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DOE OSTI2025

Congestion Management Solutions for Enhanced Distribution System Operations with Aggregated Distribution Grid Resources Providing Grid Services and Market Participation

Microgrids and other aggregations of distribution grid resources (DGRs) are poised to actively participate in electricity markets and provide essential grid services in the coming years. In fact, DGRs already play such a role through behind-the-meter (BTM) demand response programs and small-scale BTM dispatchable generation initiatives. At the same time, the rapid growth of artificial intelligence (AI) and cryptocurrency datacenters imposes significant, often unpredictable, demands on the power distribution system. Aggregated DGRs can serve as flexible resources that help mitigate these pressures by using available transmission and distribution capacity more efficiently, supporting resource adequacy and other reliability services, and providing bridge strategies while long-term transmission infrastructure is being developed. The impacts this activity will have on distribution networks are not fully understood and could present significant challenges for distribution utilities due to capacity constraints and the need for congestion management. Technical issues include reverse power flow, variability and possible degradation of equipment integrity, voltage violations, and customer power quality concerns. These issues will likely intensify as electricity market operators across the United States implement Federal Energy Regulatory Commission Order 2222 over the next few years.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Active Learning of Microgrid Frequency Dynamics Using Neural Ordinary Differential Equations

Accurate frequency modelling of inverter‐based resource (IBR)‐dominated power systems is crucial for ensuring stable, reliable and resilient operations, particularly given their inherent low‐inertia characteristics and fast dynamics that traditional swing equation‐based models inadequately capture. This paper explores neural ordinary differential equations (Neural ODEs) as a computationally efficient, data‐driven framework for modelling power system frequency dynamics, specifically within microgrids integrating high penetrations of distributed energy resources (DERs). The developed neural ODEs framework incorporates a neural network architecture designed to capture input dynamics. By actively perturbing the system with a known signal, the Python‐based neural ODEs framework was trained using measured system states and inputs, without the need for detailed system information. The framework, tested on a model of the Cordova, AK, microgrid, achieved a goodness of fit ranging from 60% to 99% across different state variables and maintained a mean square error in the 10 -6 p.u. range under square and step excitation signals. The proposed approach demonstrated robustness to measurement noise and initial condition variations while maintaining low computational complexity suitable for real‐time power system control applications. Furthermore, transfer learning enabled the neural ODEs model to adapt to the following changes in system topology or generator dispatch, highlighting its effectiveness for dynamic microgrids with frequently evolving configurations and diverse DERs.

Aryal, Tara [South Dakota State Univ., Brookings, ↗
DOE OSTI2022

An Assessment of Current Understanding of the Greenhouse Gas Impacts from H 2 Emissions

With the anticipated growth in hydrogen generation and use as part of a broad shift in energy use away from fossil fuels, concerns have been raised regarding the impact of increased H 2 emissions on global warming. Atmospheric scientists have long recognized that H 2 emissions into the atmosphere do have an indirect impact on global warming, largely because a portion of emitted H 2 is consumed by the hydroxyl radical (OH), which is the primary reactant that removes the potent greenhouse gas methane from the atmosphere. Therefore, increases in H 2 emissions will result in decreases in the average OH concentrations in the atmosphere and an increase in the atmospheric lifetime of methane. Various assessments of the impact of H 2 emissions on global warming have been performed over the past couple of decades. These assessments have yielded significant variability and recognized uncertainty in the magnitude of the warming effect of a given quantity of emitted H 2 , and an even greater uncertainty in the magnitude of H 2 leakage and releases that can be anticipated with an expanded H 2 infrastructure. Consequently, definitive estimates of the magnitude of the warming effect of additional emitted H 2 are lacking. However, given the current understanding of the warming potential of emitted H 2 and given reasonable expectations of the emission rate of an expanded H 2 infrastructure, it is anticipated that warming effects from emitted H 2 will offset no more than 5% of the reduction in warming associated with avoided CO 2 emissions from using clean H 2 . Further, it is highly unlikely that the warming effects from emitted H 2 will offset more than 10% of the benefit from avoided CO 2 emissions, at least as considered over a typical 100-year accounting period. Because of the short atmospheric lifetimes of H 2 and methane, however, the warming effect of emitted H 2 is enhanced over the first few years following increases in H 2 emission.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Modeling Present and Future Permafrost Distribution at Seward Peninsula, Alaska: Modeling Archive

