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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 127 records · Page 7

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DOE OSTI2019

Automated Design and Analysis of a Variable Displacement Linkage Motor

Hydrostatic drives consisting of a variable displacement pump and a low speed high torque (LSHT) motor are frequently used in off-highway vehicles. A variable displacement traction motor is desirable because of the ability to downsize the pump and thereby run the hydrostat at higher efficiency, as well as the possibility of hybridization of the drivetrain. Currently on the market are fixed and discrete speed LSHT radial piston motors and high speed low torque variable displacement axial piston motors. The radial piston motors are displacement dense but are not continuously variable, whereas the axial piston motors are continuously variable but require gearboxes, introducing packaging and robustness concerns. The Variable Displacement Linkage Motor (VDLM) is a LSHT motor that is continuously variable. It offers several benefits over current LSHT motors in that it is highly efficient over its operating range, it has low torque ripple, and it is displacement dense due to its multi-lobed cam and radial packaging. As with the design of any motor, the process is iterative and must be performed whenever performance objectives change. This paper describes an automated method for rapid exploration of the solution space for a variable displacement motor with specific application to the VDLM. This method leads to a motor design that theoretically can achieve 97% efficiency with a torque ripple below 5% at full displacement.

42 ENGINEERING↗

DOE OSTI2026

Evaluating Polymer Properties with Different Additives for Carbon Capture and Other Applications

Anthropogenic climate change is one of this generation’s most pressing concerns, with the potential to completely alter the delicate balance we’ve struck with nature. Already, global temperatures have risen 1.29°C, leading to disrupted weather systems, extinctions, increased risks of wildfires, and sea level rise, to name a few effects. Carbon dioxide emission from the combustion of fossil fuels and other industrial activity is a large driver of this phenomenon, as it absorbs heat before it can be radiated away from Earth, trapping it. Carbon dioxide has reached unprecedented levels in our atmosphere, showing a 50% increase from preindustrial averages to a whopping 430 ppm. Thus, reducing the amount of carbon dioxide via carbon capture technology is an important endeavor that serves to benefit everyone. The Microencapsulated CO 2 Sorbent (MECS) team at Lawrence Livermore National Laboratory (LLNL) has turned to microencapsulation to approach this endeavor. Microcapsules provide an attractive approach to carbon capture, combining large surface areas for more efficient mass transfer, regenerative abilities, reduced solvent loss, and improved handling. Additionally, while existing carbon capture technology relies on industrial plants, capsules could present a modular approach to carbon capture, reducing the need for extensive physical infrastructure. The MECS team’s design consists of a polymer membrane that contains a liquid carbon sequestering sorbent, aqueous sodium carbonate. The carbon capturing reaction occurs in three distinct steps, the first of which is the dissolution of carbon dioxide into the sorbent solution and its conversion into carbonic acid (H 2 CO 3 ), shown in equations 1 and 2 respectively. Because this step hinges upon the ability of carbon dioxide to reach the solution inside the capsule, it is necessary that the microcapsule shell is permeable to carbon dioxide gas. The MECS team produces these microcapsules using the in-air droplet encapsulation apparatus (IDEA) shown in figure 1, which can produce uniform micron-scale droplets at speeds much faster than traditional single-dispersal microfluidic-based techniques. The IDEA Is 100 times faster than these current techniques and can reach up to 1000 times their speed when incorporating a multi-nozzle design. Additionally, because droplets are produced in-air via vibration, IDEA can decrease post-processing times and material waste by 99% and can fabricate microgels that are 10 to 100 times more viscous than can be produced via traditional microfluidics. While this design represents a breakthrough in the throughput, efficiency, and tunability of microcapsule production, it imposes a major constraint on the microcapsule curing process. Because microcapsule shells are crosslinked with UV light while falling 30 cm through the air, this gives them a reaction window of approximately 0.2 seconds. Thus, the system and shell formulations must be optimized such that the shells can be fully crosslinked within this very narrow window, prompting investigations into curing behavior.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Frequency Support Enhancement of a Permanent Magnet-Based Adjustable-Speed Pumped Hydropower Plant

