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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Stabilizing dynamic subsea power cables using Bi-stable nonlinear energy sinks

This study investigates vibration mitigation of dynamic subsea cables through passive bi-stable nonlinear energy sinks (B-NESs). These devices suppress vibration energy in a broadband way, and can be regarded as extensions of classical linear tuned mass dampers (TMDs) which are narrowband devices. Through the open-source MoorDyn library, we simulated the vibrations of a vertical subsea cable equipped with a set of B-NESs. Multi-objective optimization was performed to detect the B-NES parameters for optimal mitigation of the cable vibrations. Advanced signal processing verified the efficacy of the optimized B-NESs not only to rapidly absorb and locally dissipate vibration energy, but also to nonlinearly scatter vibration energy from low to high frequencies within the cable itself. This last feature is especially beneficial for vibration mitigation of the undersea cable, as at higher frequencies the cable vibrations exhibit drastically reduced amplitudes and are more effectively dissipated by inherent structural damping and hydrodynamic radiation damping. This contrasts with traditional TMDs which can mitigate vibration only at a single frequency. Furthermore, our robustness study confirms the B-NES's effectiveness under even varying environmental conditions. Overall, the B-NES's capacity for broadband vibration mitigation renders it a promising retrofit solution for improving the performance and operational safety of dynamic power cables in offshore wind farms and other marine applications.

17 WIND ENERGY↗
DOE OSTI2019

Toward Long-Life, Ultrahigh-Nickel Layered Oxide Cathodes for Lithium-Ion Batteries: Optimizing the Interphase Chemistry with a Dual-Functional Polymer

Boosting the Ni content in LiMO 2 (M = Ni, Co, Mn, etc.) layered oxides is a promising way to establish high-energydensity, low-cost cathodes, but the poor cathode surface stability is a daunting challenge for their practical viability. Herein, by constructing a dual-functional binder framework with a conductive polymer - polyaniline (PANI), the ultrahigh-Ni layered oxide cathode (LiNi 0.94 Co 0.06 O 2 ) exhibits significantly improved cyclability, with a capacity retention greatly increased from 47% to 81% over 1,000 cycles in full cells. It is demonstrated that the acidic species (e.g. HF) in the electrolyte can be efficiently scavenged through a protonation process of PANI, hence the cathode surface reactivity is greatly suppressed and the rock-salt phase propagation into bulk structure is considerably alleviated. Furthermore, the PANI binder system effectively prevents both the cathode-electrolyte interphase (CEI) and anode-electrolyte interphase (AEI) from degrading to a thick “triple-layer” architecture upon extensive cycling, resulting in more robust, thinner CEI and AEI with regulated interphasial chemistry. Moreover, the delocalized π-conjugated electrons along the backbone of PANI facilitate fast electron transfer and promote rate capability even at low temperatures (-20 °C). Finally, this work sheds light on rational binder engineering for developing high-energy-density lithium-ion batteries with acceptable cycle life.

25 ENERGY STORAGE↗
DOE OSTI2025

CD206 + Trem2 + macrophage accumulation in the murine knee joint after injury is associated with protection against post-traumatic osteoarthritis in MRL/MpJ mice

Post-traumatic osteoarthritis (PTOA) is a painful joint disease characterized by the degradation of bone, cartilage, and other connective tissues in the joint. PTOA is initiated by trauma to joint-stabilizing tissues, such as the anterior cruciate ligament, medial meniscus, or by intra-articular fractures. In humans, ~50% of joint injuries progress to PTOA, while the rest spontaneously resolve. To better understand molecular programs contributing to PTOA development or resolution, we examined injury-induced fluctuations in immune cell populations and transcriptional shifts by single-cell RNA sequencing of synovial joints in PTOA-susceptible C57BL/6J (B6) and PTOA-resistant MRL/MpJ (MRL) mice. We identified significant differences in monocyte and macrophage subpopulations between MRL and B6 joints. A potent myeloid-driven anti-inflammatory response was observed in MRL injured joints that significantly contrasted the pro-inflammatory signaling seen in B6 joints. Multiple CD206 + macrophage populations classically described as M2 were found enriched in MRL injured joints. These CD206 + macrophages also robustly expressed Trem2 , a receptor involved in inflammation and myeloid cell activation. These data suggest that the PTOA resistant MRL mouse strain displays an enhanced capacity of clearing debris and apoptotic cells induced by inflammation after injury due to an increase in activated M2 macrophages within the synovial tissue and joint space.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Criticality in the Shallow-to-Deep Transition of Simulated Tropical Marine Convection

