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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Quantifying spatial and vertical variations in soil C:N relationships in permafrost-affected landscapes

Permafrost regions are experiencing rapid changes that affect carbon (C) and nitrogen (N) cycles, with implications for vegetation dynamics and gas exchanges with the atmosphere. Soil C:N ratio is a key indicator of organic matter quality, yet spatial estimates of N stocks and C:N ratios lag behind those for C. We used quantile regression forests to compare direct and indirect digital soil mapping approaches for predicting soil C:N ratios at 0–30, 30–60, and 60–100 cm depths across a latitudinal transect in Alaska. The indirect approach – deriving C:N from separately predicted C and N stocks – outperformed direct mapping for the surface layer (0–30 cm), while direct mapping was marginally better at greater depths. However, prediction accuracy decreased with depth for both methods. Temperature and topography were the most important predictors. Both approaches overestimated low and underestimated high C:N ratios, with direct mapping showing greater bias. Our results underscore the challenges of modeling C:N ratios in heterogeneous, data-sparse permafrost soils, but also suggest that indirect mapping holds promise if supported by more extensive datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Optimizing the optimizer for physics-informed neural networks and Kolmogorov-Arnold networks

Physics-Informed Neural Networks (PINNs) have revolutionized the computation of PDE solutions by integrating partial differential equations (PDEs) into the neural network’s training process as soft constraints, becoming an important component of the scientific machine learning (SciML) ecosystem. More recently, physics-informed Kolmogorv-Arnold networks (PIKANs) have also shown to be effective and comparable in accuracy with PINNs. In their current implementation, both PINNs and PIKANs are mainly optimized using first-order methods like Adam, as well as quasi-Newton methods such as BFGS and its low-memory variant, L-BFGS. However, these optimizers often struggle with highly nonlinear and non-convex loss landscapes, leading to challenges such as slow convergence, local minima entrapment, and (non)degenerate saddle points. In this study, we investigate the performance of Self- Scaled BFGS (SSBFGS), Self-Scaled Broyden (SSBroyden) methods and other advanced quasi-Newton schemes, including BFGS and L-BFGS with different line search strategies. These methods dynamically rescale updates based on historical gradient information, thus enhancing training efficiency and accuracy. We systematically compare these optimizers – using both PINNs and PIKANs – on key challenging PDEs, including the Burgers, Allen-Cahn, Kuramoto-Sivashinsky, Ginzburg-Landau, and Stokes equations. Additionally, we evaluate the performance of SSBFGS and SSBroyden for Deep Operator Network (DeepONet) architectures, demonstrating their effectiveness for data-driven operator learning. Our findings provide state-of-the-art results with orders-of-magnitude accuracy improvements without the use of adaptive weights or any other enhancements typically employed in PINNs. More broadly, our work reveal insights into the effectiveness of quasi-Newton optimization strategies in significantly improving the convergence and accurate generalization of PINNs and PIKANs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-Wi6 Pine barrens #1 (PB1)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Wi6 Pine barrens #1 (PB1). This is the FLUXNET version of the carbon flux data for the site US-Wi6 Pine barrens #1 (PB1) produced by applying the standard ONEFlux (1F) software. Site Description - The Wisconsin Pine Barrens site is located in the Washburn Ranger District of the northeastern section of Chequamegon National Forest. A member of the northern coniferous-deciduous biome, surveys from the mid-19th century indicate the region consisted of a mixed stand of red, white, and jack pines. After extensive timber harvesting, wildfires, and farming activity, the region turned into a fragmented mosaic of stands of various ages and composition. As an assemblage, the ten Wisconsin sites are indicative of the successional stages of development in the predominant stand types of a physically homogeneous landscape. In order to establish and maintain both natural and plantation jack pine stands, pine barrens undergo prescribed burns and harvesting rotations. Pine Barrens occupy 17% of the region in 2001.