This dataset contains results from two GIPL runs for RCP4.5 and RCP8.5 across the Seward Peninsula. The model was run on 500 m by 500 m resolution for the period 1901-2100. Meteo variables include forcing air temperature and precipitation as well as modeled maxim and average snow height. This dataset also includes ground temperature at 10 different depths for every grid cell, active layer depth and talik thickness. Auxillary variables include ecotype map and projected latitude and longitude. Ground temperature borehole data that is used for model calibration and validation of GIPL2 for Seward Peninsula 500 m resolution model runs for 1901-2100 time period. Dataset also includes calibrated model parameters for future use. The main purpose of this dataset is the reproducibility of research. Data were produced for regional permafrost distribution assessment for present and future, in addition, model parameters can be used for future model runs on adjacent territories. This dataset contains *.pdf, *.txt, *.csv, and *.nc. files. 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

Focused‐beam X‐ray fluorescence and diffraction microtomographies for mineralogical and chemical characterization of unsectioned extraterrestrial samples

Abstract This study describes the application of new synchrotron X‐ray fluorescence (XRF) and diffraction (XRD) microtomographies for the 3‐D visualization of chemical and mineralogical variations in unsectioned extraterrestrial samples. These improved methods have been applied to three compositionally diverse chondritic meteorite samples that were between 300 and 400 μm in diameter, including samples prepared from fragments of the CR2 chondrite LaPaz Icefield (LAP) 02342, H5 chondrite MacAlpine Hills (MAC) 88203, and the CM2 chondrite Murchison. The synchrotron‐based XRF and XRD tomographies used are focused‐beam techniques that measure the intensities of fluorescent and diffracted X‐rays in a sample simultaneously during irradiation by a high‐energy microfocused incident X‐ray beam. Measured sinograms of the emitted and diffracted intensities were then tomographically reconstructed to generate 2‐D slices of XRF and XRD intensity through the sample, with reconstructed pixel resolution of 1–2 μm, defined by the resolution of the focused incident X‐ray beam. For sample LAP 02342, primary mineral phases that were visualized in reconstructed slices using these techniques included isolated grains of α‐Fe, orthopyroxene, and olivine. For our sample of MAC 88203, XRF/XRD tomography allowed visualization of forsteritic olivine as a primary mineral phase, a vitrified fusion crust at the sample surface, identification of localized Cr‐rich spinels at spatial resolutions of several micrometers, and imaging of a plagioclase‐rich glassy matrix. In the sample of Murchison, major identifiable phases include clinoenstatite‐ and olivine‐rich chondrules, variable serpentine matrix minerals and small Cr‐rich spinels. Most notable in the tomographic analysis of Murchison is the ability to quantitatively distinguish and visualize the complex mixture of serpentine‐group minerals and associated tochilinite–cronstedtite intergrowths. These methods provide new opportunities for spatially resolved characterization of sample texture, mineralogy, crystal structure, and chemical state in unsectioned samples. This provides researchers an ability to characterize such samples internally with minimal disruption of sample micro‐structures and chemistry, possibly without the need for sample extraction from some types of sampling and capture media.

