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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

An ℓ 0 ℓ 2 -norm regularized regression model for construction of robust cluster expansions in multicomponent systems

In this work we introduce ℓ 0 ℓ 2 -norm regularization and hierarchy constraints into linear regression for the construction of cluster expansions to describe configurational disorder in materials. The approach is implemented through mixed integer quadratic programming (MIQP). The ℓ 2 -norm regularization is used to suppress intrinsic data noise, while the ℓ 0 -norm is used to penalize the number of nonzero elements in the solution. The hierarchy relation between clusters imposes relevant physics and is naturally included by the MIQP paradigm. As such, sparseness and cluster hierarchy can be well optimized to obtain a robust, converged set of effective cluster interactions with improved physical meaning. We demonstrate the effectiveness of ℓ 0 ℓ 2 -norm regularization in two high-component disordered rocksalt cathode material systems, where we compare the cross-validation, convergence speed, and the reproduction of phase diagrams, voltage profiles, and Li-occupancy energies with those of the conventional ℓ 1 -norm regularized cluster expansion models.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Tandem neural network-based controller for x-ray bimorph mirrors

Nanometer-scale shape control of x-ray mirrors is crucial for coherent x-ray beam experiments at low-emittance synchrotron beamline instruments. Piezoelectric bimorph mirrors offer adaptive control but are hindered by nonlinearities such as cross talk, creep, and hysteresis. To overcome these limitations, we present a novel feedback-free control solution, inspired by the proportional–integral–derivative (PID) scheme, driven by tandem neural networks (TNNs). Using task-specific datasets, the TNN-based system predicts actuator voltages with greater speed, accuracy, and stability than a single NN-based model. This approach is ideal for real-time applications, such as adapting beam focus to dynamic sample sizes while maintaining precise wavefront quality. Our findings highlight the potential of artificial intelligence in rapidly optimizing adaptive optics and managing nonlinear control systems.

Zhang, Runyu↗
DOE OSTI2026

Optimization of Processing, Microstructure, and Hardness of an Al–Ce–Ni–Mn–Zr Alloy With Laser Additive Manufacturing

Here, this study examines the processing behavior, microstructure, surface roughness, and hardness properties of an aluminum alloy containing 8.2 Ce, 4.5 Ni, 0.5 Mn, and 0.7 Zr (wt%) fabricated using laser powder bed fusion. Sixty samples were produced across a range of laser powers, scan speeds, and hatch spacings to evaluate their effect on porosity, hardness, and microstructural features. Porosity was measured using X-ray computed tomography, while microstructure and surface roughness were characterized by scanning electron (SEM) and laser confocal microscopy. High dense and cracking-free Al–Ni–Ce alloy was successfully manufactured. Porosity showed a U-shaped dependence on energy input, increasing under both insufficient and excessive melting conditions. Hardness increased with cooling rate due to finer cellular structures and solute redistribution. A general statistical model was developed to capture the relationships between processing parameters and material response. Results identify a narrow processing window defined by laser powers between 350 and 370 W, scan speeds from 1400 to 1800 mm/s, and hatch distances between 0.14 and 0.18 mm. Within this window, porosity is minimized (below 0.01%) and hardness is maximized (up to 160 HV), demonstrating that careful control of these parameters enables dense, high strength aluminum components suitable for demanding structural applications.