Chen, Jiquan↗
DOE OSTI2023

Portable Programming Model Exploration for LArTPC Simulation in a Heterogeneous Computing Environment: OpenMP vs. SYCL

The evolution of the computing landscape has resulted in the proliferation of diverse hardware architectures, with different flavors of GPUs and other compute accelerators becoming more widely available. To facilitate the efficient use of these architectures in a heterogeneous computing environment, several programming models are available to enable portability and performance across different computing systems, such as Kokkos, SYCL, OpenMP and others. As part of the High Energy Physics Center for Computational Excellence (HEP-CCE) project, we investigate if and how these different programming models may be suitable for experimental HEP workflows through a few representative use cases. One of such use cases is the Liquid Argon Time Projection Chamber (LArTPC) simulation which is essential for LArTPC detector design, validation and data analysis. Following up on our previous investigations of using Kokkos to port LArTPC simulation in the Wire-Cell Toolkit (WCT) to GPUs, we have explored OpenMP and SYCL as potential portable programming models for WCT, with the goal to make diverse computing resources accessible to the LArTPC simulations. In this work, we describe how we utilize relevant features of OpenMP and SYCL for the LArTPC simulation module in WCT. We also show performance benchmark results on multi-core CPUs, NVIDIA and AMD GPUs for both the OpenMP and the SYCL implementations. Comparisons with different compilers will also be given where appropriate.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-Wi0 Young red pine (YRP)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Wi0 Young red pine (YRP). This is the FLUXNET version of the carbon flux data for the site US-Wi0 Young red pine (YRP) produced by applying the standard ONEFlux (1F) software. Site Description - The Wisconsin Young Red Pine site is located in the Washburn Ranger District of the northeastern section of Chequamegon National Forest. A member of the northern coniferous-deciduous biome, surveys from the mid-19th century indicate the region consisted of a mixed stand of red, white, and jack pines. After extensive timber harvesting, wildfires, and farming activity, the region turned into a fragmented mosaic of stands of various ages and composition. As an assemblage, the ten Wisconsin sites are indicative of the successional stages of development in the predominant stand types of a physically homogeneous landscape. Thinned every 7 years until they reach 100 to 150 years of age, the red pine plantations of all ages occupy approximately 25% of the region.

Chen, Jiquan↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-Wi4 Mature red pine (MRP)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Wi4 Mature red pine (MRP). This is the FLUXNET version of the carbon flux data for the site US-Wi4 Mature red pine (MRP) produced by applying the standard ONEFlux (1F) software. Site Description - The Wisconsin Mature Red Pine site is located in the Washburn Ranger District of the northeastern section of Chequamegon National Forest. A member of the northern coniferous-deciduous biome, surveys from the mid-19th century indicate the region consisted of a mixed stand of red, white, and jack pines. After extensive timber harvesting, wildfires, and farming activity, the region turned into a fragmented mosaic of stands of various ages and composition. As an assemblage, the ten Wisconsin sites are indicative of the successional stages of development in the predominant stand types of a physically homogeneous landscape. Thinned every 7 years until they reach 100 to 150 years of age, the red pine plantations of all ages occupy approximately 25% of the region.

Chen, Jiquan↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-Wi9 Young Jack pine (YJP)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Wi9 Young Jack pine (YJP). This is the FLUXNET version of the carbon flux data for the site US-Wi9 Young Jack pine (YJP) produced by applying the standard ONEFlux (1F) software. Site Description - The Wisconsin Young Jack Pine site is located in the Washburn Ranger District of the northeastern section of Chequamegon National Forest. A member of the northern coniferous-deciduous biome, surveys from the mid-19th century indicate the region consisted of a mixed stand of red, white, and jack pines. After extensive timber harvesting, wildfires, and farming activity, the region turned into a fragmented mosaic of stands of various ages and composition. As an assemblage, the ten Wisconsin sites are indicative of the successional stages of development in the predominant stand types of a physically homogeneous landscape. Clearcut on 40 to 70 year intervals, jack pine stands occupy approximately 13% of the region.

