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DOE OSTI2024

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are exploring hidden geothermal resources in the U.S.A. and designing profitable enhanced geothermal systems (EGS). Many processes and parameters control geothermal exploration and energy production from geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize subsurface geothermal conditions. Sparse and multi-scale characteristics of these datasets prohibit properly leveraging these datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) promise to resolve these issues. The tremendous challenges and risks of geothermal exploration and production bring the demand for novel ML methods and tools that can (1) analyze large field datasets, (2) assimilate model simulations (large inputs and outputs), (3) process sparse datasets, (4) perform transfer learning (between sites with different exploratory levels), (5) extract hidden geothermal signatures in the field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. To address these necessities, ML-based geothermal resources exploration and enhanced geothermal systems (EGS) design tools have been developed. The exploration tool is called GeoThermalCloud and EGS design tool is called GeoDT-ML. GeoThermalCloud (https://github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. Also, it enables the identification of critical measurements needed to identify geothermal resource signatures. Alternatively, GeoDT-ML (https://github.com/SmartTensors/GeoThermalCloud.jl/tree/master/EGS) is an ML-based alternative to GeoDT (https://github.com/GeoDesignTool/GeoDT.git), a fast, simplified multi-physics solver to evaluate EGS project designs in uncertain geologic systems. GeoDT-ML leverages recent advances in deep learning and high-performance computing. It is a faster and simpler version of GeoDT. To make this project a success, we used capabilities of LANL, PNNL, Google, Stanford, and Julia Computing. We analyzed eight datasets of the U.S.A. using GeothermalCloud and demonstrated potential highly prospective geothermal resources and identified key factors defining highly prospective sites. The first data set includes 44 locations in southwest New Mexico and 18 geological, hydrogeological, geophysical, geothermal, geochemical attributes. We defined low- and medium-temperature hydrothermal systems and discovered a new highly prospective site. The second data set analyzed 18 shallow water chemistry attributes at 14,342 locations in the Great Basin. It demarcated modestly, moderately, and highly prospective sites including key attributes for each type of prospectivity. The third data set analyzed Utah FORGE data including satellite (InSAR), geophysical (gravity, seismic), geochemical, and geothermal attributes. Here, we performed prospectivity analysis to identify future drilling locations using geological, geochemical, and geophysical attributes. Maps of temperature at depth and heat flow are constructed based on the available data. Prospectivity maps were generated, and drilling locations were proposed for future geothermal field exploration. The fourth data set analyzed 21 attributes at 120 locations in Tularosa Basin, New Mexico; data comes from past play fairway analyses in this region. ML analyses identified geothermal signatures associated with modestly, moderately, and highly hydrothermal systems. We also defined dominant attributes and spatial distribution of the geothermal signatures. The fifth, sixth, seventh, and eighth datasets include Tohatchi Springs, New Mexico, Hawaii, Brady site, Nevada, and EGS Collab, respectively. Moreover, we coupled GeothermalCloud and magnetotellurics data to pinpoint drilling locations for developing geothermal projects in the Tularosa Basin, New Mexico. GeothermalCloud found potential prospective locations for geothermal resources near White Sands Missile Range and McGregor Range at Fort Bliss. Magnetotellurics data determined the potential depth (~1800m) of geothermal prospects at McGregor Range based on apparent resistivity structures/layers in the subsurface. The McGregor Range consists of three resistivity layers and two resistivity structures. Magnetotellurics data also helps identify that the western portion of the McGregor Range has thick and low-resistivity earth materials. The low resistivity to the west is most likely for a fault system. Assuming temperature is consistent with a geothermal reservoir, the west-central part of the McGregor Range has the highest geothermal potential because of the increase in porosity and associated permeability attributed to the interpreted fault system. Also, we devised a coupling strategy between a process model and GeothermalCloud to characterize hydrogeological conditions and geothermal conditions, respectively. The process model characterizes hydrogeological and geothermal conditions on highly prospective geothermal sites provided by GeothermalCloud. We developed a physics-informed neural network (PINN) version of the Burns equation that can be easily coupled with GeothermalCloud. Furthermore, we performed an optimal design decision maximizing the economic value of an EGS power plant. This study optimized the range of well spacing between injection and production wells maximizing net present value in dollars (NPV). For this task, we used the GeoDT to simulate the Utah FORGE EGS development cycle from the initial well design to the end of production. Next, we accomplished another crucial task, which is predicting permeability of geothermal reservoirs. Predicting permeability of geothermal reservoirs is a non-trivial task because of huge computational runtime of simulation and lack of measurements. To avoid these limitations, we used easy-to-measure chemical concentrations in the subsurface as measurement data and convolutional neural network based ML model of a high-fidelity model. Next, we predicted permeability using Markov chain Monte Carlo simulation. We found that Markov chain Monte Carlo simulation predicts permeability with a high certainty if the prediction zone in the simulation area has chemical concentration data. Finally, we analyzed the DOE funded INGENIOUS and GeoDAWN projects data. For discovering hidden geothermal systems in the Great Basin, the INGENIOUS project accumulated old data, collected new data, and released them in 2022. The dataset includes a total of 24 geological, geophysical, and geochemical attributes. Data resolution and scale significantly vary prohibiting an appropriate usage. To avoid such limitations, we brought all data in the same resolution and scale by applying the inverse distance weighting interpolation technique for predicting data in unsampled locations. Subsequently, we analyzed LiDAR data of the GeoDAWN project. We received data in tiles format. The DOE’s overarching goal is to use ML on LiDAR data for finding favorable geological structures (e.g., step up faults in Brady, Nevada). To serve the purpose, we need to label favorable geologic structures that correspond to LiDAR data. We wrote an algorithm to label the LiDAR data with the favorable geologic structures.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Analyses of Dose Rates for Second Inner Reflector Plug Replacement at Spallation Neutron Source

