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DOE OSTI2024

Elemental profiling and genome-wide association studies reveal genomic variants modulating ionomic composition in Populus trichocarpa leaves

The ionome represents elemental composition in plant tissues and can be an indicator of nutrient status as well as overall plant performance. Thus, identifying genetic determinants governing elemental uptake and storage is an important goal for breeding and engineering biomass feedstocks with improved performance. In this study, we coupled high-throughput ionome characterization of leaf tissues with high-resolution genome-wide association studies (GWAS) to uncover genetic loci that modulate ionomic composition in leaves of poplar ( Populus trichocarpa ). Significant agreement was observed across the three ionomic profiling platforms tested: inductively coupled plasma-mass spectrometry (ICP-MS), neutron activation analysis (NAA) and laser-induced breakdown spectroscopy (LIBS). Relative quantification of 20 elements using ICP-MS across a population of 584 genotypes, revealed larger variation in micro-nutrients and trace elements content than for macro-nutrients across genotypes. The GWAS performed using a set of high-density (>8.2 million) single nucleotide polymorphisms, identified over 600 loci significantly associated with variations in these mineral elements, pointing to numerous uncharacterized candidate genes. A significant enrichment for genes related to ion homeostasis and transport was observed, including several members of the cation-proton antiporters (CPA) family and MATE efflux transporters, previously reported to be critical for plant growth and fitness in other species. Our results also included a polymorphic copy of the high-affinity molybdenum transporter MOT1 found directly associated to molybdenum content. For the first time in a perennial plant, our results provide evidence of genetic control of mineral content in a model tree species.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

General features of the stellar matter equation of state from microscopic theory, new maximum-mass constraints, and causality

The profile of a neutron star probes a very large range of densities, from the density of iron up to several times the density of saturated nuclear matter, and thus no theory of hadrons can be considered reliable if extended to those regions. We emphasize the importance of taking contemporary ab initio theories of nuclear and neutron matter as the baseline for any extension method, which will unavoidably involve some degree of phenomenology. We discuss how microscopic theory, on the one end, with causality and maximum-mass constraints, on the other, set strong boundaries to the high-density equation of state. We present our latest neutron star predictions where we combine polytropic extensions and parametrizations guided by speed of sound considerations. The predictions we show include our baseline neutron star cooling curves.

chiral effective field theory↗

DOE OSTI2025

Effects of Quark Core Sizes of Baryons in Neutron Star Matter

We describe the quark substructure of hadrons and the equation of state of high-density neutron star matter by using the Nambu–Jona-Lasinio (NJL) model, which is an effective quark theory based on QCD. The interaction between quarks fully respects the chiral and flavor symmetries. Guided by the success of various low-energy theorems, we assume that the explicit breaking of these symmetries occurs only via the current quark masses, and all other symmetry breakings are of dynamical nature. In order to take into account the effects of the finite quark core sizes of the baryons on the equation of state, we make use of an excluded volume framework that respects thermodynamic consistency. The effects generated by the swelling quark cores generally act repulsively and lead to an increase in the pressure with increasing baryon density. On the other hand, in neutron star matter, these effects also lead to a decrease in the density window where hyperons appear because it becomes energetically more favorable to convert the faster moving nucleons into hyperons. Our quantitative analysis shows that the net effect of the excluded volume is too small to solve the long-standing “hyperon puzzle”, which is posed by the large observed masses of neutron stars. Thus, the puzzle persists in a relativistic effective quark theory which takes into account the short-range repulsion between baryons caused by their finite and swelling quark core sizes in a phenomenological way.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

A More Precise Measurement of the Radius of PSR J0740+6620 Using Updated NICER Data

PSR J0740+6620 is the neutron star with the highest precisely determined mass, inferred from radio observations to be 2.08 ± 0.07 M ⊙ . Measurements of its radius therefore hold promise to constrain the properties of the cold, catalyzed, high-density matter in neutron star cores. Previously, Miller et al. and Riley et al. reported measurements of the radius of PSR J0740+6620 based on Neutron Star Interior Composition Explorer (NICER) observations accumulated through 2020 April 17, and an exploratory analysis utilizing NICER background estimates and a data set accumulated through 2021 December 28 was presented in Salmi et al. Here we report an updated radius measurement, derived by fitting models of X-ray emission from the neutron star surface to NICER data accumulated through 2022 April 21, totaling ~1.1 Ms additional exposure compared to the data set analyzed in Miller et al. and Riley et al., and to data from XMM-Newton observations. We find that the equatorial circumferential radius of PSR J0740+6620 is ${12.92}_{-1.13}^{+2.09}$ km (68% credibility), a fractional uncertainty ~83% the width of that reported in Miller et al., in line with statistical expectations given the additional data. If we were to require the radius to be less than 16 km, as was done in Salmi et al., then our 68% credible region would become $R={12.76}_{-1.02}^{+1.49}$ km, which is close to the headline result of Salmi et al. Our updated measurements, along with other laboratory and astrophysical constraints, imply a slightly softer equation of state than that inferred from our previous measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Probing the γ -Ray Emission Origin of Two Star-forming Galaxies NGC 2403 and NGC 3424 with the Fermi-LAT