When a permanent magnet (PM) -based adjustable-speed pumped storage hydropower (AS-PSH) plant delivers frequency response via the full-scaled power converter, there is power imbalance at the PM generator during the initial stage of the frequency response. This is because the AS-PSH has the different time constants between the power converter and wicket gate in the governor valve. Thus, this imbalance causes a sudden reduction of the rotational speed of the machine during the frequency response. As a result, a voltage deficit arises at the generator terminal in proportion to the decrement in the rotational speed, and thereby it is promising that the current flow at the converter will reach its limit when attempting to inject the commanded active power at a reduced voltage level. Thus, this causes the degradation of the frequency response of the AS-PSH due to the self-demagnetization at a reduced rotational speed. This paper proposes a frequency support scheme of a PM-based AS-PSH to enhance the frequency response by bridging the gap between the different time constants. To achieve this, the frequency support scheme includes a gate opening adjustment in the governor and a dynamic ramp-down in converter controller of the AS-PSH.

13 HYDRO ENERGY↗

DOE OSTI2021

Enhancement of Industry Legacy Probabilistic Risk Assessment Methods and Tools

Probabilistic risk assessments (PRAs) are integral to nuclear power plant (NPP) operations, having tremendously benefitted the safety of the U.S. reactor fleet for decades. Insights obtained from the models have provided perspectives on a variety of applications, both at the plant and for the regulator. While these models are very useful, they are now being asked to represent and analyze aspects of the plant that were never envisioned by the initial PRA practitioners. Furthermore, heightened demands on the PRA models have led to increased computing power requirements. Additionally, as the complexity of the PRA models increased, the difficulty experienced by non-PRA experts in trying to understand these models, grasp the insights they provide, and effectively use that information has become problematic. The need for research to address key issues regarding PRA tools and methods has never been greater. Although the nuclear power industry has largely been well-served by these tools and methods, the underlying science is dated, remaining mostly unchanged for over two decades. Three areas were identified as most beneficial to address to maintain and improve the usefulness of the current practice legacy PRA tools: improvement in quantification speed, increased ability to efficiently model multi-hazard models, and improvement in modeling human action dependency in PRA. This report provides the outcomes from the FY2021 research into these three areas, identifying potential technical gaps and solutions, and charting the next steps forward to address current PRA challenges.

42 ENGINEERING↗

DOE OSTI2025

Spatial‐Uniformity–Driven Bayesian Optimization for Rapid Development of Printed Perovskite Solar Cells

Printed metal halide perovskites can enable rapid, roll-to-roll manufacturing of a broad class of optoelectronics—flexible solar cells and imagers among them—while promising cost and speed advantages over incumbent silicon. However, though current methods offer high throughput and patterning capabilities, perovskite films’ spatial heterogeneity remains a challenge for large-area devices. Here, a spatial-uniformity-driven Bayesian optimization (BO) approach is leveraged to accelerate the development of printed perovskite solar cells and improve large-area device performance. Using a BO surrogate model, a 6D design space of ink chemistry and printing physics is explored via extensive iterative experimentation (≈100) informed by an objective function capturing spatial photoluminescence (PL) variance. It is discovered that optimizing for uniformity drives rapid advances in photovoltaic performance, yielding ≈20% power conversion efficiency (PCE) for small area (0.134 cm 2 ) devices and > 16% for large area (1 cm 2 ) devices. This machine-learning approach simultaneously enables rheological comparison of ink formulations that accelerate the leveling of Saffman-Taylor artifacts and improve film uniformity. Here, this showcases uniformity-driven BO as an efficient approach for uncovering the key printing physics and mitigating spatial heterogeneity to enable device scaling beyond small cell areas.