The Inner Reflector Plug (IRP) is a central component of the Spallation Neutron Source (SNS) target monolith, which houses the liquid mercury target and four liter-sized neutron moderator units. It is exposed to high-level radiation fields during routine operation and builds up significant activity. The IRP needs to be replaced due to moderator neutron poison and decoupler burn-out, which is used for shaping neutron pulses. The first IRP exchange took place in March 2018 and next one, which is IRP2, is planned to be replaced during the facility maintenance period in the end of December 2025, beginning of January 2026 calendar year. The replacement of IRP is a complex task due to its location in the area receiving high irradiation, being under significant amount of shielding, and size, which requires removal in segments. For planning the replacement workflow to help to reduce radiation exposure to workers dose rates for each stage of extraction/replacement operation are predicted.

42 ENGINEERING↗
DOE OSTI2025

Final Design for Thermal/Epithermal eXperiments (TEX) with Lithium Absorbers to Provide Validation Benchmarks for Y-12 Electrorefining Facility

One of the main goals of the Thermal/Epithermal eXperiments (TEX) project is to use existing Nuclear Criticality Safety Program (NCSP) assets to create critical experiment plutonium and uranium test beds for materials important to criticality safety that have insufficient benchmark evaluations. The plutonium test bed experiments were completed in 2018 and are published in the 2020 edition of the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The uranium test bed assemblies were completed in 2023 and accepted in the 2024 edition of the ICSBEP Handbook. The Nuclear Criticality Safety (NCS) group at Y-12 National Security Complex has identified programmatic need for validation cases for uranium electrorefining operations at Y-12. The electrorefining operation credits lithium enriched in 6 Li in addition to 35 Cl as absorbers in the design criticality safety evaluation for precluding criticality under upset conditions in the large and geometrically unfavorable electro-refiner. There is, however, inadequate experimental validation for the 6 Li absorbers. As an extension of the TEX uranium test bed, TEX-Cl critical experiments were performed with sodium chloride salt to address the 35 Cl thermal absorption as well as other validation needs at Los Alamos National Laboratory (LANL). These experiments were completed in 2024 and accepted into the 2025 ICSBEP Handbook. To continue the methodology used in TEX-Cl, TEX-Li aims to accomplish the same. The overall design of both experiments was to use commercially available, high purity, salts with polyethylene moderator and HEU plates to configure a critical assembly. Three experiments are planned for TEX-Li using encapsulated lithium carbonate (Li 2 CO 3 ), with natural 6 Li abundance. For all experiments, the highly enriched uranium (HEU) Jemima plates will be used as fissile material. Multiple layers will be stacked together with encapsulated Li 2 CO 3 alternated with polyethylene in standard configurations. Standard stacking was found to be optimal in matching the different sensitivity profiles provided by the Y-12 models. Three configurations are proposed with varying polyethylene moderation and a constant 1/4” absorber thickness. The first uses 11 layers of 5/4” polyethylene, the second uses 9 layers of 