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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A High-Efficient Solution for Electro-Hydraulic Actuators with Energy Regeneration Capability

This paper proposes a cost-effective, robustly practical solution for a high-efficient electro-hydraulic actuator (EHA) for linear drives. The solution addresses the challenges of high costs and limited efficiency that limit the application of EHA for the electrification of many off-road vehicles. Based on a variable-speed electric motor and a low-cost technology for a fixed-displacement pump, the proposed solution is suitable for a compact implementation and it is capable of energy regeneration under overrunning load conditions. Two different architectures—an open circuit and a closed circuit one—are considered to determine the most practical and efficient configuration as well as the control features. Both architectures minimize throttling losses associated with the conventional regulation of hydraulic actuators. Actuator velocities below the minimum and beyond the maximum allowable pump flow rate are achieved in both architectures using a proportional valve that bypasses the pump flow. The paper describes the design methodology as well as the simulation and experimental activities performed to verify the control strategies as well as energy efficiency. Considering an EHA system of about 20 kW, a complete efficiency map of the system is determined for all the possible four quadrants of operation thus including both resistive and overrunning loads, where energy recuperation is implemented. Simulation and experimental results show that the energy efficiency of the hydraulic systems can reach 84.7% in resistive phases. In assistive phases, the hydraulic system can recover up to 81.8% of the actuator energy. Here, the comparison between open-circuit and closed-circuit structures shows the advantages of the former in terms of energy efficiency. The proposed solution is suitable for electrified hydraulic actuation systems, in both industrial and mobile applications. With the advantages of the low cost of the hydraulic unit and high energy efficiency, it is particularly suitable for mobile applications such as construction machines, that are recently experiencing a significant electrification trend.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

A Dataset of CFD Simulated Industrial Furnace Images for Conditional Automatic Generation with GANs

The steel industry is constantly looking for ways to automate processes and improve efficiency. A standard practice in industry is to simulate how complex systems will operate before they are actually used. Some complex systems, including steel industry processes such as blast furnaces, require complex physics-based simulations utilizing computational fluid dynamics (CFD). These CFD physics-based simulations are very accurate but can take significant time and computational resources to process, resulting in challenges for the implementation of the models in real-world operational environments. In recent years, deep learning (DL) has been considered as a substitute for these CFD models. DL models can be trained on validated CFD simulation data and then used for industrial process inference. Previous DL-based solutions have made great contributions for industrial automation but are currently missing the additional visualization component that CFD simulations also provide. In this paper, we propose a dataset for simple DL generative approaches that can help to address this issue. The dataset and methodology under development to approach this prediction are discussed in this work.

Calix, Ricardo↗
DOE OSTI2022

Grid‐responsive smart manufacturing: A perspective for an interconnected energy future in the industrial sector

Abstract With the growing amount of renewable energy sources, the grid has become responsible for accounting for intermittency and the flexibility needed to utilize dynamic sources. Expensive peaking plants and energy storage systems have been proposed as ways to mitigate those problems. There is a large group of energy consumers that can respond to grid conditions. Historically, these consumers have been residential and commercial users, but with modern innovations and practices, industrial consumers have the potential to become a major player in this space. Grid‐responsive smart manufacturing can be used to utilize modern tools in manufacturing innovation as enablers for grid response. These modern tools already exist but are not widely used for industrial grid‐side energy management. This article defines grid‐responsive smart manufacturing, identifies five major barriers to its widespread implementation, and portrays the path to getting industrial users to be key players in grid stability and flexibility.

