For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved organic carbon (DOC; measure as non-purgeable organic carbon; NPOC); (5) surface water sampling protocol; (6) sediment extraction protocol; (7) readme; (8) methods codes; (9) international generic sample number (IGSN) mapping file; and (10) folder of high resolution characterization of organic matter via 7 and 12 Tesla (7T and 12T) Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains two subfolders containing the 7T and 12T .xml data files and another subfolder containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Temporal Study 2021-2022: Sensor-Based Time Series of Surface Water Temperature, Specific Conductance, Total Dissolved Solids, Turbidity, pH, and Dissolved Oxygen from across Multiple Watersheds in the Yakima River Basin in Washington, USA (v2)

This dataset supports a broader study examining the drivers of temporal variability in sediment respiration rates in the Yakima River Basin. The dataset provides periodic (weekly or biweekly) in situ hydrological and water chemistry sensor data, handheld sensor water chemistry data, general environmental context photos, and field metadata collected at six sites within multiple rivers in the Yakima River Basin in Washington, USA. In addition to the sensor data, there are plots of continuous in situ sensor data and R scripts used to generate the plots. Related sample-based water chemistry data are published separately at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1898912.The data package was originally published in September 2022. It was updated in June 2025 (v2; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one main data folder containing two sensor-specific subfolders, and one photographs folder. The main data folder includes file-level metadata (flmd), data dictionary (dd), installation methods, field metadata, handheld sensor data, field data collection protocols, international generic sample number (IGSN) mapping file, and a readme file. Each sensor subfolder (BarotrollAtm and MantaRiverData) contains a subfolder containing sensor timeseries data and plots. The BarotrollAtm Data subfolder contains In Situ Rugged BaroTROLL sensor pressure and air temperature data. The MantaRiverData subfolder contains Eureka Manta+ 35B multisonde temperature, specific conductance, and turbidity. The FieldPhotos folder contains environmental context photographs and videos. All files are .csv, .pdf, .R, .jpg, .jpeg, .heic, .mov, or .mp4.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Soil C stock and CO2 production data for Soong et al. 2021: Effects of five years of soil warming at Blodgett Forest, CA.

Subsoils below 20 cm are an important reservoir in the global carbon cycle, but little is known about their vulnerability under climate change. We measured subsoil carbon in warmed vs control plots of a conifer forest after 4.5 years of whole-soil warming (4°C). We also measured soil CO2 efflux at the surface and soil CO2 concentrations along the soil profile. Over the 4.5 years we observed that warming resulted in a loss of subsoil carbon stocks (−33 ± 11%), primarily from unprotected particulate organic matter. Warming also stimulated a sustained 30 ± 4% increase in soil CO2 efflux due to increased CO2 production through the whole-soil profile. The observed in situ decline in subsoil carbon stocks with warming is now definitive evidence of a positive soil carbon-climate feedback, which could not be concluded based on increases in CO2 effluxes alone. This dataset comprises (1) 13C and C recovery in 2014, 2016, and 2018 1m soil cores sampled in 10cm increments. (2) Monthly surface CO2 fluxes from 2014 to 2018. (3) Monthly gas well sample [CO2] and production data. And (4) density fraction data for three depths of cores recovered in 2017.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Temporal Study 2021-2022: Sample-Based Surface Water Chemistry and Organic Matter Characterization across Watersheds in the Yakima River Basin, Washington, USA (v3)

This dataset supports a broader study examining the drivers of temporal variability in sediment respiration rates in the Yakima River Basin. The dataset provides geochemistry and organic matter characterization data generated from samples collected at weekly or bi-weekly intervals at six sites across the Yakima River Basin in Washington, USA. Related sensor data will be published separately and can be used to link sediment respiration rates to biogeochemical processing rates. The data package was originally published in November 2022. It was updated in November 2023 (v2; modified files) and April 2025 (new and modified files). See the change history section in readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved inorganic carbon (DIC), dissolved organic carbon (DOC; reported as non-purgeable organic carbon; NPOC), total nitrogen (TN), total suspended solids (TSS), and ions; (5) averaged values from water chemistry data; (6) surface water sampling protocol; (7) sensor protocol; (8) readme; (9) methods codes; (10) international generic sample number (IGSN) mapping file; and (11) folder of high resolution characterization of organic via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). This folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected our data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Spatial Study 2021: Sample-Based Surface Water Chemistry and Organic Matter Characterization across Watersheds in the Yakima River Basin, Washington, USA (v3)

