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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Friction surface layer deposition of triple-phase Al 10 Cr 12 Fe 35 Mn 23 Ni 20 high entropy alloy: Process optimization and microstructural evolution

A high-strength Co-free triple-phase Al 10 Cr 12 Fe 35 Mn 23 Ni 20 high-entropy alloy (HEA) was successfully fabricated using Friction Surface Layer Deposition (FSLD), a bulk manufacturing method. Multiple single-layer deposits were produced by varying forging force (F) and traverse speeds (T r ) to optimize the process parameters. The optimized conditions (F = 40 kN & T r = 200 mm/min) were then applied to manufacture a scaled-up multi-layer specimen. The initial microstructure of the HEA consisted of coarse grains of the soft FCC-phase, long columnar dendrites of the hard BCC-phase, and small precipitates of the harder B2-phase within the BCC-dendrites. During FSLD, the FCC-matrix underwent continuous dynamic recrystallization due to high-temperature severe plastic deformation, forming finer equiaxed grains. Simultaneously, the BCC-dendrites fractured into smaller fragments, some of which experienced partial growth and coarsening under applied stress, resulting in an hourglass morphology. In contrast, the small B2-precipitates within the BCC-fragments dissolved during the elevated temperatures of FSLD and reprecipitated as substantially finer precipitates during continuous cooling post-FSLD. Additionally, the orientation relationships between the FCC and BCC/B2 phases were completely destroyed by the severe thermoplastic deformation inherent to FSLD. The microstructural refinements led to a substantial improvement in hardness from 177 HV to 283 HV, driven by Hall-Petch strengthening. The increased number of interfaces, including coherent BCC-B2 interfaces, potentially enhances the sink strength and radiation tolerance of the HEA, making it a promising candidate for nuclear applications. In conclusion, this study also highlights FSLD as a versatile technique for achieving tunable properties in HEAs, with detailed schematics illustrating the complex mechanisms of phase transformations during processing.

Additive Manufacturing↗
DOE OSTI2025

Forecasting constraints on the high-z IGM thermal state from the Lyman-α forest flux autocorrelation function

ABSTRACT The autocorrelation function of the Lyman-$\alpha$ (Ly $\alpha$) forest flux from high-z quasars probes the small-scale structure of the intergalactic medium (IGM). The thermal state of the IGM, determined by the physics of reionization, sets the small-scale power observed in the Ly $\alpha$ forest. To explore the sensitivity of the autocorrelation function to the IGM’s thermal state, we compute the autocorrelation function from a cosmological hydrodynamical simulation with an instantaneous reionization model and 135 post-processed thermal states. Using mock data sets of 20 quasars, we forecast constraints on $T_0$ and $\gamma$, which characterize the post-processed IGM thermal state, at $5.4 \le z \le 6$. While this model simplifies the IGM’s thermal state, it serves as a key first step in assessing future observational prospects. We also perform an inference test on mocks and re-weight out posterior distributions to guarantee that they exhibit statistically correct behaviour. At $z = 5.4$, we find that an idealized data set constrains $T_0$ to 59 per cent and $\gamma$ to 16 per cent at the 1$\sigma$ equivalent confidence level. To explore more realistic, non-instantaneous reionization scenarios, we analyse four models combining temperature and ultraviolet background (UVB) fluctuations at $z = 5.8$. We find that mock data generated from a model with both temperature and UVB fluctuations can rule out a model with only temperature fluctuations at the $> 1\sigma$ level 73.9 per cent of the time.

Wolfson, Molly↗
DOE OSTI2024

Investigation of Cyrene organosolv fractionation of softwood biomass and alkaline post-incubation

Cyrene organosolv fractionation effectively extracted 78% of lignin from recalcitrant softwood biomass pine at a mild temperature of 120°C. However, the enzymatic conversion of the fractionated cellulose-rich solid did not improve significantly. Alkali post-incubation of the fractionated cellulose fraction notably enhanced the glucan conversion. This phenomenon has also been observed in other organosolv processes, but how this approach transforms pretreated biomass has not yet been comprehensively investigated. In this study, small-angle X-ray scattering (SAXS) was employed to understand the structural changes in biomass during fractionation and post-incubation at the nanometer scale. Further, no lignin aggregation was found on the microfibrils, whereas the distance between the microfibrils increased after pretreatment and decreased after alkaline post-incubation. These results suggests that the Cyrene molecules remained between the microfibrils and were removed by post-incubation. In addition, the pine lignin recovered after pretreatment was characterized by NMR to understand the impact of Cyrene pretreatment on the lignin structure.