Aluminum alloys↗
DOE OSTI2025

Synchronous Machine Governor Upgrade

Conventional generation sources play a critical role in the stability and reliability of the electrical grid, particularly as we transition towards more renewable energy sources. To understand and accurately emulate their behavior for optimizing grid operations and ensuring seamless integration with renewable technologies, it is essential to better emulate the grid- and plant-level impacts of conventional generation sources, such as natural gas (NG) driven heat recovery steam generators (HRSGs) and combustion turbines (CTs). Therefore, a governor model is developed in a programmable logic controller (PLC) to investigate the performance of the conventional generator under various dynamic operating conditions and to identify the impact on grid stability in a controlled environment. The governor model aims to enable the hardware-in-the-loop (HIL) based emulation of these conventional generation sources using the existing 2 MVA synchronous machine/generator that is driven by a flexible 2.5 MW variable speed drive. This setup will allow us to replicate the dynamic characteristics and response behaviors of NG-driven HRSGs and CTs. The controls for the emulated conventional plants follow the industry standard and are adjustable, ensuring they accurately reflect the operational capabilities and limitations of real-world systems. These controls include load-following capabilities, ramp rates, startup and shutdown sequences, and emissions characteristics. By incorporating these adjustable controls, we aim to capture the nuanced impacts of conventional generation, such as their ability to provide ancillary services like frequency regulation, voltage support, and spinning reserve. In this report, we simulate two types of dynamic operations: grid-connected and islanding. For each dynamic operation, representative starting sequences are tested, including turbine purge, ignition, speed ramping up, generator excitation and synchronizing, and breaker close. The HIL based tests provides insights for field deployment, specifically the high-fidelity governor model provides results to predict the potential stability and reliability risk and suggest possible integration measures (e.g., generation and load balancing, tuning of governor control parameters). Ultimately, this enhanced emulation capability will be integrated into our Advanced Research on Integrated Energy Systems (ARIES), enabling us to conduct comprehensive studies on the interactions between conventional and renewable energy sources. By better understanding these interactions, we can develop strategies to optimize the overall performance and reliability of the grid. This will support the deployment of advanced grid management techniques, such as demand response, grid-forming inverters, and energy storage systems. The main contributions are summarized as follows: (1) This report introduces a PLC-based governor model for gas turbines. This model accurately simulates the dynamic behavior of conventional generation sources under various operational scenarios; (2) The model is integrated with an HIL testbed that includes a 2.5 MW variable speed drive and a 2 MVA synchronous machine. This setup enables realistic, real-time emulation of conventional power plants, particularly NG driven HRSGs and CTs; (3) The developed model is adaptable to various gas turbine configurations and allows for precise control over parameters such as MW ramp rates. This flexibility makes it a valuable tool for future research and industry collaboration; and (4) By incorporating the model into the National Renewable Energy Laboratory's Advanced Research on Integrated Energy Systems, the report lays the groundwork for future studies on interactions between conventional and renewable energy sources, enhancing the ability to develop advanced grid management strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Voltage scanning and technical upgrades at the Collinear Resonance Ionization Spectroscopy experiment

To optimize the performance of the Collinear Resonance Ionization Spectroscopy (CRIS) experiment at CERN-ISOLDE, technical upgrades are continuously introduced, aiming to enhance its sensitivity, precision, stability, and efficiency. Recently, a voltage-scanning setup was developed and commissioned at CRIS, which improved the scanning speed by a factor of three as compared to the current laser-frequency scanning approach. This leads to faster measurements of the hyperfine structure for systems with high yields (more than a few thousand ions per second). Additionally, several beamline sections have been redesigned and manufactured, including a new field-ionization unit, an electrostatic bend with a larger deflection angle, and improved ion optics. The beamline upgrades are expected to yield an improvement of at least a factor of 5 in the signal-to-noise ratio by avoiding the use of high-power lasers (which yield non-resonantly produced ions) and providing time-of-flight separation between the resonant ions and the collisional background.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Techno-economic and life-cycle analysis of strategies for improving operability and biomass quality in catalytic fast pyrolysis of forest residues

Many of the challenges faced by the first commercial biorefineries were associated with feedstock handling, quality, and cost. Strategies are needed to enable further expansion of biorefineries and meet the growing demand for bio-based fuels and products. Here, we examine 2 key feedstock challenges and mitigation strategies in the context of a catalytic fast pyrolysis (CFP) biorefinery: (1) the operability of the feed system, which may be improved by modifying the minimum particle size fed to the reactor, and (2) the quality of the biomass, which may be improved by employing air classification to remove undesirable material and increase fuel yields. We conduct techno-economic analysis (TEA) and life-cycle analysis for these strategies, employing a discrete event simulation model for biomass preprocessing combined with a series of correlations developed from literature data and a rigorous CFP conversion model. Our results highlight the importance of balancing increased cost and material losses from preprocessing against improved operability and fuel yields. Economics and sustainability were optimized when operating at the lowest minimum particle size, emphasizing the importance of minimizing material losses while maintaining the operability of the process. Economically, additional costs and material losses from air classification could be acceptable due to improved biomass conversion, and an optimum air classification speed was identified; however, the fuel GHG emissions were minimized when air classification was not used. Valorizing material removed during preprocessing as a coproduct could improve economics and sustainability, decreasing the burden of material losses.

