Dynamic magnetic response of the quark-gluon plasma to electromagnetic fields
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70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
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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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Chiral Instabilities and the Onset of Chiral Turbulence in QED Plasmas
We present a first principles study of chiral plasma instabilities and the onset of chiral turbulence in QED plasmas with strong gauge matter interaction ( e 2 N f = 64 ), far from equilibrium. By performing classical-statistical lattice simulations of the microscopic theory, we show that the generation of strong helical magnetic fields from a helicity imbalance in the fermion sector proceeds via three distinct phases. During the initial linear instability regime the helicity imbalance of the fermion sector causes an exponential growth (damping) of magnetic field modes with right- (left-) handed polarization, for which we extract the characteristic growth (damping) rates. Secondary growth of unstable modes accelerates the helicity transfer from fermions to gauge fields and ultimately leads to the emergence of a self-similar scaling regime characteristic of a decaying turbulence, where magnetic helicity is efficiently transferred to macroscopic length scales. Within this turbulent regime, the evolution of magnetic helicity spectrum can be described by an infrared power spectrum with spectral exponent κ = 10.2 ± 0.5 and dynamical scaling exponents α = 1.14 ± 0.50 and β = 0.37 ± 0.13 .
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
w18_plxa Final Report Viewgraphs [Slides]
For our fusion concept, we want to look at the influence of: 1) Density perturbations of the liner [shell that pushes on the target to get the target to fusion conditions] and 2) Magnetic field and anisotropic conductivity effects. On the compression of the target (final ion temperatures, without nuclear reaction calculations)
97 MATHEMATICS AND COMPUTING↗
Workshop Report: Brightest Light Initiative (March 27-29 2019, OSA Headquarters, Washington, D.C.)
This Brightest Light Initiative (BLI) Workshop Report captures the important research ideas and recommendations for enabling that work developed by over 100 leading scientists at a community-initiated workshop held March 27-29, 2019 in Washington, DC. Workshop attendees developed an understanding of key opportunities, as well as gaps in current technologies and capabilities, for science enabled by the highest-intensity lasers.
43 PARTICLE ACCELERATORS↗
Laser-Based Means for Accelerating Nuclear Decay Rate
This project aims to replicate and build upon a reported series of results whereby nuclear decay of unstable species has been accelerated under laser irradiation in the presence of resonantly excited plasmonic nanoparticles. We are currently utilizing a laser system similar to that used within these reports as well as optimizing nanoparticle solution environments in an attempt to replicate reported results or provide alternative pathways that may explain some perceived discrepancies. The current work is being performed with equipment and techniques currently available at SRNL, including nanoparticle synthesis and pulsed lasers for plasmon excitation. The results of these experiments could provide quantitative data that can be used to resolve the discrepancies in the calculations and better estimate the ultimate utility of the process. If verified, this would represent a pathway for using readily available and scalable technology to reduce the long-term radiological storage requirements of certain forms of nuclear waste.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Final Reports of the 2020 Los Alamos National Laboratory Computational Physics Student Summer Workshop
For the past ten years, the workshop has been bringing a highly talented and diverse group of student every summer. Students work in teams of two, alongside typically two mentors, on research projects reflecting a broad range of topics within computational physics. In addition, students attend a series of lectures on topics within computational physics, facility tours, and networking events. The program lasts ten weeks, with this year’s workshop running from June 8 to August 14. At the end of the summer, students give a final presentation, along with a written report. Those reports are what make up the remaining sections of this document. Admission to the workshop is by a competitive process, with the mentors forming the selection committee. One of the important accomplishments of the workshop has been to create a student pipeline from diverse schools that sometimes are not normally tapped by LANL recruiting. Many workshop students maintain a continuing relationship with LANL, returning as students interns, post-doctoral researchers, and staff members. Additionally, workshop alumni act as ambassadors for LANL. The result is a wider awareness both of LANL as a potential employer, and of the technical work that happens at LANL. This year, the workshop format was changed in several ways, in order to accommodate the off-site, virtual format. Students worked on LANL virtual desktop systems remotely, also accessing LANL HPC resources. In order to facilitate communication, student were given accounts on both Webex, a video teleconferencing platform, and Mattermost, an online team collaboration and chat platform, similar to Slack. Daily communication between students and mentors was primarily on Mattermost, with Webex conferencing as needed. The lectures were all done on Webex. Given the difficulty of the virtual format, and a concern that students might have video teleconferencing burn-out after an academic semester largely moved to that format, all lectures were optional this year. In spite of this, the attendance was generally high. Lecturers were asked to try to move to a more high-level, ”What is it?,” format. Once again, the students did a tremendous job. Over the course of ten weeks, they did important research across a staggering array of disciplines. The following pages contain the final report for each team’s research efforts. We hope you will find reading them as exciting as it was for us to produce them.