Chen, Jiquan↗
DOE OSTI2020

Positron orbit effects during injection and confinement in a magnetic dipole trap

Lossless injection of positrons into a magnetic dipole trap and their subsequent confinement have been demonstrated. Here, we investigate by numerical single-particle simulations how the radial distribution of positrons in the trap is affected by the measurement itself, the choice of injection parameters, the asymmetry of the electric potential, and by elastic collisions. The results are compared to experimental data. A comprehensive understanding of these effects is a milestone on the road to creating an electron–positron plasma in a trap with a levitating superconducting coil.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A high-throughput workflow to analyze sequence-conformation relationships and explore hydrophobic patterning in disordered peptoids

Understanding how a macromolecule’s primary sequence governs its conformational landscape is crucial for elucidating its function, yet these design principles are still emerging for macromolecules with intrinsic disorder. Herein, we introduce a high-throughput workflow that implements a practical colorimetric conformational assay, introduces a semi-automated sequencing protocol using matrix-assisted laser desorption/ionization and tandem mass spectrometry (MALDI-MS/MS), and develops a generalizable sequence-structure algorithm. Using a model system of 20mer peptidomimetics containing polar glycine and hydrophobic N-butylglycine residues, we identified nine classifications of conformational disorder and isolated 122 unique sequences across varied compositions and conformations. Conformational distributions of three compositionally identical library sequences were corroborated through atomistic simulations and ion mobility spectrometry coupled with liquid chromatography. A data-driven strategy was developed using existing sequence variables and data-derived “motifs” to inform a machine-learning algorithm toward conformation prediction. Here, this multifaceted approach enhances our understanding of sequence-conformation relationships and offers a powerful tool for accelerating the discovery of materials with conformational control.

data-driven analysis↗
DOE OSTI2026

Decision Support System

Forest-based value chains involve decisions that begin at the landscape level and extend through processing, product manufacturing, and end-use markets. However, these decisions are often made independently across sectors, with limited visibility into how upstream resource conditions, incentives, and land management choices influence downstream production systems. In forested regions of the United States, wildfire risk, fragmented ownership, and uncertain markets for low-value residues complicate efforts to align extraction, processing, and utilization decisions. Without tools that link these stages, stakeholders may overlook opportunities to improve resource utilization or inadvertently shift impacts elsewhere in the value chain. This repository introduces a decision support system (DSS) that applies a system-impact-analysis approach to forest biomass residues and co-products. The framework integrates forest inventory data, geospatial resource assessments, and economic modeling to evaluate how biomass extraction decisions influence downstream product pathways. By linking regional feedstock avail- ability with market incentives and processing options—such as fuels, wood products, or soil amendments like biochar—the tool allows decision-makers to compare value chain outcomes across multiple utilization strategies.

Davis, Maggie [Oak Ridge National Laboratory (ORNL↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-Wi5 Mixed young jack pine (MYJP)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Wi5 Mixed young jack pine (MYJP). This is the FLUXNET version of the carbon flux data for the site US-Wi5 Mixed young jack pine (MYJP) produced by applying the standard ONEFlux (1F) software. Site Description - The Wisconsin Mixed Young Jack Pine site is located in the Washburn Ranger District of the northeastern section of Chequamegon National Forest. A member of the northern coniferous-deciduous biome, surveys from the mid-19th century indicate the region consisted of a mixed stand of red, white, and jack pines. After extensive timber harvesting, wildfires, and farming activity, the region turned into a fragmented mosaic of stands of various ages and composition. As an assemblage, the ten Wisconsin sites are indicative of the successional stages of development in the predominant stand types of a physically homogeneous landscape. Clearcut on 40 to 70 year intervals, jack pine stands occupy approximately 13% of the region.