09 - BIOMASS FUELS↗
DOE OSTI2021

Fingerprinting shock-induced deformations via diffraction

Abstract During the various stages of shock loading, many transient modes of deformation can activate and deactivate to affect the final state of a material. In order to fundamentally understand and optimize a shock response, researchers seek the ability to probe these modes in real-time and measure the microstructural evolutions with nanoscale resolution. Neither post-mortem analysis on recovered samples nor continuum-based methods during shock testing meet both requirements. High-speed diffraction offers a solution, but the interpretation of diffractograms suffers numerous debates and uncertainties. By atomistically simulating the shock, X-ray diffraction, and electron diffraction of three representative BCC and FCC metallic systems, we systematically isolated the characteristic fingerprints of salient deformation modes, such as dislocation slip (stacking faults), deformation twinning, and phase transformation as observed in experimental diffractograms. This study demonstrates how to use simulated diffractograms to connect the contributions from concurrent deformation modes to the evolutions of both 1D line profiles and 2D patterns for diffractograms from single crystals. Harnessing these fingerprints alongside information on local pressures and plasticity contributions facilitate the interpretation of shock experiments with cutting-edge resolution in both space and time.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bridging material models across scales: An integrated approach to equation of state and molecular dynamics modeling of copper

New uncertainty-aware equation of state (EOS) and electrical conductivity (EC) models for copper have been developed. The multiphase EOS/EC models are fit to experimental solid/liquid EC isobar measurements as well as density-functional theory molecular dynamics (DFT-MD) EC calculations in both expanded and compressed regimes (0.1–16 g/ cm 3 ⁠). The liquid and solid EOS phases were fit to available experimental data along with additional DFT-MD data over the same range as the EC. Leveraging the DFT-MD data, a corresponding machine-learned interatomic potential (MLIAP) for copper was trained using genetic-algorithm optimization. The copper MLIAP was constrained by EOS shock points at high compressions. The final EOS bounded MLIAP proves to be stable over a large density range (approximately 0.1–20 g/ cm 3 ) with good agreement to an isothermal compression curve, shock Hugoniot, and liquid speed of sound measurements at high pressures (100s of GPa).

Acoustic measurements and instrumentation↗
DOE OSTI2024

A Phenomenological Thermal Spray Wall Interaction Modeling Framework Applied to a High Temperature Ignition Assistant Device

Airborne compression ignition engines must operate with reliable ignition systems to achieve proper ignition at every cycle, particularly at high altitudes. Glow-plug-based ignition-assistant (IA) devices can provide the necessary energy to preheat the fuel and ensure ignitability of the fuel-air mixture. Ignitability of liquid sprays can be facilitated via direct impingement onto the hot IA surface, however this comes with adverse effects on the IA durability. Therefore, optimizing an IA’s design requires detailed understanding of the physics of fuel spray impingement of superheated surfaces. While spray impingement on relatively low wall temperatures has been extensively studied and appropriate numerical models have been proposed through the years, fundamental understanding of high-speed liquid spray impingement on superheated walls is still elusive. This work aims to formulate a phenomenological thermal spray-wall interaction framework for modeling the film-boiling-induced heat transfer, atomization, and dispersion of fuel spray droplets impinging onto a superheated IA device. A qualitative comparison of the new phenomenological model is performed against optical experiments from the literature of an F-24 fuel spray injected onto an IA device located 12 mm away from the injector tip. The temperature of the IA was set at 1400 K. The fuel injection pressure was 400 bar, while the ambient gas pressure and temperature were 30 bar and 800 K, respectively. The performance of the phenomenological model is evaluated in comparison with two other state-of-art models from the literature. A qualitative analysis of the different spray and fuel-air mixture characteristics is performed to outline the differences in the predictions offered by the new phenomenological model and the two state-of-art spray-wall interaction models.

