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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Continuous soil temperature and soil deformation measurements, Teller road Mile 47, Nome, Alaska.

The dataset comprises Soil Temperature and Deformation monitoring data gathered from a watershed situated along the Nome-Teller road at Mile 47 in Alaska. Its primary objective is to enhance comprehension of deformation mechanisms in permafrost environments by using 51 probes designed following Wielandt et al. (2022). The dataset comprises a description of Probe_ID, Location, start time, end time and probe length in the "ProbesLocations_StartEndDates.csv" file, the 51 data files encapsulated within "Data_files.zip" and the computed deformation for 2023 and 2022 in "Deformation_T47.zip".Each file in Data_files.zip is named as followed "ProbeId_StartMonth_EndMonth.csv". Within each file, the initial column denotes the timestamp in UTC, followed by the sensor’s battery voltage and temperature and acceleration values (X, Y, Z) in subsequent columns. The data collection frequency is set at 30-minute intervals. Each file in Deformation_T47.zip is named as followed "ProbeId_Temp_def_year.csv". Within each file, the initial column denotes the timestamp in UTC, followed by the temperature at each sensor and cumulative deformation from last to first sensor in subsequent columns. The data collection is daily averaged.This dataset forms an integral component of the Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic). 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 OSTI2023

PW2 Pumping: March 18 thru March 22, 2020

Processed Coherence-length-gated Microwave Photonics Interferometry (CMPI) distributed vertical strain on March 18 through March 22, 2020 at the hydromechanical test facility located at the Clemson University Simpson Station research facility in Central, South Carolina, USA. This includes ambient data in addition to a pumping test performed between 14:31-20:31 EST on 3/22/2020 from Pumping Well 2 (PW2). These data are from a strain ribbon that was deployed in the vadose zone at approximately 34.670130°N, -82.729524°E from the ground surface to a depth of 8m in saprolite containing weak reflectors pairs were placed every 0.85 m along the fiber. Each weak reflector pair forms a 15 cm cavity strain meter. Strain unit: meters/meter (strain). Sampling rate 0.1 Hz. Each column corresponds to the strain data taken at a depth d from the ground surface. c1: d = 1.00m c2: d = 1.85m c3: d = 2.70m c4: d = 3.55m (large demodulation error) c5: d = 4.40m c6: d = 5.25m c7: d = 6.10m (large demodulation error) c8: d = 6.95m

Distributed Strain Sensing↗
DOE OSTI2024

The Iowa Tribe of Kansas and Nebraska: Advancing Clean, Resilient, and Sovereign Energy (Summary Report of Communities LEAP Activities)

The Iowa Tribe of Kansas and Nebraska (ITKN) is a federally recognized Native American Tribe located along the Missouri River on the border of northeast Kansas and southeastern Nebraska. There are over 800 residents (Tribal citizens and non-Tribal) who live on the reservation, as well as more than 500 people who visit or work on the reservation on a daily basis. The ITKN faces many energy challenges, including rising service costs and dozens of power outages annually that impact resident well-being and business activities on Tribal lands. Power service issues are made more challenging by the remoteness of the reservation, which is 20 miles from the nearest town. Despite this, the ITKN has a long history of cultural and economic resilience: Local self-reliance, environmental stewardship, respecting the carrying capacity of the land, and strengthening the community are Tribal communities' traditional strengths. Long-term energy goals for the ITKN are centered around achieving energy sovereignty. Priority actions include: (1) Establishing a Tribal Utility Authority (TUA) to promote social welfare and community development.; (2) Deploying renewable community microgrids with ground-mount solar arrays and sustainable energy storage systems to advance energy sovereignty, resilience, and reliability. To advance these goals, the ITKN partnered with the U.S. Department of Energy's (DOE's) Communities LEAP (Local Energy Action Program) pilot. From August 2022 to March 2024, the ITKN community coalition collaborated with technical assistance providers at DOE's National Renewable Energy Laboratory (NREL) and Sandia National Laboratories to evaluate TUA planning needs and microgrid deployment scenarios. This final report details the Communities LEAP technical assistance process, models and analysis performed, and results.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Estimation of Corn Latent Heat Flux from High Resolution Thermal Imagery

