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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Workshop on Improving Holdup Monitoring in the US

The characterization and quantification of nuclear deposits, or residual nuclear material retained in process equipment, generally referred to as holdup, continues to challenge nuclear processing facilities in DOE program areas such as nuclear criticality safety, material control and accountability, environmental management. The efficiency and effectiveness of nuclear operations in these facilities depends heavily on the results from nondestructive techniques designed to measure nuclear materials in situ. The traditional methods used to measure holdup were established more than 30 years ago and assume unrealistic conditions for most measurement cases. These blind, in situ measurements present unique challenges due to the following attributes: unique, non-ideal geometries; unknown deposit thicknesses; lack of representative calibration standards; large number of holdup deposit locations; and poor accessibility for many measurement locations. These difficulties and the poor assumptions made to handle them have resulted in measurement uncertainties that are often too large for many programs to effectively utilize. In an effort to address and identify solutions to the current holdup challenges facing the US nuclear industry, Oak Ridge National Laboratory hosted the Technical Workshop on Improving Holdup Monitoring in the US. The two-day workshop held August 21–22, 2019, was attended by 35 holdup measurement practitioners, program managers, stakeholders from US Department of Energy sites, the Nuclear Regulatory Commission, and representatives from commercial industry. The primary objectives were to identify critical elements of a successful and defensible holdup measurement program; identify technical challenges, needs, and potential improvements associated with measurement of holdup; and share best practices and lessons learned from recent accumulation events. Fourteen presentations were delivered on holdup topics including necessary elements for effective program management, measurement needs, emerging technologies and other measurement solutions, and lessons learned from recent events. These presentations highlighted best practices related to accumulation monitoring, considerations and proactive steps to facilitate holdup in new facility designs, imaging solutions to improve holdup assumptions, and new software developed in support of holdup measurements. Breakout sessions were also employed to determine additional needs and identify potential solutions to common holdup challenges. The primary discussions focused on causes and prevention of material accumulations, needs for uranium and plutonium measurements, and reduction of measurement uncertainty, all of which were explicitly identified as critical needs during the 2018 Workshop on Technical and Programmatic Needs for a Sustainable NDA Program for the US DOE.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Resilient GaN-based Power Module with Improved Diagnostic for Future Accelerator

Los Alamos Neutron Science Center (LANSCE) and Dual-Axis Radiographic Hydrodynamic Test facility (DARHT) play a pivotal role in advancing scientific research and national security initiatives. As a premier facility for neutron science, LANSCE and DARHT provide invaluable insights into fundamental research, materials science, nuclear physics, high-energy physics, material science, and medical imaging. Existing (DC) power supply and pulse modulation technologies used in LANSCE and DARHT face limitations in terms of reliability, maintainability, and diagnostics which hinder the progress of these cutting-edge facilities. By proposing improvements to LANL accelerator facilities’ performance and addressing component failure, we aim to enhance scientific outcomes and minimize disruptions, allowing for more efficient and productive research activities while ensuring the continuity of valuable contributions to the user community. This proposal aims to revolutionize (DC) power supply and pulse power systems for future particle accelerators via the development of a resilient GaN-based power module with improved diagnostic and redundant submodules.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Degradable Biocomposite Thermoplastic Polyurethanes