Geochemistry & Geophysics↗
DOE OSTI2021

Preparing Distribution Utilities for the Future - Unlocking Demand-Side Management Potential: A Novel Analytical Framework

The balance of supply and demand in the power systems has traditionally been served solely through generation and network capacity planning and operations. However, with increased requirements for flexibility due to the uptake in variable renewable generation sources such as wind and solar there is a need to increased demand-side flexibility. In addition, there are increased communications and flexibility capabilities emerging on the demand-side from the adoption of advanced metering infrastructures and smart meter deployment and intelligent loads such as smart thermostats and schedulable white goods (e.g. dishwashers and washing machines). Unlocking demand-side flexibility can bring system benefits from peak load reduction bringing about generation capacity and network upgrade deferral, to reducing demand and more efficient utilization of generation and network capacity. Unlocking demand-side flexibility is an evolving process for utilities and solutions must be tailored to each specific customer group. Demand-side management (DSM) is a broad set of tools that can include demand response (both dispatchable and non-dispatchable), energy efficiency and distributed energy resources and demand-side technologies. The National Renewable Energy Laboratory (NREL), in collaboration with BSES Rajdhani Power Ltd. (BRPL) and Deloitte, examined the potential of DSM in BRPL’s service territory, developing detailed information on customer classes and willingness to participate in DSM. The study developed modeling frameworks for load analysis and the analysis tools to assess the potential of time-of-use tariffs in motivating customers to reduce their peak period energy consumption. The study shows that BRPL customers, specifically their domestic customers, are willing to participate in DSM programs and that time-of-use pricing can help BRPL reduce their peak demand and help unlock demand-side flexibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Seismoacoustic Analysis of the Large Surface Explosion Coupling Experiment Using a Large- N Seismic Array

Seismoacoustic signals at local distance (<~10 km) are widely used as important constraints on source parameters for near-surface events, yet the seismoacoustic wave generation and energy partitioning are not fully understood. Spatially dense sensors could provide observations in high resolution to capture the full wavefield for better understanding wave propagation and improving source estimation. Recently, spatially dense observations of the local seismoacoustic wavefield produced by a pair of 1-ton surface explosions have been recorded using a large-N seismic array. This large-N array consists of 446 geophones and covers an area of approximately 2×2.5 km 2 . The two surface explosions occur at the same location but at different times with different atmospheric conditions. Both seismic and air–ground coupled acoustic waves from the two surface explosions are well observed. Analyses of signals recorded by the large-N seismic array show different acoustic wave speed and amplitude for the two explosions. A strong spatial variability in acoustic wave speed and amplitude for each explosion is also observed. Finally, the observations suggest the important role of local atmosphere state on wave propagation and source estimation and demonstrate how the use of a large-N capability can improve characterization of the propagation medium and source.

58 GEOSCIENCES↗
DOE OSTI2022

Development of a pulsed, variable-energy positron beam for atomic scale defect studies

Positron annihilation spectroscopy provides a sensitive means of non-destructive characterization of materials, capable of probing single atom vacancies in solids with 10 –7 sensitivity. Here, in this work, we detail the development of a magnetically guided, variable energy, pulsed positron beam designed to conduct depth-dependent defect studies in metals, semiconductors, and dielectrics, which will be the first of its kind in the United States. The design of the target stage provides capabilities for measurements during in situ annealing up to 800 °C and incorporates a new approach to minimize the background due to energetic backscattered positrons. The developed beam at Bowling Green State University provides a powerful tool for characterization of thin films, devices, and ion irradiated materials.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

ARM Trajectories Data Set Value-Added Product Report

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s ARM Trajectories Data Set (ARMTRAJ) Value-Added Product (VAP) provides trajectory data sets initialized at ARM deployment coordinates and configured using ARM data sets. The six trajectory data sets support aerosol, cloud, planetary boundary layer, and related research (aerosol-cloud interactions, etc.), as well as studies using ARM Aerial Facility (AAF) and tethered balloon system (TBS) measurements. Trajectory calculations use the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model informed by the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation atmospheric reanalysis (ERA5) data set at its highest spatial resolution (~31 km). HYSPLIT also runs at multiple initial starting locations surrounding ARM deployments (in latitude/longitude and/or vertical coordinates), facilitating an ensemble for each sample in the data sets. The ensemble mean and variability reported in ARMTRAJ improve the fidelity and provide uncertainty estimates of trajectory coordinates, thermodynamic properties, and other output fields.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Sources and Variability of Nitrate on an Alaskan Hillslope Dominated by Alder Shrubs, Kougarok, Alaska, 2017 and 2018