This dataset supports a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin. The dataset provides geochemistry and organic matter characterization data generated from samples collected during the same two-week period at 47 sites within multiple rivers throughout the Yakima River Basin in Washington, USA. Related sensor data are published at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1892054. This data package was originally published September 2022. It was updated May 2023 (modified files) and November 2024 (new and modified files). See the change history section in the readme for more details. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved inorganic carbon (DIC), dissolved organic carbon (DOC; reported as non-purgeable organic carbon; NPOC), total nitrogen (TN), total suspended solids (TSS), ions, and benzene polycarboxylic acid (BPCA) concentration and stable isotope data; (5) averaged values from water chemistry data; (6) surface water sampling protocol; (7) sensor protocol (8) readme; (9) methods codes; (10) international generic-sample number (IGSN) mapping file; and (11) folder of high resolution characterization of organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). This folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formultitude (https://github.com/PNNL-Comp-Mass-Spec/Formultitude) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml. We thank the United States Forest Service, Washington Department of Natural Resources, Washington Department of Fish and Wildlife, Washington State Parks, Confederated Tribes and Bands of the Yakama Nation, and Cowiche Canyon Conservancy for access to field locations where these samples were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Raw soil carbon dioxide, moisture, temperature and micrometeorological data in the East River Watershed, Colorado June 2021-June 2024. (DE-SC0021139)

This dataset contains raw data from four tripod stations along an elevation gradient on Snodgrass Mountain in the East River Watershed, CO, USA. Each station contains a datalogger connected to 3 soil Carbon Dioxide CO2 gas probes, 3 soil temperature/moisture sensors and a micrometeorological station. Sensors are scanned every minute, and the 30 minute average is reported. The file snodgrass_soil_ESS.csv contains raw data, a row of column descriptors, and units of measurements. some data processing and QA/QC was done to filter out data from sensors that went bad and extreme outliers. CO2 sensors that went bad were replaced with new sensors as soon as possible. This research was performed to investigate the ecohydrological linkages of belowground carbon processes in the East River watershed forested communities to better understand how these ecosystems will respond to a changing cold-season moisture input. This is the second version of this data set and was modified on 10/01/2024. The primary change in the data was the addition of data from the fall of 2022 to June of 2024. In addition, minor QA/QC was done to filter out data from sensors that went bad and extreme outliers. THe filtered data are now NA's in this data frame and primarily the CO2 sensors. Limited to no QA/QC has been done on the other environmental data. This is now the third version of the data set, and was modified 03/25/2026. The primary change in the data was the addition of data from the June of 2024 to December 2025. Further r QA/QC was done with the new data to filter out bad data from faulty sensors and extreme outliers. The filtered data are now NA's in this data frame and primarily the CO2 sensors. Limited to no QA/QC has been done on the other environmental data. ##This additional data was funded under DE-SC0024218( Responses of Plant and Microbial Respiration Sources to Changing Cold Season Climate Drivers in the East River Watershed)

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Carbon dioxide (CO2) flux, amplicon sequencing and liquid chromatography–mass spectrometry (LC-MS) data for pyrogenic organic matter (PYOM) amended soil incubations in lab, Madison, WI, 2021-22

This dataset comprises soil-pyrogenic organic matter (PyOM) incubation experiments conducted in a laboratory setting. The focus was on measuring carbon dioxide (CO2) flux emitted in the headspace of incubation jars over a one-month period. The aim was to estimate carbon mineralization from two different carbon fractions in PyOM, as well as carbon mineralization from soil organic carbon (SOC). Bacterial and fungal community profiles were tracked at various time points during the incubation to observe changes in the overall community and specific responders to PyOM. LC-MS analysis of soil samples was also performed to monitor changes in the soil's chemical composition.The provided dataset includes processed CO2 flux measurements obtained from the Picarro-multiplexer measurement setup for each sample incubation jar. This data is available in the "CO2Flux.csv" file. Additionally, the dataset includes CO2 flux data partitioned to estimate mean carbon mineralization from the two PyOM carbon fractions, bulk PyOM, and SOC. The cumulative carbon mineralization data is provided in "cml_respired.csv," while the rate of carbon mineralization data is in "rate_respired.csv." The file "cml_respired_lastcyc.csv" contains cumulative carbon mineralization data for the PyOM carbon fractions, bulk PyOM, and SOC throughout the entire incubation period.For the LC-MS analysis, the raw data can be found in the "20220721_NZ_PeakHeights_FinalAnalysis.csv" file, while sample metadata is provided in "20220721_NZpilot_Metadata.csv". Processed LC-MS data is available in the file "20220721_NZ_FINAL_msdat_sub3.csv". Lastly, the dataset includes the relative abundance data for bacterial genera that exhibited a significant positive response to the addition of PyOM produced at 350 degrees Celsius, which can be found in "resp_genera_350.csv".