droplet dispersion↗
DOE OSTI2023

SPUTTERED THIN FILMS FOR VERY HIGH POWER, EFFICIENT, AND LOW-COST COMMERCIAL SOFCS

The aim of this project was to leverage the low area specific resistance (ASR) of Redox’s GDC electrolyte-based cell architecture and increase solid oxide fuel cell (SOFC) efficiency (i.e., open circuit voltage, or OCV) without significantly increasing cell resistance. The key to achieving the increased SOFC efficiency is the introduction of a thin sputtered yttria stabilized zirconia (YSZ) electron-blocking layer and a thin sputtered gadolinia doped ceria (GDC) barrier layer on top of the half-cell substrate (i.e., anode and GDC electrolyte). A key initial effort of the project was to improve the quality of the half-cell substrate surface so that any remaining defects were significantly smaller than the desired film thickness. During lab-scale trials, we had to overcome challenges with film cracking during post-sputtering treatments (e.g., thermal anneals) as well as damage to the sputtering targets. After the initial lab-scale trials, the focus shifted toward the use of commercial scale sputtering equipment with a sputtering equipment manufacturer in the microelectronics industry. Using the commercial sputtering equipment, we deposited films with different variations of power, PO2, sputtering time, platen speed, etc. We then determined the combinations of sputtering conditions and post-sputtering treatments that yielded high-quality films without cracks or other significant defects. While thin films were deposited on cells as large as 10 cm by 10 cm, the processing was optimized using 4 cm by 4 cm cells. Cell performance was evaluated in stainless-steel test fixtures between 500 °C and 700 °C with hydrogen fuel fed to the anode and air fed to the cathode. Extensive studies allowed us to determine that modified cathode and cathode contact firing processes were required to achieve theoretical OCV. Moreover, use of the new firing processes resulted in the need for a modified cathode contact to achieve a low ASR. In summary, the project demonstrated the performance of high OCV (1.13 V at 650 °C) from sputtered layers and a low ASR (~0.25 Ohms-cm2 at 650 °C) resulting from a modification of cathode/contact processing and the introduction of alternative contact layers that are sufficient to yield a Gen-1 cell with a maximum power density of approximately 1.2 W/cm2. At an operating voltage of 0.74 V, this would yield a cell power density of ~1.1 W/cm2. While not utilized in this project, a Redox Gen-2 cell has a catalyst-infiltrated porous anode that reduces the ASR by more than 50% from that of the Gen-1 cells used in this project. Therefore, if the sputtered YSZ electron-blocking layer and GDC barrier layer are added to a Gen-2 half cell with a similar increase in OCV to the theoretical value of ~1.13 V at 650 °C, and if the same improvement in ASR (from that demonstrated in this project) is achieved when using the Gen-2 half-cell architecture as a sputtered cell substrate, then the power density at 0.74 Vop could be as high as ~2.6 W/cm2. The impact of such power density gains, while still maintaining high cell efficiency, and thus high system efficiency, is a dramatic decrease in system cost because the stack represents ~30-40% of the SOFC system cost.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Development of A Multi-Spectral Pyrometry Sensor for High-Speed Transient Surface-Temperature Measurements in Combustion-Relevant Harsh Environments

Accurate and high-speed transient surface-temperature measurements of combustion devices including internal combustion (IC) engines, gas turbines, etc., provide validation targets and boundary conditions for computational fluid dynamics models, and are broadly relevant to technology advancements such as performance improvement and emissions reduction. Development and demonstration of a multi-infrared-channel pyrometry-based optical instrument for high-speed surface-temperature measurement is described. The measurement principle is based on multi-spectral radiation thermometry (MRT) and uses surface thermal radiation at four discrete spectral regions and a corresponding emissivity model to obtain surface temperature via non-linear least squares (NLLS) optimization. Rules of thumb for specifying the spectral regions and considerations to avoid interference with common combustion products are developed; the impact of these along with linear and non-linear MRT analysis are assessed as a function of temperature and signal-to-noise ratio. A multi-start method to determine the MRT-solution global optimum is described and demonstrated. The resulting multi-channel transient pyrometry instrument is described along with practical considerations including optical-alignment drift, matching intra-channel transient response, and solution-confidence indicators. The instrument demonstrated excellent >97% accuracy and >99% 2-sigma precision over the 400–800 °C range, with ~20 µs (50 kHz, equivalent to 0.2 cad at 2000 RPM IC-engine operation) transient response in the bench validation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

The Regenerative Current Mirror: A Very Low Power Front-End Amplifier for Silicon Pixel Detectors