Data provided include results of analyses of soil pore-water, soil moisture, and leaf litter samples collected at a Kougarok Hillslope site dominated by alder shrubs (KG_MM64) in the Seward Peninsula, Alaska during July and September 2017 and 2018. Samples were from surface soils in close proximity to 5 alder patches, collected upslope, within, and downslope of the alder patches. Pore water was analyzed for a comprehensive set of anions, cations, elemental analyses, and oxygen and nitrogen isotopes. Soil samples were collected for soil moisture determination. Leaf litter extracts were analyzed for carbon and nitrogen content and carbon and nitrogen isotopes. This dataset contains 3 *.csv files and 1 *.pdf file. 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

Sensitivity and Uncertainty Quantification of Transition Scenario Simulations

This report documents the first collective attempt at developing and applying capabilities to quantify uncertainties, assess parametric sensitivities, and optimize multiple parameters and metrics in fuel cycle simulations generated by the SA&I Campaign. To do this, external codes that were designed to perform sensitivity analysis and uncertainty quantification (SA&UQ) needed to be coupled to the SA&I Campaign’s nuclear fuel cycle simulators (NFCS). In FY20, two approaches were pursued: 1) coupling Cyclus to an ORNL-internal code called MOT (Metaheuristic Optimization Tool) and 2) coupling DYMOND to the opensource SA&UQ tool kit Dakota. The primary objective of having these NFCS/SA&UQ coupled capabilities is to better inform DOE-NE and other stakeholders on the results generated from the NFCS. For a given set of fuel cycle strategies, policies, and technology assumptions that make up a fuel cycle scenario, these NFCS have traditionally been used by the SA&I Campaign to provide quantitative answers in terms of year-by-year mass flows, infrastructure requirements, costs, etc. With these newly developed coupled capabilities, the SA&I Campaign can now efficiently simulate hundreds or thousands of these scenarios, sample large ranges of parameters and assumptions, and use the unique features of the SA&UQ tools to process the data. This enables providing answers with known and propagated uncertainties, determining the sensitivity of important metrics to different parameters and assumptions, quantifying how much fuel cycle and technology parameters impact each other, and producing optimized fuel cycle strategies for single and multiple variables. To demonstrate these new capabilities, the Cyclus/MOT was used to model several scenarios ranging from simple fleet retirements to transitions to advanced reactors. Specifically, for a transition scenario from LWRs to SFRs and advanced LWRs, uncertainty quantification, sensitivity analysis, and optimization studies were applied to cases involving single and multiple parameter (input) and single and multiple metric (output) variations. In addition, a similar transition scenario was modeled to demonstrate how to optimize the reprocessing capacity parameter to minimize two performance metrics while taking into account uncertainties from two other parameters. Lastly, a depletion module based on SCALE/ORIGEN was added in Cyclus to simulate the third scenario that was designed to quantify the impact of the modeling assumption that all LWR used nuclear fuel have the same burnup. The newly developed DYMOND/Dakota capability was also applied to a transition scenario from the existing fleet to small modular reactors and fast reactors. This particular scenario involves not only explicit isotopic depletion via ORIGEN-2, but also includes multirecycling and utilizing the criticality search feature to determine the fresh fuel composition of recycled fuel, a feature unique to the DYMOND NFCS. A large database of simulations were run with 4 main parameters that were sampled: start date of reprocessing, reprocessing capacity, energy demand growth rate, and advanced reactor share of the fleet. The 4 main metrics were uranium consumption, enrichment requirements, waste generation, and levelized cost of electricity using data from the Cost Basis Report. The demonstrated SA&UQ results include those that inform on how to choose parameters to avoid “failed” scenarios, Sobol’ indices that inform on the importance of various parameters individually and synergistically, and Analysis of Variance (ANOVA) studies that decompose parameter ranges into groups and informs on whether variations are statistically significant.