In this project, the team developed tough and degradable biocomposite thermoplastic polyurethanes (TPUs) by incorporating bacterial spores into TPUs as a biofunctional living filler. The team screened various bacteria and selected the Bacillus subtilis ATCC 6633 strain as the final candidate, primarily due to its genomic availability, sporulation ability and TPU assimilation activity. The heat-shock tolerance of ATCC 6633 spores was further improved through evolutionary engineering via Adaptive Laboratory Evolution (ALE), demonstrating a 17.7-fold enhanced germination efficiency post heat-shock treatment compared to the wild-type strain (WT). The team fabricated biocomposite TPUs by incorporating lyophilized powder of heat-shock tolerized (HST) spores during the hot melt extrusion (HME) of TPU at 135 °C. The baseline TPU used in this project is a commercially available soft-grade TPU (BCF45) manufactured by BASF. Colony forming unit (CFU) assays quantified that WT and HST spores in the TPU matrix retained approximately 20% and 100% survivability, respectively, after HME. Tensile testing demonstrated that the spores behaved as a polymer-reinforcing filler, positively affecting the overall tensile properties of the biocomposite TPU. For example, biocomposite TPU with WT and HST spores (BC TPU WT and BC TPU HST , respectively) exhibited up to 25% and 37% improved toughness, respectively, compared to TPU without spores. BC TPU HST showed remarkably improved disintegration in autoclaved compost (92% mass loss in 5 months), which simulated a microbially poor environment for TPU degradation. When compared to TPU without spores (44% mass loss in 5 months) the acceleration of degradation is marked. Respirometry confirmed that 72% of BC TPU HST was biomineralized into CO2 within 6 months, indicating that spores in the biocomposite TPU were germinated by utilizing nutrients in the autoclaved compost, facilitating TPU degradation at the end of the material's life. The team demonstrated the scale-up of biocomposite TPU fabrication using continuous extrusion and injection molding techniques. Processing conditions optimized in a lab-scale microcompounder were successfully transferred to a continuous extruder with a 30-fold increased throughput. Biocomposite TPUs prepared using these industry-relevant processes showed comparable toughness improvements to samples prepared in the lab-scale extruder. Excitingly, following compounding in the pilot-extruder the composite material could be injection molded, while retaining high spore viability and similar toughness improvements. The team also found that spores in biocomposite TPU served as antioxidants, preventing toughness decay during the recycled extrusion of BC TPU HST . Long-term storage tests over one year showed that the addition of spores had no negative effect on the longevity of the TPU. Furthermore, the team demonstrated the fabrication of spore-bearing biocomposite polymers with other polyesters such as PBAT, PLA, and PCL. We obtained promising preliminary data that showed overall toughness improvements for all polymers with spore addition. Finally, life cycle assessment (LCA) and techno-economic analysis (TEA) were carried out, which indicated minimal additional cost of fabrication. Overall, a tough and degradable biocomposite thermoplastic was successfully developed through this project, with all tasks completed successfully, achieving >100% of the objectives.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Study on Emulsification/Demulsification Behavior and Mechanism of Produced Liquid from Polymer Flooding on Alaska North Slope

Heavy oil reservoirs on Alaska North Slope (ANS) are unconsolidated and contain abundant clay minerals, where the first-ever field pilot is currently implemented to validate the use of polymer floods for heavy oil enhanced oil recovery (EOR). The polymer molecules and/or fine clay particles carried with the produced liquid could potentially affect the oil/water separation, which is one of the major concerns for field operators. This dissertation aims to investigate the emulsification behavior of produced liquid, understand the emulsifying mechanism, and seek an adaptive and cost-effective method to treat the produced liquid from polymer flooding. Emulsions were prepared by mechanically mixing the actual heavy oil and the produced water from the pilot site, of which the stability was investigated by bottle test method or multiple light scattering method. Drop size distribution and interfacial properties were measured via microscope and pendant drop technique to probe the stability mechanism further. Results showed that oil-continuous or water-continuous emulsion could be generated depending on the water cut, clay types, clay concentration, and polymer concentration. In the crude oil/water system, the increasing water cut triggered the phase inversion of oil-continuous emulsion to water-continuous emulsion, resulting in faster separation and lower emulsion stability. Whereas, clay particles, no matter added to the oil or water phase, resulted in an unfavorable phase inversion from the loose water-continuous emulsion to the tight oil-continuous emulsion as clay concentration increased. For all four types of clay except Ca-montmorillonite, clay particles added to water led to an earlier phase inversion and higher emulsion stability than that added to the oil. The dual function of polymer on emulsion stability was observed. On the one hand, both sheared and unsheared polymer tended to convert the oil-continuous emulsion formed in either crude oil/water system or complex crude oil/water/clay particle system to the water-continuous emulsion, acting as a weak demulsifier to accelerate the oil/water separation. On the other hand, the addition of polymer to the water-continuous emulsion could result in enhanced emulsion stability, which is primarily attributed to the increased viscosity of the continuous phase and the decreased drop size of the dispersed oil phase. Particularly, the sheared polymer had a weaker ability to stabilize the o/w emulsion than the unsheared polymer due to the lower viscosity of the sheared polymer solution resulting from the breakdown of the polymer macromolecules. As for the chemical demulsification tests, the performance of demulsifiers showed a complex dependency upon the water cut, the shearing intensity, demulsifier type and dosage, and the polymer concentration. A compound emulsion breaker, E12+E18, exhibited the most satisfactory demulsification performance despite the varied test conditions. For severe water-continuous emulsions that might require a multi-fold dosage of demulsifier, a less expensive electrolyte, KCl, was proposed to be used in combination with demulsifier E12+E18 to improve the demulsification performance. In the proposed demulsifier formula, the effectiveness of the commercial demulsifier relied on its destructive effect on the interfacial film, while the efficacy of KCl was mainly dependent on its viscosity reduction effect on the continuous phase. This dissertation illustrates that intermediate layer elimination and water clarification are the major challenges for produced liquid treatment from polymer flooding. It also provides practical and theoretical guidance in advance for the demulsification strategy of the produced liquid from the ongoing first-ever polymer flooding pilot on ANS.