Idealized simulations of tropical, marine convection depict shallow, nonprecipitating cumuli located beneath the 0°C level transitioning into cumulonimbi that reach up to 12 km and higher. The timing of the transition was only weakly related to environmental stability, and 13 of the 15 simulations run with 5 different lapse-rate profiles had rain develop at nearly the same time after model start. The key quantity that apparently controlled deep convective formation was vertical acceleration inside cloudy updrafts between cloud base and the 0°C level. Below a critical value of updraft vertical acceleration, little rainfall occurred. Just as the domain-mean updraft acceleration reached the critical value, the first convection quickly grew to past 12 km altitude. Then, as acceleration increased above the critical value, rain rate averaged in the model domain increased quickly over about a 3-h-long period. The specific value of the critical updraft acceleration depended on how updrafts were defined and in what layer the acceleration was averaged; however, regardless of how criticality was defined, a robust relationship between domain-mean updraft vertical acceleration and rain rate occurred. Positive acceleration of updrafts below the 0°C level was present below 2.75 km and was largest in the 500 m above cloud base. However, the maximum difference between updraft and environmental temperatures occurred between 2 and 3 km. The domain-mean Archimedean buoyancy of updrafts relative to some reference state was a poor predictor for domain-mean rain rate. In conclusion, the exact value of the critical updraft acceleration likely depends on numerous other factors that were not investigated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Environmentally Robust Quantum Dot Down Converters for Highly Efficient Solid State Lighting

This project contributes fundamental understanding of the chemical synthesis of cadmium free quantum dots (QDs) designed for solid state lighting (SSL). Methods to incorporate gallium into quantum dot architectures were explored, which led to more stable and brighter solid state lighting devices. These findings will help advance the incorporation of quantum dots in highly energy efficient lighting devices with a warm color spectrum. Such Cd-free lighting devices can greatly accelerate the adoption of high efficiency, warm spectrum lighting in buildings. The project targeted InP/GaP/ZnS colloidal quantum dots that more effectively absorb the blue light produced by light emitting diode packages and emit monochromatic red light with near perfect efficiency. While significant improvements in the QD absorptivity were demonstrated, the absorbance increase achieved was 3x rather than the targeted 10x increase. Similarly, the luminescence from these QDs achieved about half of the target photoluminescence quantum yield (PLQY) and twice the desired spectral width, a measure of the color purity of their luminescence. While the target characteristics and some of the year 2/2 milestones were not met, the new QD architectures did lead to greater stability on SSL packages, a sign of the long term promise of the technology.

36 MATERIALS SCIENCE↗
DOE OSTI2026

The Value of Reversible Carbon Storage in a Zero-Emissions World

Atmospheric carbon dioxide removal (CDR) is required to stabilize global temperature. CDR can be achieved via ecosystem-based approaches that are cost-effective but reversible (e.g., soil and forest management) or by more durable but expensive approaches (e.g., direct air capture coupled with geologic storage). Here, we examine trade-offs between these approaches, focusing on timing, climate impacts, and cost. We simulated reversible carbon accrual for a range of CDR contract structures using a general minimalist model of ecosystem carbon cycling, and parameterized it to simulate US agricultural soil management─specifically cover cropping─as a case study. We then quantified the resulting impact on atmospheric carbon and global temperature using a climate model emulator. We find that maintaining a patchwork of reversible CDR projects by replacing lapsed projects with new projects can reduce warming by 22–195 μ°C in 2100 and that the magnitude of this cooling effect depends on how effectively the patchwork is maintained. Long-term maintenance of reversible CDR projects requires institutional stability that cannot be guaranteed over multiple decades. Consequently, effective CDR ultimately requires replacing reversible projects with durable projects. To address this problem, we modeled the cost of replacing reversible agricultural soil CDR with geologic CDR. We found that using reversible CDR as a bridge to durable CDR is potentially more cost-effective as a global cooling strategy (0.20–0.81 billion USD per μ°C avoided) than perpetual maintenance of reversible CDR (0.32–1.31 billion USD per μ°C avoided) or an immediate transition to durable CDR (1.37–2.19 billion USD per μ°C avoided). However, we emphasize that institutional commitments to maintain reversible CDR projects cannot be guaranteed. Reliance on reversible CDR as a bridge to durable CDR therefore carries an unknown amount of risk and will only function if efforts to maintain reversible CDR are robust.

carbon capture and storage↗
DOE OSTI2021

Roles of Dynamic State Estimation in Power System Modeling, Monitoring and Operation

—Power system dynamic state estimation (DSE) remains an active research area. This is driven by the absence of accurate models, the increasing availability of fast-sampled, time synchronized measurements, and the advances in the capability, scalability, and affordability of computing and communications. This paper discusses the advantages of DSE as compared to static state estimation, and the implementation differences between the two, including the measurement configuration, modeling framework and support software features. The important roles of DSE are discussed from modeling, monitoring and operation aspects for today’s synchronous machine dominated systems and the future power electronics-interfaced generation systems. Several examples are presented to demonstrate the benefits of DSE on enhancing the operational robustness and resilience of 21st century power system through time critical applications. Future research directions are identified and discussed, paving the way for developing the next generation of energy management systems.

