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DOE OSTI2024

A functional microbiome catalogue crowdsourced from North American rivers

Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires knowledge of the spatial drivers of river microbiomes. However, understanding of the core microbial processes governing river biogeochemistry is hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we used a community science effort to accelerate the sampling, sequencing and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). GROWdb profiles the identity, distribution, function and expression of microbial genomes across river surface waters covering 90% of United States watersheds. Specifically, GROWdb encompasses microbial lineages from 27 phyla, including novel members from 10 families and 128 genera, and defines the core river microbiome at the genome level. GROWdb analyses coupled to extensive geospatial information reveals local and regional drivers of microbial community structuring, while also presenting foundational hypotheses about ecosystem function. Building on the previously conceived River Continuum Concept, we layer on microbial functional trait expression, which suggests that the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures, so that it can be widely accessed across disciplines for watershed predictive modelling and microbiome-based management practices.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Using Community Science to Reveal the Global Chemogeography of River Metabolomes

River corridor metabolomes reflect organic matter (OM) processing that drives aquatic biogeochemical cycles. Recent work highlights the power of ultrahigh-resolution mass spectrometry for understanding metabolome composition and river corridor metabolism. However, there have been no studies on the global chemogeography of surface water and sediment metabolomes using ultrahigh-resolution techniques. Here, we describe a community science effort from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium to characterize global metabolomes in surface water and sediment that span multiple stream orders and biomes. We describe the distribution of key aspects of metabolomes including elemental groups, chemical classes, indices, and inferred biochemical transformations. We show that metabolomes significantly differ across surface water and sediment and that surface water metabolomes are more rich and variable. We also use inferred biochemical transformations to identify core metabolic processes shared among surface water and sediment. Finally, we observe significant spatial variation in sediment metabolites between rivers in the eastern and western portions of the contiguous United States. Our work not only provides a basis for understanding global patterns in river corridor biogeochemical cycles but also demonstrates that community science endeavors can enable global research projects that are unfeasible with traditional research models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Effect of ATF Cr-coated-Zircaloy on BWR In-vessel Accident Progression during a Station Blackout

The deposition of protective coatings on nuclear fuel cladding has been considered as a near-term Accident Tolerant Fuel (ATF) concept that will reduce the high-temperature oxidation rate and enhance accident tolerance of the cladding while providing additional benefits during normal and transient. In this study, the performance of the proposed ATF concept of Cr-coated-Zircaloy is assessed using a generic Boiling Water Reactor MELCOR plant model considering a Short-term Station Blackout (STSBO) scenario. Simulation results indicate that the use of Cr-coated-Zircaloy as cladding and canister material mitigates the core degradation process as compared to the traditional Zircaloy cladding and canister design. The onset of fuel degradation and collapse is delayed by over thirty minutes, and the extent of fuel degradation is reduced. Specifically, the gross in-vessel hydrogen generation decreased by almost a factor of three. Although the eutectic reaction between Cr-coating and Zircaloy could cause an early failure of the coating, the improvement in the delay of fuel degradation is still notable. In addition, a thicker coating is found helpful to obtain additional coping time and to decrease hydrogen generation. In addition to the eutectic formation that may compromise Cr-coated Zr, a different failure mode is identified for the Cr-coated-Zr when compared to Zircaloy; i.e., a complete melt of base material leads to component collapse before the coating is oxidized and consumed. These findings can help the industry focus on productive areas of research and development for accident-tolerant fuel concepts and enhancement of core safety margins.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Material Interactions in Severe Accidents – Benchmarking the MELCOR V2.2 Eutectics Model for a BWR-3 Mark-I Station Blackout: Part II – Uncertainty Analysis