Chang, Hongli↗
DOE OSTI2023

Evolving efforts to maintain and improve XPS analysis quality in an era of increasingly diverse uses and users

Based on literature analysis, X-ray photoelectron spectroscopy (XPS) use continues to increase exponentially. This increased use is accompanied by anecdotal reports and systematic analyses indicating a growing presence of significantly flawed data analyses. Recognition of this problem within the surface analysis community has increased with an understanding that both inexperienced users and increased use of XPS outside the surface analysis community contribute to the problem. The XPS community has initiated several efforts to help address the problem, which is not unique to XPS. This paper describes some of the specific problems identified and some of the community efforts intended to address them. Here, we describe activities focused on three specific issues: (i) requests for detailed guides and protocols and bite-sized versions of information for non-experts, (ii) incomplete data and analysis reporting, and (iii) the high rate of peak fitting problems. A 2019 survey identified the need for guides, protocols, and standards to assist XPS users. One set of such guides has been published, and another is being assembled. Providing incremental bites of useful information is the goal of a series of papers on specific challenges to surface analysis with example solutions has been initiated as Notes and Insights papers in Surface and Interface Analysis. Examination of XPS-containing papers finds that information to establish the credibility and reproducibility of XPS results is often very incomplete. Unfortunately, ISO and ASTM standards require an amount of parameter reporting that seems excessive and unrealistic for many research publications. Initial approaches to develop and distribute a graded approach to parameter reporting are briefly described. Multiple efforts are underway to address the high rate of problems associated with photoelectron peak fitting. These include guides to peak fitting, guides to peak identification and fitting for specific elements, and the development of a peak fitting social network. The fitting social network is designed to facilitate interactions between new and experienced XPS users; analysts trying to fit XPS data (for publication or other reasons) can ask questions and establish dynamic conversations. Encouraging and enabling high-quality XPS analysis and reporting requires several different types of effort from all members of the surface and interface analysis community.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Learning in continuous action space for developing high dimensional potential energy models

Reinforcement learning (RL) approaches that combine a tree search with deep learning have found remarkable success in searching exorbitantly large, albeit discrete action spaces, as in chess, Shogi and Go. Many real-world materials discovery and design applications, however, involve multi-dimensional search problems and learning domains that have continuous action spaces. Exploring high-dimensional potential energy models of materials is an example. Traditionally, these searches are time consuming (often several years for a single bulk system) and driven by human intuition and/or expertise and more recently by global/local optimization searches that have issues with convergence and/or do not scale well with the search dimensionality. Here, in a departure from discrete action and other gradient-based approaches, we introduce a RL strategy based on decision trees that incorporates modified rewards for improved exploration, efficient sampling during playouts and a “window scaling scheme" for enhanced exploitation, to enable efficient and scalable search for continuous action space problems. Using high-dimensional artificial landscapes and control RL problems, we successfully benchmark our approach against popular global optimization schemes and state of the art policy gradient methods, respectively. We demonstrate its efficacy to parameterize potential models (physics based and high-dimensional neural networks) for 54 different elemental systems across the periodic table as well as alloys. We analyze error trends across different elements in the latent space and trace their origin to elemental structural diversity and the smoothness of the element energy surface. Broadly, our RL strategy will be applicable to many other physical science problems involving search over continuous action spaces.

