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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Performance evaluation of finned tube heat exchanger using curved wavy delta winglet vortex generators with circular perforations

Vortex generation is recognized as an effective passive approach to improve the heat transfer rate in fin and tube heat exchangers (FTHEs). The current study proposed innovative designs of curved wavy delta winglet vortex generators (CWDWVGs), both without and with circular perforations, to improve the heat transfer efficiency of FTHEs. There is potential to increase heat transfer performance further through various CWDWVG designs. Here, this study explores seven unique CWDWVG configurations, from 1-wave to 7-wave. A 3-D computational numerical model is utilized to evaluate the Thermo-hydraulic performance of FTHEs fitted with these different CWDWVG configurations across Reynolds numbers from 400 to 2000. This comparative analysis of the Thermo-hydraulic performance of FTHEs featuring four parallel circular tube layouts assesses configurations both with and without vortex generators (VGs) and various hole configurations. The evaluation of Thermo-hydraulic performance involves different parameters, including the London area goodness factor (LAGF), Colburn factor (j), friction factor (f), pressure drop (?P), and Nusselt number (Nu). Results demonstrate that the various CWDWVG configurations and the number of holes in them substantially affect the efficiency, as evaluated by the dimensionless Performance Evaluation Criteria (PEC). Notably, the 7-wave CWDWVGs surpassed other configurations, and integrating circular punched perforations further improved the thermal-hydraulic performance of FTHE. Specifically, the 7-wave CWDWVGs without holes demonstrated superior performance over other configurations, showing a significant increase in Nusselt number by 75.18% and 85.16% at Reynolds numbers of 2000 and 400, respectively, alongside an increase in pressure drop by 216.38% to 224.96%. Meanwhile, the 7-wave CWDWVGs with eight holes, in comparison to those without holes, exhibited a Nusselt number increase of 0.85%, a pressure drop decrease of 7.31%, and a reduction in the friction factor by 5.82%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Regulation of muscle hypertrophy: Involvement of the Akt-independent pathway and satellite cells in muscle hypertrophy

Highlights: • Involvement of Akt-independent mTOR activation in early mechanical overload. • Re-recognized critical roles of MuSCs in mechanical load-dependent muscle hypertrophy. • mTOR and MuSCs are involved in sarcopenia. Skeletal muscles are composed of multinuclear cells called myofibers and have unique abilities, one of which is plasticity. In response to the mechanical load induced by physical activity, skeletal muscle exerts several local adaptations, including an increase in myofiber size and myonuclear number, known as muscle hypertrophy. Protein synthesis and muscle satellite cells (MuSCs) are mainly responsible for these adaptations. However, the upstream signaling pathways that promote protein synthesis remain controversial. Further, the necessity of MuSCs in muscle hypertrophy is also a highly debated issue. In this review, we summarized the insulin-like growth factor 1 (IGF-1)/Akt-independent activation of mammalian target of rapamycin (mTOR) signaling in muscle hypertrophy and the involvement of mTOR signaling in age-related loss of skeletal muscle function and mass and in sarcopenia. The roles and behaviors of MuSCs, characteristics of new myonuclei in muscle hypertrophy, and their relevance to sarcopenia have also been updated in this review.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Towards POI-based large-scale land use modeling: spatial scale, semantic granularity, and geographic context

The combination of spatial distribution, semantic characteristics, and sometimes temporal dynamics of POIs inside a geographic region can capture its unique land use characteristics. Most previous studies on POI-based land use modeling research focused on one geographic region and select one spatial scale and semantic granularity for land use characterization. There is a lack of understanding on the impact of spatial scale, semantic granularity, and geographic context on POI-based land use modeling, particularly large-scale land use modeling. In this study, we developed a scalable POI-based land use modeling framework and examined the impact of these three factors on POI-based land use characterization using data from three geographic regions. We developed a unified semantic representation framework for POI semantics that can help fuse heterogeneous POI data sources. Then, by combining POIs with a neural network language model, we developed a spatially explicit approach to learn the embedding representation of POIs and AOIs. We trained multiple supervised classifiers using AOI embeddings as input features to predict AOI land use at different semantic granularities. The classification performance of different land use classes was analyzed and compared across three geographic regions to identify the semantic representativeness of POI-based AOI embedding and the impact of geographic context.