Chen, Jiquan↗
DOE OSTI2024

A globally sampled high-resolution hand-labeled validation dataset for evaluating surface water extent maps

Effective monitoring of global water resources is increasingly critical due to climate change and population growth. Advancements in remote sensing technology, specifically in spatial, spectral, and temporal resolutions, are revolutionizing water resource monitoring, leading to more frequent and high-quality surface water extent maps using various techniques such as traditional image processing and machine learning algorithms. However, satellite imagery datasets contain trade-offs that result in inconsistencies in performance, such as disparities in measurement principles between optical (e.g., Sentinel-2) and radar (e.g., Sentinel-1) sensors and differences in spatial and spectral resolutions among optical sensors. Therefore, developing accurate and robust surface water mapping solutions requires independent validations from multiple datasets to identify potential biases within the imagery and algorithms. However, high-quality validation datasets are expensive to build, and few contain information on water resources. For this purpose, we introduce a globally sampled, high-spatial-resolution dataset labeled using 3 m PlanetScope imagery. Our surface water extent dataset comprises 100 images, each with a size of 1024×1024 pixels, which were sampled using a stratified random sampling strategy covering all 14 biomes. We highlighted urban and rural regions, lakes, and rivers, including braided rivers and coastal regions. We evaluated two surface water extent mapping methods using our dataset – Dynamic World, based on Sentinel-2, and the NASA IMPACT model, based on Sentinel-1. Dynamic World achieved a mean intersection over union (IoU) of 72.16 % and F1 score of 79.70 %, while the NASA IMPACT model had a mean IoU of 57.61 % and F1 score of 65.79 %. Performance varied substantially across biomes, highlighting the importance of evaluating models on diverse landscapes to assess their generalizability and robustness. Our dataset can be used to analyze satellite products and methods, providing insights into their advantages and drawbacks. Our dataset offers a unique tool for analyzing satellite products, aiding the development of more accurate and robust surface water monitoring solutions. The dataset can be accessed via https://doi.org/10.25739/03nt-4f29.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-Wi7 Red pine clearcut (RPCC)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Wi7 Red pine clearcut (RPCC). This is the FLUXNET version of the carbon flux data for the site US-Wi7 Red pine clearcut (RPCC) produced by applying the standard ONEFlux (1F) software. Site Description - The Wisconsin Clearcut Red Pine site is located in the Washburn Ranger District of the northeastern section of Chequamegon National Forest. A member of the northern coniferous-deciduous biome, surveys from the mid-19th century indicate the region consisted of a mixed stand of red, white, and jack pines. After extensive timber harvesting, wildfires, and farming activity, the region turned into a fragmented mosaic of stands of various ages and composition. The red pine clearcut site is one of ten sites that collectively represent the successional stages of development in the predominant stand types of a physically homogeneous landscape. Thinned every 7 years until they reach 100 to 150 years of age, the red pine plantations or all ages occupy approximately 25% of the region.

Chen, Jiquan↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-Wi8 Young hardwood clearcut (YHW)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Wi8 Young hardwood clearcut (YHW). This is the FLUXNET version of the carbon flux data for the site US-Wi8 Young hardwood clearcut (YHW) produced by applying the standard ONEFlux (1F) software. Site Description - The Wisconsin Clearcut Young Hardwood site is located in the Washburn Ranger District of the northeastern section of Chequamegon National Forest. A member of the northern coniferous-deciduous biome, surveys from the mid-19th century indicate the region consisted of a mixed stand of red, white, and jack pines. After extensive timber harvesting, wildfires, and farming activity, the region turned into a fragmented mosaic of stands of various ages and composition. The young hardwood clearcut site is one of ten sites that collectively represent the successional stages of development in the predominant stand types of a physically homogeneous landscape. In 2001, northern hardwood stands of all ages occupied 45% of the region.