Feng, B.↗
DOE OSTI2021

Investigating the Causes and Impacts of Convective Aggregation in a High Resolution Atmospheric GCM

Abstract A ∼50 km resolution atmospheric general circulation model (GCM) is used to investigate the impact of radiative interactions on spatial organization of convection, the model's mean state, and extreme precipitation events in the presence of realistic boundary conditions. Mechanism‐denial experiments are performed in which synoptic‐scale feedbacks between radiation and dynamics are suppressed by overwriting the model‐generated atmospheric radiative cooling rates with its monthly varying climatological values. When synoptic‐scale radiative interactions are disabled, the annual mean circulation and precipitation remain almost unchanged, however tropical convection becomes less aggregated, with an increase in cloud fraction and relative humidity in the free troposphere but a decrease in both variables in the boundary layer. Changes in cloud fraction and relative humidity in the boundary layer exhibit more sensitivity to the presence of radiative interactions than variations in the degree of aggregation. The less aggregated state is associated with a decrease in the frequency of extreme precipitation events, coincident with a decrease in the dynamical contribution to the magnitude of extreme precipitation. At regional scales, the spatial contrast in radiative cooling between dry and moist regions diminishes when radiative interactions are suppressed, reducing the upgradient transport of energy, degree of aggregation, and frequency of extreme precipitation events. However, the mean width of the tropical rain belt remains almost unaffected when radiative interactions are disabled. These results offer insights into how radiation‐circulation coupling affects the spatial organization of convection, distributions of clouds and humidity, and weather extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

An Assessment of Non-Powered Dam Hydropower Development Opportunities in the United States

Retrofitting non-powered dams (NPDs) to add hydropower offers multiple benefits over traditional, new hydropower development. Since much of the civil works infrastructure already exists, many retrofits require minimal new construction and can leverage existing water conveyances and discharge for generation. Although NPDs vary considerably in terms of their defining characteristics, identifying similarities helps support targeted investment and find opportunities to develop solutions for common challenges. With the publication of NPD-related data in 2022 (Hansen et al. 2022b), the US Department of Energy and relevant stakeholders are equipped with key information across roughly 89,000 US NPDs. These data represent the best-available information to date and extend beyond previous assessments of potential power capacity by describing design, operational, socioeconomic, environmental aspects of NPDs (Hadjerioua et al. 2012). To capitalize on these efforts to improve breadth and depth of NPD data access, this study uses a data-driven approach to assess NPD hydropower development opportunities in the United States. To help describe project feasibility drivers for NPDs, recent NPD retrofits were reviewed to examine variability with respect to a variety of characteristics. Based on the assessment of recent retrofits and data availability, several attributes were selected to characterize the remaining NPD population: (1) owner type, (2) 30% exceedance flow (a common design flow that describes the flow that is exceeded by 30% of the flow in the record), (3) hydraulic head, and (4) maximum reservoir storage. These four characteristics were used as inputs to a statistical clustering analysis (a common technique for grouping individuals of a population based on similarities or how closely associated individuals are to one another) of a set of 2,709 NPDs with at least 100 kW potential capacity and recently retrofit dams with available data. With the large dataset of NPDs, the clusters help describe how the population breaks down into different types (i.e., how many types of dams there are and what portion of the population belongs to each cluster).