Star-forming galaxies (SFGs) are a subclass of γ-ray emitters, and a correlation between their γ-ray luminosity (L γ ) and the total infrared (IR) luminosity (L IR ) has been established based on the Fermi Large Area Telescope (LAT) data. NGC 2403 and NGC 3424 have been reported as outliers in the L γ –L IR correlation with light curves showing significant variability, which contrasts with the temporally stable γ-ray emission in other SFGs, originating primarily from cosmic rays interacting with interstellar medium. In this study, we reanalyze the γ-ray emission in the directions of NGC 2403 and NGC 3424 using more than 16.5 yr Fermi-LAT data. NGC 3424 is found to be spatially coincident with the detected γ-ray source, while NGC 2403 is significantly offset from the nearest γ-ray source, suggesting an implausible association. We confirm the previously reported variability of both γ-ray sources and the significant deviation from the L γ –L IR correlation when assuming an association of both γ-ray sources with the two galaxies. Our findings lend further support to the interpretation that their γ-ray emission is driven primarily by alternative radiative processes—rather than by star formation activity—such as the ejecta of the Type IIP supernova SN 2004dj in NGC 2403 interacting with a surrounding high-density shell and an obscured active galactic nucleus in NGC 3424.

Liu, Linjie [Chinese Academy of Sciences (CAS), Ku↗

DOE OSTI2024

Constraining the Dense Matter Equation of State with New NICER Mass–Radius Measurements and New Chiral Effective Field Theory Inputs

Pulse profile modeling of X-ray data from the Neutron Star Interior Composition Explorer is now enabling precision inference of neutron star mass and radius. Combined with nuclear physics constraints from chiral effective field theory (χEFT), and masses and tidal deformabilities inferred from gravitational-wave detections of binary neutron star mergers, this has led to a steady improvement in our understanding of the dense matter equation of state (EOS). Here, we consider the impact of several new results: the radius measurement for the 1.42 M ⊙ pulsar PSR J0437−4715 presented by Choudhury et al., updates to the masses and radii of PSR J0740+6620 and PSR J0030+0451, and new χEFT results for neutron star matter up to 1.5 times nuclear saturation density. Using two different high-density EOS extensions—a piecewise-polytropic (PP) model and a model based on the speed of sound in a neutron star (CS)—we find the radius of a 1.4 M ⊙ (2.0 M ⊙ ) neutron star to be constrained to the 95% credible ranges ${12.28}_{-0.76}^{+0.50}$ km (${12.33}_{-1.34}^{+0.70}$ km) for the PP model and ${12.01}_{-0.75}^{+0.56}$ km (${11.55}_{-1.09}^{+0.94}$ km) for the CS model. The maximum neutron star mass is predicted to be ${2.15}_{-0.16}^{+0.14}$M ⊙ and ${2.08}_{-0.16}^{+0.28}$M ⊙ for the PP and CS models, respectively. We explore the sensitivity of our results to different orders and different densities up to which χEFT is used, and show how the astrophysical observations provide constraints for the pressure at intermediate densities. Moreover, we investigate the difference R 2.0 − R 1.4 of the radius of 2 M ⊙ and 1.4 M ⊙ neutron stars within our EOS inference.