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Continuous snow depth, ground interface temperature and shallow soil temperature measurements from 2021-10-1 to 2022-6-14, Seward Peninsula, Alaska

The dataset contains co-located snow depth, ground interface temperature, and shallow soil temperature measured at 98 discrete locations in a watershed located along the Nome-Teller road at mile marker 27 (referred to as T27), and at 53 discrete locations on a hillslope located along the Kougarok road at mile marker 64 (referred to as K64), in Seward Peninsula, Alaska. The dataset aims to understand the local heterogeneity of snow depth, snow temperature, and soil temperature dynamics and their interactions in a discontinuous permafrost region. The dataset is also valuable to train and evaluate machine learning and physical models to predict snow depth or the impact of snow depth on ground surface temperature. At each location, temperatures above and below the ground surface were measured by a pair of vertically deployed distributed temperature profiling probes designed based on Dafflon et al (2022). The probes have high precision temperature sensors spaced at 5 or 10 cm. The mean daily snow depth was estimated by identifying the pair of consecutive sensors with maximum drop of daily temperature high-frequency fluctuations. The ground interface temperature was measured by the sensor located 1-5 cm above the ground surface at 15-minute intervals. The shallow soil temperature was measured by the sensor located 1-5 cm below the ground surface at 15-minute intervals. The dataset includes a description of the probe locations in the "Probe_locations_*.csv" file and the 3 data files (Snow_depths_*.csv, Ground_interface_temperatures_*.csv, Shallow_soil_temperatures_*.csv). * is either T27 or K64, which are the two study sites. In each data file, each column corresponds to a measurement location. Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in xxxx_flmd.csv. A more detailed description of data processing, along with an updated dataset incorporating multiple seasons and improved snow depth estimation is available at https://doi.org/10.15485/2480365 (Wang et al., 2025a, Wang et al., 2025b).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

X-ray Absorption Spectroscopy and Neutron Scattering Data, Mineral Incubation Experiment, Walker Branch Watershed, TN (2020 - 2021)

Iron (Fe) (oxyhydr)oxides are well-recognized contributors to soil carbon (C) storage, but the effects of manganese (Mn) oxides on carbon storage and transformation are relatively unexplored. Here, the relative capacities of Fe and Mn oxides to bind and stabilize soil organic C were directly compared using an in-situ incubation experiment. Quartz sands coated with either poorly crystalline Mn(III/IV) oxides or Fe(III) oxides, or left uncoated, were buried in a temperate forest soil for up to one year. This data package contains processed data outputs of carbon near edge x-ray absorption fine structure spectroscopy (C NEXAFS), iron and manganese x-ray absorption near edge structure spectroscopy (XANES), and small angle neutron scattering (SANS) data collected for initial oxide-coated and uncoated quartz sands and for those buried in the temperate forest soil for 365 days.

Energy (eV)↗

DOE OSTI2021

Illinois State Geological Survey (ISGS), Illinois Basin - Decatur Project (IBDP) Geological Models, July 7, 2021. Midwest Geological Sequestration Consortium (MGSC) Phase III Data Sets. DOE Cooperative Agreement No. DE-FC26-05NT42588.

Three geological models in Petrel (Mark of Schlumberger) and data output from shallow groundwater modeling using TOUGH Codes from Lawrence Berkeley National Laboratory, included under folders: Static_Geologic_Model, Dynamic_Reservoir_Model, Geomechanical_Model, and Groundwater_Model.

3D Geological Model↗

DOE OSTI2021

Illinois State Geological Survey (ISGS), Illinois Basin - Decatur Project (IBDP) Seismic Data, July 7, 2021. Midwest Geological Sequestration Consortium (MGSC) Phase III Data Sets. DOE Cooperative Agreement No. DE-FC26-05NT42588.

Seismic data from the IBDP, included primarily under folders: Active_Seismic_Data and Passive_Seismic_Events_Monitoring. The data included under IBDP_Located_Microseismic_Event_Data are a subset of microseismic (Passive Seismic Events Monitoring) data acquired throughout the project from pre-injection to shut-in. These data represent the “located” microseismic events and the two datasets, located in folders Downhole_Geophone_Data and Surface_Seismometer_Data, are correlated.

3D Seismic,Carbon Sequestration,Decatur,Illinois B↗

DOE OSTI2023

Water resource recovery modelling 2021 (WRRmod2021 conference)

Our society is transitioning fast into the digital age, spurred by development of cheap and new sensing technology, breakthroughs in computing, and development of efficient algorithms for optimization. This transition is also visible in the field of wastewater treatment and is driving new model developments, especially by exploiting the large data sets available with many utilities. Not surprisingly, WRRmod2021 had featured a strong session on ‘data-driven models and digitalization’ focused on this hot topic. At the same time, engineering practice calls for more robust models for performance evaluation and optimization of both conventional facilities and innovative processes. As a result, the WRRmod2021 program also exhibited sessions on modelling of new process units (e.g., aerobic granular sludge), modelling of the nitrogen cycle, and integrated/plant-wide modelling.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