Zhao, Junbo↗
DOE OSTI2023

Versatile tape-drive target for high-repetition-rate laser-driven proton acceleration

We present the development and characterization of a high-stability, multi-material, multi-thickness tape-drive target for laser-driven acceleration at repetition rates of up to 100 Hz. The tape surface position was measured to be stable on the sub-micrometre scale, compatible with the high-numerical aperture focusing geometries required to achieve relativistic intensity interactions with the pulse energy available in current multi-Hz and near-future higher repetition-rate lasers ( > kHz). Long-term drift was characterized at 100 Hz demonstrating suitability for operation over extended periods. The target was continuously operated at up to 5 Hz in a recent experiment for 70,000 shots without intervention by the experimental team, with the exception of tape replacement, producing the largest data-set of relativistically intense laser–solid foil measurements to date. This tape drive provides robust targetry for the generation and study of high-repetition-rate ion beams using next-generation high-power laser systems, also enabling wider applications of laser-driven proton sources.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Quaternized Polynorbornene Random Copolymers for Fuel Cell Devices

Quaternized polymers are critical components for various energy devices. Vinyl-addition polynorbornenes provide high mechanical strength, high ion conductivity, and chemical stability in a wide range of pH environments due to the all-C–C bond backbone. In this paper, we present the synthesis of a series of quaternized polynorbornene random copolymers via vinyl addition polymerization and elucidate the impact of polymer composition on their properties. The quaternary ammonium alkyl tether length and the ratio of n-hexylnorbornene to unsubstituted norbornene are systemically tailored. A copolymer of 5-(3-bromopropyl)-2-norbornene and norbornene with pendant trimethylammonium groups achieved hydroxide conductivity of 109 mS/cm at 80 °C with a modest water uptake of 72%. The addition of n-hexylnorbornene to the copolymer, to make a terpolymer, allows for the polymer composition to be tailored for properties, including a decrease in water uptake and higher processability, despite a slightly decreased hydroxide conductivity. Moreover, the developed membranes are chemically robust and highly mechanically stable, enabling thin membranes to be easily fabricated. This study provides insight into important design parameters for quaternized polynorbornenes for a variety of energy storage and conversion devices, especially fuel cells.

25 ENERGY STORAGE↗
DOE OSTI2023

Development of New Magnetron Sputter Deposition Processes for Laser Target Fabrication

Magnetron sputter deposition is an enabling technology for laser target fabrication. Solutions are readily available for the deposition of most sub-micron-thick elemental films on planar substrates. However, major challenges still remain for the development of robust deposition processes in regimes of ultrathick (over ~10 μm) coatings and nonplanar substrates. These challenging deposition regimes are directly relevant to laser target applications, including both sphero-cylindrical hohlraums and spherical ablators for inertial confinement fusion (ICF) targets. Understanding underlying physical mechanisms for a specific material system is crucial for process development, given the overall complexity of the deposition process, its nonlinear dependence on deposition parameters, and a very large process space, often precluding conventional process optimization approaches. Here, we describe our approach to developing new deposition processes and give practical advice with examples of new results from our ongoing studies of glassy boron carbide ceramics for next-generation ICF ablators and nonequilibrium gold-tantalum alloys for hohlraums for magnetized ICF schemes. Emphasis is given to two major challenges of ultrathick coatings related to achieving process stability and reducing residual stress.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tuning Catalytically Active Single Sites in Nonstoichiometric, Mixed Metal Oxides for Oxygen Electrocatalysis (Final Technical Report)

The objective of the proposed work is to employ controlled synthesis, advanced characterization, detailed electrochemical testing and theoretical calculations to develop a framework that would guide the design of robust, non-stoichiometric mixed metal oxides for oxygen electrocatalysis. In this research plan, we focus around the idea of tuning the metal ion composition and environment to create single atom centers with the utmost electrocatalytic activity. We hypothesized that tuning the cationic sites in nonstoichiometric mixed metal oxides will lead to single 4d/5d metal surface sites with optimal catalytic activity for low temperature oxygen reduction (ORR) and oxygen evolution (OER) at solid/liquid interfaces. We will focus on different crystal structures of these oxides including Ruddlesden-Popper (R-P) oxides, simple perovskites and pyrochlores due to their flexibility in accommodating different metal cation dopants, and the fact that they represent variations in the cationic arrangements in non-stoichiometric mixed metal oxide structures, which will lead to an understanding of how bulk crystal structure effects catalytic activity and stability of these systems.

