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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Conceptualizing Coproduced Climate Research as Care: Practical Lessons Learned With Women Farmland‐Owners in the Central Midwest United States

ABSTRACT This article's team of interdisciplinary researchers and conservation educator‐practitioners learned with, and from, a group of women farmland‐owners regarding how to conceptualize coproduced climate research by putting “care” at the center—care for the soil, for relationships, for data. We outline the creation and evolution of a storytelling‐based conservation program that allowed our diverse group to discover how the language of care could integrate climate analysis, conservation, and relationship‐building to foster tangible solutions. As a result of the project, the women landowners took actions that supported social‐environmental resilience—from planting cover crops to fostering watershed/neighborhood relationships. Our diverse group of women landowners and researchers had very different experiences with conservation and often very different views on climate change itself, but, through storytelling and the language of care, we not only coproduced knowledge but also created relationships and action. This article outlines specific practices for how to inflect a coproduced process for climate resilience with practices that promote care and yield action projects.

Shenk, Linda [Department of English Iowa State Uni↗
DOE OSTI2024

Applying Machine‐Learning Methods to Laser Acceleration of Protons: Lessons Learned From Synthetic Data

ABSTRACT In this study, we consider three different machine‐learning methods—a three‐hidden‐layer neural network, support vector regression, and Gaussian process regression—and compare how well they can learn from a synthetic data set for proton acceleration in the Target Normal Sheath Acceleration regime. The synthetic data set was generated from a previously published theoretical model by Fuchs et al. 2005 that we modified. Once trained, these machine‐learning methods can assist with efforts to maximize the peak proton energy, or with the more general problem of configuring the laser system to produce a proton energy spectrum with desired characteristics. In our study, we focus on both the accuracy of the machine‐learning methods and the performance on one GPU including memory consumption. Although it is arguably the least sophisticated machine‐learning model we considered, support vector regression performed very well in our tests.

Desai, Ronak↗
DOE OSTI2026

Lessons from LHCb and Belle II measurements of B → J/ψπ and B → J/ψK decays

The LHCb collaboration has recently measured the CP asymmetry in B + → J/ψπ + decay, while the Belle II collaboration has recently measured the CP asymmetries in B 0 →J/ψπ 0 decay. Within the Standard Model, and using flavor-SU(3) relations including first-order breaking corrections, these measurements lead to new predictions with regard to CP violation in B + → J/ψK + and B s → J/ψ$\bar{K}$ 0 decays, the difference between S ψK S and sin 2β, and the rate and CP asymmetries in B s → J/ψπ 0 decay.

Bottom Quarks↗
DOE OSTI2024

Anticipating how rain-on-snow events will change through the 21st century: lessons from the 1997 new year’s flood event

The California-Nevada 1997 New Year’s flood was an atmospheric river (AR)-driven rain-on-snow (RoS) event and remains the costliest in their history. The joint occurrence of saturated soils, rainfall, and snowmelt generated inundation throughout northern California-Nevada. Although AR RoS events are projected to occur more frequently with climate change, the warming sensitivity of their flood drivers across scales remains understudied. We leverage the regionally refined mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) to recreate the 1997 New Year’s flood with horizontal grid spacings of 3.5 km across California, with forecast lead times of up to 4 days, and across six warming levels ranging from pre-industrial conditions to +3.5° C. We describe the sensitivity of the flood drivers to warming including AR duration and intensity, precipitation phase, intensity and efficiency, snowpack mass and energy changes, and runoff efficiency. Our findings indicate current levels of climate change negligibly influence the flood drivers. At warming levels ≥ 1.7° C, AR hazard potential increases, snowpack nonlinearly decreases, antecedent soil moisture decreases (except where the snowline retreats), and runoff decreases (except in the southern Sierra Nevada where antecedent snowpack persists). Storm total precipitation increases, but at rates below warming-induced increases in saturation-specific humidity. Warming intensifies short-duration, high-intensity rainfall, particularly where snowfall-to-rainfall transitions occur. This study highlights the nonlinear tradeoffs in 21st-century RoS flood hazards with warming and provides water management and infrastructure investment adaptation considerations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Global lessons: a comparative analysis of nuclear gamification's impact in American and British students