Single case comparisons between severe accident simulations can provide detailed insights into severe accident model behavior, however, they cannot offer insights into model uncertainty, sensitivity to uncertain parameters, or underlying model biases.Here in this analysis, the single case benchmark comparison of the MELCOR material interaction models for a station blackout (SBO) scenario of a boiling water reactor (BWR) using representative Fukushima Daiichi Unit 1 boundary conditions is expanded to include an uncertainty analysis. As part of this uncertainty analysis, 1200 simulations are performed for each material interaction model (2400 total), with random sampling of 14 uncertain MELCOR input parameters. Input parameters are selected for their impact on models representing core degradation processes. These include candling, fuel rod failure, debris quenching and dryout. The analysis performed here is not a traditional “best-estimate” uncertainty analysis that uses best-estimate parameters or identifies best-estimate figure of merit distributions. Instead, it is an exploratory uncertainty analysis that identifies and interrogates underlying model form biases of the two material interaction models (eutectics and interactive materials models). Uniform distributions are applied to all uncertain parameters to ensure coverage of the model parameter uncertainty space. Key findings from this study include underlying model form biases exhibited by material interaction models, and notable differences in accident progression outcomes between the material interaction models. This uncertainty study extends and confirms the conclusions from the first part of this study, which compared the impact of material interaction modeling on simulation of a short-term station blackout scenario with representative Fukushima Daiichi Unit I boundary conditions. In particular, this study confirms that the eutectics model generally exhibits accelerated degradation and failure of fuel components, the core plate, and the lower head. The eutectics model also has a tendency to exhibit a greater degree of core degradation, greater debris mass formation, and larger debris mass ejection. Finally, the eutectics model exhibits higher maximum temperatures for fuel, cladding, particulate debris, oxidic molten pool, and metallic molten pool components than the interactive materials model; interactive materials model simulations exhibit a soft “limitation” on maximum temperatures that is related to the temperature at which material relocation occurs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Equity and modeling in sustainability science: Examples and opportunities throughout the process

Equity is core to sustainability, but current interventions to enhance sustainability often fall short in adequately addressing this linkage. Models are important tools for informing action, and their development and use present opportunities to center equity in process and outcomes. This Perspective highlights progress in integrating equity into systems modeling in sustainability science, as well as key challenges, tensions, and future directions. We present a conceptual framework for equity in systems modeling, focused on its distributional, procedural, and recognitional dimensions. We discuss examples of how modelers engage with these different dimensions throughout the modeling process and from across a range of modeling approaches and topics, including water resources, energy systems, air quality, and conservation. Synthesizing across these examples, we identify significant advances in enhancing procedural and recognitional equity by reframing models as tools to explore pluralism in worldviews and knowledge systems; enabling models to better represent distributional inequity through new computational techniques and data sources; investigating the dynamics that can drive inequities by linking different modeling approaches; and developing more nuanced metrics for assessing equity outcomes. We also identify important future directions, such as an increased focus on using models to identify pathways to transform underlying conditions that lead to inequities and move toward desired futures. By looking at examples across the diverse fields within sustainability science, we argue that there are valuable opportunities for mutual learning on how to use models more effectively as tools to support sustainable and equitable futures.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Climate Change Impacts on the South American Monsoon System and Its Surface–Atmosphere Processes Through RegCM4 CORDEX-CORE Projections

Here, we evaluate projected changes in surface water and energy balances and surface–atmosphere coupling in the South American Monsoon System (SAMS) for the end of the century (2080–2099). The analyses are based on two ensemble datasets, which follow Representative Concentration Pathway 8.5 in the future period, and cover four subdomains (Northern and Southern—NAMZ and SAMZ—Amazon, La Plata Basin—LPB, and Southern Southeast Brazil—SSB). One ensemble consists of three Global Climate Models (HadGEM2-ES, MPI-ESM-MR and NorESM1-M), while the other consists of their dynamically downscaled version at 25 km horizontal grid spacing using Regional Climate Model version 4 (RegCM4). As both ensembles are able in reproducing the annual cycle of the components of the surface water and energy balances in the present climate, they can be used in the study of future climate. During the wet season (November–March), both ensembles project a decrease in precipitation over NAMZ and SAMZ (an exception is RegCM4 that projects a slight increase in SAMZ), and an increase across the LPB and SSB. These changes do not cause retreat or expansion of the monsoon area over the continent, which is similar to the present climate (1995–2014). For the wet season, the ensembles are in line with the presence of a strong surface–atmosphere coupling in LPB and SSB, weak coupling in SAMZ and very weak coupling in NAMZ. For future climate, the coupling is even weaker in NAMZ, which may be a driver for the negative changes in precipitation. For the other subdomains, while the ensembles project similar signals of precipitation changes, they disagree with the surface-atmosphere coupling highlighting the uncertainties in future climate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Portable chemical detection platform for on-site monitoring of odorant levels in natural gas