36 MATERIALS SCIENCE↗
Report on PTT Imaging of Defects in AM Metallic Materials-Part 2
Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study.
36 MATERIALS SCIENCE↗
Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components (Final Technical Report)
Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study. In another approach, we investigate Thermal Tomography (TT), which is a computational method for reconstruction of depth profile of internal material defects from PIT nondestructive evaluation (NDE). TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of subsurface internals defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. Performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shape imported from scanning electron microscopy (SEM) images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on TT images of elliptical defects is capable of classifying shape and orientation of irregular defects. Training the CNN on irregular defect shapes instead of on elliptical shapes would make the resulting classifications more descriptive of actual defect shapes. However, this requires a much higher volume of SEM images of material defects, which are difficult to obtain because of random occurrence of defects in LPBF. To address this challenge, we developed a generative adversarial network (GAN) to augment the existing dataset of SEM defect images. The GAN model is demonstrated to create novel yet realistic defect shapes that can be used as input for simulated PTT images to train CNN. We also investigate several approaches based on Gaussian Random Circle and Bezier Curves for constructing parametric models of irregular-shape defects.
36 MATERIALS SCIENCE↗
Microstructure-Based Understanding of High-Temperature Deformation Behaviors in Laser Powder Bed Fusion (LPBF) 316H Stainless Steel
This report presents the results of high-temperature mechanical property testing and microstructural analysis of laser powder bed fusion (LPBF) 316H stainless steel (SS) conducted during Fiscal Year 2025 (FY25) under the U.S. Department of Energy, Office of Nuclear Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program. The study builds upon prior work by expanding the mechanical property test matrix and advancing a microstructure-based mechanistic understanding of LPBF 316H SS performance, with a focus on the solution annealed (SA, 1100°C for 1 hour) materials. High-temperature tension, creep, fatigue, and creep-fatigue tests were performed. Thermal aging studies were conducted. Advanced characterization techniques, including scanning electron microscopy (SEM), scanning transmission electron microscopy (STEM), and high-energy synchrotron X-ray diffraction, were employed to investigate the microstructural evolution during thermal aging and mechanical testing. It was discovered that the as-built (AB) LPBF 316H SS exhibited precipitation kinetics during thermal aging that are 10–100 times faster than its wrought counterpart due to the presence of high densities of preferred nucleation sites, while the precipitation kinetics in SA LPBF 316H was under investigation. The accelerated precipitation of embrittling phases such as sigma phase in LPBF 316H SS compared to its wrought counterpart led to significant impacts on creep ductility. The influence of laser printing parameters and build orientations on fatigue and creep-fatigue performance was observed. In assessing the creep-fatigue performance, it was discovered that the SA LPBF 316H samples failed in less than 200 cycles under 595°C, 0.5% (strain amplitude) with a 60-minute hold time. This work establishes a mechanistic framework for predicting the long-term behavior of LPBF 316H SS, supporting its rapid qualification under the ASME BPVC. The findings contribute to the broader goal of enabling the deployment of advanced materials in next-generation nuclear energy systems. An outlook for FY26 work, including continued aging studies, mechanical testing, and microstructural characterization, is provided.
36 MATERIALS SCIENCE↗
XCP 2025 Computational Physics Student Summer Workshop Final Presentation
Explore the source record for details and available documents.
36 MATERIALS SCIENCE↗
THOR: Developing a Next-Generation Platform for Radflow and Opacity Measurements
Explore the source record for details and available documents.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
X-ray emission from high temperature plasmas
The physical processes occurring in plasma focus devices were studied. These devices produce dense high temperature plasmas, which emit X rays of hundreds of KeV energy and one to ten billion neutrons per pulse. The processes in the devices seem related to solar flare phenomena, and would also be of interest for controlled thermonuclear fusion applications. The high intensity, short duration bursts of X rays and neutrons could also possibly be used for pumping nuclear lasers.
Harries, W. L.↗
High-Pulse Energy / High-Repetition Rate Laser
Explore the source record for details and available documents.