Billings, Blake W.↗
DOE OSTI2025

CeO 2 Promoted CuO/MgO-Al 2 O 3 Catalyst with Enhanced Activity and Water-Resistance for CO Oxidation

Copper (Cu)-based catalysts have emerged as cost-effective and sustainable alternatives to noble metal systems (e.g., Pt, Pd) for catalytic CO oxidation. However, their practical application is hindered by insufficient low-temperature activity and rapid deactivation under wet conditions containing moisture. To address these challenges, this work introduces CeO 2 -modified CuO/MgO-Al 2 O 3 (Cu-Ce/MA) catalysts, strategically designed to enhance the catalytic performance and water resistance simultaneously. These catalytic materials were evaluated for CO oxidation under both dry and humid conditions, revealing that CeO 2 modification significantly improves the low-temperature activity. Specifically, the optimal catalyst, Cu-30Ce/MA, achieved a 50% CO conversion temperature (T 50 ) of 151 °C, a marked reduction from 218 °C on Cu/MA reference catalyst. Furthermore, the water resistance improves in a CeO 2 content-dependent manner, with higher CeO 2 loadings imparting greater stability in humid environments. Detailed characterizations demonstrate that CeO 2 promotes the dispersion of CuO and stabilizes Cu sites, while also enhancing the low-temperature reducibility and CO adsorption capacity. Crucially, CeO 2 modification suppresses the competitive H 2 O adsorption, mitigating water-induced deactivation. These synergistic effects collectively rationalize the superior activity and durability of Cu-Ce/MA catalysts. By elucidating the dual role of CeO 2 in optimizing Cu-based systems, this study advances the rational design of cost-effective catalysts for real-world CO emission control, particularly under water-rich industrial conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A bending test protocol for characterizing the mechanical performance of flexible photovoltaics

Flexible photovoltaics (PV) represents a promising research field with great potential for wearable, portable, and indoor applications. Significant progress has been made in recent years, with flexible emerging PV reporting power conversion efficiency (PCE) over 24%. Yet, there is a need for a unifying protocol to assess PV performance, compare research results, and evaluate the state- of-the-art achievements in flexible PV. In this paper, a consensus protocol is presented for measuring PCE over 1,000 bending cycles under 1% strain. Moreover, several good practice guidelines are proposed including bending procedures, flexibility testing with and without encapsulation, and ambient conditions during testing (e.g., temperature, humidity, illumination). Notably, the importance of uniform application of bending radius and the testing of parallel and perpendicular orientations of bending axis with respect to the direction of the electric current are emphasized. These recommendations aim to promote consistency in device comparison and allow for better reproducibility.

Fukuda, Kenjiro↗
DOE OSTI2026

Performance of Heterostructural TaC/AlGaN Schottky Diodes Based on First Principles Electronic Structure Properties

Advances in ultra-wide bandgap materials, such as high Al-content AlxGa1-xN (AlGaN), are essential for next generation power electronics, but the requirement for lattice matched substrates is currently a significant obstacle. Recently, conductive TaC has emerged as a promising virtual substrate for AlGaN heteroepitaxy, with wurtzite (0001) AlxGa1-xN lattice-matched to rocksalt (111) TaC at x ~ 0.5. Thus, understanding and controlling the electronic properties of the TaC/AlGaN interface is key for developing technological applications based on TaC/AlGaN devices. Using density functional theory and electronic structure calculations, we here investigate TaC/Al0.5Ga0.5N interfaces, where we include explicit alloy models in the slab calculations. We predict the Schottky barrier height and the electric field discontinuity resulting from interface charges. Considering all possible combinations of (Ta, C) substrate termination, (Al/Ga, N) nucleation, and (Al/Ga, N) polarity, we construct a chemical potential phase diagram to identify the stable interfaces that can be accessed through variation of the synthesis conditions. The predicted interface electronic properties are implemented in device performance simulations to demonstrate a practical design for a strain-free, high-efficiency TaC/AlGaN Schottky diode with a low barrier height and without interface charges, underscoring the potential of TaC as a substrate for ultra-wide bandgap devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Spectral density reconstruction with Chebyshev polynomials

Accurate calculations of the spectral density in a strongly correlated quantum many-body system are of fundamental importance to study its dynamics in the linear response regime. Typical examples are the calculation of inclusive and semiexclusive scattering cross sections in atomic nuclei and transport properties of nuclear and neutron star matter. Integral transform techniques play an important role in accessing the spectral density in a variety of nuclear systems. However, their accuracy is in practice limited by the need to perform a numerical inversion which is often ill-conditioned. Here, in the present work we extend a recently proposed quantum algorithm which circumvents this problem. We show how to perform controllable reconstructions of the spectral density over a finite energy resolution with rigorous error estimates. An appropriate expansion in Chebyshev polynomials allows for efficient simulations also on classical computers. We apply our idea to obtain the local density of states for graphene in a magnetic field as a proof of principle. This paves the way for future applications in nuclear and condensed matter physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Distinguishing between Quantum and Classical Markovian Dephasing Dissipation