09 BIOMASS FUELS↗
DOE OSTI2025

The CHIMERAS project: design framework for the Collisionless HIgh-beta Magnetized Experiment Researching Astrophysical Systems

From the near-Earth solar wind to the intracluster medium of galaxy clusters, collisionless, high-beta, magnetized plasmas pervade our universe. Energy and momentum transport from large-scale fields and flows to small-scale motions of plasma particles is ubiquitous in these systems, but a full picture of the underlying physical mechanisms remains elusive. The transfer is often mediated by a turbulent cascade of Alfvénic fluctuations as well as a variety of kinetic instabilities; these processes tend to be multi-scale and/or multi-dimensional, which makes them difficult to study using spacecraft missions and numerical simulations alone. Meanwhile, existing laboratory devices struggle to produce the collisionless, high ion beta (β i ≳ 1), magnetized plasmas across the range of scales necessary to address these problems. As envisioned in recent community planning documents, it is therefore important to build a next generation laboratory facility to create a β i ≳ 1, collisionless, magnetized plasma in the laboratory for the first time. A working group has been formed and is actively defining the necessary technical requirements to move the facility towards a construction-ready state. Recent progress includes the development of target parameters and diagnostic requirements as well as the identification of a need for source-target device geometry. As the working group is already leading to new synergies across the community, we anticipate a broad community of users funded by a variety of federal agencies (including National Aeronautics and Space Administration, Department of Energy and National Science Foundation) to make copious use of the future facility.

astrophysical plasmas↗
DOE OSTI2024

Viscosity Measurements at High Pressures: A Critical Appraisal of Corrections to Stokes' Law

Abstract Fluids and melts in planetary interiors significantly influence geodynamic processes from volcanism to global‐scale differentiation. The roles of these geofluids depend on their viscosities ( η ). Constraining geofluid η at relevant pressures and temperatures relies on laboratory‐based measurements and is most widely done using Stokes' Law viscometry with falling spheres. Yet small sample chambers required by high‐pressure experiments introduce significant drag on the spheres. Several correction schemes are available for Stokes' Law but there is no consensus on the best scheme(s) for high‐pressure experiments. We completed high‐pressure experiments to test the effects of (a) the relative size of the sphere diameter to the chamber diameter and (b) the top and bottom of the chamber, that is, the ends, on the sphere velocities. We examined the influence of current correction schemes on the estimated viscosity using Monte Carlo simulations. We also compared previous viscometry work on various geofluids in different experimental setups/geometries. We find the common schemes for Stokes' Law produce statistically distinct values of η . When inertia of the sphere is negligible, the most appropriate scheme may be the Faxén correction for the chamber walls. Correction for drag due to the chamber ends depends on the precision in the sinking distance and may be ineffective with decreasing sphere size. Combining the wall and end corrections may overcorrect η . We also suggest the uncertainty in η is best captured by the correction rather than propagated errors from experimental parameters. We develop an overlying view of Stokes' Law viscometry at high pressures.

Geochemistry & Geophysics↗
DOE OSTI2025

Small Scale Melter Testing of HLW Algorithm Glasses: Matrix 1 Tests

The principal objectives of the DM100 tests were to determine the effects of glass property extremes (glass viscosity, electrical conductivity, and T1%), minimum and maximum concentrations of several major and minor glass components, +/-15% batching errors in the addition of Glass Forming Chemicals (GFCs) to the feed, and variation in the sources of boron and sodium used in the GFCs on processing rates and melter conditions (off-gas characteristics, glass processing, foaming, cold cap, etc.) at constant bubbling rate.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