In pixelized detectors, reducing power consumption in the front end ASIC chips becomes a crucial demand. Optimization based on mature pre-amplifier schemes today is unlikely to bring sufficient improvements. A new CMOS front-end gain stage topology with very low power consumption called regenerative current mirror is developed to fulfill the demand. The circuit takes advantage of high speed performance of current amplification while operating with relatively low bias current. The regenerative current mirror uses a NMOS current mirror and a PMOS current mirror, both with nominal gain of 1, to form a loop-back topology that provides a positive feedback. An NMOS FET with an external adjustable voltage applied to it gate terminal is used to limit open loop gain of the current mirrors to be slightly lower than 1. This yields a net gain of the positive feedback loop to be much larger than 1 while operating the current mirrors under relatively low bias currents. Simulation shows that in 65 nm fabrication process, the power consumption of the gain stages suitable for silicon pixel detectors can be controlled < 10 micro-Watts per channel.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Proceedings from the State of the Science and Technology for Minimizing Impacts to Bats from Wind Energy

The U.S. Department of Energy Wind Energy Technologies Office (DOE WETO), and the National Renewable Energy Laboratory convened a workshop entitled the State of the Science and Technology for Minimizing Impacts to Bats from Wind Energy on 13–14 November 2019. The objectives of the workshop were to (1) Identify the current impact minimization measures that are, or can be, used to reduce bat fatalities at wind energy facilities, (2) Assess the current effectiveness of those minimization measures, (3) Identify and assess the research and development (R&D) opportunities needed to optimize and improve the effectiveness of current minimization and deterrent technologies and inform the development of future solutions; and (4) Identify potential emerging or novel methods for informing impact minimization measures at or around wind energy facilities. Specifically, the workshop focused on deterrent and curtailment strategies. For deterrents, the discussion centered on the existing technology (i.e., ultrasonic deterrents, dim-UV light, and texture coating), integration with wind turbines (either retrofitting or out of the box installation), effectiveness, validation studies, and cost (e.g., technology, installation, validation, and maintenance). For curtailment, the conversation was divided into blanket curtailment (i.e., based on time and wind speed) and smart curtailment (i.e., blanket curtailment plus additional variables such as temperature or bat activity). The workshop included plenary presentations, panels, and breakout sessions to share data and stakeholder perspectives, and engage participants. Although there are several priority topics related to bat and wind energy, this workshop focused the discussion on the current technologies and strategies that are, or can be, used to reduce bat fatalities at wind energy facilities, status of research and development (R&D) of minimization measures, opportunities to optimize costs and improve effectiveness, and potential emerging or novel approaches to explore. This workshop took a holistic approach and discussed all aspects associated with advancing deterrent technologies and curtailment strategies, including the technological, biological, economic, and regulatory barriers faced by the wind energy and wildlife community.

13 HYDRO ENERGY↗
DOE OSTI2020

Using Machine Learning Tools to Predict Compressor Stall

Clean energy has become an increasingly important consideration in today’s power systems. As the push for clean energy continues, many coal-fired power plants are being decommissioned in favor of renewable power sources such as wind and solar. However, the intermittent nature of renewables means that dynamic load following traditional power systems is crucial to grid stability. With high flexibility and fast response at a wide range of operating conditions, gas turbine systems are poised to become the main load following component in the power grid. Yet, rapid changes in load can lead to fluid flow instabilities in gas turbine power systems. These instabilities often lead to compressor surge and stall, which are some of the most critical problems facing the safe and efficient operation of compressors in turbomachinery today. Although the topic of compressor surge and stall has been extensively researched, no methods for early prediction have been proven effective. This study explores the utilization of machine learning tools to predict compressor stall. The long short-term memory (LSTM) model, a form of recurrent neural network (RNN), was trained using real compressor stall datasets from a 100 kW recuperated gas turbine power system designed for hybrid configuration. Two variations of the LSTM model, classification and regression, were tested to determine optimal performance. The regression scheme was determined to be the most accurate approach, and a tool for predicting compressor stall was developed using this configuration. Overall, results show that the tool is capable of predicting stalls 5–20 ms before they occur. With a high-speed controller capable of 5 ms time-steps, mitigating action could be taken to prevent compressor stall before it occurs.