58 GEOSCIENCES↗
DOE OSTI2020

Partitioning net carbon dioxide fluxes into photosynthesis and respiration using neural networks

The eddy covariance (EC) technique is used to measure the net ecosystem exchange (NEE) of CO 2 between ecosystems and the atmosphere, offering a unique opportunity to study ecosystem responses to climate change. NEE is the difference between the total CO 2 release due to all respiration processes (RECO), and the gross carbon uptake by photosynthesis (GPP). These two gross CO 2 fluxes are derived from EC measurements by applying partitioning methods that rely on physiologically based functional relationships with a limited number of environmental drivers. However, the partitioning methods applied in the global FLUXNET network of EC observations do not account for the multiple co-acting factors that modulate GPP and RECO flux dynamics. To overcome this limitation, we developed a hybrid data-driven approach based on combined neural networks (NN C-part ). NN C-part incorporates process knowledge by introducing a photosynthetic response based on the light-use efficiency (LUE) concept, and uses a comprehensive dataset of soil and micrometeorological variables as fluxes drivers. We applied the method to 36 sites from the FLUXNET2015 dataset and found a high consistency in the results with those derived from other standard partitioning methods for both GPP (R 2 > .94) and RECO (R 2 > .8). High consistency was also found for (a) the diurnal and seasonal patterns of fluxes and (b) the ecosystem functional responses. NNC-part performed more realistic than the traditional methods for predicting additional patterns of gross CO 2 fluxes, such as: (a) the GPP response to VPD, (b) direct effects of air temperature on GPP dynamics, (c) hysteresis in the diel cycle of gross CO 2 fluxes, (d) the sensitivity of LUE to the diffuse to direct radiation ratio, and (e) the post rain respiration pulse after a long dry period. In conclusion, NN C-part is a valid data-driven approach to provide GPP and RECO estimates and complementary to the existing partitioning methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

National Ignition Facility Opacity Time Resolved Spectrometer Systems Engineering Final Project

The National Ignition Facility (NIF) is the world’s largest and most energetic laser facility. The NIF system is designed to produce high energy density (temperature and pressure) conditions through the application of its 192 laser beams. One of the users of NIF is the opacity platform developed to study the opacities at temperatures and densities relevant to the solar interior and stellar evolution. The platform was developed to study iron (Fe) opacity at temperatures relevant to the solar interior. The opacity campaign uses spectrometers to gather data. Spectrometers utilize crystals to produce x-ray spectra that are recorded on time-integrated and time-resolved detectors. The opacity spectrometer (OpSpec) currently fielded and in use at NIF uses a time integrated film channel to collect data. The opacity spectrometer time resolved (OpSpecTR) will utilize novel hCMOS detectors to capture time resolved images of spectra of interest. The key stakeholders identified for OpSpecTR included the physicists responsible for OpSpec and OpSpecTR, the Target Area Science and Engineering (TASE) department at NIF, the NIF and Photon Science (NIF & PS) Opacity program, the Nevada National Security Site (NNSS) Physics and Engineering program, the Sandia hCMOS manufacturing and testing program, and the Los Alamos National Laboratory (LANL) program sponsor. The Target and Experimental Operations (TEXOPS) was identified as a key stakeholder because the group includes the individuals that will physically interact with the OpSpecTR system as it participates in NIF experiments. The opacity platform collects data in a unique orientation relative to the existing diagnostics fielded at NIF. The existing infrastructure at NIF uses a diagnostic manipulator (DIM) to insert the diagnostic near the target chamber center to collect data during a NIF shot. Existing diagnostics collect data through the center line of the DIM axis and collect relevant data perpendicular to this axis. The opacity platform requires crystals mounted in a specific orientation which requires data collection parallel to the DIM axis. This deviation from standard NIF practices was a key factor in developing requirements.