SynthEsizing Novel H2 Sensors for Operational Resilience in Pipeline Infrastructure (SENSOR) (CRADA Final Report)

Hydrogen (H₂) is gaining attention as a versatile energy carrier with potential applications across industrial processes, power generation, and transportation. However, its practical deployment, particularly in large-scale distribution systems, faces significant infrastructure challenges. Transporting hydrogen through dedicated pipelines or blending it into existing natural gas networks can lead to serious issues, such as leakage due to the small size of hydrogen molecules and material degradation in pipelines through embrittlement. These technical risks raise safety concerns and could limit the integration of hydrogen into current energy infrastructures. Additionally, using hydrogen-enriched gas mixtures in combustion systems like turbines and engines introduces new performance and compatibility challenges that must be resolved before widespread use becomes feasible.

08 HYDROGEN↗
DOE OSTI2025

Aerosol-Cloud Interactions and the Intersection of Climate Forcing and Feedback

The goal of this project has been to understand at the process level how the interaction of aerosols and cloud microphysics may alter the cloud response to climate change from the scale of turbulence to the global scale. Atmospheric aerosols (suspended particulates) have a unique role to play in the climate system. Anthropogenic aerosols may be an air pollution hazard and degrade human health. Their presence also results in the direct scattering or absorption of sunlight, with small net impacts on climate. But aerosols are also a key part of cloud formation, as the locations on which cloud droplets and ice crystals form. Understanding these Aerosol Cloud Interactions (ACI) is a critical uncertainty for climate models, including the Energy Exascale Earth System Model (E3SM), and affects how well models like E3SM can simulate the past and future. This work aims to understand cloud microphysics as well as the interaction of aerosol forcing and cloud feedback through improving our understanding of aerosol-cloud interactions (ACI) by looking at their uncertainty in critical environments at the process level. It will also contribute to the development of E3SM. Specific goals include: first, high level analysis of Perturbed Parameter Ensemble (PPE) simulations already available from the Community Earth System Model (CESM) and E3SM. Second, detailed analysis of recent changes to temperature and the role of aerosols.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Knowledge gaps for neuromorphic ionic computing

BACKGROUND Neuromorphic computing, inspired by the human brain’s ability to process information efficiently, represents a transformative approach to computation. In this Review, we explore the emerging field of neuromorphic ionic computing, which leverages ionic conduction and coupling to mimic neural processes, and identify critical knowledge gaps that must be addressed to realize its full potential. A central theme of the discussion is energy efficiency, a challenge that is both a limitation and an opportunity for this technology. Although complementary metal-oxide semiconductor (CMOS)–based neuromorphic technologies have made strides in scaling to billions of neurons and are increasingly applied in artificial intelligence and numerical computing, they remain orders of magnitude behind the human brain in terms of connectivity and energy efficiency. Neuromorphic ionic computing promises to overcome these limitations by leveraging the distinct architectural and operational principles of the brain. Our brains achieve this energy efficiency by combining several key features: using the same network elements to store and process information; using an incredibly complex and massively interconnected three-dimensional (3D) network of locally active elements that enables sparsity, robustness in the presence of noise, adaptation, and life-long learning; computing at comparatively low voltage and frequency; and last, taking advantage of a plethora of ions and small molecules as information carriers. Here, we propose that ionic computing systems can take advantage of similar features to achieve substantial gains in energy efficiency. ADVANCES Since the first reports of neuromorphic ionic behavior in nanofluidic channels, we have witnessed an explosion of reports that used ionic devices to produce synaptomimetic behaviors. However, achieving the goals of ionic computing requires not only implementation of much more sophisticated device functionality but also overcoming fundamental barriers in materials science, device architecture, and system integration. Current ionic devices, even those incorporating state-of-the-art materials, still suffer from limited functionality and stability, which restrict their performance and increase energy demands. Developing new materials with enhanced ionic properties is essential to overcome these limitations. Similarly, the design of neuromorphic devices must evolve to leverage the particular advantages of ionic processes. Existing architectures often follow a single-information-carrier logic of conventional electronics or are constructed of mesoscale fluidics, failing to capitalize on the energy-efficient mechanisms inherent to ionic systems or implement the multiple-information-carrier paradigm. Current neuromorphic chips focus on large-scale networks of analog memory elements based on mechanisms such as charge trap (flash), filamentary, phase change, or spin, which are built on top of a network of artificial CMOS neurons. Although such prototype networks have achieved impressive performance, it is difficult to envision how they can implement the key features such as massive connectivity, sophisticated plasticity, adaptability, sparsity, and “multichromatic” computing. Although small-scale devices have demonstrated promising results, integrating them, maintaining energy efficiency, and implementing temperature control as systems grow in complexity and size to computationally relevant scale remain major hurdles. Furthermore, interfacing neuromorphic ionic devices with existing computing technologies presents technical and conceptual challenges that will require innovative approaches that combine insights from neuroscience, materials science, and engineering. OUTLOOK Despite these challenges, the potential impact of neuromorphic ionic computing is profound with potential applications ranging from artificial intelligence to robotics and beyond. We also argue that neuromorphic ionic computing systems should not, at least in the beginning, compete with CMOS technologies but rather should focus on applications that require extreme energy efficiency with chemical and/or biological compatibility, such as biomedical applications (for example, brain-computer interfaces), environmental monitoring, and agricultural and food applications. Ultimately, this Review highlights the crucial role of interdisciplinary collaboration in advancing the field. Neuromorphic ionic computing is not merely a technological innovation; it represents a substantial step toward sustainable computation, aligning with the growing demand for energy-conscious solutions in a world that is increasingly reliant on data and computation.