Crop evapotranspiration (ET), which is directly related to latent heat flux, is also a key indicator in determining the water status of crops. In order to estimate the latent heat flux, two-source energy balance (TSEB) models have been developed for thermal imagery from satellite platforms. However, because of the coarse resolution of thermal sensors on the satellite, distinguishing soil and vegetation is difficult which complicates the calculation process and introduces errors in latent heat estimates. In this research, high-resolution thermal datasets (0.05 m) and corresponding RGB datasets (0.03 m) were used for calculating crop latent heat flux using an adapted TSEB model. The RGB datasets were used for supervised classification of soil and vegetation, and the classification results were then used to filter the thermal mosaics to separate vegetation and soil temperatures. The vegetation temperature is used for calculating latent heat flux and the results are validated against the ground reference measurements of latent heat using a handheld porometer. The objective of this research is to introduce a workflow including an adapted TSEB model which is customized for high resolution thermal images from unmanned aircraft systems (UAS) to estimate the latent heat flux of row crops in agricultural fields. Nine dates of data collection in 2018 and 2020 have been evaluated and the root mean square error (RMSE) varies between 16 to 106 W/m2 depending on the days after planting (DAP) and the time of measurement for each day. The results indicate that the workflow introduced here is able to provide estimates of instantaneous latent heat flux (evapotranspiration) measurements for row crops in agricultural fields which will enable people to make reliable decisions related to irrigation scheduling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Low-Power, Flexible Sensor Arrays with Solderless Board-to-Board Connectors for Monitoring Soil Deformation and Temperature: Supporting Data

This dataset was used to assess the potential of a Soil Deformation and Temperature Monitoring System developed and presented in the article named "Low-Power, Flexible Sensor Arrays with Solderless Board-to-Board Connectors for Monitoring Soil Deformation and Temperature" and published in Sensors. There are 21 comma-delimited data files (.csv). 14 files contain current measurements performed in a lab setting, enabling the electrical evaluation of the sensor probe. These files are generated by the Keithley DMM6500 multimeter, and list the measured supply current (first column) as a function of time (3rd column). Another set of 6 files is also acquired in lab experiments, but contain soil temperature an deformation measurements, enabling an assessment of the developed device's accuracy. In these files, the first column contains the time (UTC), followed by the sensor's battery voltage and temperature and acceleration values (X, Y, Z) in subsequent columns. The measurements were acquired every 5 seconds. Another .csv file contains field data in a similar format (time, temperature, acceleration) collected at the Teller road (mile 27) site near Nome, Alaska with one probe. 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 OSTI2020

Bayesian Approach to Estimation of Water Table Elevations Using Historical Rasters as Prior Information 2019 - 20430

In cases of complex but only partially known geology and a lack of spatial control in observation well locations, water table elevation estimation is very challenging. In some cases, auxiliary information, such as observations of the movement of tracers, operation of injection and extraction wells, and calibration of groundwater models against the historical elevation data, can be combined with expert judgement to estimate flow directions in areas of sparse data and to aid in the production of more reliable contour maps (and associated rasters) than could be produced by relying on sparse well elevation data alone. Given a historical sequence of these raster maps, the question arises how to automate, to the extent possible, the process of producing new raster maps to reflect data from previous times, the current data and the operation of expert judgement. One solution is to adopt a Bayesian point of view and to regard the historical well elevation data, auxiliary information and historical raster maps as prior information. The well elevations for water table wells, as well as those for injection/extraction wells and the data associated with other relevant variables, can be viewed as predictors for the raster surface. From this prior information, we can, conditional on the values of these predictors for a new time period, compute an expected value map and a standard deviation map for the new raster. These then can be taken to specify a prior predictive distribution for the pixels in the new raster map. Then we condition the pixels, corresponding to water level observation wells within the raster, on the observed values in those wells (which in general will differ from the regression estimate) for the new time period. Given the smoothness of the water table surface, we then smooth the surface of deviations from the mean surface, based on the variograms of the historical rasters, and add this smoothed surface to the regression mean surface. The error structure of the produced raster map is defined by the regression error structure and the error due to smoothing based on the estimated variograms. This methodology has been developed and is being further refined for groundwater monitoring and remediation at LANL. It is a very flexible method that can also be applied with a variety of other predictors applied to model the water level wells in the area of interest over the historical record. The smoothness of the spatial process and its possible evolution over time can then be estimated from the residuals from this regression. This can be augmented by expert hydrogeological opinion based on site topography and hydrogeology. (authors)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