The global nuclear skills shortage demands urgent educational investment, particularly for students aged 11–18. To help address this, we have introduced RAD Ratings, an interactive card game designed to improve the teaching of nuclear concepts to students, which includes subjects such as half-lives, types of radiation, and radionuclide applications. RAD Ratings has already been successfully piloted in the United Kingdom and in this paper, we present a comparison in selected American schools for the first time. Snapshot survey results show RAD Ratings improve interest in nuclear science and careers, offering insights into gamification’s potential to improve engagement across different geographic locations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

GPS-supported smartphone app-based integrated travel diary and time-use data collection: challenges and lessons learned

Travel behaviour and time-use data are two vital data sources for travel demand modelling. Travel behaviour is traditionally collected through household travel surveys, enhanced by using GPS-supported smartphone apps for passive location data collection. However, recruiting individuals willing to install these apps with sustained motivation to continue participation has been a critical challenge. This paper shares insights from a travel and time-use data collection procedure in Chicago and Sydney using the Fourstep app. Social media platforms were utilised as a solution to recruit participants in Chicago, where an international market research company failed to accomplish the task. This paper also discusses the challenges we faced and suggests ways to overcome them, offering valuable guidance to researchers in recruiting participants for smartphone application-based data collection. It also offers an analysis of travel, time-use, and travel-based multitasking behaviours based on the data collected from the Chicago and Sydney samples.

GPS-supported smartphone apps↗
DOE OSTI2025

Lessons learned from the design and operation of a small-scale cross-flow tidal turbine

In 2023, a first-generation prototype of a small-scale marine current turbine was operated in Sequim Bay, Washington (USA) for 141 days. The system, referred to as the Turbine Lander, was the product of a laboratory-to-field effort to develop a system that enables enhanced ocean sensing or vehicle recharge in remote, energetic settings. The turbine consists of a vertical-axis, cantilevered rotor (1.19 m x 0.85 m) with four foils installed on a gravity foundation. A broader range of constraints including the deployment strategy, site characteristics, and estimated loads, drove the system’s design. This work presents the design, characterization, operation, and post-recovery engineering assessment of the Turbine Lander. Pre-deployment characterization efforts yielded a peak power coefficient of approximately 0.3 for the rotor, although system losses resulted in much lower water-to-wire efficiencies under most operating conditions. The results demonstrate the importance of co-design among key components of the powertrain and control systems to achieve acceptable system efficiency across operating conditions.

Co-design↗
DOE OSTI2025

Deploying advanced supervisory control strategies to small- and medium-sized commercial buildings: Case study and lessons learned

Deploying advanced supervisory control strategies (ASCSs) in small- and medium-sized commercial buildings (SMBs) is vital but faces two issues: (1) a lack of building control and communication infrastructure (BCCI) in SMBs and (2) the significant engineering efforts required to implement and configurate ASCSs. Despite hindering the large-scale adoption of ASCSs in SMBs, these issues have not been adequately explored in the literature, which tends to focus more on feasibility than scalability. This paper provides a comprehensive evaluation of these two issues through a case study of an occupied SMB in eastern Tennessee of the United States. Specifically, we design and implement a BCCI for the studied building with commercial off-the-shelf products to accommodate the needs for deploying ASCSs. Here, we then deploy two ASCSs—a rule-based setback control and a model predictive control (MPC)—with the BCCI and evaluate their performance throughout the summer of 2024. This study reveals that the main bottlenecks in establishing BCCIs for SMBs are the high initial cost (∼$56/m 2 ) and communication delays (up to 9 min). Additionally, the assessment of the two ASCSs indicates that the majority (∼75 %) of the engineering effort required for implementation and configuration is spent on model identification, debugging, and tuning.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Hydrogen technology for maritime applications: A review of challenges, opportunities, and lessons from the port authority of New York and New Jersey

The maritime industry faces increasing demand for energy security, operational efficiency, and environmental performance improvements. Hydrogen technology, considered a potential energy carrier, is being explored for port operations, including cargo-handling equipment, heavy-duty vehicles, and stationary power systems. This review evaluates the feasibility, challenges, and potential benefits of hydrogen integration within port infrastructure, using the Port Authority of New York and New Jersey as a representative case study. Drawing on case studies, technical reports, and policy analyses, this study examines the infrastructural, regulatory, and operational factors influencing large-scale deployment, emphasizing supply chain development, storage requirements, and refueling infrastructure. By situating hydrogen within broader maritime energy transition efforts, this review provides an evidence-based assessment of its role in port operations and energy diversification strategies. In conclusion, the findings outline key barriers to adoption and emphasize the need for coordinated efforts among stakeholders to determine hydrogen's role alongside other emerging energy technologies.