gravitational wave sources↗

DOE OSTI2025

Origin of the ring ellipticity in the black hole images of M87*

We investigate the origin of the elliptical ring structure observed in the images of the supermassive black hole M87*, aiming to disentangle contributions from gravitational, astrophysical, and imaging effects. Leveraging the enhanced capabilities of the Event Horizon Telescope (EHT)'s 2018 array, including improved (u,v)-coverage from the Greenland Telescope, we measured the ring's ellipticity using five independent imaging methods, obtaining a consistent average value of τ = 0.08−0.02+0.03 with a position angle of ξ = 50.1−7.6+6.2 degrees. To interpret this measurement, we compared it to general relativistic magnetohydrodynamic (GRMHD) simulations spanning a wide range of physical parameters including the thermal or nonthermal electron distribution function, spins, and ion-to-electron temperature ratios in both low- and high-density regions. We find no statistically significant correlation between spin and ellipticity in GRMHD images. Instead, we identify a correlation between ellipticity and the fraction of non-ring emission, particularly in nonthermal models and models with higher jet emission. These results indicate that the ellipticity measured from the M87* emission structure is consistent with that expected from simulations of turbulent accretion flows around black holes, where it is dominated by astrophysical effects rather than gravitational ones. Future high-resolution imaging, including space very long baseline interferometry and long-term monitoring, will be essential to isolate gravitational signatures from astrophysical effects.Key words: accretion, accretion disks / black hole physics / gravitation / galaxies: active** These authors have contributed equally to this work.*** NASA Hubble Fellowship Program, Einstein Fellow.† Deceased.

Dahale, Rohan [Granada U., Theor. Phys. Astrophys.↗

DOE OSTI2025

Application of PRIM for understanding patterns in carbon dioxide model-observation differences

Reducing uncertainties in regional carbon balances requires a better understanding of CO 2 transport in synoptic weather systems. Here, we apply the Patient Rule Induction Method (PRIM), a data-mining method to identify high-density regions for a target-class within an input parameter space, to airborne observations of potential temperature, wind speed, water vapor mixing ratio, and CO 2 dry mol fraction gathered during the Atmospheric Carbon and Transport (ACT)-America Summer 2016 and Winter 2017 campaigns. ACT observations were targeted at expert-designated cases of fair weather and near-frontal warm and cold sector air at atmospheric boundary-layer, lower-, and higher free tropospheric levels (ABL, LFT, and HFT, respectively). We investigate atmospheric characteristics of these pre-defined cases and associated CO 2 model-observation-differences in the mesoscale WRF-Chem model. PRIM results separate winter- and summertime observations as well as observations from ABL, LFT, and HFT with enrichment factors of 4.0–20.5 inside the PRIM box compared to the entire dataset but cannot distinguish between near-frontal warm and cold sector observations in the higher free troposphere. Analyzing of the parameter space constrained by PRIM, we find that large magnitude model observation differences preferentially associated with times when atmospheric conditions are less typical. This association suggests that PRIM could provide a useful tool for isolating atmospheric conditions with large-magnitude and non-Gaussian CO 2 -residuals for targeted transport model evaluation and to potentially improve inversion results during synoptically active periods.

Gerken, Tobias [James Madison Univ., Harrisonburg,↗

DOE OSTI2026

Seasonal Precipitation Classification during Surface Atmosphere Integrated Field Laboratory Campaign

The Surface Atmosphere Integrated Field Laboratory (SAIL) campaign, conducted from September 2021 to June 2023 in Crested Butte, Colorado, aimed to characterize precipitation processes in the Upper Colorado River Basin (UCRB). This increased observations of snowfall accumulation in this hydrologically significant watershed would be useful for quantitative precipitation estimates (QPE). Therefore, the Surface Quantitative Precipitation Estimate (SQUIRE) product was developed using the ARM-supported Colorado State University (CSU) X-band Precipitation Radar. Although SQUIRE will be only released for snowfall, by categorizing precipitation types, users can effectively utilize relevant datasets under diverse meteorological conditions. Moreover, the dataset facilitates validation of the QPE product and the analysis of seasonal variations in precipitation types at the surface. Hydrometeors classes are organized based on their phase and physical characteristics mapping the CSU (both winter Summer) and Py-ART classifications into four groups. 1. Liquid Precipitation: includs drizzle, rain, and large raindrops. 2. Frozen Snow and Ice : Pure Snow, combining ice crystals, aggregates, and vertically oriented ice structures. 3. Dense and Large frozen hydrometeors: including low- and high-density graupel and dry hail. 4.Melting: Wet Snow and Melting Hail, hydrometeors exhibiting both liquid and frozen characteristics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Exploring the QCD Phase Diagram

Exploring the QCD phase diagram through relativistic heavy-ion collisions is a primary goal of modern nuclear physics. This contribution focuses on fluctuations and correlations of conserved charges — specifically net-baryon and net-charge cumulants — as sensitive probes of the phase structure and the QCD critical point. We discuss recent theoretical and experimental advancements, highlighting constraints from lattice QCD and new results from the RHIC Beam Energy Scan program. Key challenges in theory-to-experiment comparisons at high baryon density are discussed, alongside the systematic requirements for meaningful physical interpretation. Finally, we identify open issues and outline the discovery potential of future low-energy experiments, such as CBM, in resolving the high-density regime of the phase diagram.