13 HYDRO ENERGY↗
DOE OSTI2025

High Energy Density Physics of Inertial Confinement Fusion Ablator Materials

The historic December 5, 2022 experiment at Lawrence Livermore National Lab’s (LLNL) National Ignition Facility (NIF) reached fusion energy ignition for the first time. This is the most important scientific breakthrough of the 21st century paves the way to future clean inertial fusion energy (IFE). The diamond (high density carbon (HDC)) ablator material used in this experiment displays detrimental effects due to the development of hydrodynamic instabilities at the diamond/fuel interface under shock compression. New alternatives to diamond ablators are required to step up the energy yield in ICF experiments. The unique combination of mechanical strength (approaching that of diamond), the ability to accommodate high-Z dopants (in contrast to diamond), and the tunability of the properties (through synthesis material with varying sp 3 content) make amorphous carbon (a-C) a promising material for next-generation IFE ablative capsules. However, despite its critical importance to the IFE program, the behavior of a-C carbon at extreme temperatures and pressures remains largely unexplored. The primary goals of this project were to perform groundbreaking dynamic compression experiments and predictive simulations to uncover the fundamental high-energy-density physics of amorphous carbon. Our goals were (1) to uncover the metastability range of amorphous carbon and probe phase transitions to diamond or metastable supercooled liquid carbon; (2) to acquire high-quality equation of state (EOS) data and develop an experimentally validated EOS from machine-learning MD simulations of the complex states of carbon; and (3) to uncover the complex behavior of carbon liquid in both thermodynamically stable and metastable supercooled states by accessing large areas of carbon phase diagram with amorphous samples with variable sp 3 content. Our proposed experimental program included measurements of equation of state and diffraction measurements using the Omega EP laser at the Laboratory of Laser Energetics at the University of Rochester. The theoretical/simulation program involved the development of machine-learning models of the complex response of amorphous carbon under dynamic compression by performing molecular dynamics simulations at experimental time and length scales using leadership class DOE supercomputers. Simulations guided experiments to observe predicted phenomena and acquire critical experimental data in specific pressure-temperature domains to validate theoretical models. This research delivered fundamental properties of novel amorphous carbon IFE ablator material, including phase diagram and EOS. These results will aid in IFE target design and implosion experiments. A unique combination of predictive simulations and dynamic and static experiments provided a highly inspirational intellectual environment for graduate students and postdocs involved in this project.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Assessing the Relative Climate Impact of Carbon Utilization for Concrete, Chemical, and Mineral Production

Estimates show that 6.2 gigatons of carbon dioxide (CO2) can be captured and utilized across three pathways, concrete, chemical, and minerals, by 2050. However, it is difficult to compare the climate benefit across these three carbon capture and utilization (CCU) pathways to determine the most effective use of captured CO2. The life cycle assessment methods to evaluate the climate benefit of CCU chemicals should additionally account for the change in material properties of concrete due to CO2 utilization. Furthermore, with most CO2 utilization technologies being in the early stages of research and development, the uncertainty and variability in process and inventory data present a significant challenge in evaluating the climate benefit. We present a stochastically determined climate return on investment (ROI) metric to rank and prioritize CO2 utilization across 20 concrete, chemical and mineral pathways based on the realized climate benefit. We show that two concrete pathways, which use CO2 during concrete mixing, and two chemical pathways, which produce formic acid through hydrogenation of CO2 and carbon monoxide through dry reforming of methane, generate the greatest climate ROI and are the only CCU pathways with a higher likelihood of generating a climate benefit than a climate burden.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Radio AGN selection in LoTSS DR2

ABSTRACT The wide-area component of the LOFAR Two-Metre Sky Survey (LoTSS) is currently the largest radio survey ever carried out, and a large fraction of the 4.5 million radio sources it contains have been optically identified with galaxies or quasars with spectroscopic or photometric redshifts. Identification of radio-luminous active galactic nucleus (AGN) from this LoTSS source catalogue is not only important from the point of view of understanding the accretion history of the universe, but also enables a wide range of other science. However, at present the vast majority of the optical identifications lack spectroscopic information or well-sampled spectral energy distributions. We show that colour and absolute magnitude information from the Wide-Field Infrared Survey Explorer (WISE) allows for the robust and efficient selection of radio AGN candidates, generating a radio AGN candidate sample of around 600 000 objects with flux density $> 1.1$ mJy, spanning 144-MHz luminosities between $10^{21}$ and $10^{29}$ W Hz$^{-1}$. We use the catalogue to constrain the total sky density of radio-luminous AGN and the evolution of their luminosity function between $z=0$ and $z\approx 1$, and show that the typical mass of their host galaxies, around $10^{11} {\rm M}_\odot$, is essentially independent of radio luminosity above around $L_{144} \approx 10^{24}$ W Hz$^{-1}$. Combining with Very Large Array Sky Survey (VLASS) data, we show that the core prominences, radio spectral indices and variability of extended sources from the sample are qualitatively consistent with the expectations from unified models. A catalogue of the radio AGN candidates is released with this paper.