14 SOLAR ENERGY↗

DOE OSTI2024

Long-term, non-invasive FTIR detection of low-dose ionizing radiation exposure

Non-invasive methods of detecting radiation exposure show promise to improve upon current approaches to biological dosimetry in ease, speed, and accuracy. Here we developed a pipeline that employs Fourier transform infrared (FTIR) spectroscopy in the mid-infrared spectrum to identify a signature of low dose ionizing radiation exposure in mouse ear pinnae over time. Mice exposed to 0.1 to 2 Gy total body irradiation were repeatedly measured by FTIR at the stratum corneum of the ear pinnae. We found significant discriminative power for all doses and time-points out to 90 days after exposure. Classification accuracy was maximized when testing 14 days after exposure (specificity > 0.9 with a sensitivity threshold of 0.9) and dropped by roughly 30% sensitivity at 90 days. Infrared frequencies point towards biological changes in DNA conformation, lipid oxidation and accumulation and shifts in protein secondary structure. Since only hundreds of samples were used to learn the highly discriminative signature, developing human-relevant diagnostic capabilities is likely feasible and this non-invasive procedure points toward rapid, non-invasive, and reagent-free biodosimetry applications at population scales.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2020

Toward DMRG-tailored coupled cluster method in the 4c-relativistic domain

There are three essential problems in computational relativistic chemistry: Electrons moving at relativistic speeds, close lying states, and dynamical correlation. Currently available quantum-chemical methods are capable of solving systems with one or two of these issues. However, there is a significant class of molecules in which all the three effects are present. These are the heavier transition metal compounds, lanthanides, and actinides with open d or f shells. For such systems, sufficiently accurate numerical methods are not available, which hinders the application of theoretical chemistry in this field. In this paper, we combine two numerical methods in order to address this challenging class of molecules. These are the relativistic versions of coupled cluster methods and the density matrix renormalization group (DMRG) method. To the best of our knowledge, this is the first relativistic implementation of the coupled cluster method externally corrected by DMRG. The method brings a significant reduction of computational costs as we demonstrate on the system of TlH, AsH, and SbH.

Brandejs, Jan (ORCID:0000000221073095)↗

DOE OSTI2021

wtDigiTwin (Wind Turbine Digital Twin) [SWR-21-15]

This wind turbine digital twin software (wtDigiTwin) provides a digital twin solution for wind turbine applications. The focus of wtDigiTwin is to estimate loads, motions and environmental conditions for an operating wind turbine. The program uses supervisory control and data acquisition (SCADA) measurements as inputs, together with a wind turbine model. The wind industry is currently challenged by the high cost of operation and maintenance. These costs could be mitigated if component failures are predicted, but such predictions are difficult unless the turbines are equipped with expensive measuring devices. The alternative is to use a digital twin such as wtDigiTwin to estimate the necessary signals. wtDigiTwin can perform online prediction of signals that are otherwise not measured, using a limited set of reliable measurements and a physics-based model. The predicted signals can be used in applications that have direct cost benefits: 1) real-time estimation of the fatigue consumption of key components of the wind turbine; 2) root cause analyses and failure detections ; 3) lifetime reassessments ; 4) improvements to follow-on designs. The current version provides examples to estimate wind speed, thrust, torque, tower-top position, and tower loads on an onshore wind turbine using the following measurements tower top acceleration, generator torque, pitch, and rotational speed. The model combines a linear state-space model, a wind speed estimator, and a Kalman filter algorithm that integrates measurements with the state model to perform state estimations. The state space model is obtained either using OpenFAST linearizations, or using the yams package provided with the software.