3/4” polyethylene, and the third uses 10 layers of 1/2” polyethylene. Calculations showed that some alternative forms of lithium-based materials provided slightly less-optimal sensitivity profiles when compared to lithium carbonate but come with other drawbacks. These alternatives included lithium aluminate (LiAlO 2 ), Aluminum-2050 alloy, Aluminum-8090, Aluminum-2095, lithium hydride (LiH), and lithium fluoride (LiF). Lithium aluminate and aluminum-2050 provided comparable sensitivity profiles when compared to lithium carbonate and can be used instead if lithium carbonate cannot be readily procured. After a broad material study, lithium carbonate outperformed any alternative material with a balance in affordability and workability. The assessment of experimental uncertainties of the non-absorber and absorber components was predicted to be 0.00089 and 0.00093 Δk eff , respectively. The largest uncertainties may be reduced with precision dimensional inspection of the components. Many of the parts and equipment for IER 575 have already been fabricated or procured for previous projects and therefore do not contribute significantly to the overall cost of this experiment. This includes the Jemima plates and Comet critical assembly machine, which are existing NCSP assets, as well as the aluminum platen and polyethylene reflector rings, which were fabricated and authorized for the TEX experiment involving HEU with polyethylene. Lithium carbonate containers will be procured by LANL and will be filled by LLNL. The total material costs for TEX-Li experiments are estimated to be on the order of $\$$47,400. Precision inspection, including dimensional, mass, density, and impurity, is recommended for all components for an estimated cost of $\$$12,000.

35Cl↗
DOE OSTI2025

Degradation of Be 2 C at conditions expected in molten salt environments

This technical report is in submission of completion of the Level 4 milestone number M4AT-25OR1101021, titled “Degradation of Be 2 C at conditions expected in molten salt environments”, for the AT-25OR110102 “Beryllium Carbide as moderator for MSRs—ORNL” WBS number 2.04.11.01 within the larger Advanced Reactor Technologies program at Oak Ridge National Laboratory. This effort is an initial study of the viability of Be 2 C as a future neutron moderator for molten salt reactors and other high-temperature reactors. The research was awarded funding in September 2022, and this Level 4 milestone presents the work that completed by the end of July 2025. This work is a collaboration between Oak Ridge National Laboratory and the University of Michigan.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Spectral Flux Measurements on SNS Direct Geometry Spectrometers at IRP-2 End-of-Life

The Inner Reflector Plug (IRP) of the Spallation Neutron Source (SNS) was replaced during the SNS shutdown period beginning 25 November 2025. This IRP, IRP-2, was first placed in service in May 2018, and was in use for 42.5 GW-hrs of operation, somewhat longer than its original design life of 30 GW-hrs, or even a refined estimate of 33 GW-hrs for the water moderator poison plate and 39 GW-hrs on the decoupled-poisoned hydrogen moderator decoupler (Gallmeier, Lu, and Iverson 2018). The time-integrated power history for IRP-2 is tracked in Figure 1.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Microreactor Core Transportation Cask Model Description for Criticality Safety Validation Basis Assessment (Rev. 2)