Koch, V. [Lawrence Berkeley National Laboratory (L↗

DOE OSTI2025

Measurement of the Neutron Electromagnetic Form Factors at High Momentum Transfer Using a Polarized 3He Target at Jefferson Lab

Ever since the composite structure of nucleons was uncovered, many experiments have been commissioned with the purpose of extracting parameters that shape our understanding of this structure. Form factors are powerful tools that rest at the forefront of the nucleon structure study. In the non-relativistic limit, they describe the magnetic and charge distributions inside the nucleon. The GEn-II experiment, which ran in Hall A of Jefferson Lab as a part of the SuperBigbite Spectrometer (SBS) program, aimed to extract the ratio of the neutron’s electric to magnetic Sachs form factors (GnE/GnM. This was accomplished using the double polarization technique: scattering polarized electrons with initial energies up to 8.45 GeV off high-density polarized 3He targets. The experiment was a coincidence measurement, with the scattered electrons detected in the BigBite Spectrometer and the recoil nucleons in a hadron calorimeter, a part of the SuperBigbite Spectrometer. The convection-style target cells used in this experiment have a 60cm long target chamber, an increase from the 40 cm cell used in the most recent polarized 3He target experiment. In addition, the cells were optically pumped from two sides of the pumping chamber. These improvements in design and functionality introduced world-record-breaking luminosity. This thesis presents preliminary results of the GEn-II experiment for the following 4-momentum transfer (Q2) values: 2.93, 6.76, and 9.78 GeV2, in addition to target performance and preliminary polarimetry results.

Presley, Hunter [Univ. of Virginia, Charlottesvill↗

DOE OSTI2025

Developing New Fuels for High Performance Research Reactors

The National Nuclear Security Administration (NNSA) Material Management and Minimization (M3) program works globally to minimize the civilian use of highly enriched uranium (HEU), a weapon-usable nuclear material. Supporting this effort, M3’s Office of Reactor Conversion and Uranium Supply is developing new fuels capable of converting research reactors from HEU fuel to high-assay low-enriched uranium (HALEU) fuel. Some of the remaining research and test reactors (RTRs) operating on HEU today have unique designs, fuel configurations, and demanding performance requirements that cannot be met with an existing regulatory-approved low-enriched uranium (LEU) fuel. M3, DOE’s national laboratories, and other industry partners are qualifying new high-density LEU fuels to convert these RTRs while maintaining their unique capabilities supporting a wide variety of science and technology research in areas such as medicine, industry, defense, education, and training. Current efforts are focused on two options for the remaining US high-performance research reactor conversions: a monolithic uranium 10wt% molybdenum (U-10Mo) fuel form and a dispersion uranium silicide fuel form. This paper reviews the history and status of M3’s fuel qualification efforts for the U-10Mo LEU fuel form.

Montgomery, Rose [ORNL] (ORCID:0000000286038936)↗

DOE OSTI2025

LC-Opt: Benchmarking Reinforcement Learning and Agentic AI for End-to-End Liquid Cooling Optimization in Data Centers

Liquid cooling is critical for thermal management in high-density data centers with the rising AI workloads. However, machine learning-based controllers are essential to unlock greater energy efficiency and reliability, promoting sustainability. We present LC-Opt, a Sustainable Liquid Cooling (LC) benchmark environment, for reinforcement learning (RL) control strategies in energy-efficient liquid cooling of high-performance computing (HPC) systems. Built on the baseline of a high-fidelity digital twin of Oak Ridge National Lab's Frontier Supercomputer cooling system, LC-Opt provides detailed Modelica-based end-to-end models spanning site-level cooling towers to data center cabinets and server blade groups. RL agents optimize critical thermal controls like liquid supply temperature, flow rate, and granular valve actuation at the IT cabinet level, as well as cooling tower (CT) setpoints through a Gymnasium interface, with dynamic changes in workloads. This environment creates a multi-objective real-time optimization challenge balancing local thermal regulation and global energy efficiency, and also supports additional components like a heat recovery unit (HRU). We benchmark centralized and decentralized multi-agent RL approaches, demonstrate policy distillation into decision and regression trees for interpretable control, and explore LLM-based methods that explain control actions in natural language through an agentic mesh architecture designed to foster user trust and simplify system management. LC-Opt democratizes access to detailed, customizable liquid cooling models, enabling the ML community, operators, and vendors to develop sustainable data center liquid cooling control solutions.