Neuromorphic↗
DOE OSTI2026

Activating magnetite ores for aqueous ironmaking at high current densities

Low-temperature electrochemical cells reducing iron oxides to metal in alkaline electrolytes can support fully electrified steelmaking processes. Previous studies on these cells have primarily focused on high-surface-area hematite, Fe 2 O 3 , reactants whereas attempts to reduce suspensions of magnetite, Fe 3 O 4 —one of the two feedstocks for existing ironmaking reactors—have generally been limited to low rates of reaction (<30 mA cm −2 ). Here, in this study, we control the crystalline domain size of Fe 2 O 3 and Fe 3 O 4 particles in 10 M NaOH electrolytes to study how the nanoscale morphology of oxides controls the rate of electrochemical ironmaking. Rotating-ring disk electrode measurements of Fe 2+ , in situ Raman spectroscopy of the electrode surface, and ex situ electron microscopy were consistent with a hypothesized passivation process at Fe 3 O 4 surfaces that may prevent the continuous formation of soluble intermediates. Sufficiently small (<100 nm diameter) oxide particles yielded Fe partial current densities >160 mA cm −2 , a fivefold increase relative to previously reported rates for Fe 3 O 4 suspensions and comparable to active Fe 2 O 3 . Electron microscopy revealed that electrodeposited films were composed of micron-scale crystalline Fe domains with a porous film of Fe 3 O 4 nanoparticles and supports a model where Fe is grown primarily from soluble Fe 2+ intermediates. Based on these insights, inactive blast-furnace-grade iron-oxides were transformed into high surface area nanoparticles (1.6 to 229.2 m 2 g −1 ) via reprecipitation, leading to a ninefold enhancement in faradaic efficiency and an Fe partial current density of 120 mA cm −2 . When integrated with chlor-iron cells producing reagents for reprecipitation, this approach could lead to a cost-competitive process for electrochemical ironmaking from industrially relevant feedstocks.

TEM↗
DOE OSTI2024

Non-Invasive Biophysical Techniques to Monitor the Structural Plasticity of the Photosynthetic Machinery of Live Diatom Cells