36 MATERIALS SCIENCE↗
DOE OSTI2023

End-of-Winter Snow Depth, Temperature, Density, and SWE Measurements at Kougarok Road Site, Seward Peninsula, Alaska, 2022

Measurements of end-of-winter snow properties were collected at the NGEE Arctic Kougarok Road Site at mile marker 64 (KG_MM64) from April 2 to April 5, 2022. This dataset contains three *.csv data files of spatially distributed values of snow depth, snow water equivalent (SWE), and snow temperature at the snow surface and at the bottom of the snowpack. Data were collected toward the end of the winter season during early April, when the snowpack would be near its maximum. A Snow-Hydro MagnaProbe (http://www.snowhydro.com/products/column2.html) was used to improve collection efficiency and enhance spatial coverage. A user guide is included as a *.pdf. This dataset is a continuation of the previous end-of-winter snow surveys conducted at the Kougarok Road Site in 2018 (Wilson et al., 2021; https://doi.org/10.5440/1593874).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

Compressive strength improvements from noncircular carbon fibers: A numerical study

The benefits of high-performance unidirectional carbon fiber composites are limited in many cost-driven industries due to the high cost relative to alternative reinforcement fibers. Low-cost carbon fibers have been previously proposed, but the longitudinal compressive strength continues to be a limiting factor or studies are based on simplifications that warrant further analysis. A micromechanical model is used to (1) determine if the longitudinal compressive strength of composites can be improved with noncircular carbon fiber shapes and (2) characterize why some shapes are stronger than others in compression. In comparison to circular fibers, the results suggest that the strength can be increased by 10%–13% by using a specific six-lobe fiber shape and by 6%–9% for a three-lobe fiber shape. A slight increase is predicted in the compressive strength of the study two-lobe fiber but has the highest uncertainty and sensitivity to fiber orientation and misalignment direction. The underlying mechanism governing the compressive failure of the composites was linked to the unique stress fields created by the lobes, particularly the pressure stress in the matrix. Importantly, this work provides mechanics-based evidence of strength improvements from noncircular fiber shapes and insight on how matrix yielding is altered with alternative fiber shapes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

EvoNet: A phylogenomic and systems biology approach to identify genes underlying plant survival in marginal, low‐N soils

The DOE‐BER “EvoNet” project investigates the genetic and molecular basis of plant resilience in extreme environments. We do this by identifying key genes that enable “extreme survivor” species to thrive in the nitrogen-poor soils of Chile’s hyper-arid Atacama Desert. Our collections focus on 32 Atacama extremophile species, including seven grass species with potential biofuel applications. To identify genes-of-importance to survival we compared genomic and transcriptomic profiles of extremophile species that thrive in the Atacama to those of closely related “sister” species from nitrogen-rich arid and mesic regions of California. Deep RNA sequencing and de novo transcriptome assembly across these triplet species sets supported a phylogenomic framework for identifying positively selected genes associated with adaptive divergence. Our integrative analysis combined ecological and environmental data, metagenomics, evolutionary and systems biology, and metabolomics. This enabled us to create an unprecedented framework for systematically understanding how non-model plants have adapted to survive in extreme conditions. Our resulting database of positively selected ortholog groups in the extremophile plants offers promising targets for engineering crop and biofuel species with enhanced resilience to drought and extreme weather. Additionally, our newest dataset explores and exploits a complementary metabolomic approach. This new aspect provides innovative strategies to manipulate plant cell metabolism, further supporting efforts to improve agricultural productivity in the face of extreme climates. Importantly, our combined evolutionary- and metabolomic-based strategies focused on convergent patterns of adaptation, providing a genetic and metabolomic toolkit for improving crop and biofuel resilience across diverse plant species. Finally, our novel exploration of ecological and evolutionary dynamics delivered to the community a phylogenomic computational pipeline called “PhyloGeneious.” Our continued adaptations of this pipeline are publicly available to expedite evolutionary genomic research for future scientific discoveries. In total, our DOE-BER has provided genomic, metabolomic, and computational strategies to understand how extremophile plants provide evolutionary and physiological targets for improving agricultural and biofuel production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Highly efficient separation membrane based on cellulose acetate/chitosan fibrous composite substrate with activated carbon functional adsorption layer