Criticality safety analyses are completed on transportation casks used for microreactor whole core shipment to provide examples of models and analyses to industry, regulators, and nuclear community at large to be used in verification and validation analyses of similar applications. The microreactors considered are based on a Gas-Cooled Microreactor (GCMR) and a Heat-Pipe Microreactor (HPMR), both utilize HALEU fuel in the form of TRISO particles and various other design options considered in industry microreactor designs. Variant design options of GCMR and HPMR were also investigated to provide a wider application range for each technology. Criticality safety analyses for the GCMR and HPMR packages were performed using the CSAS6 sequence of SCALE 6.3.2 with the ENDF/B-VII.1-based continuous energy neutron libraries. Different scenarios were investigated, including normal operation and water flooded conditions to represent nominal and hypothetical accident scenarios. Sensitivity and similarity analyses are also performed using the TSUNAMI sequence of SCALE 6.3.2, and the similarity analysis uses all the experiments from the ICSBEP Handbook with High Enriched Uranium (HEU), Intermediate and mixed Enriched Uranium (IEU) and Low Enriched Uranium (LEU) systems. Many ICSBEP experiments were found marginally similar, with similarity index (ck) values greater than 0.8, to the GCMR and HPMR cask models, especially in flooded conditions that may be more constraining due to reduced reactivity margins. Some experiments using TRISO fuel particles and graphite moderator, including the recent THETA and Deimos experiments from LANL, together with some IRPhEP experiments, were also used for the similarity analyses. These TRISO-fueled and graphite moderated experiments behaved similarly to the GCMR models, with maximum ck value greater than 0.9, but they are less similar to the HPMR models. This observation indicates that additional critical experiments might be needed to further validate the criticality safety models, especially for heat-pipe based microreactor transport packages and for non-flooded transportation configurations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

IER-620 CED-3b: Experiment Execution Summary for the Pulsed-Neutron Die-Away Experiments (PNDA) with Propylene Glycol and Mobilmet 423

There is a strong need for new benchmarks to validate neutron thermal scattering laws (TSLs). Lawrence Livermore National Laboratory (LLNL) has designed a Pulsed-Neutron Die Away (PNDA) testbed for this purpose. The experiment has a deuterium-tritium (D-T) neutron generator that impinges a 10 -4 s, mono-energetic pulse of 14.1 MeV neutrons on a target sample. After the pulse, the neutron population moderates and establishes a thermal equilibrium within the sample, with a fundamental spatial mode and characteristic decay-time eigenvalue, ⍺. The ⍺ eigenvalue can be extracted from the experimental measurements of the time-dependent neutron flux coming off the surface of the sample and can then be used as an integral parameter (similar to k eff ) to validate nuclear data involved with neutron migration, thermalization, and absorption. For moderating materials and geometric configurations, the ⍺ eigenvalue is heavily dependent on thermal neutron scattering of the target material. For that reason, a PNDA experiment can have a higher sensitivity to TSLs than is commonly available with the k eff parameter in critical experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Research Requirements to Move the Bar forward Using Aqueous Formate Salts as H 2 Carriers for Energy Storage Applications

In this perspective on hydrogen carriers, we focus on the needs for the development of robust active catalysts for the release of H 2 from aqueous formate solutions, which are non-flammable, non-toxic, thermally stable, and readily available at large scales at reasonable cost. Formate salts can be stockpiled in the solid state or dissolved in water for long term storage and transport using existing infrastructure. Furthermore, formate salts are readily regenerated at moderate pressures using the same catalyst as for the H 2 release. There have been several studies focused on increasing the activity of catalysts to release H 2 at moderate temperatures, i.e., < 80 °C, below the operating temperature of a proton exchange membrane (PEM) fuel cell. One significant challenge to enable the use of aqueous formate salts as hydrogen carriers is the deactivation of the catalyst under operating conditions. In this work we provide a review of the most efficient heterogeneous catalysts that have been described in the literature, their proposed modes of deactivation, and the strategies reported to reactivate them. We discuss potential pathways that may lead to deactivation and strategies to mitigate it in a variety of H 2 carrier applications. We also provide an example of a potential use case employing formate salts solutions using a fixed bed reactor for seasonal storage of energy for a microgrid application.