Understanding whether dissipation in an open quantum system is truly quantum is a question of both fundamental and practical interest. We consider n qubits subject to correlated Markovian dephasing and present a sufficient condition for when bath-induced dissipation can generate system entanglement and hence must be considered quantum. Surprisingly, we find that the presence or absence of time-reversal symmetry plays a crucial role: broken time-reversal symmetry is required for dissipative entanglement generation. Further, simply having nonzero bath susceptibilities is not enough for the dissipation to be quantum. We also present an explicit experimental protocol for identifying truly quantum dephasing dissipation and lay the groundwork for studying more complex dissipative systems and finding optimal noise mitigating strategies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Desmearing two-dimensional small-angle neutron scattering data by central moment expansions

Resolution smearing is a critical challenge in the quantitative analysis of two-dimensional small-angle neutron scattering (SANS) data, particularly in studies of soft-matter flow and deformation using SANS. Here, we present a central moment expansion technique to address smearing in anisotropic scattering spectra, offering a model-free desmearing methodology. By accounting for directional variations in resolution smearing and enhancing computational efficiency, this approach reconstructs desmeared intensity distributions from smeared experimental data. Computational benchmarks using interacting hard-sphere fluids and Gaussian chain models validate the accuracy of the method, while simulated noise analyses confirm its robustness under experimental conditions. Experimental validation using rheological SANS data from shear-induced micellar structures demonstrates the practicality and effectiveness of the proposed algorithm. The desmearing technique provides a powerful tool for advancing the quantitative analysis of anisotropic scattering patterns, enabling precise insights into the interplay between material microstructure and macroscopic flow behavior.

anisotropic scattering spectra↗
DOE OSTI2026

Advanced LiFSI-LiPF6 Electrolyte for Wide-Temperature and Thermally Stable Lithium-Ion Batteries

A new optimized LiFSI–LiPF6 dual-salt controlled-solvation electrolyte (E-DS) is demonstrated to enable practical graphite||LiNi0.8Mn0.1Co0.1O2 cells (˜4.0 mAh cm?²) to achieve exceptional performance and safety under extreme conditions. By optimizing anion coordination with the smaller, more dissociating FSI? anion, the E-DS forms ultrathin, dense, and inorganic-rich electrode/electrolyte interphases that dramatically suppress solvent decomposition, transition-metal dissolution, and surface reconstruction compared to the conventional LiPF6/carbonate electrolyte. Consequently, E-DS cells deliver >78% capacity retention after 300 cycles at 60 °C, retain fast discharging capacity at 30 °C, and operate effectively at -20 °C. Most strikingly, fully charged full cells with E-DS, even under overcharging to 4.8 V, show a lower heat evolution in stable formulations — transforming a traditionally unstable high-voltage/high-temperature configuration into an intrinsically safe state. This work establishes a new benchmark for carbonate-containing electrolytes, simultaneously achieving high energy density, fast-discharging capability, wide-temperature operation (-20 to 60 °C), and outstanding thermal safety in nickel-rich lithium-ion batteries.

electrode/electrolyte interphase↗
DOE OSTI2024

Transitioning from Simulation to Reality: Applying Chatter Detection Models to Real-World Machining Data