Abstract BACKGROUND For improving the permeability and selectivity of adsorption separation membranes, membrane materials, structural morphology and separation technology must continue to be investigated. Development of a membrane that is environmentally friendly, cost‐effective and with high filter precision is an important direction in current research. RESULTS The air pressure spraying method was used to prepare an activated carbon (AC)–cellulose acetate/chitosan (CA/CS) composite membrane. The CA/CS fiber composite membrane was prepared as substrate layer, and AC was loaded on the surface of the CA/CS composite membrane as a functional adsorption layer. When the spraying pressure was 0.01 MPa and the mass ratio of AC/CS was 2:1, a composite membrane with even and compact morphology could be obtained. Both the compact AC functional layer and complete CA/CS substrate layer endowed the AC–CA/CS composite membrane with an excellent water filtration property. At low feeding pressure, the permeate flux and rejection rate of bisphenol A (BPA) could reach 9.27 × 10 3 L m −2 h −1 and 98.31%, respectively. Meanwhile, the adsorption capacities of the membrane were investigated. It tended to equilibrate quickly in 2 min for dyes and BPA. The equilibrium adsorption capacities of the membrane for acid blue, acid yellow and BPA were 175.80, 164.0815 and 79.58 mg g −1 , respectively. The adsorption process conformed to pseudo‐second‐order kinetics and the Langmuir monolayer adsorption model. CONCLUSIONS This work could provide a practical and effective feasibility for membrane separation technology. © 2020 Society of Chemical Industry (SCI)

Zhao, Xiaoyan↗
DOE OSTI2022

Forbidden scalar dark matter and dark Higgses

As experimental searches for WIMP dark matter continue to yield null results, models beyond the WIMP paradigm have proliferated in order to elude ever improving observational constraints, among them that of sub-GeV dark matter mediated by a massive vector portal (a dark photon) associated with a new dark U(1) gauge symmetry. It has been previously noted that for a significant range of the parameter space of this class of models, the annihilation of dark matter particles into a pair of dark photons can dominate the freeze-out process even when this process is kinematically forbidden for dark matter at rest — this is known as the “forbidden dark matter” (FDM) regime. Prior studies of this regime, however, assume that any “dark Higgs” associated with breaking the dark U(1) and imparting mass to the dark photon is decoupled from the dark matter and as such plays no role in the freeze-out process. In this paper, we explore the effects of a dark Higgs on sub-GeV dark matter phenomenology in this FDM regime by considering the simplest possible construction in which there exist non-trivial dark matter-dark Higgs couplings: a model with a single complex scalar DM candidate coupled directly to the dark Higgs field. We find that for a wide range of parameter space, the dark Higgs can alter the resulting relic abundance by many orders of magnitude, and that this effect can remain significant even for a small dark matter-dark Higgs coupling constant. Considering measurements from direct detection and measurements of the CMB, we further find that points in this model’s parameter space which recreate the appropriate dark matter relic abundance suffer only mild constraints from other sources at present, but may become accessible in near-future direct detection experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Semi-integral LOCA test of cold-spray chromium coated zircaloy-4 accident tolerant fuel cladding

Enhancing the accident tolerance of PWRs came under serious consideration following the 2011 Fukushima Daiichi nuclear power plant events. While the current nuclear fuels are based on mature technology and have an excellent operational record, further enhancing their strength through accident tolerant fuel (ATF) research and development continues to be of interest. Particularly, the chromium coated clad ATF technology represents an evolutionary change to improve the high temperature performance of existing Zircaloy claddings. Additionally, despite several years of investigation of coated cladding, the integral loss of coolant accident (LOCA) performance of chromium coated cladding has had little attention. In this work, cold-spray chromium coated zircaloy-4 claddings are evaluated using EDF's semi-integral LOCA test facility. Results show that the chromium coating induces a reduced ballooning and burst and an increased burst temperature in the investigated conditions. However, these tests exhibit limited benefits concerning the post-quench behavior of the coated specimens which occurs in the last stage of a prototypical LOCA scenario.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Small Molecule Inhibitor-Modulated Al 2 O 3 Atomic Layer Deposition on Monolayer MoS 2 for Controlled Nucleation

