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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Ectomycorrhizal fungi enhance pine growth by stimulating iron‐dependent mechanisms with trade‐offs in symbiotic performance

Iron (Fe) is crucial for metabolic functions of living organisms. Plants access occluded Fe through interactions with rhizosphere microorganisms and symbionts. Yet, the interplay between Fe addition and plant–mycorrhizal interactions, especially the molecular mechanisms underlying mycorrhiza-assisted Fe processing in plants, remains largely unexplored. Here, we conducted mesocosms in Pinus plants inoculated with different ectomycorrhizal fungi (EMF) Suillus species under conditions with and without Fe coatings. Meta-transcriptomic, biogeochemical, and X-ray fluorescence imaging analyses were applied to investigate early-stage mycorrhizal roots. While Fe addition promoted Pinus growth, it concurrently reduced mycorrhiza formation rate, symbiosis-related metabolites in plant roots, and aboveground plant carbon and macronutrient content. This suggested potential trade-offs between Fe-enhanced plant growth and symbiotic performance. However, the extent of this trade-off may depend on interactions between host plants and EMF species. Interestingly, dual EMF species were more effective at facilitating plant Fe uptake by inducing diverse Fe-related functions than single-EMF species. This subsequently triggered various Fe-dependent physiological and biochemical processes in Pinus roots, significantly contributing to Pinus growth. However, this resulted in a greater carbon allocation to roots, relatively reducing the aboveground plant carbon content. Our study offers critical insights into how EMF communities rebalance benefits of Fe-induced effects on symbiotic partners.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bias-Variance Trade-Off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs

Physics-Informed Neural Networks (PINNs) have triggered a paradigm shift in scientific computing, leveraging mesh-free properties and robust approximation capabilities. While proving effective for low-dimensional partial differential equations (PDEs), the computational cost of PINNs remains a hurdle in high-dimensional scenarios. This is particularly pronounced when computing high-order and high-dimensional derivatives in the physics-informed loss. Randomized Smoothing PINN (RS-PINN) introduces Gaussian noise for stochastic smoothing of the original neural net model, enabling the use of Monte Carlo methods for derivative approximation, which eliminates the need for costly automatic differentiation. Despite its computational efficiency, especially in the approximation of high-dimensional derivatives, RS-PINN introduces biases in both loss and gradients, negatively impacting convergence, especially when coupled with stochastic gradient descent (SGD) algorithms. We present a comprehensive analysis of biases in RS-PINN, attributing them to the nonlinearity of the Mean Squared Error (MSE) loss as well as the intrinsic nonlinearity of the PDE itself. We propose tailored bias correction techniques, delineating their application based on the order of PDE nonlinearity. The derivation of an unbiased RS-PINN allows for a detailed examination of its advantages and disadvantages compared to the biased version. Specifically, the biased version has a lower variance and runs faster than the unbiased version, but it is less accurate due to the bias. To optimize the bias-variance trade-off, we combine the two approaches in a hybrid method that balances the rapid convergence of the biased version with the high accuracy of the unbiased version. In addition to methodological contributions, we present an enhanced implementation of RS-PINN. Extensive experiments on diverse high-dimensional PDEs, including Fokker-Planck, Hamilton-Jacobi-Bellman (HJB), viscous Burgers’, Allen-Cahn, and Sine-Gordon equations, illustrate the bias-variance trade-off and highlight the effectiveness of the hybrid RS-PINN. Empirical guidelines are provided for selecting biased, unbiased, or hybrid versions, depending on the dimensionality and nonlinearity of the specific PDE problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Quantum Advantage in Trading: A Game-Theoretic Approach

Quantum games, like quantum algorithms, exploit quantum entanglement to establish strong correlations between strategic player actions. This paper introduces quantum game-theoretic models applied to trading and demonstrates their implementation on an ion-trap quantum computer. The results showcase a quantum advantage, previously known only theoretically, realized as higher-paying market Nash equilibria. This advantage could help uncover alpha in trading strategies, defined as excess returns compared to established benchmarks. These findings suggest that quantum computing could significantly influence the development of financial strategies.