Branlard, Emmanuel↗

DOE OSTI2022

LightSlingers

LightSlingers are a novel type of directional broadband antenna capable of “slinging” tightly focused wave packets with precision toward a target location. Unlike conventional antennas, they use polarization currents, animated to faster-than-light speeds, as their emission mechanism. Sturdy, small, and versatile, they have the potential to disrupt the telecommunications market. The document serves as documentation/a brochure for the 2022 R&D 100 Award entry.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Solutions for Enhanced Legacy Probabilistic Risk Assessment Tools and Methodologies: Improving Efficiency of Model Development and Processing via Innovative Human Reliability Dependency Analysis

Probabilistic risk assessments (PRAs) are integral to nuclear power plant (NPP) operations, having tremendously benefitted the safety of the U.S. reactor fleet for decades. Insights obtained from the models have provided perspectives on a variety of applications, both at the plant and for the regulator. While these models are very useful, they are now being asked to represent and analyze aspects of the plant that were never envisioned by the initial PRA practitioners. Furthermore, heightened demands on the PRA models have led to increased computing power requirements. Additionally, as the complexity of the PRA models increased, the difficulty experienced by non-PRA experts in trying to understand these models, grasp the insights they provide, and effectively use that information has become problematic. The need for research to address key issues regarding PRA tools and methods has never been greater. Although the nuclear power industry has largely been well-served by these tools and methods, the underlying science is dated, remaining mostly unchanged for over two decades. Three areas were identified as most beneficial to address to maintain and improve the usefulness of the current practice legacy PRA tools: improved quantification speed, increased ability to efficiently model multi-hazard models, and improved modeling human action dependency in PRA. This report is focused on the third critical area, improvements in dependency analysis of human actions conducted as part of a typical human reliability assessment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Final Report for Grant

This is the final report for this project. The major objectives were to develop full models and standard cells of CMOS silicon photomultipliers (SiPM) for neutron detection applications. Specifically, the research seeks to replace photomultiplier tubes, used in neutron detection applications, with SiPMs containing integrated readout electronics fabricated in standard CMOS processes. The detectors improve on the detection efficiency, readout speed, resolution (sensitivity), and spatial resolution of current systems. In particular, this work involved collaboration with the instrument and detector group at ORNL who build detectors based on discrete commercially available PMTs and SiPMs. The SiPM detectors developed in this work are based on Perimeter Gated Single Photon Avalanche Diodes (PGSPAD). These devices have tunable breakdown voltage which affects other performance characteristics of the detectors. The ability of the detectors to have integrated readout and tune the noise floor and dynamic range in addition to offering a method for non-uniformity compensation in a compact form significantly impacts the imaging research field and includes the nuclear sciences field, circuits and systems field in addition to varied fields such as geography and biology/medicine.

42 ENGINEERING↗

DOE OSTI2021

Prevention of lithium-ion battery thermal runaway using polymer-substrate current collectors

Isolating electronically conducting material from internal short circuits is a promising way to prevent the onset of thermal runaway within lithium-ion cells. Here, a metal-coated polymer current collector, which is designed to disconnect internal short circuits by withdrawing from the heating region, is tested in 18650 cells. In addition to having lower mass and manufacturing costs, cells with metal-coated polymer current collectors demonstrate a reduced risk of thermal runaway during nail penetration. High-speed synchrotron X-ray radiography of 18650 cells during nail-penetration testing, in tandem with pre- and post-mortem X-ray computed tomography, provides insights into the function of the current collectors. The results are compared with those of 18650 cells with standard commercial aluminum and copper current collectors. Cells with aluminum-coated polymer current collectors demonstrated 100% success in thermal runaway prevention during nail penetration, retaining a cell voltage >4.00 V, while standard cells consistently experienced thermal runaway.

25 ENERGY STORAGE↗

DOE OSTI2023

Study of dielectric breakdown in liquid xenon with XeBrA: The xenon breakdown apparatus