08 HYDROGEN↗
DOE OSTI2026

Generating multiple benefits from forests by producing value-added products: Lessons from the Pacific Northwestern US

This paper asks what conditions are needed to counteract a declining forest industry. The mobilization of supply chains for new value-added forest products and services can be supported by programs designed to simultaneously achieve multiple goals related to health, climate, and rural economic development. But several challenges are identified that underscore the need to stack benefits and incentives to achieve muti-sectoral goals. Based on a case study in Washington state, we find opportunities and constraints for sourcing forest products are determined by the local and regional conditions such as availability of working forests and their residues, socioeconomic conditions, workforce availability, transportation options, and perceptions about social license of the new industry. Key recommendations are the need for (1) a consistent demand and resilient supply chain for the new product; (2) a stable, supportive policy and assessment framework; (3) timely, transparent, and trusted monitoring and reporting of benefits and costs; (4) fostering engagement and buy-in from stakeholders; (5) a context-specific evaluation of opportunities and constraints; and (6) agreement on the goals of sustainable forestry. A diversity of products and markets builds a more resilient forest-based economy by mitigating impacts of disruptions in any individual market, adding value to biomass, increasing employment, and reducing forest risks to fire, insects, and disease.

Bioenergy↗
DOE OSTI2026

Simplifying the Chemical Design of Nonfused-Ring Electron Acceptors─Lessons Learned from Thienothiophene and Benzodithiophene Cores

Nonfused-ring electron acceptors (NFREA)s have been proposed as alternatives to fused-ring acceptors in organic photovoltaics (OPV)s. The simpler molecular design of NFREAs results in a reduced synthetic complexity, potentially lowering manufacturing costs, and easier access to desired optoelectronic properties by structural modifications. However, they have not seen the same rise in popularity as fused nonfullerene acceptors (NFA)s due to their lower performances in devices. In this work, we explore structure–property relationships of three NFREA molecules based on thieno[3,2-b]thiophene (TT) and benzo[1,2-b:4,5-b′]dithiophene (BDT) cores and malononitrile functionalized-isatin end group acceptors. We describe their synthetic routes, computational analysis, and photophysical and electronic properties. Here, we investigated the effect of changing the core from TT to BDT on electronic properties of the molecules─a result of raising/lowering of the frontier molecular orbital (FMO) levels. We also explored the effect of branched vs nonbranched alkyl groups on the morphological and blend-capabilities in bulk heterojunction (BHJ) OPV devices. These effects were then reflected in the overall device performances, primarily due to favorable FMO energy alignment between the NFREA and polymer. To investigate the behavior of the excited states of the NFREAs within the active layer of the devices, we performed time-resolved microwave conductivity and transient absorption experiments, which confirmed that the TT molecules exhibited very low conductance while the BDT molecule showed moderate photoconductance. Our combined theoretical, synthetic, device, and charge carrier dynamics studies of these materials reveal the central role that structure–property relationships play in future molecular designs of NFREAs that can perform as well as their fused counterparts.

14 SOLAR ENERGY↗
DOE OSTI2024

Data Imbalance, Uncertainty Quantification, and Transfer Learning in Data‐Driven Parameterizations: Lessons From the Emulation of Gravity Wave Momentum Transport in WACCM

Abstract Neural networks (NNs) are increasingly used for data‐driven subgrid‐scale parameterizations in weather and climate models. While NNs are powerful tools for learning complex non‐linear relationships from data, there are several challenges in using them for parameterizations. Three of these challenges are (a) data imbalance related to learning rare, often large‐amplitude, samples; (b) uncertainty quantification (UQ) of the predictions to provide an accuracy indicator; and (c) generalization to other climates, for example, those with different radiative forcings. Here, we examine the performance of methods for addressing these challenges using NN‐based emulators of the Whole Atmosphere Community Climate Model (WACCM) physics‐based gravity wave (GW) parameterizations as a test case. WACCM has complex, state‐of‐the‐art parameterizations for orography‐, convection‐, and front‐driven GWs. Convection‐ and orography‐driven GWs have significant data imbalance due to the absence of convection or orography in most grid points. We address data imbalance using resampling and/or weighted loss functions, enabling the successful emulation of parameterizations for all three sources. We demonstrate that three UQ methods (Bayesian NNs, variational auto‐encoders, and dropouts) provide ensemble spreads that correspond to accuracy during testing, offering criteria for identifying when an NN gives inaccurate predictions. Finally, we show that the accuracy of these NNs decreases for a warmer climate (4 × CO 2 ). However, their performance is significantly improved by applying transfer learning, for example, re‐training only one layer using ∼1% new data from the warmer climate. The findings of this study offer insights for developing reliable and generalizable data‐driven parameterizations for various processes, including (but not limited to) GWs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Exposing and Reducing Biases of Simulating Mixed-Phase Clouds in the Convection-Permitting E3SM Atmosphere Model: Lessons From an Arctic Cold-Air Outbreak