Khan, Faisal Shah [Taqtics LLC, USA, Rethinc. Labs↗
DOE OSTI2023

Data for Climate vs Energy Security: Quantifying the Trade-offs of BECCS Deployment and Overcoming Opportunity Costs on Set-Aside Land

Bioenergy with carbon capture and storage (BECCS) sits at the nexus of the climate and energy security. We evaluated trade-offs between scenarios that support climate stabilization (negative emissions and net climate benefit) or energy security (ethanol production). Our spatially explicit model indicates that the foregone climate benefit from abandoned cropland (opportunity cost) increased carbon emissions per unit of energy produced by 14–36%, making geologic carbon capture and storage necessary to achieve negative emissions from any given energy crop. The toll of opportunity costs on the climate benefit of BECCS from set-aside land was offset through the spatial allocation of crops based on their individual biophysical constraints. Dedicated energy crops consistently outperformed mixed grasslands. We estimate that BECCS allocation to land enrolled in the Conservation Reserve Program (CRP) could capture up to 9 Tg C year–1 from the atmosphere, deliver up to 16 Tg CE year–1 in emissions savings, and meet up to 10% of the US energy statutory targets, but contributions varied substantially as the priority shifted from climate stabilization to energy provision. Our results indicate a significant potential to integrate energy security targets into sustainable pathways to climate stabilization but underpin the trade-offs of divergent policy-driven agendas.

Field Data↗
DOE OSTI2022

Performance trade-offs in reconfigurable networks for HPC

Designing efficient interconnects to support high-bandwidth and low-latency communication is critical toward realizing high performance computing (HPC) and data center (DC) systems in the exascale era. At extreme computing scales, providing the requisite bandwidth through overprovisioning becomes impractical. These challenges have motivated studies exploring reconfigurable network architectures that can adapt to traffic patterns at runtime using optical circuit switching. Despite the plethora of proposed architectures, surprisingly little is known about the relative performances and trade-offs among different reconfigurable network designs. We aim to bridge this gap by tackling two key issues in reconfigurable network design. First, we study how cost, power consumption, network performance, and scalability vary based on optical circuit switch (OCS) placement in the physical topology. Specifically, we consider two classes of reconfigurable architectures: one that places OCSs between top-of-rack (ToR) switches—ToR-reconfigurable networks (TRNs)—and one that places OCSs between pods of racks—pod-reconfigurable networks (PRNs). Second, we tackle the effects of reconfiguration frequency on network performance. Our results, based on network simulations driven by real HPC and DC workloads, show that while TRNs are optimized for low fan-out communication patterns, they are less suited for carrying high fan-out workloads. PRNs exhibit better overall trade-off, capable of performing comparably to a fully non-blocking fat tree for low fan-out workloads, and significantly outperform TRNs for high fan-out communication patterns.

Teh, Min Yee↗
DOE OSTI2022

Cost Efficient-by-Design Microreactors: Trade-offs between cost, technical, and regulatory factors

This research evaluates a cost reduction investigation through adoption of a functional containment approach on the microreactor system and structure. Trade-offs between microreactor system designs, fuels and reactor module sizes are evaluated based on performance-based and risk-informed design procedures. Cost savings are evaluated against trade-offs in the reliability of passive heat removal systems, reactivity control, and radioactive material containment. Results can inform the Microreactor Program and reactor designs on “sweet spots” for microreactors that are cost-efficient while meeting required safety limits.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Core Model Proposal #: 374 Global Iron and Steel Trade

This core model proposal (CMP) enables GCAM to track the gross trade of regional iron and steel commodities. Following the logit-based Armington trade modeling framework, this CMP aims to improve the representation of physical output (Mt) flows in GCAM v6.0’s iron and steel sector. In addition, the core model proposal also updates the regional steel demand and improves the representation of iron and steel technologies (and their energy coefficients) across all GCAM regions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Core Model Proposal #389: Ammonia Trade and Miscellaneous GCAM 7.0 Bugfixes

This proposal re-structures the N fertilizer sector in the model, replacing the trade structure which was implemented before GCAM had the capability to trade secondary goods between regions, and re-naming the production commodity "ammonia" in order to better set up the model for representing ammonia as an energy carrier in subsequent work. Several bugfixes for GCAM 7.0 are also included in the proposal.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Thriving in the Carbon-Aware Market: How to Account for Emissions in the Era of Carbon-Centered Trade Policies