42 ENGINEERING↗
DOE OSTI2023

Mining the Penicillium expansum Genome for Virulence Genes: A Functional-Based Approach to Discover Novel Loci Mediating Blue Mold Decay of Apple Fruit

Blue mold, a postharvest disease of pome fruits, is caused by the filamentous fungus Penicillium expansum. In addition to the economic losses caused by P. expansum, food safety can be compromised, as this pathogen is mycotoxigenic. In this study, forward and reverse genetic approaches were used to identify genes involved in blue mold infection in apple fruits. For this, we generated a random T-DNA insertional mutant library. A total of 448 transformants were generated and screened for the reduced decay phenotype on apples. Of these mutants, six (T-193, T-275, T-434, T-588, T-625, and T-711) were selected for continued studies and five unique genes were identified of interest. In addition, two deletion mutants (Δt-625 and Δt-588) and a knockdown strain (t-434 KD ) were generated for three loci. Data show that the Δt-588 mutant phenocopied the T-DNA insertion mutant and had virulence penalties during apple fruit decay. We hypothesize that this locus encodes a glyoxalase due to bioinformatic predictions, thus contributing to reduced colony diameter when grown in methylglyoxal (MG). This work presents novel members of signaling networks and additional genetic factors that regulate fungal virulence in the blue mold fungus during apple fruit decay.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Linear and Nonlinear Solvers for Simulating Multiphase Flow within Large-Scale Engineered Subsurface Systems

Simulation of multiphase flow in the subsurface is well-known to be computationally challenging. While there have been many studies that have explored approaches to overcoming these challenges, they often utilize relatively simple case studies. In this paper, we focus on the unique numerical challenges posed by modeling large-scale engineered subsurface systems, characterized by discrete features embedded in a heterogeneous natural subsurface setting. The man-made features such as shafts, tunnels, and barriers often cause multiple challenges in modeling the domain for multiphase porous media flow. This flow scenario can have a wide range of applications such as nuclear waste repositories, enhanced recovery of a petroleum reservoir, geothermal engineering, and carbon sequestration. An example of these severe numerical challenges is the case of performance assessment (PA) for Waste Isolation Pilot Plant (WIPP), the only operating deep geological repository in the US, which simulates extreme material properties of bedded salt rock formation and extreme contrast due to open excavation next to the formation. The models have extremes not only of permeability and porosity but also of the constitutive models needed for multiphase flow; additionally, they have process models like salt creep closure reducing porosity over time, fracturing in clay and anhydrite interbeds of the bedded salt, gas generation from the waste materials, and unintentional human borehole intrusions in some scenarios. Numerical simulations require the solution of coupled systems of nonlinear PDEs; in our work, we use the open-source simulator PFLOTRAN which is based on Finite Volume discretization. The solution of the nonlinear equations requires use of the Newton-Raphson iteration at each time step, which entails the solution of the linearized Jacobian system at each iteration. The effects of all the processes (i.e., large number of unknowns, highly nonlinear constitutive relations, large contrasts in material properties in short distances) lead to an ill-conditioned Jacobian matrix that severely challenges traditional linear solver, i.e., stabilized biconjugate gradient with block Jacobi incomplete LU preconditioner (BCGS-ILU) leading to non-convergence for traditional Newton-Raphson nonlinear solver causing unacceptably long computation time for each model. This paper presents linear solvers such as constrained pressure residual (CPR) two-stage preconditioner with alternate-block-factorization (ABF) and quasi- implicit pressure and explicit saturation (QIMPES) decouplers and flexible generalized residual solver (FGMRES). The new general-purpose nonlinear solver, Newton trust-region dogleg Cauchy (NTRDC), is also introduced to resolve extreme nonlinearities in the models. We demonstrate the effectiveness of each method relative to the default BCGS-Newton solver. The two best cases had nearly 50 times speed-up and achieved completion of a simulation in 14 hours that never completed due to non-convergence with the default solver. We also investigate the strong scalability of each method and discuss some of the deficiencies found for Block Jacobi preconditioner using parallel domain decomposition, and node packing effects of modern processor architecture.

Preconditioner, Nonlinear, Porous media, Multiphas↗
DOE OSTI2020

Ecohydrology of wetland plant communities along an estuarine to tidal river gradient