Naug, Avisek [Hewlett Packard Enterprise]↗

DOE OSTI2026

Study of Epoxy Sealant Layer for Use in Tank Bottom Refurbishment for the DOE EM Tank Waste R&D Program

This study addresses the DOE National Laboratory Program on Hanford Tank Waste Cleanup Research and Development, focusing on tank waste retrieval, transport, and closure. Millions of gallons of high-level waste are stored in the double shell tanks (DSTs) at Hanford site. The waste is stored in the primary tank, while the secondary shell acts as a buffer between the primary tank and environment. The DSTs’ bottoms could be corroded due to the corrosive waste properties and contents. Therefore, they are being emptied, and refurbishment is needed before waste storage continues. SRNL addresses the refurbishment of still operational DSTs bottoms with a two-layer refurbishment approach. We propose that the bottom layer consists of a high-density cementitious material to shield the epoxy top layer from radioactive residuals, while the top layer serves as an epoxy sealant. This work focuses on the experimental evaluation on the formulation and testing of the epoxy layer.

Blue, Kareen [Savannah River National Laboratory (↗

DOE OSTI2026

Integrating Cybersecurity Risk Assessment with Process Safety in Chemical Process Industries

This dissertation bridges the gap between industrial cybersecurity and traditional process safety by introducing an integrated Cyber-LOPA framework that combines the Purdue Enterprise Reference Architecture, Cyber Kill Chain, and CVSS v4.0 metrics. Demonstrated on a High-Density Polyethylene slurry process, the work illustrates how cyber threats targeting automation systems can bypass physical protection layers, proving the necessity of unified risk assessments to prevent cyber-induced physical incidents in chemical manufacturing plants.

Cyber-LOPA (CLOPA)↗

DOE OSTI2026

A Physics-Informed Reinforcement Learning Framework for Economic-Thermal Co-Optimization of Crypto Mining Data Centers: Preprint

The rapid expansion of cryptocurrency mining has created a new class of high-density data centers characterized by extreme thermal flux and high sensitivity to volatile economic markets. Traditional thermal management strategies, typically reliant on rule-based control, maintain static setpoints that fail to account for fluctuating electricity prices and cryptocurrency values - factors critical to mining profitability. To address this, we present a physics-informed reinforcement learning (PIRL) framework for economic-thermal co-optimization in crypto mining data centers. This framework consists of a proximal policy optimization (PPO) agent, a virtual testbed powered by high-fidelity physics-based models, and an interactive frontend dashboard. The PPO agent is trained using the virtual testbed and strict hardware safety limits. This physics-informed approach allows the agent to learn a stochastic policy that dynamically balances mining revenue against operational costs by co-optimizing HVAC cooling setpoints and IT computational hashrate. The simulation results demonstrate that the integrated framework achieved an 8.62% increase in net operational profit compared to traditional baseline strategies while strictly adhering to safety-critical temperature constraints (coolant supply temperature < 32 degrees C). This work provides a scalable template for the deployment of reinforcement learning in mission critical facilities where economic volatility and physical safety must be managed simultaneously.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Implosion simulations and optimum times of radiographic Images in OMEGA high-density-carbon cylinder experiments

The Los Alamos Ignition Threshold team is planning direct-drive cylinder implosion experiments (CylDRT24B) at the OMEGA laser, scheduled for Thursday 23 May 2024, to investigate the effect of granular microstructure in high density carbon (HDC) shells. Granular microstructure is believed to play a crucial role in seeding perturbations, reducing compression, and enhancing mix in the implosion of HDC shells at the National Ignition Facility (NIF). But the ICF community lacks a detailed understanding of how grains induce these effects, owing partly to the practical difficulty of numerically simulating the behavior of tiny nanometer-scale granular structures in laboratory-scale experiments. Our planned experiments are aimed at acquiring data to help constrain simulations and calibrate reduced models.

36 MATERIALS SCIENCE↗

DOE OSTI2024

TEX-Hf Assemblies: Highly Enriched Uranium Plates with Hafnium Using Polyethylene Moderator and Polyethylene Reflector

This report documents the integral experiment evaluation and publication for IER-532 (TEX-Hf), Thermal/Epithermal eXperiments (TEX) with highly enriched uranium (HEU) fuel and hafnium (Hf), moderated and reflected by polyethylene. The design of TEX-Hf is a variation of IER-297 (TEX-HEU), with the inclusion of hafnium as a diluent material. The experiment and evaluation include seven configurations, all of which were acceptable as benchmark cases. These benchmark cases provide validation for hafnium in the thermal, intermediate, and fast neutron energy regimes by maximizing the sensitivity in k eff to the hafnium cross sections. The evaluation was reviewed and accepted by the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Technical Review Group on April 17, 2024, and was submitted to the ICSBEP in August 2024 following subgroup approval.

42 ENGINEERING↗