Emerging global policies, such as the European Union's enacted Carbon Border Adjustment Mechanism and similar policies under development in Canada, Australia and the United Kingdom, will place a premium on goods traded into their territories with higher embedded emissions than those produced domestically. U.S. manufacturers could stand to benefit from such policies; given the investments U.S. industry has made to reduce the energy and emission intensities of its operations. For example, the overall GHG intensity of U.S. steel production in 2019 was ~0.96 t CO2/t steel, less than half that of China (~1.97 t CO2/t steel), and bested only by Italy. To realize these benefits, transparent, accurate, interoperable and accepted embedded emissions accounting and calculation methods are required. Achieving this requires overcoming challenges related to data availability, boundary definitions, and product definitions among others, both at individual facilities as well as through value chains. We will present technical findings on methodology considerations and data-availability constraints for determining the emissions of traded goods, using steel as a pilot and leveraging publicly available data. Issues such as determining the appropriate scope for emissions accounting, implications of the specificity of product chosen, emissions allocation in multi-product facilities, and enumeration of emissions for products manufactured across multiple facilities will be discussed. By sharing the results of our efforts, we aim to inform the development and execution of embedded emissions accounting methods from a technical perspective such that U.S. manufacturers can thrive in emerging global markets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Singleton Sieving: Overcoming the Memory/Speed Trade-Off in Exascale k-mer Analysis

Traditional filter data structures, such as Bloom filters, do not offer necessary features that modern high-performance data analytics applications need in order to efficiently perform complex data analysis tasks. For example, MetaHipMer, a de novo metagenome assembler, can use filters to weed out singleton k-mers and reduce memory usage by 30%-70%. However, the filter needs the ability to associate values with k-mers in order to perform the analysis in a single communication pass. Bloom filters do not support value associations and cause the application to perform an extra communication pass, thereby increasing the run time. Therefore, MetaHipMer faces a trade off between memory and speed due to the limited capabilities of traditional filters. In this paper, we overcome the memory and speed trade off in MetaHipMer by integrating a GPU-based feature-rich filter, the Two-Choice filter (TCF), in the MetaHipMer pipeline. The TCF uses key-value association to approximately store k-mers with extensions. This allows MetaHipMer to perform k-mer analysis on the GPUs in a single communication pass. Our empirical analysis shows a 50% reduction in memory usage in k-mer analysis on each node in MetaHipMer without any effect on the overall run time or assembly quality. The memory reduction in turn results in a 43% reduction in the number of nodes required to assemble datasets and enables MetaHipMer to scale to much larger datasets.

McCoy, Hunter↗
DOE OSTI2021

Trade-Offs in Phosphorus Acquisition Strategies of Five Common Tree Species in a Tropical Forest of Puerto Rico

Tree species that are successful in tropical lowlands have different acquisition strategies to overcome soil phosphorus (P) limitations. Some of these strategies belowground include adjustments in fine-root traits, such as morphology, architecture, association with arbuscular mycorrhizal fungi, and phosphatase activity. Trade-offs among P-acquisition strategies are expected because of their respective carbon cost. However, empirical evidence remains scarce which hinders our understanding of soil P-acquisition processes in tropical forests. Here, we measured seven fine-root functional traits related to P acquisition of five common tree species in three sites of the Luquillo Experimental Forest in Puerto Rico. We then described species-specific P-acquisition strategies and explored the changes in fine-root trait expression from 6 months before to 6 months after two consecutive hurricanes, Irma and María, passed over the island. We found that variations in root trait expression were driven mainly by the large interspecific differences across the three selected sites. In addition, we revealed a trade-off between highly colonized fine roots with high phosphatase activity and fine roots that have a high degree of branching. Furthermore, the former strategy was adopted by pioneer species ( Spathodea campanulata and Cecropia schreberiana ), whereas the latter was adopted by non-pioneer species (mostly Dacryodes excelsa and Prestoea montana ). Additionally, we found that root trait expression did not change comparing 6 months before and after the hurricanes, with the exception of root phosphatase activity. Altogether, our results suggest a combination of structural and physiological root traits for soil P acquisition in P-poor tropical soils by common tropical tree species, and show stability on most of the root trait expression after hurricane disturbances.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Exploring Trait Trade-Offs for Fungal Decomposers in a Southern California Grassland