Abiotic filters that interact with wetland plant communities along tidal–fluvial gradients are highly dynamic, and understanding their quantitative thresholds and relationships to interspecific competition is important during an era of sea-level rise and watershed hydrologic change. Yet, landscape-scale studies of major coastal rivers from the river mouth to the head of tide, such as this study, remain rare. Here, we develop a new predictive framework for estuarine–tidal river research and management using a river-specific low-water datum and the wetland inundation indicator SEVg, the growing-season sum exceedance value of hourly surface-water depth. The distribution and variability of the wetland species pool (n = 203) on the 234 river kilometer (rkm) lower Columbia River and estuary floodplain are described for the first time. 4,940 quadrats at 50 marshes were surveyed (2005–2016). Throughout the estuarine–tidal river system, SEVg was well suited to describe the wetland inundation regime and its variability based on the combination of longitudinal river position and elevation. SEVg increased significantly landward. Two primary wetland inundation regimes were identified: the seaward-tidal, usually greatest during the winter months, and landward-fluvial, greatest during the growing season. Nearest the ocean, salinity is the abiotic factor limiting species richness and non-native species. Farther upriver, the daily, seasonal, and interannual variability of the wetting and drying cycle encourage disturbance-tolerant species and non-natives and limit the number of hydrophytes and total vegetative cover. Hence, the average between-year similarity of site-scale areal cover significantly decreased landward. Hierarchical cluster analysis indicated five vegetative groups and five ecohydrologic zones between rkm 0 and 234 were discriminated with 76 significant species–zone associations. All zones had unique indicator species. Species with high indicator values were Carex lyngbyei throughout the estuarine zones, and Eleocharis palustris, Sagittaria latifolia, and the invasive non-native Phalaris arundinacea in the upper estuarine and lower, middle, and upper tidal river zones (IV > 0.90). Competition from C. lyngbyei nearest the ocean and P. arundinacea in the tidal river was associated with reduced species richness when total cover was >65%. This framework of filters informs the design and prediction of future wetland plant communities on coastal river floodplains.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Quantitative relationships between film morphology, charge carrier dynamics, and photovoltaic performance in bulk-heterojunction binary vs. ternary acceptor blends

Addressing pertinent and perplexing questions regarding why nonfullerene acceptors (NFAs) promote higher power conversion efficiencies (PCEs) than traditional fullerenes and how photoactive bulk heterojunction (BHJ) film morphology, charge photogeneration, and recombination dynamics dictate solar cell performance have stimulated many studies of polymer solar cells (PSCs), yet quantitative relationships remain limited. Better understanding in these areas offers the potential to advance materials design and device engineering, afford higher PCEs, and ultimate commercialization. Here we probe quantitative relationships between BHJ film morphology, charge carrier dynamics, and photovoltaic performance in model binary and ternary blend systems having a wide bandgap donor polymer, a fullerene, and a promising NFA. We show that optimal PC 71 BM incorporation in a PBDB-TF:ITIC-Th binary system matrix retains the original π-face-on orientation, ITIC-Th crystallinity and BHJ film crystallite dimensions, and reduces film upper surface ITIC-Th segregation. Such morphology changes together simultaneously increase hole (μ h ) and electron (μ e ) mobilities, facilitate light-activated ITIC-Th to PC 71 BM domain electron delocalization, reduce free charge carrier (FC) bimolecular recombination (BR) within PBDB-TF:ITIC-Th mixed regions, and increase FC extraction pathways viaPBDB-TF:PC 71 BM pairs. The interplay of these effects yields significantly enhanced inverted cell short-circuit current density (J SC ), fill factor (FF), and PCE. Unexpectedly, we also find that excessive PC 71 BM in the PBDB-TF:ITIC-Th binary system alters the PBDB-TF orientation to π-edge-on, increases large scale PC 71 BM-rich aggregations and BHJ upper surface PC 71 BM composition. Further, these morphology changes increase parasitic decay processes such as intersystem crossing from photoexcited PC 71 BM, compromising the J SC , FF, and PCE metrics. ITIC-Th X-ray diffraction reveals a unique sidechain-dominated molecular network with previously unknown sidechain-end group stacking, rationalizing the STEM and GIWAXS results, photophysics, and the high μ e . DFT computation reveals charge transfer networks within ITIC-Th crystallites, supporting excited-state electron delocalization from ITIC-Th to PC 71 BM. This structure–property understanding leads to a newly reported NFA blend with PCE near 17%.