25 ENERGY STORAGE↗
DOE OSTI2021

A New Field Instrument for Leaf Volatiles Reveals an Unexpected Vertical Profile of Isoprenoid Emission Capacities in a Tropical Forest

Both plant physiology and atmospheric chemistry are substantially altered by the emission of volatile isoprenoids (VI), such as isoprene and monoterpenes, from plant leaves. Yet, since gaining scientific attention in the 1950’s, empirical research on leaf VI has been largely confined to laboratory experiments and atmospheric observations. Here, we introduce a new field instrument designed to bridge the scales from leaf to atmosphere, by enabling precision VI detection in real time from plants in their natural ecological setting. With a field campaign in the Brazilian Amazon, we reveal an unexpected distribution of leaf emission capacities (EC) across the vertical axis of the forest canopy, with EC peaking in the mid-canopy instead of the sun-exposed canopy surface, and moderately high emissions occurring in understory specialist species. Compared to the simple interpretation that VI protect leaves from heat stress at the hot canopy surface, our results encourage a more nuanced view of the adaptive role of VI in plants. We infer that forest emissions to the atmosphere depend on the dynamic microenvironments imposed by canopy structure, and not simply on canopy surface conditions. We provide a new emissions inventory from 52 tropical tree species, revealing moderate consistency in EC within taxonomic groups. We highlight priorities in leaf volatiles research that require field-portable detection systems. Our self-contained, portable instrument provides real-time detection and live measurement feedback with precision and detection limits better than 0.5 nmol VI m -2 leaf s -1 . We call the instrument ‘PORCO’ based on the gas detection method: photoionization of organic compounds. We provide a thorough validation of PORCO and demonstrate its capacity to detect ecologically driven variation in leaf emission rates and thus accelerate a nascent field of science: the ecology and ecophysiology of plant volatiles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Dynamic subcanopy leaf traits drive resistance of net primary production across a disturbance severity gradient

Across the globe, the forest carbon sink is increasingly vulnerable to an expanding array of low- to moderate-severity disturbances. However, some forest ecosystems exhibit functional resistance (i.e., the capacity of ecosystems to continue functioning as usual) following disturbances such as extreme weather events and insect or fungal pathogen outbreaks. Unlike severe disturbances (e.g., stand-replacing wildfires), moderate severity disturbances do not always result in near-term declines in forest production because of the potential for compensatory growth, including enhanced subcanopy production. Community-wide shifts in subcanopy plant functional traits, prompted by disturbance-driven environmental change, may play a key mechanistic role in resisting declines in net primary production (NPP) up to thresholds of canopy loss. However, the temporal dynamics of these shifts, as well as the upper limits of disturbance for which subcanopy production can compensate, remain poorly characterized. In this study, we leverage a 4-year dataset from an experimental forest disturbance in northern Michigan to assess subcanopy community trait shifts as well as their utility in predicting ecosystem NPP resistance across a wide range of implemented disturbance severities. Through mechanical girdling of stems, we achieved a gradient of severity from 0% (i.e., control) to 45, 65, and 85% targeted gross canopy defoliation, replicated across four landscape ecosystems broadly representative of the Upper Great Lakes ecoregion. We found that three of four examined subcanopy community weighted mean (CWM) traits including leaf photosynthetic rate (p = 0.04), stomatal conductance (p = 0.07), and the red edge normalized difference vegetation index (p < 0.0001) shifted rapidly following disturbance but before widespread changes in subcanopy light environment triggered by canopy tree mortality. Surprisingly, stimulated subcanopy production fully compensated for upper canopy losses across our gradient of experimental severities, achieving complete resistance (i.e., no significant interannual differences from control) of whole ecosystem NPP even in the 85% disturbance treatment. Additionally, we identified a probable mechanistic switch from nutrient-driven to light-driven trait shifts as disturbance progressed. Our findings suggest that remotely sensed traits such as the red edge normalized difference vegetation index (reNDVI) could be particularly sensitive and robust predictors of production response to disturbance, even across compositionally diverse forests. The potential of leaf spectral indices to predict post-disturbance functional resistance is promising given the capabilities of airborne to satellite remote sensing. We conclude that dynamic functional trait shifts following disturbance can be used to predict production response across a wide range of disturbance severities.

resistance↗
DOE OSTI2021

Resource Occurrence and Productivity in Existing and Proposed Wind Energy Lease Areas on the Northeast US Shelf