The integration of ultrathin dielectrics on two-dimensional (2D) semiconductors is essential for advancing beyond-Si electronics. However, the intrinsic inertness of van der Waals 2D basal planes remains a primary bottleneck to achieving uniform dielectric nucleation and growth. Here, in this study, we introduce a small molecule inhibitor (SMI)-modulated thermal atomic layer deposition (ALD) strategy, exemplified by aluminum oxide (Al 2 O 3 ) ALD on monolayer molybdenum disulfide (1L MoS 2 ) with acetic acid (HAc) SMI. The ABC-type sequence comprises HAc inhibitor (A), trimethylaluminum (TMA) precursor (B), and deionized H 2 O coreactant (C). In situ quartz crystal microbalance (QCM) studies reveal robust HAc adsorption on Al 2 O 3 and suppression of subsequent oxide growth on HAc-passivated surfaces. When applied to 1L MoS 2 , this inhibitory pathway enables HAc to selectively passivate nascent Al 2 O 3 nuclei formed on the MoS 2 surface, limiting their three-dimensional (3D) island coarsening and redirecting precursor adsorption toward the uncovered basal plane. Consequently, nearly continuous ultrathin (∼1.5 nm) Al 2 O 3 films are achieved on 1L MoS 2 with markedly improved uniformity compared to standard Al 2 O 3 ALD using TMA and H 2 O, as validated by atomic force microscopy (AFM), cross-sectional scanning transmission electron microscopy (STEM), and energy-dispersive X-ray spectroscopy (EDS). Density functional theory (DFT) calculations further provide atomistic insight into HAc-modulated Al 2 O 3 nucleation, corroborating the energetic preference of HAc for Al 2 O 3 over MoS 2 and attenuated TMA adsorption on HAc-passivated surfaces. Spatially resolved Raman spectroscopy also confirms that the HAc-modulated process preserves the structural integrity of 1L MoS 2 , with only minimal strain and doping perturbations observed after dielectric deposition. This SMI-modulated approach offers a broadly applicable framework for controlling ALD nucleation across various inhibitors, ALD chemistries, and 2D materials, opening opportunities for reliable dielectric integration in next-generation nanoelectronics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Improving ideal MHD equilibrium accuracy with physics-informed neural networks

We present a novel approach to compute three-dimensional magnetohydrodynamic equilibria with isotropic pressure profiles and nested surfaces by parametrizing Fourier modes with artificial neural networks (NNs). The full nonlinear global force residual of single equilibria across the volume in real space is then minimized with first order optimizers and compared to equilibria computed by conventional solvers. Already, we observe competitive computational cost to arrive at the same minimum residuals computable with existing codes. With increased computational cost, lower minima of the residual are computable with the NNs than with any other tested solver, establishing a new lower bound for the force residual. We use minimally complex NNs, and we expect significant improvements for solving not only single equilibria with NNs, but also for creating NN models valid over continuous distributions of equilibria.

ideal magnetohydrodynamics↗
DOE OSTI2025

Proximal remote sensing: an essential tool for bridging the gap between high‐resolution ecosystem monitoring and global ecology

Summary A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or ‘proximal’ remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site‐level eddy‐covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high‐spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions. We provide current best practices for data availability and metadata for proximal remote sensing: spectral reflectance, solar‐induced fluorescence, thermal infrared radiation, microwave backscatter, and LiDAR. Our paper outlines the steps necessary for making these data streams more widespread, accessible, interoperable, and information‐rich, enabling us to address key ecological questions unanswerable from space‐based observations alone and, ultimately, to demonstrate the feasibility of these technologies to address critical questions in local and global ecology.