14 SOLAR ENERGY↗
DOE OSTI2025

Insight into the deformation features and capacity loss mechanisms of lithium-ion pouch cells under spherical indentation conditions

Mechanical deformation under extreme conditions is one of the important reasons for the failure of lithium-ion batteries in automotive application. However, the deformation features and component failure of lithium-ion cells to external loading has never been a design consideration. Here, in this study, we conduct spherical indentation tests on a dozen of lithium-ion cells with different capacities under different control mode conditions to investigate their deformation features and capacity loss mechanisms. The experimental results show that, under mechanical deformation conditions, internal faults of cells occur in stages, and energy accumulation and sudden release are two key processes of cell's mechanical failure. The cells' state of charge is the main factor affecting their thermal runaway behaviors. In addition, a finite element model is developed to simulate the deformation features and the failure mechanism of key components of lithium-ion pouch cells; the 3D x-ray computed tomography is employed to demonstrate its internal configuration. With this model, the force-strain response, the deformation features as well as the size of the failure area of lithium-ion cells under spherical indentation conditions are accurately predicted. In 3D x-ray computed tomography images, unique mud cracks in cooper current collector are observed, and the influence mechanisms of the isolated fragments on the cell capacities are revealed. These results may provide useful information for the mechanical structure design of the components of lithium-ion pouch cells.

25 ENERGY STORAGE↗
DOE OSTI2025

Pathology and Therapeutic Significance of Fibroblast Growth Factors

The fibroblast growth factor (FGF) family includes 22 proteins in humans. Based on their mode of action, there are three families of FGFs: paracrine FGFs (FGF 1–10, 16, 17, 18, 20, and 22), intracrine FGFs (FGF 11–14), and endocrine FGFs (FGF 19, 21, and 23). FGF signaling plays critical roles in embryonic development, tissue repair, regeneration, angiogenesis, and metabolic regulation. They exert their cellular functions by binding, dimerization, and activation of transmembrane FGF receptors (FGFRs). Aberrant FGF signaling is associated with various human diseases. Thus, understanding the unique properties of FGF signaling will help to explore new therapeutic interventions against FGF-mediated pathological conditions. This review will discuss the differential expression and regulation of each FGF under normal human physiological and pathological conditions. Moreover, we will outline current therapeutics and treatment strategies that have been developed against FGF-related pathology.

Edirisinghe, Oshadi↗
DOE OSTI2025

A bipartite bacterial virulence factor targets the complement system and neutrophil activation

Abstract The complement system and neutrophils constitute the two main pillars of the host innate immune defense against infection by bacterial pathogens. Here, we identify T-Mac, a novel virulence factor of the periodontal pathogen Treponema denticola that allows bacteria to evade both defense systems. We show that T-Mac is expressed as a pre-protein that is cleaved into two functional units. The N-terminal fragment has two immunoglobulin-like domains and binds with high affinity to the major neutrophil chemokine receptors FPR1 and CXCR1, blocking N -formyl-Met-Leu-Phe- and IL-8-induced neutrophil chemotaxis and activation. The C-terminal fragment functions as a cysteine protease with a unique proteolytic activity and structure, which degrades several components of the complement system, such as C3 and C3b. Murine infection studies further reveal a critical T-Mac role in tissue damage and inflammation caused by bacterial infection. Collectively, these results disclose a novel innate immunity-evasion strategy, and open avenues for investigating the role of cysteine proteases and immunoglobulin-like domains of gram-positive and -negative bacterial pathogens.

Kurniyati, Kurni↗
DOE OSTI2025

Alfvén mode spectrum in the advanced steady-state tokamak scenario with negative triangularity

In the earlier studies [Zheng et al. Fundam. Plasma Phys. 10, 100051 (2024)], the negative triangularity tokamak was shown to have a unique and outstanding feature for the steady-state confinement. In addition to relieving the divertor heat load concern, it can reach a much higher beta limit in the nearly steady-state confinement, about twice the Troyon limit in the positive triangularity case. In this work, we extend the investigation to the Alfvén spectrum and toroidal Alfvén eigenmodes (TAEs). This helps to evaluate the property of energetic particle confinement in this advanced scenario of a negative triangularity tokamak. We found that, because of the large safety factor and reversed magnetic shear in the core plasma region near the magnetic axis, the TAE gap tends to be closed or have only a short radial extension between the continua. in the on-axis core region and open primarily in the off-axis region, where TAEs are shown to be present. This indicates that energetic particle confinement in the core region near the magnetic axis, where nuclear fusion reactions prevail, is not seriously affected by the excitation of TAEs in this scenario. The configuration with off-axis TAEs helps the confinement of energetic particles as compared to the configuration with near-axis TAEs. The results show that the advanced steady-state tokamak scenario with negative triangularity, because of the rapid variation of the safety factor, also has a favorable feature for energetic particle confinement.