MAGNETICALLY SUSPENDED CANNED ROTOR PUMPS FOR THE INTEGRAL MOLTEN SALT REACTOR

This project developed a molten salt pump design for small modular reactors, concentrated solar, and Gen IV nuclear reactors with a magnetically levitated rotor that can operate at temperatures of up to 700 °C. This eliminates the need for rotating seals and roller element bearings which require maintenance and are prone to failure. The pump design is also more compact than existing molten salt pump designs which require long shafts to thermally isolate the electric motor. The aims of the project are to: 1) design and test the molten salt pump, 2) develop and test a high temperature position sensor needed for magnetic bearing control, and 3) develop and test high temperature coil fabrication methods for electric motor and magnetic bearing fabrication. To develop the high temperature coils, conductor materials were analyzed for oxidation, diffusion, cladding, and resistivity. Of the candidate conductor materials that met the requirements, silver was chosen. The long-term impact of radiation on silver resistivity was analyzed by developing a model of a generic molten salt fast reactor to model the conductor irradiation in worst case scenarios. The analysis showed that increased resistivity due to transmutation of silver decreases exponentially with the reactor reflector thickness. Different electrical insulation materials were tested and the final high temperature coils developed were able to withstand conductor to ground voltages up to 1800 V before insulation breakdown. Magnetic bearings require high-precision high-speed measurements of the rotor position to operate. Current commercial position sensors can only operate up to 550 °C so a novel position sensor was developed that can operate up to 800 °C. These sensors were also designed to measure the position of the metallic rotor through a thin metallic corrosion barrier that protects that coils, insulation, and magnetic cores so that the salt containment barrier does not have any penetrations. The high-temperature sensor was tested and had comparable performance to commercially available inductive position sensors. The sensor design and signal processing has led to several invention disclosures. The magnetically levitated molten salt pump design was completed and analyzed. The chloride salt test loop at Oak Ridge National Laboratory was chosen to test the pump and the pump hydraulics and power were designed for the test loop flow and pressure requirements. Classes of motor designs that do not utilize permanent magnetic were considered for the high-temperature motor. After extensive analysis of their performance, a synchronous reluctance motor was chosen for the pump. The design was refined and analyzed to optimize performance. The magnetic bearings were designed to meet the force and frequency requirements necessary to levitate the rotor and reject disturbances from rotor imbalance, motor forces, and hydraulic forces. Compliant mounts for the position sensors were designed that would not damage the ceramic sensor components and maintain sensor alignment over a wide temperature range. A thermal hydraulic analysis of the molten salt coolant flow used to cool the rotor and stator was performed to ensure that the maximum temperature in the rotor and stator will not exceed 725 °C. The corrosion barrier and casing were designed to maintain the salt fluid boundary by using compliant features to absorb large expansion mismatches due to different coefficients of thermal expansion (CTE). Finally, the salt drain and fill systems were designed along with the pump support structure, integration with the test loop, and thermal insulation and heating. Corrosion barrier fabrication experiments were performed to assess using laser cladding to apply a sub-millimeter corrosion barrier to the surface of a Fe-Co-V magnetic core material. The cladding method showed minimal mixing between materials at their interface and withstood temperature cycling without damage to the cladding. The technology commercialization is focused on the high-temperature position sensors and there has been significant interest from the nuclear industry in utilizing these sensors along with some interest from the aerospace industry. The project also led to a research collaboration with a fusion energy industrial partner to study barriers to scaling the pump design from the kW size to the MW size. This research collaboration will also study methods to create high-temperature coils that have conductor to ground breakdown voltages above 5 kV. The successful development of high-temperature electromagnetic coils and high-temperature position sensors greatly increases the temperature limits for electromagnetic devices that don’t rely on permanent magnets. This includes electric motors, magnetic bearings, linear actuators, rotary position and velocity sensing, actuated valves, and generators to name a few. This will fill a current need in molten salt reactors, concentrated solar, and fusion energy for these critical peripheral devices needed for practical reactor designs that do not currently have commercial solutions.