Maintaining the electric fields necessary for the current generation of noble liquid time projection chambers (TPCs), with drift lengths exceeding 1 m, requires a large negative voltage applied to their cathode. Delivering such high voltage is associated with an elevated risk of electrostatic discharge and electroluminescence, which would be detrimental to the performance of the experiment. The Xenon Breakdown Apparatus (XeBrA) is a 5-l, high voltage test chamber built to investigate the contributing factors to electrical breakdown in noble liquids. Here, in this work, we present the main findings after conducting scans over stressed electrode areas, surface finish, pressure, and high voltage ramp speed in the medium of liquid xenon. Area scaling and surface finish were observed to be the dominant factors affecting breakdown, whereas no significant changes were observed with varying pressure or ramp speed. A general rise in both the anode current and photon rate was observed in the last 30 s, leading up to a breakdown, with a marked increase in the last couple of seconds. In addition, the position of breakdowns was reconstructed with a system of high-speed cameras and a moderate correlation with the Fowler–Nordheim field emission model was found. Tentative evidence for bubble nucleation being the originating mechanism of breakdown in the liquid was also observed. We deem the results presented in this work to be of particular interest for the design of future, large TPCs, and practical recommendations are provided.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Amorphous Indium Oxide Channel FEFETs With Write Voltage of 0.9 V and Endurance >10 12 for Refresh-Free Embedded Memory

This work presents, for the first time, a back-end-of-the-line (BEOL)-compatible W-doped indium oxide (IWO) ferroelectric field-effect transistor (FEFET) with a record-low operating voltage below 0.9 V and a write speed of 20 ns while achieving a transient read current window (CW) ratio ( I LVT /I HVT ) greater than 10 4 . The device also exhibits exceptional reliability characteristics such as: 1) measured bipolar write endurance up to 10 12 cycles; 2) a fast read speed of 50 ns; 3) read endurance surpassing 10 12 cycles; and 4) retention exceeding 10 4 s at 85 ∘ C. Furthermore, a physics-based numerical model has been developed to investigate the nanoscale characteristics of BEOL FEFET devices, leveraging nucleation-limited switching in HfO 2 ferroelectrics and dc characterization to extract material and channel parameters for accurate device simulation. The simulation uncovers the stochastic switching behavior of BEOL amorphous oxide semiconductor (AOS) FEFETs and demonstrates an intrinsic switching time as low as 1 ps, highlighting the potential of BEOL AOS FEFETs for ultrafast memory applications. These results establish AOS FEFETs as a compelling candidate for high-density embedded memory applications for last-level cache (LLC) (L4) in advanced CMOS technology nodes.

1-V ferroelectric field-effect transistor (FEFET)↗

DOE OSTI2022

Measuring characteristic differences between high- and low-performing discharges on the MegaJOuLe Neutron Imaging Radiography (MJOLNIR) DPF

A dense plasma focus (DPF) is a compact coaxial plasma gun, which completes its discharge as a Z-pinch, producing short (<100 ns) pulses of ions, x rays, and/or neutrons. Lawrence Livermore National Laboratory recently constructed and began operating a new device, the MJOLNIR (MegaJOuLe Neutron Imaging Radiography) DPF, which is designed for single-pulse flash neutron radiography. This device has achieved neutron yields of up to 4.1×10 11 neutrons/pulse at 3.3 MA peak current, and higher-current commissioning is under way. Like most DPFs, MJOLNIR exhibits variable yields in some configurations. Here, we present evidence of the role of parasitic current paths within the gun in stochastically influencing the yield. First through “conditioning shots,” where new hardware has been introduced, we show that increased run-down and run-in speeds correlate with higher yields. These observations are consistent with current being delivered to the electrodes but not to the main plasma sheath, degrading the implosion-driving force. Once nominal conditions are established, we correlate low-performing discharges with smaller current dip and associated voltage spike for a fixed machine configuration. A snow-plow model is able to recreate small-magnitude current dips through the introduction of a parasitic current path, and particle-in-cell simulations establish how parasitic current paths lower the ion beam energy available to produce neutrons. Finally, we observe an increased likelihood of shots with low yield and smaller current dip with increasing fill pressure.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

High-Speed Diagnostic and Simulation Capabilities for Reacting Hypersonic Reentry Flows (LDRD Final Report)