States in the Northeast United States have the ambitious goal of producing more than 22 GW of offshore wind energy in the coming decades. The infrastructure associated with offshore wind energy development is expected to modify marine habitats and potentially alter the ecosystem services. Species distribution models were constructed for a group of fish and macroinvertebrate taxa resident in the Northeast US Continental Shelf marine ecosystem. These models were analyzed to provide baseline context for impact assessment of lease areas in the Middle Atlantic Bight designated for renewable wind energy installations. Using random forest machine learning, models based on occurrence and biomass were constructed for 93 species providing seasonal depictions of their habitat distributions. We developed a scoring index to characterize lease area habitat use for each species. Subsequently, groups of species were identified that reflect varying levels of lease area habitat use ranging across high, moderate, low, and no reliance on the lease area habitats. Among the species with high to moderate reliance were black sea bass ( Centropristis striata ), summer flounder ( Paralichthys dentatus ), and Atlantic menhaden ( Brevoortia tyrannus ), which are important fisheries species in the region. Potential for impact was characterized by the number of species with habitat dependencies associated with lease areas and these varied with a number of continuous gradients. Habitats that support high biomass were distributed more to the northeast, while high occupancy habitats appeared to be further from the coast. There was no obvious effect of the size of the lease area on the importance of associated habitats. Model results indicated that physical drivers and lower trophic level indicators might strongly control the habitat distribution of ecologically and commercially important species in the wind lease areas. Therefore, physical and biological oceanography on the continental shelf proximate to wind energy infrastructure development should be monitored for changes in water column structure and the productivity of phytoplankton and zooplankton and the effects of these changes on the trophic system.

17 WIND ENERGY↗
DOE OSTI2022

The Genetic Architecture of Nitrogen Use Efficiency in Switchgrass ( Panicum virgatum L.)

Switchgrass (Panicum virgatum L.) has immense potential as a bioenergy crop with the aim of producing biofuel as an end goal. Nitrogen (N)-related sustainability traits, such as nitrogen use efficiency (NUE) and nitrogen remobilization efficiency (NRE), are important factors affecting switchgrass quality and productivity. Hence, it is imperative to develop nitrogen use-efficient switchgrass accessions by exploring the genetic basis of NUE in switchgrass. For that, we used 331 diverse field-grown switchgrass accessions planted under low and moderate N fertility treatments. We performed a genome wide association study (GWAS) in a holistic manner where we not only considered NUE as a single trait but also used its related phenotypic traits, such as total dry biomass at low N and moderate N, and nitrogen use index, such as NRE. We have evaluated the phenotypic characterization of the NUE and the related traits, highlighted their relationship using correlation analysis, and identified the top ten nitrogen use-efficient switchgrass accessions. Our GWAS analysis identified 19 unique single nucleotide polymorphisms (SNPs) and 32 candidate genes. Two promising GWAS candidate genes, caffeoyl-CoA O-methyltransferase (CCoAOMT) and <alfin-like 6(AL6), were further supported by linkage disequilibrium (LD) analysis. Finally, we discussed the potential role of nitrogen in modulating the expression of these two genes. Our findings have opened avenues for the development of improved nitrogen use-efficient switchgrass lines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Increasing evapotranspiration decouples the positive correlation between vegetation cover and warming in the Tibetan plateau

Plant growth generally responds positively to an increase in ambient temperature. Hence, most Earth system models project a continuous increase in vegetation cover in the future due to elevated temperatures. Over the last 40 years, a considerable warming trend has affected the alpine ecosystem across the Tibetan Plateau. However, we found vegetation growth in the moderately vegetated areas of the plateau were negatively related to the warming temperatures, thus resulting in a significant degradation of the vegetative cover (LAI: slope = -0.0026 per year, p < 0.05). The underlying mechanisms that caused the decoupling of the relationship between vegetation growth and warming in the region were elaborated with the analysis of water and energy variables in the ecosystem. Results indicate that high temperatures stimulated evapotranspiration and increased the water consumption of the ecosystem (with an influence coefficient of 0.34) in these degrading areas, significantly reducing water availability (with an influence coefficient of -0.68) and limiting vegetation growth. Moreover, the negative warming effect on vegetation was only observed in the moderately vegetated areas, as evapotranspiration there predominantly occupied a larger proportion of available water (compared to the wet and highly vegetated areas) and resulted in a greater increase in total water consumption in a warmer condition (compared to dry areas with lower levels of vegetation cover). These findings highlight the risk of vegetation degradation in semi-arid areas, with the degree of vulnerability depending on the level of vegetation cover. Furthermore, results demonstrate the central role of evapotranspiration in regulating water stress intensity on vegetation under elevated temperatures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Biochemical responses of hairgrass (Deschampsia caespitosa) to hydrological change