Hines, J Wesley↗
DOE OSTI2024

A novel methodology for gamma-ray spectra dataset procurement over varying standoff distances and source activities

The adoption of machine learning approaches for gamma-ray spectroscopy has received considerable attention in the literature. Many studies have investigated the deployment of various algorithm architectures to a specific task. However, little attention has been afforded to the development of the datasets leveraged to train the models. Such training datasets typically span a set of environmental or detector parameters to encompass a problem space of interest to a user. Variations in these measurement parameters will also induce fluctuations in the detector response, including expected pile-up and ground scatter effects. Fundamental to this work is the understanding that 1) the underlying spectral shape varies as the measurement parameters change and 2) the statistical uncertainties associated with two spectra impact their level of similarity. While previous studies attribute some arbitrary discretization to the measurement parameters for the generation of their synthetic training data, this work introduces a principled methodology for efficient spectral-based discretization of a problem space. A signal-to-noise ratio (SNR) respective spectral comparison measure and a Gaussian Process Regression (GPR) model are used to predict the spectral similarity across a range of measurement parameters. This innovative approach effectively showcased its capability by dividing a problem space, ranging from 5 cm to 100 cm standoff distances and 5 μCi–100 μCi of 137 Cs, into three unique combinations of measurement parameters. The findings from this work will aid in creating more robust datasets, which incorporate many possible measurement scenarios, reduce the number of required experimental test set measurements, and possibly enable experimental training data collection for gamma-ray spectroscopy.

data science↗
DOE OSTI2026

Importance of finite-size corrections for accurate ab initio modeling of carrier capture at semiconductor defects: A case study of substitutional C N in GaN