Fourier analysis↗
DOE OSTI2020

Climate Influences on Capacity Expansion Planning with Application to the Western U.S

Electric power system planners utilize a variety of planning tools to inform decisions concerning generation and transmission additions to the electric grid, the need for operational changes, and to evaluate potential stressors on the system. Numerous factors contribute to the planning process including projected fuel and technology costs, policy and load profiles. There is also a growing recognition of the interdependency of the electric grid with other natural and engineered systems. Here we explore how future climate change and hydropower operability might influence decisions related to electricity capacity expansion planning and operations. To do so we assemble a multi-model framework. Specifically, water resource modeling is used to simulate climate impacts on future water supply for thermoelectric and hydropower generation. Separately, temperature impacts on electricity load are evaluated. Together, these climate factors spatially constrain a capacity expansion model that projects generation and transmission additions to the grid. The projected new capacity-builds are then evaluated on their operations, reliability, and cost under average and extreme climate conditions using production cost modeling. This coupled framework is demonstrated on the electric grid in the Western U.S., supporting capacity expansion planning by WECC, the North American Electric Reliability Corporation (NERC) regional entity responsible for reliability assurance of the Western Interconnection. This region was selected in part because the West is unique in that it has high potential for renewable penetrations and is experiencing large retirements/displacements of baseload resources, primarily coal, leading to possible operational challenges in terms of changing resource mix and the need for resource flexibility. Toward this challenge, planning scenarios encompass a range of alternative energy, climate and drought futures. In this context we explore answers to two strategic questions: 1) How does changing climate influence electricity expansion planning (generation and transmission) and future operations, including type and capacity of new builds, system reliability, cost and environmental impacts? 2) How does the representation of hydropower in the modeling framework influence the evaluation of bulk power system operations? Results indicate that climate has a measurable influence on recommendations concerning the capacity, type and location of new generation and transmission additions, with up to 17 GW additional capacity needed by 2038 to meet peak loads (~6.6% increase over capacity-builds based on historical climate). The extent of additional infrastructure needs is strongly influenced by future water availability for hydropower and the potential deployment of demand response technologies. Systems designed for future climate conditions were found to maintain high system reliability under a range of electricity and water availability scenarios (including significant drought), with minimal system curtailments. Additional capacity needs due to higher load tend to increase cumulative 20-year investment and operating costs by $\$$5-$\$$17 billion and generation costs increase by 9 to 19%. Finally, changing the representation of hydropower flexibility has a relatively small influence on capacity expansion in the Western Interconnection through 2038, but hydropower flexibility impacts generation costs to a similar extent as climate.

13 HYDRO ENERGY↗
DOE OSTI2022

Does mycorrhizal symbiosis determine the climate niche for Populus as a bioenergy feedstock?

This is the final technical and scientific report for DE-SC0016097, in which we investigated the role of symbiotic fungi in determining the climatic niche of trees. While microbes have long been viewed as agents of disease, recent explorations of the microbiome have led biologists to recognize that beneficial microbes play an equally vital role in maintaining the health of plants and animals. Perhaps the most ubiquitous form of beneficial interaction in terrestrial ecosystems occurs between fungi and plant roots. These fungus-root, or “mycorrhizal”, symbioses involve the reciprocal exchange of plant sugars for soil nutrients obtained by the fungus, such as nitrogen and phosphorous, which are critical for plant growth. It is known that mycorrhizal associations are widespread - occurring in approximately 90% of plant species - and diverse, with single plants able to associate simultaneously with over 100 species of fungi. Despite this, the ecological factors that control large-scale distribution and abundance of mycorrhizal symbioses are still poorly known, making it challenging to predict how mycorrhizal symbioses may change in future climate conditions or how these fungal communities might be manipulated to improve regional agriculture or forestry projects. In this research project we focused on a native North American tree with strong biofuel potential – Populus – to answer fundamental questions about the role of climate, soil environment, and mycorrhizal interactions in determining growth and competition in plant communities. Populus provides a unique opportunity for ecologically relevant experiments because of its widespread distribution across North America and its natural variability in mycorrhizal association types.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Extrapolation Domains for Aggregating Environmental Outcomes from Local to Regional Levels