Chatter, a self-excited vibration phenomenon, is a critical challenge in high-speed machining operations, affecting tool life, product surface quality, and overall process efficiency. While machine learning models trained on simulated data have shown promise in detecting chatter, their real-world applicability remains uncertain due to discrepancies between simulated and actual machining environments. The primary goal of this study is to bridge the gap between simulation-based machine learning models and real-world applications by developing and validating a Random Forest-based chatter detection system. This research focuses on improving manufacturing efficiency through reliable chatter detection by integrating Operational Modal Analysis (OMA), Receptance Coupling Substructure Analysis (RCSA), and Transfer Learning (TL). The study applies a Random Forest classification model trained on over 140,000 simulated machining datasets, incorporating techniques like Operational Modal Analysis (OMA), Receptance Coupling Substructure Analysis (RCSA), and Transfer Learning (TL) to adapt the model for real-world operational data. The model is validated against 1600 real-world machining datasets, achieving an accuracy of 86.1%, with strong precision and recall scores. The results demonstrate the model’s robustness and potential for practical implementation in industrial settings, highlighting challenges such as sensor noise and variability in machining conditions. This work advances the use of predictive analytics in machining processes, offering a data-driven solution to improve manufacturing efficiency through more reliable chatter detection.

42 ENGINEERING↗
DOE OSTI2025

Drought adaptation index (DAI) based on BLUP as a selection approach for drought-resilient switchgrass germplasm

This study introduces a Drought Adaptation Index (DAI), derived from Best Linear Unbiased Prediction (BLUP), as a method to assess drought resilience in switchgrass (Panicum virgatum L.). A panel of 404 genotypes was evaluated under drought-stressed (CV) and well-watered (UC) conditions over four consecutive years (2019–2022). BLUP-estimated biomass yields were used to calculate the DAI, which enabled classification of genotypes into four adaptation groups: very well-adapted, well-adapted, adapted, and unadapted. The DAI was compared with conventional drought tolerance indices, including the Stress Susceptibility Index (SSI), Stress Tolerance Index (STI), Geometric Mean Productivity (GMP), and Yield Stability Index (YSI). Correlation analyses demonstrated strong agreement between DAI and these indices, supporting its validity and consistency. Biplot analyses using the Genotype plus Genotype-by-Environment Interaction (GGE) and Additive Main Effects and Multiplicative Interaction (AMMI) models revealed significant genotype-by-environment interactions (GEI) and identified J222.A, J463.A, and J295.A. A as high-performing genotypes, with J222.A exhibiting greater yield stability across treatments and years. Additionally, DAI isoline curves provided a graphical representation of differential genotype performance under drought and control conditions. These visualizations aided in distinguishing genotypes with stable and superior biomass yield across contrasting environments. Overall, the BLUP-based DAI is a robust and practical selection tool that improves the accuracy of identifying drought-resilient, high-yielding switchgrass genotypes. Its integration into breeding programs offers a comprehensive framework for improving biomass productivity and stress adaptation under variable climatic conditions. The application of DAI supports the development of climate-resilient cultivars and contributes to sustainable bioenergy and forage production systems.

BLUP↗
DOE OSTI2022

Methods of producing cobalt nanoparticles and hollow gold nanospheres and kits for practicing same

Provided are methods of producing cobalt nanoparticles (Co NPs). The methods include combining a cobalt salt, a capping agent, and a reducing agent, under Co NP synthesis conditions including a temperature selected to produce cobalt nanoparticles of a pre-selected diameter, where the temperature and pre-selected diameter are inversely related. In certain aspects, the methods further include producing hollow gold nano spheres (HGNs) using the cobalt nanoparticles as scaffolds. Also provided are cobalt nanoparticles and hollow gold nano spheres (HGNs) produced according to the present methods. Kits that find use in practicing the methods of the present disclosure are also provided.