In ab initio studies of carrier-capture processes in defective semiconductor materials, the single-effective-mode formalism and the static-coupling approximation have become the predominant theoretical approaches for determining carrier-capture coefficients. The single-mode formalism relies on accurate nonequilibrium defect energies obtained from density-functional theory (DFT), where required inputs are a series of configurationally displaced, defect-containing supercells obtained using an interpolative ansatz, and where the DFT outputs are corresponding total energies that have traditionally been postprocessed using a long-established ground-state formulation of finite-size corrections and defect-formation energies. This formulation remains commonly used even though the defects that form a configuration-coordinate (CC) diagram typically exist as structures that are displaced from the ground state. To remedy this inconsistency, Kumagai has recently proposed novel methods for implementing finite-size corrections specifically intended for DFT calculations of the defect energies used to construct CC diagrams and implement the single-mode formalism [Y. Kumagai, Phys. Rev. B 107, L220101 (2023)]. Kumagai's approach builds on the latest finite-size-correction methods introduced to describe vertical charge-state transitions for charge-localizing point defects in semiconductors and insulators [T. Gake et al., Phys. Rev. B 101, 020102 (2020); S. Falletta et al., Phys. Rev. B 102, 041115 (2020)]. The newly identified finite-size artifact treated in these studies is the polarization charge induced on a configurationally frozen defect and its subsequent interaction with a vertical transition in charge state. In this work, we evaluate Kumagai's proposed methodology by applying it in a high-precision DFT study of carrier capture by substitutional C N in GaN, a well-characterized and technologically relevant defect and material. We have rigorously calculated C N defect energies across various supercell sizes for each defect configuration and charge state on the hole-capture CC diagram of C N (𝑞=−1), enabling a direct comparison of the slopes of the defect energies versus inverse cell size with those predicted by Kumagai. The most consequential prediction of Kumagai's method is that these slopes distinctly vary as the square of the linear-interpolation parameter used to construct the nonequilibrium defect configurations. Our results quantitatively support this prediction. Moreover, with these new finite-size corrections and multiple-cell-size DFT calculations in place, we find that the classical energy barrier for hole capture by C N (𝑞=−1) in GaN decreases to 0.092–0.127 eV. This finding confirms the recent ≈ 0.1 eV prediction of Reshchikov based on the weak temperature dependence for hole capture observed in photoluminescence experiments [M. A. Reshchikov, J. Appl. Phys. 129, 121101 (2021)]. These results stand in stark contrast to previously calculated barriers of 0.486 and 0.73 eV, which also used the single-mode formalism but were obtained by instead using ground-state-based finite-size corrections. Our reduced classical barrier for capture increases the temperature-dependent hole-capture coefficient of a C N (𝑞=−1) defect by more than two to four orders of magnitude for temperatures of 100–600 K, compared to the previous 0.486 eV results. While other defects may not be as dramatically affected as here, we suggest that incorporating proper finite-size corrections for the vertical-transition-like states embedded within CC diagrams is an essential, yet previously unrecognized, component of accurate modeling of carrier-capture when using the single-effective-mode formalism.

dielectric properties↗
DOE OSTI2021

Total absorption spectroscopy of the β decay of 101,102 Zr and 109 Tc

The β decay of 101,102 Zr and 109 Tc was studied using the technique of total absorption spectroscopy. The experiment was performed at the National Superconducting Cyclotron Laboratory using the Summing NaI(Tl) (SuN) detector in the first-ever application of total absorption spectroscopy with a fast beam produced via projectile fragmentation. The β -decay feeding intensity and Gamow-Teller transition strength distributions were extracted for these three decays. The extracted distributions were compared to three different quasiparticle random-phase approximation (QRPA) models based on different mean-field potentials. A comparison with calculations from one of the QRPA models was performed to learn about the ground-state shape of the parent nucleus. For 101 Zr and 102 Zr, calculations assuming a pure shape configuration (oblate or prolate) were not able to reproduce the extracted distributions. These results may indicate that some type of mixture between oblate and prolate shapes is necessary to reproduce the extracted distributions. For 109 Tc, a comparison of the extracted distributions with QRPA calculations suggests a dominant oblate configuration. The other two QRPA models are commonly used to provide β-decay properties in r-process network calculations. This work shows the importance of making comparisons between the experimental and theoretical β-decay distributions, rather than just half-lives and β-delayed neutron emission probabilities, as close to the r-process path as possible.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Strategic roadmap to assess forest vulnerability under air pollution and climate change

Abstract Although it is an integral part of global change, most of the research addressing the effects of climate change on forests have overlooked the role of environmental pollution. Similarly, most studies investigating the effects of air pollutants on forests have generally neglected the impacts of climate change. We review the current knowledge on combined air pollution and climate change effects on global forest ecosystems and identify several key research priorities as a roadmap for the future. Specifically, we recommend (1) the establishment of much denser array of monitoring sites, particularly in the South Hemisphere; (2) further integration of ground and satellite monitoring; (3) generation of flux‐based standards and critical levels taking into account the sensitivity of dominant forest tree species; (4) long‐term monitoring of N, S, P cycles and base cations deposition together at global scale; (5) intensification of experimental studies, addressing the combined effects of different abiotic factors on forests by assuring a better representation of taxonomic and functional diversity across the ~73,000 tree species on Earth; (6) more experimental focus on phenomics and genomics; (7) improved knowledge on key processes regulating the dynamics of radionuclides in forest systems; and (8) development of models integrating air pollution and climate change data from long‐term monitoring programs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Coupled Heat Power Operation of Smart Buildings via Modular Pumped Hydro Storage