Plant Sciences↗
DOE OSTI2025

Stability-preserving Lossy Compression for Large-scale Partial Differential Equations

Checkpoint/Restart (C/R) strategies are vital for fault tolerance in PDE-based scientific simulations, yet traditional checkpointing incurs significant I/O overhead. Lossy compression offers a scalable solution by reducing checkpoint data size, but conventional methods often lack control over physical invariants (e.g., energy), leading to instability such as oscillations or divergence in Partial Differential Equations (PDE) systems. This paper introduces a stability-preserving compression approach tailored for PDE simulations by explicitly controlling kinetic and potential energy perturbations to ensure stable restarts. Extensive experiments conducted across diverse PDE configurations demonstrate that our method maintains numerical stability with minimal error magnification—even across multiple checkpoint-restart cycles—outperforming state-of-the-art lossy compressors. Parallel evaluations on the Frontier supercomputer show up to 8.4× improvement in checkpoint write performance and 6.3× in read performance, while maintaining relative L2 errors ∼ 2e-6 throughout continued simulation. These results provide practical guidance for balancing compression accuracy, stability, and computational efficiency in large-scale PDE applications.

Gong, Qian [ORNL] (ORCID:0000000235704142)↗
DOE OSTI2020

A Multi-Instrument Cloud Condensation Nuclei Spectrum Product (Final Technical Report)

A wealth of observational data exists on the characteristics of atmospheric particulate matter, over multiple years, at the DOE ARM Southern Great Plains (SGP) Central Facility site. This site is located in a region of the country that frequently experiences weather extremes, and that is removed from many local sources of pollution but is affected by transported smoke, dust, and urban emissions. The relationships between particulate matter, cloud formation and evolution, and precipitation are therefore of strong interest, and are being explored via modeling on a variety of scales. These models require as input detailed information on the characteristics of particles capable of serving as the nuclei for cloud formation. Sufficient data exist to be able to put together a picture of the nature of the total aerosol and the cloud condensation nuclei (CCN) subset, and their variability, through merged data products. This study was aimed at exploiting the multiple measurement types at SGP to develop the first such multi-year estimates. Further, the resulting data were analyzed to understand temporal patterns ranging from hourly to seasonal, thereby gaining insights into the particle sources affecting the atmosphere in this region. DOE-funded datasets that were analyzed in this study include total particle number concentrations, submicron aerosol scattering coefficients, dry aerosol size distributions, and more recently, time-resolved submicron aerosol chemical composition. Data are also available for the number concentrations of particles that are activated in a cloud condensation nucleus instrument at a series of setpoint supersaturations, providing direct observations of the number concentrations of “CCN”. This variable is the quantity that is generally desired for inclusion in numerical models that seek to represent and predict the impacts of varying aerosol characteristics on the formation and microphysical properties of clouds. One limitation of the use of direct CCN observations is that they are not available for supersaturations larger than about 1%, which is insufficient for deep convection and may be insufficient even for shallow convection, depending on the nature of the available CCN and the dynamics of the cloud. We developed a data-based approach to representing the full aerosol size spectrum with size-dependent hygroscopicity, and used this to extrapolate CCN spectra beyond the limited measurements. Five years of SGP aerosol data (2009 -2013) were analyzed. As a side product of our work, we identified and communicated several previously-unflagged data quality issues. The resulting merged aerosol distributions, along with fits for seasonal averages, were published and submitted to the ARM archive as a special value-added product (VAP; submitted as a PI product). CCN spectra were computed for the same data period and will similarly be published and submitted to the archive for use by the community. We also note that our methodologies and findings have been discussed at several Joint ARM User Facility/Atmospheric System Research (ASR) Principal Investigators Meetings and that recent ARM/ASR aerosol data reporting strategies have included similar ideas for data merging, indicating that this work has had a lasting impact on ARM aerosol data acquisition and reporting. The proposed work advances the science of the interactions of aerosols, clouds and precipitation, with direct application to improve representation of such interactions for clouds in regional and global climate models. The archived data will continue to serve research studies in the future.

54 ENVIRONMENTAL SCIENCES↗