Billions of dollars are invested every year to run field experiments to quantify the response of crops to new technologies and associated environmental outcomes. Given the diversity of environments where crop production occurs, conducting these research studies without a robust framework for research site selection and upscaling results to larger spatial scales is inefficient. In this project, researchers from the University of Nebraska-Lincoln used their unique Technology Extrapolation Domains framework (TED) as a tool to guide the selection of experimental sites and as basis for aggregating and validating environmental outcomes from local to regional levels. In the present project, we first used the TED framework to evaluate the current distribution and area coverage of the current SMARTFARM sites. The purpose was to showcase how it is possible to use the TED framework to guide site selection and extrapolate results over space. Additionally, the original TED framework was expanded to account for other factors influencing environmental outcomes by inclusion of three additional variables: soil organic matter, soil texture, and topographic wetness index. The resulting expanded framework (TED-E) was validated using nitrogen (N) losses from corn in the United States as a case study. To do so, we used N balance as a proxy to N losses and we evaluated the capacity of the framework to explain variation in N balance across fields and across countries. We found that the TED-E has substantially higher predictive power than the original TED framework to explain spatial variation in N balance. However, improvements in predictive power with the TED-E tool come at the expense of a higher number of TEDs needed to achieve a given crop area coverage compared with the original TED framework. We conclude that the new TED-E framework can help aggregate and extrapolate environmental outcomes from research sites to regional levels and improve the visualization of their spatial patterns across the United States. An online version of the framework is available at: https://www.toolted.org/

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Understanding Geometry and Microstructure Interactions In LPBF By Linking Lab Scale Studies To Real Part Case Examples

The mechanical properties derived from simple tensile tests are uniquely important in the design and qualification of load bearing metallic components. The tensile properties in standards for wrought metallic materials are generally accessible for design and simulation engineers, but this is not the case for additively manufactured metals. This work investigates the influence of tensile specimen geometry on the mechanical properties of laser powder bed fusion (LPBF) additively manufactured Ti-6Al-4V, particularly in relation to properties measured from specimens excised from an exemplar part. A comprehensive analysis was conducted across various specimen geometries, considering factors such as thermal history, cross-sectional area, shape, and surface roughness. Key findings reveal that sample size, particularly cross-sectional area, significantly affects reported tensile properties, with ASTM E8 flat and round specimens exhibiting differences in elastic modulus (13%), yield strength (17%), ultimate tensile strength (UTS) (14%), and elongation to failure (11%). Additionally, surface roughness was found to have a limited impact on ASTM round geometries, but it becomes critical in thin-walled and small high-throughput samples. The ASTM flat samples closely matched the properties of samples excised from the exemplar part, underscoring the necessity of testing witness samples that accurately represent end-use conditions. Furthermore, mechanical properties of samples built within the stitch zone of the exemplar part demonstrated reduced ductility, highlighting the importance of laser alignment and qualification in multi-laser additive manufacturing processes. Overall, this study emphasizes the need for careful consideration of specimen geometry and testing conditions to ensure accurate reporting of mechanical properties in LPBF Ti-6Al-4V.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Real-Time Artificial Intelligence for Particle Reconstruction and Higgs Physics

With the discovery of the Higgs boson at the CERN LHC, the world's highest-energy particle accelerator complex, scientists have acquired an important tool to study the fundamental building blocks of the universe. Precision measurements of Higgs bosons produced with large momentum allow for unique insights into the structure of the interactions of the Higgs boson with other particles that may shed light on physics beyond the standard model. While experimentally challenging, exploring such interactions with novel artificial intelligence (AI) methods can advance our understanding of the Higgs sector, including the Higgs boson's self-interaction. Moreover, the LHC is undergoing a major upgrade to further increase its particle collision rate and thereby operate for an additional decade. The experimental detectors at the upgraded facility must process at least a factor of ten more data at rates of hundreds of terabytes per second all under challenging conditions. New AI techniques are required to reconstruct and select, or trigger on, the most physics-sensitive events in real-time to handle the resulting avalanche of data. The proposed research will achieve the goals of the LHC program at the CMS experiment by developing a sub-microsecond event reconstruction system using real-time AI algorithms that employ field-programmable gate array technologies. By harnessing sophisticated AI techniques, this research focuses on measuring the production of Higgs bosons at large momentum while enhancing particle reconstruction methods in the trigger and beyond. Overall, the proposed research has broader implications for the use of AI in resource-constrained, low-latency embedded applications across all fields of science.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