43 PARTICLE ACCELERATORS↗
Laser powder bed fusion of ODS Fe–Cr–Al (0.3Zr, 0.3Y 2 O 3 ): Unveiling processing-microstructure- mechanical property relationships
Here, this study investigates the fabrication of oxide dispersion strengthened (ODS) Fe-Cr-Al alloys via laser powder bed fusion (LPBF) with strategic additions of 0.3 wt% Zr and 0.3 wt% Y 2 O 3 for enhanced mechanical performance in nuclear applications. Systematic processing parameter optimization yielded three distinct conditions: one low-density product with significant defects and two near-full-density materials with improved consolidation. Comprehensive characterization confirmed single-phase α-ferrite matrix formation with successful incorporation of Y-, Zr-, O-, and C-rich precipitates characteristic of ODS alloys. However, precipitate density remained low (∼10 7 cm −3 ), resulting in sink strength values substantially below optimal levels for radiation resistance. Microhardness values (mid-200s HV) correlated inversely with grain size following the Hall-Petch relationship, indicating grain boundary strengthening as the dominant mechanism rather than precipitation strengthening. The optimized processing conditions achieved excellent mechanical properties with room temperature yield strength of approximately 500 MPa and 30 % elongation, demonstrating superior strength-ductility synergy compared to other additively manufactured ODS materials and performance consistent with literature values for LPBF-processed ODS-FeCrAl alloys. This investigation reveals both the potential and limitations of LPBF processing for ODS Fe-Cr-Al alloys. While successful defect-free fabrication was achieved, results highlight the critical need for systematic optimization of processing parameters and post-processing heat treatments to enhance precipitate density for effective dispersion strengthening and radiation resistance while maintaining additive manufacturing advantages.
Additive manufacturing↗
Development, validation, and verification of multi-pass thermo-mechanical welding simulations using the open-source MOOSE framework: NeT TG4 benchmark weldment
This study develops and validates a sequentially coupled thermo-mechanical welding simulation for the three-pass 316L stainless steel NeT TG4 benchmark weldment using the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) and the Nuclear Engineering Material model Library (NEML). A diffused ellipsoidal heat source was calibrated against thermocouple data and weld macrographs to accurately model the fusion zone geometry and transient thermal fields. Material hardening is represented using the Lemaitre-Chaboche mixed isotropic-kinematic hardening model, while four annealing models - no annealing, single-stage at 1050 °C and 1300 °C, and two-stage at 800 °C/1300 °C - were implemented to assess the impact of annealing models on the accuracy of the predicted welding-induced plasticity, distortions, and residual stresses. The predictions were validated against experimental measurements and benchmarked against results from commercial software, demonstrating that thermo-mechanical MOOSE welding simulations achieve comparable accuracy with enhanced computational efficiency. This work highlights the potential of using open-source finite element frameworks like MOOSE for advanced manufacturing simulations.
Ji, Wendy [Australian Nuclear Science and Technolo↗
Evaluation of In-Situ AM Process Monitoring Techniques and Potential for Detecting Process Anomalies and Undesirable Microstructures
The US Department of Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing rapid qualification of new materials for fabrication of nuclear relevant components using advanced manufacturing techniques. Particular interest is placed on code-qualifying stainless steel (SS) 316H processed by laser powder bed fusion (LPBF) additive manufacturing. A paradigm that incorporates data from in-situ sensing during the printing, ex-situ characterization, and advanced artificial intelligence–based models was established under the Transformation Challenge Reactor (TCR) program to develop a pedigree for each fabricated component that could be tracked from the feedstock to the component’s release for application. Under the TCR program, the Peregrine software was developed as a tool for incorporating the vast amounts of in-situ and ex-situ characterization data collected; all data stored on a rapidly growing digital platform. The digital platform allows for users to link site-specific process anomalies to the macro- and microstructure. The platform will eventually be able to predict component performance, which will be crucial to qualifying materials and components in risk-averse industries such as those supporting and building nuclear reactors. Current in-situ process monitoring techniques that are already integrated with software like Peregrine are advantageous for identifying process anomalies including powder spatter, component edge swelling, recoating-build interactions, and so on. However, additional data are required to fully predict the resulting microstructures needed for identifying relationships to component performance. The rapid cooling rates observed in LPBF are some of the highest of any bulk manufacturing process, resulting in heterogenous microstructures and typically causing anisotropy in mechanical properties. Moreover, evolved residual thermal stresses are high, which can cause severe defects such as delamination or cracking. Therefore, other in-situ monitoring methods are warranted for exploration to measure and map the thermal history, and potentially the stress state, of each build. This report summarizes different in-situ monitoring strategies proposed for LPBF with a focus on the more developed sensor systems. Novel capabilities for measuring melt pool temperatures are also addressed to better inform modeling efforts.