In the United States, building sector is responsible for around 40% of total energy consumption and contributes about 40% of carbon emissions since 2012. Within the past several years, various optimization models and control strategies have been studied to improve buildings’ energy efficiency and reduce operational expenses under the constraints of satisfying occupants’ comfort requirements. However, the majority of these studies consider building electricity demand and thermal load being satisfied by unidirectional electricity flow from the power grid or on-site renewable energy generation to electrical and thermal home appliances. Opportunities for leveraging low-grade heat for electricity have largely been overlooked due to impracticality at small scale. In 2016, a modular pumped hydro storage technology was invented in Oak Ridge National Laboratory, named Ground Level Integrated Diverse Energy Storage (GLIDES). In GLIDES, employing high-efficiency hydraulic machinery instead of gas compressor/turbine, liquid is pumped to compress gas inside high-pressure vessel creating head on ground level. This unique design eliminates the geographical limitation associated with the existing state-of-the-art energy storage technologies. It is easy to be scaled for building level, community level, and grid level applications. By using this novel hydro-pneumatic storage technology, opportunities for leveraging low-grade heat in building can be economical. In this research, the potential of utilizing low-grade thermal energy to augment electricity generation of GLIDES is investigated. Since GLIDES relies on gas expansion in the discharge process and the gas temperature drops during this non-isothermal process, available thermal energy, e.g., from thermal storage, combined cooling, heat and power system (CCHP), can be utilized by GLIDES to counter the cooling effect of the expansion process and elevate the gas temperature and pressure and boost the roundtrip efficiency. Here, several groups of comparison experiments have been conducted, and the experimental results show that a maximum 12.9% cost saving could be achieved with unlimited heat source for GLIDES, and a moderate 3.8% cost improvement can be expected when operated coordinately with CCHP and thermal energy storage in a smart building.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Description of reaction and vibrational energetics of CO 2 –NH 3 interaction using quantum computing algorithms

CO 2 capture is critical to solving global warming. Amine-based solvents are extensively used to chemically absorb CO 2 . Thus, it is crucial to study the chemical absorption of CO 2 by amine-based solvents to better understand and optimize CO 2 capture processes. Here, we use quantum computing algorithms to quantify molecular vibrational energies and reaction pathways between CO 2 and a simplified amine-based solvent model—NH 3 . Molecular vibrational properties are important to understanding kinetics of reactions. However, the molecule size correlates with the strength of anharmonicity effect on vibrational properties, which can be challenging to address using classical computing. Quantum computing can help enhance molecular vibrational calculations by including anharmonicity. We implement a variational quantum eigensolver (VQE) algorithm in a quantum simulator to calculate ground state vibrational energies of reactants and products of the CO 2 and NH 3 reaction. The VQE calculations yield ground vibrational energies of CO 2 and NH 3 with similar accuracy to classical computing. In the presence of hardware noise, Compact Heuristic for Chemistry (CHC) ansatz with shallower circuit depth performs better than Unitary Vibrational Coupled Cluster. The “Zero Noise Extrapolation” error-mitigation approach in combination with CHC ansatz improves the vibrational calculation accuracy. Excited vibrational states are accessed with quantum equation of motion method for CO 2 and NH 3 . Using quantum Hartree–Fock (HF) embedding algorithm to calculate electronic energies, the corresponding reaction profile compares favorably with Coupled Cluster Singles and Doubles while being more accurate than HF. Our research showcases quantum computing applications in the study of CO 2 capture reactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Regional biogeography versus intra-annual dynamics of the root and soil microbiome