Fungi are important decomposers in terrestrial ecosystems, so their responses to climate change might influence carbon (C) and nitrogen (N) dynamics. We investigated whether growth and activity of fungi under drought conditions were structured by trade-offs among traits in 15 fungal isolates from a Mediterranean Southern California grassland. We inoculated fungi onto sterilized litter that was incubated at three moisture levels (4, 27, and 50% water holding capacity, WHC). For each isolate, we characterized traits that described three potential lifestyles within the newly proposed “YAS” framework: growth yield, resource acquisition, and stress tolerance. Specifically, we measured fungal hyphal length per unit litter decomposition for growth yield; the potential activities of the extracellular enzymes cellobiohydrolase (CBH), β -glucosidase (BG), β -xylosidase (BX), and N-acetyl- β - D -glucosaminidase (NAG) for resource acquisition; and ability to grow in drought vs. higher moisture levels for drought stress tolerance. Although, we had hypothesized that evolutionary and physiological trade-offs would elicit negative relationships among traits, we found no supporting evidence for this hypothesis. Across isolates, growth yield, drought stress tolerance, and extracellular enzyme activities were not significantly related to each other. Thus, it is possible that drought-induced shifts in fungal community composition may not necessarily lead to changes in fungal biomass or decomposer ability in this arid grassland.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Expanding the design space of stratospheric aerosol geoengineering to include precipitation-based objectives and explore trade-offs

Previous climate modeling studies demonstrate the ability of feedback-regulated, stratospheric aerosol geoengineering with injection at multiple independent latitudes to meet multiple simultaneous temperature-based objectives in the presence of anthropogenic climate change. However, the impacts of climate change are not limited to rising temperatures but also include changes in precipitation, loss of sea ice, and many more; knowing how a given geoengineering strategy will affect each of these climate metrics is vital to understanding the limits and trade-offs of geoengineering. Here, we first introduce a new method of visualizing the design space in which desired climate outcomes are represented by 2-D surfaces on a 3-D graph. Surface orientations represent how different injection choices influence that objective, and intersecting surfaces represent objectives which can be met simultaneously. Using this representation as a guide, we present simulations of two new strategies for feedback-regulated aerosol injection, using the Community Earth System Model with the Whole Atmosphere Community Climate Model – CESM1(WACCM). The first simultaneously manages global mean temperature, tropical precipitation centroid, and Arctic sea ice extent, while the second manages global mean precipitation, tropical precipitation centroid, and Arctic sea ice extent. Both simulations control the tropical precipitation centroid to within 5 % of the goal, and the latter controls global mean precipitation to within 1% of the goal. Additionally, the first simulation overcompensates sea ice, while the second undercompensates sea ice; all of these results are consistent with the expectations of our design space model. In addition to showing that precipitation-based climate metrics can be managed using feedback alongside other goals, our simulations validate the utility of our design space visualization in predicting our climate model behavior under a given geoengineering strategy, and together they help illustrate the fundamental limits and trade-offs of stratospheric aerosol geoengineering.

58 GEOSCIENCES↗
DOE OSTI2026

Framework for Modeling 3D-Printed Concrete Construction to Assess Energy Efficiency and Backup Power Trade-Offs in a Mixed-Use, New Construction Neighborhood Development

This paper presents a framework that expands the URBANopt(TM) modeling platform to include 3D-printed concrete wall assemblies and assess energy efficiency and backup power trade-offs in new housing developments. Applied to a planned mixed-use neighborhood in Oil City, Pennsylvania, the workflow integrates building energy and distributed energy resource (DER) modeling to evaluate envelope and equipment upgrades alongside DER operations. Results show that advanced 3D-printed envelopes combined with efficient systems and onsite photovoltaics (PV) and storage reduce energy use intensity and sustain critical loads during outages. The framework supports planning for emerging construction technologies by quantifying key trade-offs between energy efficiency and backup power performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

A Trade-Off Study Between the Primary and Transient Responses of Grid-Forming Inverters

The control parameters of the grid-forming (GFM) inverter-based resources (IBRs) directly impact power system dynamics. The primary control requires the GFM inverter to balance generation and load. It is also preferred that a GFM inverter maintain the terminal frequency after a power system fault. In this paper, we investigate the trade-off between the primary control objective and the transient response. To quantify the transient performance of the GFM inverter, we introduce a new real-time transient stability index (TSI). This index plays a crucial role in our investigation, as it allows us to compare the performance trade-offs of different sets of GFM control parameters.