The photosynthetic performance of diatoms depends largely on the organization and structural flexibility of their thylakoid membranes, the densely packed, highly organized membrane vesicles in which light reactions of photosynthesis occur. Different regulatory mechanisms that fine tune the photosynthetic functions affect the organization of the photosynthetic machinery at different levels of structural complexity, from the level of individual protein complexes to the macroarray of membrane proteins and the remodeling of the entire thylakoid membrane system. To monitor these reorganizations, non-invasive techniques are of special value. In this chapter, we focus our attention on three of these techniques, which have been demonstrated to provide unique and useful information on the structure and structural and functional plasticity of live diatom cells: (i) circular dichroism (CD) spectroscopy, which has provided unique information on the chiral (macro-)organization of protein complexes and on their rapid, reversible reorganizations, fine-tuning the light-harvesting processes, as well as on variations in the short-range excitonic interactions in the antenna complexes; (ii) small-angle neutron scattering (SANS), which has been used to determine the periodic organization of the thylakoid membranes and to monitor reversible ultrastructural changes on the time-scale of minutes, induced by variations in the environmental conditions such as changes in temperature or light intensity; and (iii) electrochromic shift absorbance transients (ΔA ECS ), a spectroscopic tool which has been shown to be capable of identifying distinct functional groups of the light-harvesting carotenoid fucoxanthin in different diatoms and in cells exposed to different light intensities. Future use of these techniques will most certainly contribute to the deeper understanding of key regulatory mechanisms of photosynthesis in diatoms.

Szabo, Milan↗
DOE OSTI2026

Exploring the partonic collectivity in small systems at energies available at the CERN Large Hadron Collider

Using the Hydro-Coal-Frag model that combines hydrodynamics at low p T , quark coalescence at intermediate p T , and the LBT transport model at high p T , we study the spectra and elliptic flow of identified hadrons in high multiplicity p–Pb and p–p collisions at the CERN Large Hadron Collider (LHC). In p–Pb collisions, the Hydro-Coal-Frag model gives a good description of the differential elliptic flow over the p T range from 0 to 6 GeV and the approximate number of constituent quark (NCQ) scaling at intermediate p T . Although the Hydro-Coal-Frag model can also roughly describe the elliptic flow in high multiplicity p–p collisions with the quark coalescence process, the larger contribution from the string fragmentations leads to a notable violation of the NCQ scaling of v 2 at intermediate p T as observed in the experiment. Comparison runs of the Hydro-Frag model without the coalescence process demonstrate that regardless the parameter adjustments, the Hydro-Frag model cannot simultaneously describe the p T spectra and the elliptic flow of identified hadrons in either p–Pb collisions or p–p collisions. In conclusion, the calculations in this paper thus provide support for the existence of partonic degrees of freedom and the possible formation of the QGP in the small systems created at the LHC.

Wang, Yuanyuan [Peking University, Beijing (China)↗
DOE OSTI2025

A Multi-Sensor Approach for Measuring Bird and Bat Collisions with Offshore Wind Turbines (Final Technical Report)

Collision of birds and bats with wind turbines is a conservation concern for both land-based and offshore wind projects. The fatality rates of birds and bats at land-based turbines are well documented. The measurement strategies on land focus on finding carcasses following collision, estimating the number of carcasses missed through searcher efficiency, carcass persistence trials and carcass fall distributions, and modeling statistically robust fatality rates. Few technologies have been developed to monitor offshore bird and bat collisions, and many that have been developed focused on detecting collisions with large birds. The few studies that have attempted to document collisions at offshore turbines do not account for smaller bodied animals or for collisions that might be missed, which prevents the calculation of statistically robust fatality rates. The overall goal of this report, A Multi-Sensor Approach for Measuring Bird and Bat Collisions with Offshore Wind Turbines (Project), was to develop an effective multi-sensor system for quantifying bird and bat collision rates, specifically for offshore wind facilities. The Project goal and resulting automated collision detection system was achieved through two major technological advancements: 1) refining The Netherlands Organisation for Applied Scientific Research’s (TNO’s) existing WT-Bird® vibration sensing system, that had successfully detected large bird collisions during daytime, to allow for improved detection of smaller birds and bats during both daytime and nighttime hours and 2) improving image processing systems and developing and integrating machine learning algorithms to automatically detect and classify small and large bird and bat collisions with offshore turbines. This final technical report (FTR) summarizes Methods , Results , Conclusions , and Lessons Learned during each of the five Tasks identified for this research and development effort. This FTR includes summaries of the following: Task 1. Initial Engineering Tests to Improve WT-Bird® Task 2. Installation of WT‐Bird® on a Utility-scale Turbine at the National Wind Technology Center – National Renewable Energy Laboratory Task 3. Field Tests and Refinement of the Object Detection System Task 4. Validation of WT-Bird® on a Land-based Turbine Task 5. Preparation for the Implementation of WT-Bird® on an Offshore Turbine. This research and development effort documented successful improvement of the WT Bird® collision detection system to detect small birds and bats, and WT-Bird® is the first collision detection system to validate results compared to land-based post-construction monitoring. The collision trials provide estimates of missed targets that can be used to estimate fatality rates, a significant improvement relative to other offshore collision monitoring systems. Advances were made in developing an edge-processing solution to reduce data storage requirements, which is important if the system is deployed for long periods of time at offshore turbines. The improved WT-Bird® system also provides an important option for wind operators on land or offshore who need to document specific details about when collisions occur, particularly efforts to further research on bat impact minimization, or when standard fatality searches are impractical (e.g. offshore) or inadequate (e.g. challenging locations on land).