42 ENGINEERING↗
DOE OSTI2021

Ducted Fuel Injection and Cooled Spray Technologies for Particulate Control in Heavy-Duty Diesel Engines

Heavy-Duty diesel engine manufacturers are continuously in pursuit of simple and low-cost technologies that can reduce emissions. Ducted fuel injection (DFI) and Cooled Spray (CS) technologies are two technologies that continue to show promise for significant particulate emissions reductions. These technologies represent a breakthrough in diesel engine combustion from the potential of nearly sootless diesel combustion. This can provide a significant decrease in harmful PM emissions and may enable further system optimization for reduced NOx emissions and increased efficiency. Combustion vessel experiments and engine demonstrations at Sandia, together with the large bore engine tests performed by Wabtec show that this technology may be applicable to heavy duty diesel engines across a wide range of engine sizes and speeds representing the majority of off-road diesel engines. However, very little is known about the ideal geometry, scaling properties or effectiveness of these technologies over the engine operating map. This project will address those uncertainties through a series of experiments performed in an optical and a metal single-cylinder engine.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Fuel Effects on Multimode Engine Operation (Sandia National Laboratories) (DOE VTO Annual Progress Report for FY21)

In total, light-duty vehicles in the United States travel on the order of 3 trillion miles annually, providing tremendous societal and personal benefits. However, the environmental burden is excessive, prompting Co-Optimization of Fuel and Engines (Co-Optima) program efforts to provide the science needed to increase engine efficiency and produce non-fossil fuels with reduced greenhouse gas emissions. Boosted spark-ignition (SI) engines provide high power density by offering high loads and engine speeds, making them light-weight and attractive for light-duty vehicles. Unfortunately, the engine efficiency drops off at lower loads and speeds, where the engine spends most time during typical driving. Multimode SI engines can use a more efficient advanced lean combustion mode at lower loads and speeds, while reverting to boosted SI under high-load conditions. Within Co-Optima, multiple advanced lean combustion modes have been explored; these include stratified-charge SI, pre-chamber lean SI, and advanced compression ignition (ACI) techniques such as spark-assisted compression ignition (SACI). For these combustion modes, focus has been on determining fuel properties that enable higher engine efficiency, clean and stable combustion, and effective exhaust aftertreatment. This report highlights recent efforts funded by the Vehicle Technologies Office at multiple National Laboratories that supported the multimode project in Co-Optima. It also includes a brief summary of biofuel production research funded by the Bioenergy Technologies Office.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

The Regenerative Current Mirror: A Very Low Power Front-End Amplifier for Silicon Pixel Detectors

In pixelized detectors, reducing power consumption in the front- end ASIC chips becomes a crucial demand. Optimization based on mature pre-amplifier schemes today is unlikely to bring sufficient improvements. A new CMOS front-end gain stage topology with very low power consumption called regenerative current mirror is developed to fulfill the demand. The circuit takes advantage of high-speed performance of current amplification while operating with relatively low bias current. The regenerative current mirror uses a NMOS current mirror and a PMOS current mirror, both with nominal gain of 1, to form a loop-back topology that provides a positive feedback. An NMOS FET with an external adjustable voltage applied to it gate terminal is used to limit open loop gain of the current mirrors to be slightly lower than 1. This yields a net gain of the positive feedback loop to be much larger than 1 while operating the current mirrors under relatively low bias currents. Simulation shows that in 65 nm fabrication process, the power consumption of the gain stages suitable for silicon pixel detectors can be controlled < 10 micro-Watts per channel. Another novel low-power circuit called Pseudo-Thyristor presented in another document will replace traditional discriminator and the Regenerative Current Mirror plus Pseudo- Thyristor will provide a full solution for the silicon pixel low-power frontend ASIC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Characterization of Build Parameters and Microstructure in Low Heat Input WAAM of Ni-Based Superalloy Haynes 282

Ni-based superalloy Haynes® 282® is being targeted for various applications in advanced power generation systems for its superior fabricability, weldability, and excellent high temperature creep and corrosion performance. This process optimization study aims to use a low heat-input, high deposition rate, controlled Gas Metal Arc Welding (GMAW) process, Cold Metal Transfer (CMT) by Fronius, attempting to achieve fully dense fabrication and possibly avoid the need for HIP. Twenty-one multilayer blocks (~25x100x40 mm3) were deposited to explore a large set of build parameters variations that focused on varying the travel speed from 14 to 42 inches per minute (ipm) and wire feed speed from 150 to 450 ipm. A strong correlation has been observed between arc energy – controlled primarily by travel and wire feed speed. Initial visual inspection, internal microstructural examination, and computed tomography (CT) have been used to determine the effects of built parameters on evolution of internal porosity and defects. Scanning electron microscopy techniques enabled structural and compositional imaging of heterogeneity and changes in microstructural properties.

additive manufacturing↗