The adequate odorization of natural gas is critical to identify gas leaks and to reduce accidents. To ensure odorization, natural gas utility companies collect samples to be processed at core facilities or a trained human technician smells a diluted natural gas sample. In this work, we report a detection platform that addresses the lack of mobile solutions capable of providing quantitative analysis of mercaptans, a class of compounds used to odorize natural gas. Detailed description of the platform hardware and software components is provided. Designed to be portable, the platform hardware facilitates extraction of mercaptans from natural gas, separation of individual mercaptan species, and quantification of odorant concentration, with results reported at point-of-sampling. The software was developed to accommodate skilled users as well as minimally trained operators. Detection and quantification of six commonly used mercaptan compounds (ethyl mercaptan, dimethyl sulfide, n-propylmercaptan, isopropyl mercaptan, tert–butyl mercaptan, and tetrahydrothiophene) at typical odorizing concentrations of 0.1–5 ppm was performed using the device. We demonstrate the potential of this technology to ensure natural gas odorizing concentrations throughout distribution systems.

03 NATURAL GAS↗

DOE OSTI2023

Residual estimation for grid modification in wall-modeled large eddy simulation using unstructured high-order methods

Here, the accuracy and computational cost of a large eddy simulation are highly dependent on the computational grid. Building optimal grids manually from a priori knowledge is not feasible in most practical use cases; instead, solution-adaptive strategies can provide a robust and cost-efficient method to generate a grid with the desired accuracy. We adapt the residual estimation algorithm developed by Toosi and Larsson for Discontinuous Galerkin Spectral Elements Methods (DGSEM) to guide the grid-adaptation process. The core of the method is the computation of the estimated modeling residual using the polynomial basis functions used in DGSEM, and the averaging of the estimated residual over each element. The final method is assessed in multiple channel flow test cases and for the transonic flow over an airfoil, in both cases making use of mortar interfaces between elements with hanging nodes. The method is found to be robust and reliable, and to provide solutions on grids with significantly fewer elements at comparable accuracy compared to when using human-generated grids.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

ON-OFF neuromorphic ISING machines using Fowler-Nordheim annealers

We introduce NeuroSA, a neuromorphic architecture specifically designed to ensure asymptotic convergence to the ground state of an Ising problem using a Fowler-Nordheim quantum mechanical tunneling based threshold-annealing process. The core component of NeuroSA consists of a pair of asynchronous ON-OFF neurons, which effectively map classical simulated annealing dynamics onto a network of integrate-and-fire neurons. The threshold of each ON-OFF neuron pair is adaptively adjusted by an FN annealer and the resulting spiking dynamics replicates the optimal escape mechanism and convergence of SA, particularly at low-temperatures. To validate the effectiveness of our neuromorphic Ising machine, we systematically solved benchmark combinatorial optimization problems such as MAX-CUT and Max Independent Set. Across multiple runs, NeuroSA consistently generates distribution of solutions that are concentrated around the state-of-the-art results (within 99%) or surpass the current state-of-the-art solutions for Max Independent Set benchmarks. Furthermore, NeuroSA is able to achieve these superior distributions without any graph-specific hyperparameter tuning. For practical illustration, we present results from an implementation of NeuroSA on the SpiNNaker2 platform, highlighting the feasibility of mapping our proposed architecture onto a standard neuromorphic accelerator platform.