17 WIND ENERGY↗
DOE OSTI2024

Dissolution zone model of the oxide structure in additively manufactured dispersion-strengthened alloys

The structural evolution of oxides in dispersion-strengthened superalloys during laser-powder bed fusion is considered in detail. Alloy chemistry and process parameter effects on oxide structure are assessed through a parameter study on the model alloy Ni-20Cr, doped with varying concentrations of Y 2 O 3 and Al. Small angle neutron scattering measurements of the dispersoid size distribution show the dispersoid size increases with higher laser power, slower scan speed, and increasing Y 2 O 3 and Al content. Complementary electron microscopy measurements reveal reactions between Y 2 O 3 and Al, even in nanoscale dispersoids, and the presence of micron-scale oxide slag inclusions in select specimens. A scaling analysis of mass and momentum transport within the melt pool, presented here, establishes that diffusional structural evolution mechanisms dominate for nanoscale dispersoids, while fluid forces and advection become significant for larger slag inclusions. These findings are developed into a theory of dispersoid structural evolution, integrating quantitative models of diffusional processes – dispersoid dissolution, nucleation, growth, coarsening – with a reduced order model of time-temperature trajectories of fluid parcels within the melt pool. Calculations of the dispersoid size in single-pass melting reveal a zone in the center of the melt track in which the oxide feedstock fully dissolves. Within this zone the final Y 2 O 3 size is independent of feedstock size and determined by nucleation and growth kinetics. If the dissolution zones of adjacent melt tracks overlap sufficiently with each other to dissolve large oxides, formed during printing or present in the powder feedstock, then the dispersoid structure throughout the build volume is homogeneous and matches that from a single pass within the dissolution zone. Gaps between adjacent dissolution zones result in oxide accumulation into larger slag inclusions. Predictions of final dispersoid size and slag formation using this dissolution zone model match the present experimental data and explain process-structure linkages speculated in the open literature.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Mapping Dark Matter on Small Scales with the Cosmic Microwave Background (Final Report)

Sehgal was funded by DOE Grant DE-SC0020441 over the period from 11/1/2019 - 04/30/2024 (no remaining funds are anticipated). Most recently, Sehgal and her group completed a publication forecasting cosmological parameter constraints for a CMB-HD survey, in addition to SO and CMB-S4 (1). One focus of this work was determining the improvement in parameter constraints when removing the gravitational lensing effect from the primordial CMB (a process called delensing). This work also explored the bias to parameters from neglecting baryonic effects, and ways to mitigate that. In addition, this work highlighted that a CMB-HD N eff measurement could tightly constrain the QCD axion in a modelindependent way (see left panel of Figure 1). Sehgal also developed a novel way to probe inflation via CMB experiments by measuring inflationary magnetic fields (IMFs) (2). IMFs are thought to seed the large magnetic fields we observe in galaxies today, and can be measured by looking for anisotropic rotation of the CMB polarization vectors across the sky (an effect called cosmic birefringence). The cosmic birefringence from IMFs has a unique frequency dependence, allowing it to be separated from other sources of cosmic birefringence. In (2), Sehgal and her postdoc also presented a novel way to remove foreground contamination from Galactic magnetic fields using measurements of the polarization of nearby radio sources. The removal of this Galactic contamination is necessary when measuring IMFs at the level of 0.1 nG; IMFs with a strength of at least 0.1 nG are needed to seed the magnetic fields in galaxies we observe today. Since only inflation can generate such a strong magnetic field, measuring such a signal would be a “smoking gun” signature that inflation occurred. Sehgal showed in (2) that CMB-HD could detect such IMFs with at least 3σ significance (see right panel of Figure 1).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Oxide Dispersion Strengthened Ferritic Steel Wire Feedstock Development for Larger Format Additive Manufacturing (CRADA Final Report)