Abstract Background Root and soil microbial communities constitute the below-ground plant microbiome, are drivers of nutrient cycling, and affect plant productivity. However, our understanding of their spatiotemporal patterns is confounded by exogenous factors that covary spatially, such as changes in host plant species, climate, and edaphic factors. These spatiotemporal patterns likely differ across microbiome domains (bacteria and fungi) and niches (root vs. soil). Results To capture spatial patterns at a regional scale, we sampled the below-ground microbiome of switchgrass monocultures of five sites spanning > 3 degrees of latitude within the Great Lakes region. To capture temporal patterns, we sampled the below-ground microbiome across the growing season within a single site. We compared the strength of spatiotemporal factors to nitrogen addition determining the major drivers in our perennial cropping system. All microbial communities were most strongly structured by sampling site, though collection date also had strong effects; in contrast, nitrogen addition had little to no effect on communities. Though all microbial communities were found to have significant spatiotemporal patterns, sampling site and collection date better explained bacterial than fungal community structure, which appeared more defined by stochastic processes. Root communities, especially bacterial, were more temporally structured than soil communities which were more spatially structured, both across and within sampling sites. Finally, we characterized a core set of taxa in the switchgrass microbiome that persists across space and time. These core taxa represented < 6% of total species richness but > 27% of relative abundance, with potential nitrogen fixing bacteria and fungal mutualists dominating the root community and saprotrophs dominating the soil community. Conclusions Our results highlight the dynamic variability of plant microbiome composition and assembly across space and time, even within a single variety of a plant species. Root and soil fungal community compositions appeared spatiotemporally paired, while root and soil bacterial communities showed a temporal lag in compositional similarity suggesting active recruitment of soil bacteria into the root niche throughout the growing season. A better understanding of the drivers of these differential responses to space and time may improve our ability to predict microbial community structure and function under novel conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Geophysical Retrievals in an Artificial Intelligence (AI) Framework for Illuminating Processes Controlling Water Cycle

Focal Area(s): This white paper responds to Focal Area #3: Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI. Science Challenge: This white paper addresses the water-cycle and data-model integration grand challenge. It leverages data from the Atmospheric Radiation Measurement (ARM) Climate Research Facility, and Next-Generation Ecosystem Experiment (NGEE), and Science Focus Area (SFA). The white paper focuses on controlling cloud, precipitation, and radiative properties as observed and simulated by the Earth System Models (ESM). The described framework can be readily applied to any other ensemble of instruments, including satellites and other ground-based networks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Co-located temperature and electrical resistivity measurements for permafrost mapping, Teller 27, Teller 47 and Kougarok 64, Seward Peninsula, Alaska, late summers of 2018, 2019, 2021, and 2022

This data set contains co-located shallow soil (0.8m below ground level) and electrical resistivity at various depth extracted from Electrical Resistivity Tomography (ERT) measurements. Data were acquired at three watersheds on the southern Seward Peninsula during the late summers of 2018, 2019, 2021, and 2022. The three watersheds are located along the Nome-Teller Highway at mile markers 27 and 47, and along Kougarok Road mile marker 64. The co-located temperature and electrical resistivity data were used to (1) map the spatial extend of near surface permafrost, and (2) for supervised classification of permafrost bodies. This dataset contains .csv, .txt, .srv files and flmd reporting format with data dictionary. Find information about the .srv files at "https://e4d-userguide.pnnl.gov/e4d_guide/elec/e4d_e4d-survey.html". 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 OSTI2024

Invasive Plant Species Management Plan for Los Alamos National Laboratory (Rev.3)