Hardcastle, M. J. (ORCID:0000000342231117)↗
DOE OSTI2022

Regional Feedstock Partnership Biomass Quality Assessment Final Report

The United States (U.S.) Department of Energy (DOE) developed the Billion-Ton Vision to enable production of one-billion tons of sustainable, reliable biomass for the bioenergy industry by 2030 (Perlack et al., 2005). The Sun Grant Regional Feedstock Partnership (RFP) was organized to fill information gaps and validate biomass yield assumptions related to the Billion-Ton Study (Owens, 2018; Owens, Karlen, and Lacey, 2016). Along with the more than 130 scientific publications generated from these studies, yield and sustainability data from the RFP field trials not only validated the Billion-Ton estimates, but were critical in developing both the U.S. Billion-Ton Update report in 2011 and the 2016 Billion-Ton Report (DOE, 2011; 2016). The intention of this biomass quality assessment report is to build on these initial successes from the RFP field trials by focusing on variability in biomass quality data necessary to evaluate conversion performance. This report contains a summary of chemical quality results from samples collected as part of the RFP field trials. This report focuses on assessment of the impact of experimental agronomic designs on biomass properties followed by analyses of the impact of environmental and production variables on biomass properties. Datasets include species and other genetic variables, fertilizer treatments, harvest information, and yield, as well as other publicly available data such as precipitation, temperature, soil properties, and drought. The key outcomes from this chemical quality focused assessment have included: • Complete evaluation of the impacts of agronomic designs, genetics, and environmental conditions on chemical properties for Miscanthus, switchgrass, sorghum, energycane, mixed perennial grasses, and shrub willow short-rotation feedstocks • Over 30 peer review publications and technical reports focused on variability in quality data • Development of spatial and temporal environmental quality prediction maps for Miscanthus and switchgrass feedstocks allowing for comprehensive evaluation of variability in feedstock chemical quality across U.S. regions and over multiple harvest years

09 BIOMASS FUELS↗
DOE OSTI2024

MEMS RF accelerators for nuclear energy and advanced manufacturing

Energetic ions are widely used to develop radiation hard structural materials and fuels for advanced nuclear energy. Ion beams are also used to generate neutrons for nuclear materials testing, as well as in a series of high impact, high value adding manufacturing processes (ranging from doping of semiconductors to hardening of materials against wear and to increase bio-compatibility of materials). But to date, high power beams of high energy ions are simply too expensive because they are delivered from large single beam accelerators. We have recently demonstrated that MEMS technology enables massively parallel, low cost batch fabrication of ion beams. We propose to scale intense ion accelerators based on MEMS (micro-electro mechanical systems) to high beam power (>10 kW). With our approach, hundreds to thousands of ion beamlets will be densely packed on silicon wafers. Ions are injected and accelerated across gaps formed in stacks of wafers, leading to uniquely high current densities for intense ion accelerators with variable kinetic energy (0.1 to 10 MeV) and variable ion species. Our team brings together experts in high power ion accelerators from Lawrence Berkeley National Laboratory and leading experts in MEMS technology from Cornell University. We will deliver a disruptive technology of low cost, flexible and massively scalable ion accelerators that will enable the rapid development of radiation hard nuclear materials for advanced nuclear energy and enable new applications in manufacturing.

43 PARTICLE ACCELERATORS↗