42 ENGINEERING↗

DOE OSTI2026

Dynamic strength of iron under pressure-temperature conditions of Earth’s inner core

Iron (Fe) is a primary constituent of terrestrial planetary cores, yet its rheological properties under extreme conditions remain uncertain. Here we present direct measurements of Fe strength at 310-430 GPa pressures and 3700-5800 K temperatures, obtained using Rayleigh-Taylor (RT) instability experiments at the National Ignition Facility. Single-crystal α-Fe samples with [001] and [111] orientations are shock-ramp compressed past the α-ε transition along paths approaching Earth’s inner core conditions. We find that ε-Fe derived from [001] α-Fe is consistently stronger (11-20 GPa) than that from [111] α-Fe (8-18 GPa), contrary to the trend at ambient conditions. Large-scale molecular dynamics simulations reproduce this atypical strength anisotropy and attribute it to microstructural evolution during the phase transition and subsequent ε-phase plasticity. Ripple growth analysis further constrains viscosities of 100-170 Pa·s under the driven conditions. Our results provide experimental benchmarks for Fe rheology at inner-core conditions, with implications for seismic anisotropy and the geodynamo.

Condensed-matter physics↗

DOE OSTI2020

Towards single-species selectivity of membranes with subnanometre pores

Synthetic membranes with pores at the subnanometre scale are at the core of processes for separating solutes from water, such as water purification and desalination. While these membrane processes have achieved substantial industrial success, the capability of state-of-the-art membranes to selectively separate a single solute from a mixture of solutes is limited. Such high-precision separation would enable fit-for-purpose treatment, improving the sustainability of current water-treatment processes and opening doors for new applications of membrane technologies. In this paper, we introduce the challenges of state-of-the-art membranes with subnanometre pores to achieve high selectivity between solutes. Here, we then analyse experimental and theoretical literature to discuss the molecular-level mechanisms that contribute to energy barriers for solute transport through subnanometre pores. We conclude by providing principles and guidelines for designing next-generation single-species selective membranes that are inspired by ion-selective biological channels.

42 ENGINEERING↗

DOE OSTI2025

The structure of liquid carbon elucidated by in situ X-ray diffraction

Carbon has a central role in biology and organic chemistry, and its solid allotropes provide the basis of much of our modern technology. However, the liquid form of carbon remains nearly uncharted, and the structure of liquid carbon and most of its physical properties are essentially unknown. But liquid carbon is relevant for modelling planetary interiors and the atmospheres of white dwarfs, as an intermediate state for the synthesis of advanced carbon materials, inertial confinement fusion implosions, hypervelocity impact events on carbon materials and our general understanding of structured fluids at extreme conditions. Here we present a precise structure measurement of liquid carbon at pressures of around 1 million atmospheres obtained by in situ X-ray diffraction at an X-ray free-electron laser. Our results show a complex fluid with transient bonding and approximately four nearest neighbours on average, in agreement with quantum molecular dynamics simulations. The obtained data substantiate the understanding of the liquid state of one of the most abundant elements in the universe and can test models of the melting line. The demonstrated experimental abilities open the path to performing similar studies of the structure of liquids composed of light elements at extreme conditions.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

Tunable x-ray free electron laser multi-pulses with nanosecond separation

X-ray Free Electron Lasers provide femtosecond x-ray pulses with narrow bandwidth and unprecedented peak brightness. Special modes of operation have been developed to deliver double pulses for x-ray pump, x-ray probe experiments. However, the longest delay between the two pulses achieved with existing single bucket methods is less than 1 picosecond, thus preventing the exploration of longer time-scale dynamics. We present a novel two-bucket scheme covering delays from 350 picoseconds to hundreds of nanoseconds in discrete steps of 350 picoseconds. Performance for each pulse can be similar to the one in a single pulse operation. The method has been experimentally tested with the Linac Coherent Light Source (LCLS-I) and the copper linac with LCLS-II hard x-ray undulators.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Protecting scientific integrity in an age of generative AI

Revolutionary advances in AI have brought us to a transformative moment for science. AI is accelerating scientific discoveries and analyses. At the same time, its tools and processes challenge core norms and values in the conduct of science, including accountability, transparency, replicability, and human responsibility (1–3). These difficulties are particularly apparent in recent advances with generative AI. Future innovations with AI may mitigate some of these or raise new concerns and challenges.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Future Industrial Demand: Large, Elastic, and Concentrated [Guest Editorial]

Here, the future industrial demand on the grid is expected to be large, price sensitive, and concentrated. Grid industrial demand increasingly encompasses a new customer type defined as a large flexible load (LFL). This LFL type defines customers with consumption that responds quickly to price or other incentives without interrupting their core business process, such cryptocurrency mining. This customer type can often ramp up and down quickly, which across an entire industry can mean gigawatts of power within a few minutes. In addition to these price-sensitive loads, significant growth is also anticipated in sectors like manufacturing, data centers, and electrification of transportation and buildings.