Mixed-phase clouds modulate the water and energy cycles of high-latitude regions, yet their liquid-ice phase partitioning has long been poorly simulated in climate models. Here, simulations of Arctic mixed-phase clouds by the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) are assessed against large-eddy simulations, satellite data, and ground-based observations during the Cold-Air Outbreaks in the Marine Boundary Layer Experiment field campaign. SCREAM simulates nearly completely frozen clouds, which is attributed largely to the unreasonably strong Wegener–Bergeron–Findeisen (WBF) process that converts liquid to ice excessively and partly to the early over-abundant ice production at cold temperatures from a temperature-deterministic deposition ice nucleation scheme. Assuming no subgrid variation for the WBF process in the original formulation particularly conflicts with the instantaneous saturation adjustment assumption in the condensation scheme that assumes subgrid variability, leading to exaggerated WBF process rates. A proposed simple physically-based improvement on the treatment of subgrid cloud overlap substantially increases supercooled liquid water content and notably improves cloud-top phase partitioning, aligning better with observations. Improvement of supercooled liquid water content also converges with increasing horizontal resolution. The deposition ice nucleation scheme is found responsible for a falsely-produced ice cloud aloft that is not observed, biasing the simulated cloud radiative effects and top-of-atmosphere radiative fluxes. This study identifies key deficiencies in cloud parameterizations that continue to challenge convection-permitting models.

Geosciences↗
DOE OSTI2026

Concentrating solar thermal power in the U.S.: lessons from setbacks at Ivanpah, light for the future

Concentrating solar thermal power (CSP) exhibits promise as a source of firm electricity. The proposed termination of Ivanpah’s power purchase agreement hinders confidence in the country’s CSP future. This work highlights how the lack of thermal energy storage (TES) undermined the first-of-a-kind plant’s economics as California’s grid transformed. Then, possible futures of the Ivanpah facility are analyzed; results show retrofitting with state-of-the-art TES systems could provide better returns.

14 SOLAR ENERGY↗
DOE OSTI2025

Subsurface hydrogen, curvature, and strain: lessons from electro-reduction of benzaldehyde on nano-structured Pd catalysts

The unique ability of palladium (Pd) to absorb hydrogen and form a bulk hydride is vital for chemical transformations that involve hydrogenation reactions. Nano-structured Pd catalysts offer a promise of tuning these reaction rates by exploiting variations of reactant binding energies depending on the surface structure and morphological constraints that result in inhomogeneous strain. However, the interplay between the nano-structure of Pd and the ability of Pd to adsorb (and absorb) hydrogen as well as other reactive species needs to be better understood for a rational understanding of competitive chemical transformations at Pd surfaces. We consider the effects of the surface corrugation, strain, and subsurface Pd hydride on the reduction of benzaldehyde to benzyl alcohol in two qualitatively different samples – Pd nanoparticles and Pd gels formed by quasi-one-dimensional chains of these nanoparticles. Our electrochemical measurements and computational modelling suggest that surface concave sites, inherent to Pd gels, facilitate hydrogen transfer to the Pd subsurface region, thus weakening benzaldehyde binding to the surface. This effect is further modulated by the strain, depending on the local coordination environment on the corrugated surface. Furthermore, these findings demonstrate how structurally complex samples in the form of gels provide degrees of freedom for controlling the behavior of metal catalysts that are not available in isolated nanoparticles, which paves the way for new approaches in the design of catalytic materials and synthesis of metal hydrides.

Padavala, Sri Krishna Murthy [University of Minnes↗
DOE OSTI2025

The lessons learned from ephemeral nuclei

Recent experimental analyses of fleeting clusters of protons and neutrons put the very notion of the atomic nucleus in a new light.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