Lin, Xuheng↗
DOE OSTI2024

Beneficiaries, equity, and trade-offs in estuarine and coastal ecosystem services

Estuarine and coastal ecosystems support human populations in myriad ways. Traditionally, researchers have focused on the biophysical processes that underlie these benefits and their economic values. In the decade since the 1st Treatise, the literature on cultural ecosystem services, human health benefits, and the equitable distribution of societal benefits and burdens has grown tremendously. In this chapter we outline three dimensions of equity as they relate to estuarine and coastal ecosystems: procedural, recognitional, and distributional equity. We then apply the dimensions of equity to a suite of provisioning, regulating, and cultural ecosystem services. Finally, we explore trade-offs and beneficiaries of these ecosystem services using three case studies that consider equity in a variety of estuarine and coastal management decisions.

beneficiaries↗
DOE OSTI2022

The economic impacts of carbon emission trading scheme on building retrofits: A case study with U.S. medium office buildings

As a popular emission reduction tool, the carbon emission trading scheme (ETS) can potentially add an economic incentive for building owners to retrofit buildings in addition to the cost savings in energy. However, the additional economic benefits of building retrofits brought by ETS has not been quantitively investigated yet. Here, in order to fill this gap, this study proposed a systematic economic evaluation method to investigate the economic impacts of ETS on building retrofits. The reduction of the payback period and the increase of the return on investment are adopted as evaluation metrics. Using medium office buildings as an example, this study predicted the economic impacts of ETS on building retrofits at four locations in the U.S., and three different carbon prices were investigated. The results show that carbon prices have significant economic impacts on building retrofits. With the relatively low forecasted time-variant carbon prices (around 10 USD per ton), the economic impacts of ETS on building retrofits are small. When carbon prices increase, the impacts of ETS would be up to 25% for 50 USD per ton (current prices in European Union) and 51% for 100 USD per ton. Furthermore, locations with more fossil energy have higher relative changes in the payback period and ROI but are more sensitive to carbon prices.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Overcoming the Conductance versus Crossover Trade-off in State-of-the-Art Proton Exchange Fuel-Cell Membranes by Incorporating Atomically Thin Chemical Vapor Deposition Graphene

Permeance–selectivity trade-offs are inherent to polymeric membranes. In fuel cells, thinner proton exchange membranes (PEMs) could enable higher proton conductance and increased power density with lower area-specific resistance (ASR), smaller ohmic losses, and lower ionomer cost. However, reducing thickness is accompanied by an increase in undesired species crossover harming performance and long-term efficiency. Here, we show that incorporating atomically thin monolayer graphene synthesized via scalable chemical vapor deposition (CVD) and tunable defect density into PEMs (Nafion, ~5–25 μm thick) can allow for reduced H 2 crossover (~34–78% of Nafion of a similar thickness) while maintaining adequate areal proton conductance for applications (>4 S cm –2 ). In contrast to most prior work using >50 μm symmetric Nafion sandwich structures, we elucidate the interplay of graphene defect density and Nafion proton transport resistance on the performance of Nafion|graphene composite membranes and find high-quality low-defect density CVD graphene (G) supported on Nafion 211 (~25 μm); i.e., N211|G has a high areal proton conductance (~6.1 S cm –2 ) and the lowest H 2 crossover (~0.7 mA cm –2 ). Fully functional centimeter-scale N211|G fuel-cell membranes demonstrate performance comparable to that of state-of-the-art Nafion N211 at room temperature as well as standard operating conditions (~80 °C, ~150–250 kPa-abs) with H 2 /air (power density ~0.57–0.63 W cm –2 ) and H 2 /O 2 feed (power density ~1.4–1.62 W cm –2 ) and markedly reduced H 2 crossover (~53–57%).

25 ENERGY STORAGE↗