A Detailed Vehicle Simulation Process to Support CAFE and CO 2 Standards (MY 2021–2026 Final Rule Analysis)

In 1975, Congress passed the Energy Policy and Conservation Act (EPCA), requiring standards for corporate average fuel economy (CAFE), and charging the U.S. Department of Transportation (DOT) with the establishment and enforcement of these standards. The Secretary of Transportation has delegated these responsibilities to the National Highway Traffic Safety Administration (NHTSA). NHTSA has contracted the DOT Volpe National Transportation Systems Center (Volpe Center) to provide analytical support for NHTSA’s regulatory and analytical activities related to fuel economy standards. Unlike long-standing safety and criteria pollutant emissions standards, fuel economy standards apply to manufacturers’ overall fleets rather than to individual vehicle models. In developing the standards, NHTSA made use of the CAFE Compliance and Effects Modeling System (the “CAFE model”), which was developed by DOT’s Volpe Center for the 2005-2007 CAFE rulemaking and has been continually updated since. The model is the primary tool used by the agency to evaluate potential CAFE stringency levels by applying technologies incrementally to each manufacturer’s fleet until the requirements under consideration are met. The CAFE model relies on numerous technology-related and economic inputs such as market forecasts and technology cost and effectiveness estimates; these inputs are categorized by vehicle classification, technology synergies, phase-in rates, cost learning curve adjustments, and technology “decision trees.” The Volpe Center assists NHTSA in the development of the engineering and economic inputs to the CAFE model by analyzing the application of potential technologies to the current automotive industry vehicle fleet to determine the feasibility of future CAFE standards, the associated costs, and the benefits of the standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Phase Contrast Imaging Diagnostic on DIII-D (1994-2007); Phase Contrast Imaging Diagnostic on DIII-D and Alcator C-Mod (2007-2010); Experimental Study of Waves, Turbulence and Transport, and Model Validation with Phase Contrast Imaging on DIII-D and Alcator C-Mod (2010-2012); Phase Contrast Imaging Diagnostic Upgrade on DIII-D for Measuring High-k Turbulence and Alfven modes (2021-2016); Phase Contrast Imaging Diagnostic Upgrade on DIII-D for Full Multi-Scale Measurements (2016-2020) (Final Report)

This report describes the first twenty-five years of development and use of the Phase Contrast Imaging (PCI) diagnostic for measuring plasma fluctuations on the DIII–D tokamak. One of the key challenges in moving tokamak technology forward to the stage of a nuclear reactor remains understanding how energy and particles are transported across the magnetic field by the action of turbulence and waves, and PCI provides a highly flexible and capable measurement of these fluctuations. The PCI diagnostic uses a laser beam to probe the plasma and optical filtering to produce an amplitude variation on a linear detector array which provides an image of the density waves in the plasma. The PCI covers an exceptional range in frequency and wavelength of the measured fluctuations, allowing observation of plasma-sized magnetohydrodynamic (MHD) modes and ion- and electron-scale turbulence. Modulation of the beam amplitude allows measurement of radio frequency (RF) waves.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

National Security Research Center 2021 Strategic Plan

The National Security Research Center (NSRC) is a dynamic organization staffed with an expert, highly trained experts. The NSRC opened its doors in June 2019, making it one of the newest large organizations at Los Alamos National Laboratory (LANL). It supports a broad range of researchers within the LANL Weapons Program, customers across other National Nuclear Security Administration (NNSA) labs and sites, and partners in the Department of Defense (DoD). The maintenance and growth of the NSRC necessitate strategy and foresight. The NSRC leadership has developed a series of strategic goals through discussions with NSRC staff, customers, LANL leadership, and similar research institutions around the country to guide the NSRC leadership in moving the Center forward over the next five years.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2020

2021 Stewardship Science Academic Programs Annual

I am a staff scientist at Sandia National Laboratories (SNL). I work on multiple fundamental-science projects and lead modeling/data-analysis for the stellar opacity experiments. I also work with theorists to refine plasma material-property calculations to make NNSA simulations more predictable. These are challenging and important problems for national security. In fact, our experiments raised questions about “opacity”, the property of matter that controls energy transport inside stars. This work was published by Nature due to its serious implication over broad applications, and our team received NNSA Defense Program Award of Excellence, both in 2015. Work at SNL is collegial and full of learning through interactions with the world’s finest experimentalists and theorists. When I started my Ph.D. program, working at a national lab was a dream position. Today, I collaborate with top scientists to solve mission-critical problems. The Stewardship Science Academic Programs (SSAP) and National Laser Users’ Facility (NLUF) played a vital role in the efficient learning and seamless transition to SNL.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