08 HYDROGEN↗
DOE OSTI2021

A weighted Shifted Boundary Method for free surface flow problems

The Shifted Boundary Method (SBM) belongs to the class of unfitted (or immersed, or embedded) finite element methods and was recently introduced for the Poisson, linear advection/diffusion, Stokes, Navier-Stokes, acoustics, and shallow-water equations. By reformulating the original boundary value problem over a surrogate (approximate) computational domain, the SBM avoids integration over cut cells and the associated problematic issues regarding numerical stability and matrix conditioning. Accuracy is maintained by modifying the original boundary conditions using Taylor expansions. Hence the name of the method, that shifts the location and values of the boundary conditions. In this article, we extend the SBM to the simulation of incompressible Navier-Stokes flows with moving free-surfaces, by appropriately weighting its variational form with the elemental volume fraction of active fluid. This approach prevents spurious pressure oscillations in time, which would otherwise be produced if the total active fluid volume were to change abruptly over a time step. In fact, the proposed weighted SBM method induces small mass (i.e., volume) conservation errors, which converge quadratically in the case of piecewise-linear finite element interpolations, as the grid is refined. Finally, we present an extensive set of two- and three-dimensional tests to demonstrate the robustness and accuracy of the method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Seismic Waveform Inversion Capability on Resource-Constrained Edge Devices

Seismic full wave inversion (FWI) is a widely used non-linear seismic imaging method used to reconstruct subsurface velocity images, however it is time consuming, has high computational cost and depend heavily on human interaction. Recently, deep learning has accelerated it’s use in several data-driven techniques, however most deep learning techniques suffer from overfitting and stability issues. In this work, we propose an edge computing-based data-driven inversion technique based on supervised deep convolutional neural network to accurately reconstruct the subsurface velocities. Deep learning based data-driven technique depends mostly on bulk data training. In this work, we train our deep convolutional neural network (DCN) (UNet and InversionNet) on the raw seismic data and their corresponding velocity models during the training phase to learn the non-linear mapping between the seismic data and velocity models. The trained network is then used to estimate the velocity models from new input seismic data during the prediction phase. The prediction phase is performed on a resource-constrained edge device such as Raspberry Pi. Raspberry Pi provides real-time and on-device computational power to execute the inference process. In addition, we demonstrate robustness of our models to perform inversion in the presence on noise by performing both noise-aware and no-noise training and feeding the resulting trained models with noise at different signal-to-noise (SNR) ratio values. We make great efforts to achieve very feasible inference times on the Raspberry Pi for both models. Specifically, the inference times per prediction for UNet and InversionNet models on Raspberry Pi were 22 and 4 s respectively whilst inference times for both models on the GPU were 2 and 18 s which are very comparable. Finally, we have designed a user-friendly interactive graphical user interface (GUI) to automate the model execution and inversion process on the Raspberry Pi.

Manu, Daniel (ORCID:0000000154982677)↗
DOE OSTI2026

Radiation Effects in Next Generation Used Nuclear Fuel Reprocessing Strategies

With the global community committed to significantly expanding nuclear energy capacity, the development of efficient used nuclear fuel (UNF) management strategies has become more critical than ever. These strategies are vital to fostering the widespread adoption of closed fuel cycles, which are essential for sustainable nuclear energy production and security. Achieving this ambitious goal necessitates a comprehensive understanding of radiation effects on next-generation technologies, as radiolysis can often limit the longevity and performance of these systems. This seminar will provide an overview of next-generation UNF reprocessing strategies, highlighting the latest advancements and innovative approaches in the field. Particular attention will be given to two key areas of recent research: 1. Radiation robustness and performance of advanced sulfur chloride-based chlorination technologies. We will explore the efficacy of sulfur chloride-based chlorination processes in the presence of surrogate cladding materials, specifically aluminum. These processes have shown promise in the dissolution, decontamination, and recovery of cladding materials for reuse. Detailed findings on how the composition and performance of these sulfur chloride solvents respond to radiation exposure will be discussed. 2. Impacts of metal ion complexation and direct dissolution conditions on monoamide-based reprocessing strategies. We will delve into the time-resolved and dose accumulation effects of irradiation on the direct dissolution of voloxidized uranium and rhenium using N,N-di-(2-ethylhexyl) butyramide (DEHBA) or N,N-di-(2-ethylhexyl)isobutyramide (DEHiBA) in pre-equilibrated n-dodecane solvent. The implications of these interactions on dissolution efficiency, radiolytic stability, and overall process performance will be examined. These studies aim to underscore the importance of understanding radiation effects in the development of next-generation UNF reprocessing technologies and the global transition towards more sustainable and efficient nuclear energy systems.