Pu, Ying-Chih↗
DOE OSTI2025

Enhancing Biomass Productivity by Forecast‐Informed Pond Operations

ABSTRACT Microalgal cultivation for biofuels and proteins holds significant promise but faces challenges in achieving economically viable biomass productivity under variable environmental conditions. This study introduces a forecast‐informed pond operation (FIPO) system that uses numerical weather prediction (NWP) ensemble forecasts and the biomass assessment tool (BAT) to optimize daily dilution rates for enhanced biomass production. In contrast to the current practice, where fixed dilution rates are based on operator experience, the FIPO system determines the optimal dilution rate based on future weather forecasts and biomass growth conditions. Our experiments validate the effectiveness of FIPO in both short‐ and long‐term growth scenarios. In short‐term experiments, FIPO increased biomass production by 21.3% compared to batch growth and 7.4% over fixed dilution (60% every 3 days) operations. The NWP forecast‐informed operations achieved biomass production nearly identical to that using perfect weather forecasts, highlighting the accuracy of current NWP forecasts for guiding pond operations. In long‐term experiments, FIPO resulted in biomass production increases of 13.3% and 17.8% compared to two fixed dilution rates (60% every 3 days and 20% daily). These findings underscore the viability of using NWP forecasts to optimize microalgal cultivation systems. By adjusting daily dilution rates in response to forecasted weather, operators can achieve higher biomass yields and mitigate risks associated with environmental variability. This study provides a foundation for future research and practical applications in commercial‐scale microalgal production.

Yan, Hongxiang [Energy and Environment Directorate↗
DOE OSTI2024

A Novel Method for Setting Meaningful Thresholds for RMS-Energy Oscillation Detectors

Oscillation detection and mitigation is a crucial aspect of reliable power system operation. Several transmission system operators and reliability coordinators use the RMS-energy method of oscillation detection, but the process of setting thresholds is time and labor intensive. The current industry practice in the United States is to set thresholds based on the RMS-energy's value during ambient conditions, which can often lead to nuisance alarms that require thresholds to be manually retuned. In this paper, we propose a method for setting RMS-energy thresholds that directly accounts for oscillation amplitudes specified by the user. A theoretical analysis of the statistical properties of the RMS-energy incorporates these user-specified amplitudes, resulting in thresholds that reliably detect oscillations of interest while avoiding nuisance alarms. Theoretical results are validated with simulated measurements and the real-world practicality of the method is established with publicly available field-measured data from the Grid Event Signature Library.

Follum, James D.↗
DOE OSTI2024

Electrical and thermal characteristics of LaB6 thermionic hollow cathodes operating in He, D2, Ar, and Xe at 4–200 Pa and 0.25–5 A cm−2

We report characteristics of lanthanum hexaboride (LaB6) cathodes for conditions relevant to a high-voltage, high-current switching device. LaB6 is selected because of its relatively low work function, stability in the presence of many common gas impurities, and a low evaporation rate (long life) at operating temperatures. We have investigated the effect of cathode geometry, gas type, pressure, and current on a LaB6 hollow cathode in a diode configuration with an opposing planar anode. The gas is stagnant at a relatively low pressure of 4–200 Pa (0.03–1.5 Torr) because of device high-voltage standoff requirements. In all cases, the plasma voltage decreases to a plateau value with increasing current where a practical device would operate. The plateau voltage aligns with the fill gas excitation or ionization voltage, depending on conditions. At high current, the cathode temperature exceeds that required for thermionic emission to supply the total current, a behavior that is understood by accounting for back-diffusing bulk electrons.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Towards the first plasma-electron screening experiment

The enhancement of fusion reaction rates in a thermonuclear plasma by electron screening of the Coulomb barrier is an important plasma-nuclear effect that is present in stellar models but has not been experimentally observed. Experiments using inertial confinement fusion (ICF) implosions may provide a unique opportunity to observe this important plasma-nuclear effect. Herein, we show that experiments at the National Ignition Facility (NIF) have reached the relevant physical regime, with respect to the density and temperature conditions, but the estimated impacts of plasma screening on nuclear reaction rates are currently too small and need to be increased to lower the expected measurement uncertainty. Detailed radiation hydrodynamics simulations show that practical target changes, like adding readily available high-Z gases, and significantly slowing the inflight implosion velocity, while maintaining inflight kinetic energy, might be able to push these conditions to those where plasma screening effects may be measurable. We also perform synthetic data exercises to help understand where the anticipated experimental uncertainties will become important. But challenges remain, such as the detectability of the reaction products, non-thermal plasma effects, species separation, and impacts of spatial and temporal gradients. This work lays the foundation for future efforts to develop an important platform capable of the first plasma electron screening observation.

inertial confinement fusion↗