Plant growth and development are closely related to water availability. Water deficit and water excess are detrimental to plants, causing a series of damage to plant morphology, physiological and biochemical processes. In the long evolutionary process, plants have evolved an array of complex mechanisms to combat against stressful conditions. In the present study, the duration-dependent changes in ascorbate (AsA) and glutathione (GSH) contents and activities of enzymes involved in the AsA-GSH cycle in hairgrass ( Deschampsia caespitosa ) in response to water stress was investigated in a pot trial using a complete random block design. The treatments were as follows: (1) heavily waterlogging, (2) moderate waterlogging, (3) light waterlogging, (4) light drought, (5) moderate drought, (6) heavily drought, and (7) a control (CK) with plant be maintained at optimum water availability. The hairgrass plants were subjected to waterlogging or drought for 7, 14, 21 and 28 days and data were measured following treatment. Results revealed that hairgrass subjected to water stress can stimulate enzymatic activities of ascorbate peroxidase (APX), glutathione peroxidase (GPX), glutathione reductase (GR), dehydroascorbate reductase (DHAR), monodehydroascorbate reductase (MDHAR) and L-galactono-1, 4-lactone dehydrogenase (GalLDH), switched on the ascorbate-glutathione (AsA-GSH) cycle and the L-galactose synthesis, up-regulated the contents of AsA and GSH, and maintained higher ratios of ascorbate to dehydroascorbate (AsA/DHA) and reduced glutathione to oxidized glutathione (GSH/GSSG) to alleviate potential oxidative damage. However, the light waterlogging did not induce hairgrass under stress to switch on the AsA-GSH pathway. In general, the critic substances and enzyme activities in AsA-GSH metabolic pathway increased as the increase of water stress intensity. As the increase of exposure duration, the critic antioxidant substances content and enzyme activities increased first and then maintained a relatively stable higher level. Our findings provide comprehensive information on biochemical responses of hairgrass to hydrological change, which would be a major step for accelerating ecological restoration of degradation alpine marshes in the Qinghai-Tibetan Plateau.

Luo, Qiaoyu↗
DOE OSTI2024

Impact of ultraviolet-B radiation on early-season morpho-physiological traits of indica and japonica rice genotypes

Ultraviolet (UV)-B radiation is considered one of the major detrimental rays coming from the Sun. UV-B radiation has a harmful impact on plant growth and development. The effect of UV-B radiation was studied on 64 rice (Oryza sativa L.) genotypes during the vegetative season. An equal number of genotypes from the japonica (50%) and indica (50%) subspecies were phenotyped using the Soil-Plant-Atmosphere-Research (SPAR) units. The 10 kJ UV-B was imposed 12 days after planting (DAP) and continued for three weeks (21 d). Based on the combined ultraviolet-B radiation response index (CUVBRI) for each genotype, the 64 rice genotypes were classified into sensitive, moderately sensitive, moderately tolerant, and tolerant. Various shoot traits, such as plant height, tiller, and leaf numbers, were measured. We also studied critical root phenological traits like root volume, diameter, tips, and forks. Out of all the studied shoot traits, leaf area showed maximum reduction for both indica (54%) and japonica (48%). Among the root traits, root length decreased by negligible (1%) for indica as compared to japonica (5%), while root crossing and forks showed a maximum decline for japonica (37 and 42%), respectively. This study is timely, meaningful, and required because it will help breeders select a tolerant or sensitive rice line for better yield and production under abiotic stresses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Efficacy of the Cell Perturbation Method in Large-Eddy Simulations of Boundary Layer Flow over Complex Terrain