38 - RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCL↗
DOE OSTI2021

Distributional Deep Reinforcement Learning-Based Emergency Frequency Control

Emergency frequency control is one of the most critical approaches to maintain power system stability after major disturbances. With the increasing number of grid-connected renewable energy sources, existing model-based methods of frequency control are facing up with challenges of computational speed and scalability for large-scale systems. In this paper, the emergency frequency control problem is formulated as a Markov Decision Process (MDP) and solved through a novel Distributional Deep Reinforcement Learning (DDRL) method, namely the distributional soft actor critic (DSAC) method. Compared with other RL methods that only estimate the mean value, the proposed DSAC model estimates the distribution of value function over returns. This advancement can lead to more insights and knowledge for the agent, with the benefit of a much faster and more stable learning process, and the improved frequency control performance. Here, the simulation results on IEEE 39-bus and IEEE 118-bus systems demonstrate the effectiveness and robustness of proposed models, as well as the advantage compared to other state-of-the-art DRL algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Innovations in underground hydrogen storage with multiphysics simulations, optimization, and monitoring: A review

Underground Hydrogen Storage (UHS) is a promising solution for large-scale energy storage and a critical component in advancing low-carbon energy system. Ensuring the safety and efficiency of UHS necessitates a comprehensive understanding of multiphysical interactions driven by cyclic pore fluid pressure fluctuations and coupled physicochemical processes. Here, this review examines the key geomechanical responses in UHS, including rock property variations under cyclic loading, fracture evolution and propagation, reservoir stress sensitivity, and fault stability. It also explores the impact of geochemical and microbial reactions on geomechanical characteristics. We provide an in-depth analysis of Thermal-Hydraulic-Mechanical-Chemical (THMC) coupled numerical simulations, highlighting their potential for future multi-scale modeling. Limitations of current machine learning (ML) approaches in addressing UHS challenges are highlighted, emphasizing the need for innovative ML-based methodologies. Operational strategies for hydrogen injection and production are reviewed, focusing on safety, efficiency, and economic viability. The necessity for multi-objective optimization (MOO) to balance storage efficiency, risk mitigation, and cost-effectiveness is also discussed. Current monitoring technologies are evaluated to ensure safe and efficient UHS operations. Finally, this review identifies critical knowledge gaps and underscores the importance of advancing geomechanical understanding under multiphysics-coupling. We highlight the need for ML-driven multiphysics theories, enhanced modeling techniques, and robust optimization strategies to improve UHS performance. This study serves as a comprehensive reference for future research and the large-scale implementation of UHS systems.

25 ENERGY STORAGE↗
DOE OSTI2025

Breeding of microbiomes conferring salt tolerance to plants

Microbiome breeding through host-mediated selection is a technique to artificially select for microbiomes conferring beneficial properties to plants. Using a systematic selection protocol that maximises the heritability of microbiome effects, transmission fidelity, and microbiome stability through multiple selection cycles, we previously developed root-associated microbial communities conferring sodium and aluminium tolerance to Brachypodium distachyon, a model for cereal crops. Here, we explore the physiological mechanisms underlying our selected microbiomes’ effect on plant fitness and analyse how our selection protocol shaped the composition and structure of these microbiomes. We analysed the effects of our selected microbiomes on plant fitness and tissue-nutrient concentration, then used 16S rRNA amplicon sequencing to examine microbial community composition and co-occurrence network patterns. Our sodium-selected microbiomes reduced leaf sodium concentration by ~ 50%, whereas the aluminium-selected microbiomes had no effect on leaf-tissue nutrient concentration, suggesting different mechanisms underlying the microbiome-mediated stress tolerance. By testing the selected microbiomes in a cross-fostering experiment, we show that our artificially selected microbiomes attained (a) ecological robustness contributing to transplantability (i.e. inheritance) of microbiome-encoded effects between plants; and (b) network features identifying key bacteria promoting salt-stress tolerance. Combined, these findings elucidate critical mechanisms underlying host-mediated artificial selection as a framework to breed microbiomes with targeted benefits for plants under salt stresses, with significant implications for sustainable agriculture.

59 BASIC BIOLOGICAL SCIENCES↗