This CRADA project funded through DOE’s INFUSE program sought to demonstrate the viability of fabricating large, complex parts from oxide dispersion strengthened (ODS) steel with advanced manufacturing. Exhibiting excellent radiation tolerance and high mechanical performance at elevated temperatures, ODS steel is a promising structural material candidate for near-plasma components in fusion energy systems. Its use, however, has been limited by a lack of manufacturability. This project sought to produce ODS steel wire through a solid-state shear assisted extrusion process and then demonstrate that the wire can undergo controlled local melting while being welded with the final part sufficiently retaining the beneficial properties of ODS steel. This would allow the use of wire-arc additive manufacturing (WAAM) to manufacture large-scale ODS parts, even though ODS is currently only available as a powder. WAAM is a promising technique for producing components like the replaceable ARC vacuum vessel in CFS’ fusion reactor design. Meanwhile, this project will also expand PNNL’s capability in producing custom wire feedstock with friction extrusion, enabling downstream large-scale manufacturing with WAAM and solid-state based additive manufacturing. The project achieved its goals of developing tooling and fixturing to produce ODS wire at smaller diameters than previous projects. Several small lengths of wire of 1.5 mm and 2.5 mm diameter in the range of 2.5-30 mm long were produced at tool temperatures that are known to cause ODS particle coarsening (~1200 °C). Fixtures and tooling for longer (>1 m) wires were developed but further process development is needed reduce tool temperature during extrusions and to increase wire length needed for WAAM testing and development.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Feasibility of Correlation-Aware Inference and Universal Precision Scaling in Bonse–Hart Ultra-Small-Angle Neutron Scattering

Bonse–Hart ultra-small-angle neutron scattering (USANS) provides access to micrometre-scale structure, but useful measurements often require long counting times. In this work, we test whether the expected smoothness of the scattering profile can be exploited to improve data quality at lower counting statistics. We apply a Gaussian-process-based method to Bonse–Hart USANS data and evaluate its performance on pseudo-measurements generated from high-statistics experiments under Poisson statistics. This provides a stringent test of how well the underlying I(Q) profile can be reconstructed when the available counts are substantially reduced. We further show that, in the counting-limited regime, the reconstruction error follows a universal scaling behaviour that differs from the usual independent-counting expectation. At higher counts, the improvement crosses over to a resolution-limited regime set by analyser-angle discretization and rocking-curve width. These results clarify when correlation-aware inference is useful in USANS and provide a practical basis for improving measurement efficiency and beam-time usage.

Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)↗
DOE OSTI2024

Recent Advances of PyROS: A Pyomo Solver for Nonconvex Two-Stage Robust Optimization in Process Systems Engineering

This poster highlights uncertainty and technical risk reduction capabilities in CCSI2, with a focus on robust optimization. It presents recent advances of the two-stage robust optimization (RO) solver PyROS and applications to advanced energy systems optimization. To demonstrate the computational performance and reliability of PyROS, a benchmarking study on a library of over 8,500 small-scale RO problems is presented. Further, PyROS is used to obtain robust system designs of a MEA-based CO2 absorber under uncertainty in the thermodynamic property models for a variety of CO2 capture rate threshold requirements. Overall, the results demonstrate that the PyROS solver, including recent extensions to multi-stage RO settings, provides a reliable avenue to optimize the design and operation of advanced energy systems subject to various sources of parametric uncertainty.

Sherman, Jason↗