A challenge to simulating turbulent flow in multiscale atmospheric applications is the efficient generation of resolved turbulence motions over an area of interest. One approach is to apply small perturbations to flow variables near the inflow planes of turbulence-resolving simulation domains nested within larger mesoscale domains. While this approach has been examined in numerous idealized and simple terrain cases, its efficacy in complex terrain environments has not yet been fully explored. Here, we examine the benefits of the stochastic cell perturbation method (CPM) over real complex terrain using data from the 2017 Perdigão field campaign, conducted in an approximately 2-km wide valley situated between two nearly parallel ridges. Following a typical configuration for multiscale simulation using nested domains within the Weather Research and Forecasting (WRF) model to downscale from the mesoscale to a large-eddy simulation (LES), we apply the CPM on a domain with horizontal grid spacing of 150 m. At this resolution, spurious coherent structures are often observed under unstable atmospheric conditions with moderate mean wind speeds. Results from such an intermediate resolution grid are often nested down for finer, more detailed LES, where these spurious structures adversely affect the development of turbulence on the subsequent finer grid nest. We therefore examine the impacts of the CPM on the representation of turbulence within the nested LES domain under moderate mean flow conditions in three different stability regimes: weakly convective, strongly convective, and weakly stable. In addition, two different resolutions of the underlying terrain are used to explore the role of the complex topography itself in generating turbulent structures. We demonstrate that the CPM improves the representation of turbulence within the LES domain, relative to the use of high-resolution complex terrain alone. During the convective conditions, the CPM improves the rate at which smaller-scales of turbulence form, while also accelerating the attenuation of the spurious numerically generated roll structures near the inflow boundary. During stable conditions, the coarse mesh spacing of the intermediate LES domain used herein was insufficient to maintain resolved turbulence using CPM as the flow develops downstream, highlighting the need for yet higher resolution under even weakly stable conditions, and the importance of accurate representation of flow on intermediate LES grids.

17 WIND ENERGY↗
DOE OSTI2024

Coercivity of (Fe 0.7 Co 0.3 ) 2 B Nanowire and Its Bonded Magnet

(Fe 0.7 Co 0.3 ) 2 B are potential permanent magnets material due to its large saturation magnetization and high Curie temperature. However, it has moderate magnetocrystalline anisotropy (MCA) and low coercivity. One way to improve its coercivity is to combine the contributions from magnetocrystalline- and magnetic-shape anisotropy by preparing (Fe 0.7 Co 0.3 ) 2 B nanowires. We study the effects of size, morphology, and surface defects on the hard magnetic properties of nanowires using micromagnetic simulation. The hard magnetic properties of (Fe 0.7 Co 0.3 ) 2 B nanowire-bonded magnets are estimated, including the role of inter-wire magnetostatic interaction. By considering the existence of local reductions in MCA energy of up to 30% on the surface layer of nanowires, the anisotropic bonded magnet with a 65% vol. of (Fe 0.7 Co 0.3 ) 2 B nanowires would have typical remanence, B r = 7.6–8.4 kG, coercivity, H ci = 9.6–9.9 kOe, and maximum energy product, (BH) m = 14–17.8 MGOe. Developing effective technology for synthesizing nanowires and fabricating corresponding bonded magnets is promising for manufacturing practical magnets based on the magnetic phase with a relatively low or moderate MCA, such as (Fe 0.7 Co 0.3 ) 2 B.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effectiveness and Long-Term Effects of SER+ FELIZ(mente): A School-Based Mindfulness Program for Portuguese Elementary Students

School-based mindfulness programs (SBMPs) have gained global popularity. Yet, there is a need for more rigorous procedures to develop and assess them. This study aimed to address these limitations by examining the effectiveness of a Portuguese SBMP, called SER + FELIZ(mente). The final sample included 190 third and fourth-graders: 99 in the SBMP group and 91 in a wait-list group. Effects on attentional control, emotional regulation and wellbeing were examined in the short term (T2) and 6 months later (T3). We also tested the moderating role of age, gender, and baseline scores. Using a multilevel modeling approach, results showed a clear benefit of SBMP on emotional wellbeing at T2 but not T3. Despite SBMP students surpassing wait-list students in attentional control, cognitive reappraisal, and social wellbeing at T2, these effects were due to a levelling off among SBMP students, coupled with a decline among wait-list students from T1 to T2. These effects were moderated by age at T3. While universal improvements were limited, our SBMP seemed to have acted as a shield against school stressors (i.e., likely, test anxiety at T2). This opens a new avenue for research concerning the role of SBMPs in preventing (rather than repairing) mental-health issues in elementary students.

Magalhães, Sofia↗