Native species are plants and animals that continually occupy a natural range without direct or indirect introduction and/or care by humans. They are adapted to the environmental conditions and processes of the ecosystem in which they reside. A species introduced into a novel ecosystem can either exploit that ecosystem and thrive or be unable to survive in that ecosystem (Hobbs et al. 2006). Alien or non-native species are species that are intentionally or accidentally introduced into a novel ecosystem and are capable of living and propagating within the physical parameters of that ecosystem. Invasive species is a species that is non-native (or alien) to the ecosystem under consideration and a noxious species are those whose introduction causes or is likely to cause economic or environmental harm. The term invasive species is applicable to plants and animals alike; however, this invasive species management plan currently focuses on invasive vegetation. Invasive plant species are usually capable of rapid colonization of disturbed ground, such as after a change in wildfire regime intensity and frequency (Reilly et al. 2020) or anthropogenic ground disturbance (Burke and Grime 1996; Hobbs and Huenneke 1992). Climate change facilitates the spread and establishment of many alien species and creates new opportunities for them to become invasive (Turbelin and Catford 2021). As climate change impacts increase in the coming decades, we may see in an increase in invasive species establishment. See a list of definitions of terms pertinent to this document in Appendix A: Definitions. Los Alamos National Laboratory (LANL) hosts populations of non-native and invasive species all typical of the northern New Mexico region (Martin 2004; NMDA 2020). By implementing an invasive species management plan, LANL will have readily accessible management strategies for invasive species that are found on-site. The benefits of managing invasive species include a decrease in wildland fire risks, an increase in soil productivity, an increase in (productive or beneficial) wildlife habitat, an increase in water quantity and quality, and the restoration of impacted areas (Burke and Grime 1996; Hobbs and Huenneke 1992; D’Antonio and Hobbie 2005; MacDougall et al. 2013; Reilly et al. 2020). The aforementioned benefits from invasive species management directly enable the LANL mission by ensuring compliance requirements are met and site-wide programs, such as the Vulnerability Assessment and Resilience Plan, are supported for a mutually beneficial outcome. An example for the LANL site specifically, controlling non-native annual plant species, for example, could reduce the costs associated with stabilizing soils during the stormwater pollution prevention compliance process. Roadway and utility right-of-way areas are another place where an integrated vegetation management strategy would promote low growing perennial plants in a way that is mutually beneficial to habitat and the institution through lowered maintenance costs. There is also an economic benefit to managing invasive species. In one nationwide study, invasive plants had an estimated impact cost of $190.45 billion (Fantel-Lepczyk et al. 2022). Investing in preventative measures and surveillance could help to offset future control and management costs of invasive species that have the potential to become established. The State of New Mexico has developed plant species lists and recommendations through the New Mexico Department of Agriculture’s Noxious Weeds Management Act, Article 7D (NM Statute § 76-7D-4 2021); however, effective invasive species management must rely on local knowledge of the site and region. Los Alamos County (LAC) has already compiled a target invasive plant species list and species-specific management objectives (Martin 2004). Therefore, the New Mexico Noxious Weed List and the LAC invasive plant species list, as well as management objectives from those documents, are integrated into LANL’s invasive plant species management plan.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The Observed Effects of Cold Pools on Convection Triggering and Organization during DYNAMO/AMIE

Cold pools that form from existing convection can generate new clouds nearby, a process that has been suggested to contribute to cloud organization. However, some disagreement exists on the role of cold pools in cloud organization over tropical oceans, and much remains to be understood on how this role depends on the state of large-scale disturbances such as the Madden-Julian Oscillation (MJO). Here, this study addresses this question by examining the intraseasonal variability in the properties of cold pools and their effects on convection triggering using observations. The unique set of surface meteorology data and ground-based radars deployed during the DYNAMO/AMIE field campaign are used to identify cold pools and the associated spatiotemporal evolution of rainfall. The results suggest that cold pools enhance rainfall at their expected speed of 3–8 m s –1 , which includes the Doppler-shifting effect by the background wind. The cold pools also enhance rainfall mainly within a 20 km radius, especially in the direction of boundary-layer vertical wind shear. However, gravity waves appear to contribute predominantly to the propagation of convection over a wider range of distances due to their faster propagation speeds. The interface of convection triggering and propagation at different speeds of cold pools and gravity waves seems to contribute to cloud organization. The effectiveness of cold pools and gravity waves on cloud organization also depends highly on the MJO due to the combined effects of changes in environmental humidity and boundary to lower-tropospheric wind.

54 ENVIRONMENTAL SCIENCES↗