Mukherjee, Srijib [Oak Ridge National Laboratory (↗

DOE OSTI2025

High-Performance Computing Based EMT Simulation: Power Grid with IBRs

Electromagnetic transient (EMT) simulation of power grids with high-fidelity models of inverter-based resources (IBRs) is time-consuming and difficult to scale. The necessity for high-fidelity models of IBRs that incorporate the dynamics of individual inverters within IBRs has been showcased in recent studies. These studies focused on events with partial power reduction in each IBR during a transmission line fault in the power grid. These types of events have been documented in multiple North American Electric Reliability Council (NERC) reports in the past decade. It is imperative then to find solutions to speed-up EMT simulations and scale the size of the region with IBRs studied in EMT simulations. In this paper, a combination of numerical simulation algorithms with high-performance computing techniques are employed in discretization and linear solvers employed in the proposed RE-INTEGRATE EMT simulation platform for power grid with IBRs. For ease of scalability, modular and object-oriented programming is used as these techniques are implemented. Additionally, automation software is developed to convert legacy software codes to the proposed RE-INTEGRATE EMT simulation platform. Thereafter, this platform is evaluated on multi-core central processing units (CPUs). Finally, scale-up tests are performed to showcase the scalability that is possible.

Marthi, Phani Ratna Vanamali [ORNL] (ORCID:0000000↗

DOE OSTI2023

COWALKER:EFFECTIVE TRANSPORT PROPERTIES OF COMPOSITE MATERIALS

SF-23-026 This software computes effective transport properties of composite materials involving fibers and nanoparticles using a random-walk algorithm that efficiently scales to an arbitrary number of processes and cores. Effective transport properties (thermal, electrical) are key to bridge the microstructure of complex materials with its macroscopic behavior. Traditional approaches either use effective medium approximations (closed mathematical expressions that are approximation for certain conditions) or continuum simulation models such as finite element or finite volume, which require the generation of a mesh for each configuration explored. cowalker leverages the equivalence between laplacian or heat equation-based models and random walks to compute the asymptotic transport properties from an ensemble of first sojourn times of a random walker moving through the composite material. This allows us to directly define a composite material as a collection of particles and use algorithms developed for molecular dynamics to quickly compute the intersection of the walker with the different interfaces in the material. cowalker is developed in C++, and it relies on the GNU Scientific Library for random generation. cowalker is currently delivered as source code, so the GSL library is not included in cowalker's distribution. A more userfriendly version, cowalker.jl is currently in development and will be released as part of cowalker.

YANGUAS-GIL, ANGEL↗

DOE OSTI2025

Plant Reload Optimization (prlo)

The PRLO framework is built on a modular and extensible architecture that tightly couples advanced evolutionary optimization algorithms with nuclear fuel depletion solvers (i.e., nuclear physics neutronics code). It supports exploring complex, high-dimensional design spaces constrained by user-specified operational, safety, and economic constraints. Objectives such as minimizing fresh fuel enrichment, flattening radial and axial power distributions, and maximizing discharge burnup are evaluated. PRLO’s equilibrium cycle optimization capability enables the identification of core configurations that maintain fuel cycle sustainability over extended planning horizons. Its integration with the RAVEN platform facilitates optimization of loading patterns or fuel shuffling schemes across multiple cycles. The interface with SIMULATE, a licensed industry-standard nodal code developed by Studsvik, ensures accurate neutronic and thermal-hydraulic feedback for reactor core design. PRLO’s automated workflow engine supports iterative design refinement, enabling utilities to streamline core design processes and meet evolving performance and regulatory targets.

Kim, Junyung [Idaho National Laboratory] (00090005↗