High-enthalpy hypersonic flight represents an application space of significant concern within the current national-security landscape. The hypersonic environment is characterized by high-speed compressible fluid mechanics and complex reacting flow physics, which may present both thermal and chemical nonequilibrium effects. We report on the results of a three-year LDRD effort, funded by the Engineering Sciences Research Foundation (ESRF) investment area, which has been focused on the development and deployment of new high-speed thermochemical diagnostics capabilities for measurements in the high-enthalpy hypersonic environment posed by Sandia's free-piston shock tunnel. The project has additionally sponsored model development efforts, which have added thermal nonequilibrium modeling capabilities to Sandia codes for subsequent design of many of our shock-tunnel experiments. We have cultivated high-speed, chemically specific, laser-diagnostic approaches that are uniquely co-located with Sandia's high-enthalpy hypersonic test facilities. These tools include picosecond and nanosecond coherent anti-Stokes Raman scattering at 100-kHz rates for time-resolved thermometry, including thermal nonequilibrium conditions, and 100-kHz planar laser-induced fluorescence of nitric oxide for chemically specific imaging and velocimetry. Key results from this LDRD project have been documented in a number of journal submissions and conference proceedings, which are cited here. The body of this report is, therefore, concise and summarizes the key results of the project. The reader is directed toward these reference materials and appendices for more detailed discussions of the project results and findings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

How Snow Aggregate Ellipsoid Shape and Orientation Variability Affects Fall Speed and Self-Aggregation Rates

Snow aggregate shapes and orientations have long been known to exhibit substantial variability. Despite this observed variability, most weather and climate prediction models use fixed power-law functions that deterministically map particle size to mass and fall speed. As such, integrated quantities like precipitation and self-aggregation rates currently ignore nonlinear effects resulting from variation in shape and orientation for aggregates of the same size. This study therefore develops an analytic framework that couples an empirically based bivariate distribution of ellipsoid shapes to classical hydrodynamic theory so as to capture an appropriate dispersion of masses, projected areas, and fall speeds for an assumed size distribution. For a fixed aggregate size, shape variations produce approximately ±0.13 m s -1 standard deviation of fall speed which increases the mass flux fall speed dispersion by more than 100% over traditional microphysics models. This increased fall speed dispersion results predominantly from shape-induced mass dispersion whereas orientation and drag dispersion play a lesser role. Shape variations can increase mass- and reflectivity-weighted fall speeds by up to 60% of traditional models whereas self-aggregation rates can increase by a factor of 100 for very small slope parameters. This implies that aggregate shape variations effectively forestall the theorized onset of fall speed distribution narrowing and subsequent quenching of the aggregation process. As a result, it is likely that secondary ice formation is necessary to prevent an ever decreasing slope parameter. The mathematical theory presented in this study is used to develop simple correction factors for snow forecast and climate models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

A Comprehensive Methodology to Evaluate Losses and Process Variations in Silicon Solar Cell Manufacturing

Novel, high-throughput metrology methods are used in this paper for detailed performance loss analysis of approximately 400 industrial crystalline silicon solar cells, all coming from the same production line. The characterization sequence combines traditional global cell measurements (e.g., current-voltage, Suns-VOC) with camera-based cell imaging of voltage distribution and power dissipation from photoluminescence and lock-in thermography, respectively. Spatial variations in current collection are visualized using a high-speed external quantum efficiency and reflectance measurement technique. A nondestructive transfer length method (TLM) measurement technique is also implemented, featuring circular TLM structures hidden within the busbars of the cells. The variance of individual loss parameters and their impact on cell performance are quantified for this large group of cells. Based on correlations performed across parameters, recombination losses in the bulk and rear surface of the cell are shown to be the primary limiting factor for the cell efficiency. The nature of these distributions and correlations provide important insights about loss mechanisms in industrial solar cells, helping to prioritize efforts for optimizing the performance of the production line. Additionally, many of the parameters extracted from these techniques can be tied back to incoming material quality issues (e.g., poor bulk carrier lifetime, nonuniform wafer doping) and to individual unit processes (e.g., texturing, phosphorus diffusion, silicon nitride deposition, metallization), allowing the data to be used directly for process control in manufacturing. All of the datasets are made available for download.

14 SOLAR ENERGY↗