Chen, Jiquan↗
DOE OSTI2024

Search for a light sterile neutrino with 7.5 years of IceCube DeepCore data

We present a search for an eV-scale sterile neutrino using 7.5 years of data from the IceCube DeepCore detector. The analysis uses a sample of 21,914 events with energies between 5 and 150 GeV to search for sterile neutrinos through atmospheric muon neutrino disappearance. Improvements in event selection and treatment of systematic uncertainties provide greater statistical power compared to previous DeepCore sterile neutrino searches. Our results are compatible with the absence of mixing between active and sterile neutrino states, and we place constraints on the mixing matrix elements |U μ⁢4 | 2 < 0.0534 and |U $\tau$⁢4 | 2 < 0.0574 at 90% CL under the assumption that Δ⁢m$^{2}_{41}$ ≥ 1 eV 2 . These null results add to the growing tension between anomalous appearance results and constraints from disappearance searches in the 3+1 sterile neutrino landscape.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Timing and extent of crop damage by wild pigs (Sus scrofa Linnaeus) to corn and peanut fields

The global expansion of wild pigs over the last few decades has resulted in an increase in extent and distribution of damages to crops, placing a growing strain on agricultural producers and land managers. Despite the extent of wild pig damage to agriculture, there is little data regarding timing and spatial variability of damage to corn (Zea mays Linnaeus) and we found no data regarding the effect of these factors on peanuts (Arachis hypogaea Linnaeus). Our objective was to determine the timing and extent of wild pig damage to corn and peanut fields, as well as the extent to which local habitat attributes are useful predictors of damage to these crops. During 2017–2018 we performed ground-based surveys throughout the growing season for 29 corn and 41 peanut fields in South Carolina, USA to determine the most important growth stages for wild pig depredation in both crops. Damage to corn peaked shortly after planting during the seedling stage, fell to nearly zero during V4–V6 stages, and resumed during the silk and mature stages. Peanut damage was almost exclusively limited to the seedling stage. Landscape models for both crops identified the extent of forested and wetland areas surrounding crop fields as the most important attributes positively associated with wild pig damage, while the amount of adjacent agricultural area and paved roads were associated negatively. The number of wild pigs identified by remote cameras also was an important indicator of the extent of damage to peanut fields. Results suggest management efforts to limit crop depredation by wild pigs should be targeted shortly prior to planting. Further, because damage was positively associated with the availability of wetland and forest habitats, our results suggest agricultural damage by wild pigs may be most severe near areas of preferred native habitats.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Potential Suitability of Subirrigation for Field Crops in the U.S. Midwest

Subirrigation through subsurface tile drains has potential to increase crop yields and improve water quality in tile-drained landscapes, but it has not been widely implemented. Identifying locations with high potential suitability for subirrigation may help the planning and implementation of this practice. In this study, we developed a fuzzy rating system for subirrigation suitability using the Gridded Soil Survey Geographic Database (gSSURGO). Maps of the fuzzy rating system identified locations of high potential suitability for subirrigation and highlighted physiographic regions highly conducive to the practice. We identified 78,500 km2, about 9%, of agricultural land in the Midwest with high potential suitability for subirrigation where onsite investigation may be targeted. The largest areas of high potential suitability were found in Minnesota, Illinois, and Indiana. Results from the fuzzy rating analysis are provided to the public through three channels: a downloadable data repository, map service, and web map tool. Ultimately, this study can facilitate the adoption of subirrigation by highlighting areas where subirrigation may potentially be a viable practice.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The ab initio amorphous materials database: Empowering machine learning to decode diffusivity

Amorphous materials exhibit unique properties that make them suitable for various applications in science and technology, ranging from optical and electronic devices and solid-state batteries to protective coatings. However, data-driven ex- ploration and design of amorphous materials is hampered by the absence of a com- prehensive database covering a broad chemical space. In this work, we present the largest computed amorphous materials database to date, generated from sys- tematic and accurate ab initio molecular dynamics (AIMD) calculations. We also show how the database can be used in simple machine-learning models to connect properties to composition and structure, here specifically targeting ionic conductiv- ity. These models predict the Li-ion diffusivity with speed and accuracy, offering a cost-effective alternative to expensive density functional theory (DFT) calculations. Furthermore, the process of computational quenching amorphous materials provides a unique sampling of out-of-equilibrium structures, energies, and force landscape, and we anticipate that the corresponding trajectories will inform future work in uni- versal machine learning potentials, impacting design beyond that of non-crystalline materials.

36 MATERIALS SCIENCE↗