36 MATERIALS SCIENCE↗
FY24 Integrated Results for High-Temperature Mechanical Testing of LPBF 316H Stainless Steel
This report provides the mechanical test data of laser powder bed fusion (LPBF) 316H stainless steel (SS) collected during Fiscal Year 2024 (FY 24) under the US Department of Energy, Office of Nuclear Energy’s Advanced Materials and Manufacturing Technologies program, along with the current state of microstructural-based understandings of the behaviors. Materials with variabilities in manufacturing site, machine, laser parameters, powder chemistry, porosity, specimen geometry and heat treatment were tested in high-temperature tension, creep, fatigue and creep-fatigue. Electron microscopy and optical microscopy were performed on selected materials before and after the tests to provide microstructural-based understandings to the mechanical behavior. It was discovered that the as-built (AB) and stress-relieved (SR) materials exhibit similar behaviors in tension and creep, as do the solution-annealed (SA) and hot-isostatic pressed (HIP) materials. The AB and SR materials are softer but more ductile than the SA and HIP materials in tension. In creep, the LPBF materials have comparable rupture times but lower rupture strains compared to the wrought materials. The AB and SR materials have low creep rupture strains (<10%) when tested at 720°C and 800°C, while the SA and HIP materials are much more ductile. The LPBF materials exhibit large scatter in fatigue and creep-fatigue lives. The cyclic lives of creep-fatigue tests are lower than those of fatigue tests. In fatigue and creep-fatigue, SR materials outperform SA materials. A common observation from the cyclic tests is that, given the same post-build heat treatment, a lower initial peak stress generally results in a longer cyclic life regardless of hold time. It was also discovered that the batch variation can be more impactful than heat treatment, as demonstrated by the overall better performance of one batch of material than another, regardless of the heat treatment. The results provided insights into how different factors impact the behaviors of LPBF 316H SS. An outlook to FY 25 work scope is provided.
36 MATERIALS SCIENCE↗
NIAC Phase-2 Final Report for Astrophysics and Technical Lab Studies of a Solar Neutrino Spacecraft Detector
The Sun provides all the energy that our planet needs for life and has been doing so for five billion years. Understanding our Sun and its interior is one of the major goals of the NASA Science program. Still this is a very difficult task because very little makes it directly out of the Sun’s interior. The energy we see today, that warms the Earth, was made 50,000 to 80,000 years ago and is only now coming to the surface to make light. However, neutrinos penetrate matter almost without interaction and make it to Earth in only eight minutes from creation. Since neutrinos interact only weakly they are hard to detect; never-the-less within the last ten years neutrino detectors on Earth have started to reliably detect neutrinos from the fusion reactions in the interior of the Sun and scientists have started to use this information to investigate the Sun’s nuclear furnace. Changes in solar neutrino flux make it advantageous to take a neutrino detector into space since the solar neutrino intensity changes dramatically as the inverse square of the distance from the Sun, by five orders of magnitude when going from the Earth to the Sun. Launch of a neutrino detector into space toward the Sun will: a) aim to significantly increase the neutrino flux 10,000x allowing for a smaller detector which improves detector energy resolution and performance, b) attempt to completely eliminate background terrestrial neutrino sources for improved measurement accuracy, and c) conduct unique science experiments near the Sun not achievable with much larger detectors on the Earth. NASA's interest in deep space exploration has been a key factor in its unmanned spacecraft development and launch of exploration science satellites and spacecraft. NASA has done exceptional experiments in space where science benefits from the unique platform of spacecraft that provides unprecedented views. For example, the Hubble Space Telescope is really a small and very common instrument, but when it is put into an orbit high above the Earth, it becomes one of the most powerful optical observatories man has ever made. Moving neutrino observations to space is the next obvious step. The concept of putting a neutrino detector in close orbit of the sun is completely unexplored and innovative. Its scientific return is to vastly enhance the understanding of the solar interior which is a NASA major goal as stated in the decadal survey. Preliminary calculations show that such a spacecraft if properly shielded, can operate in this environment both taking data of neutrino interactions which can be distinguished from random background rates of solar Electromagnetic emissions, Galactic charged cosmic-ray, and gamma-rays by using a double pulsed signature. The NIAC Phase-1 simulations have shown this idea to be very successful in eliminating background and identifying the neutrino interaction signal, hence this spacecraft detector concept once demonstrated to be Technical Readiness Level 7 and flight mission-ready would enable a whole new type of mission to explore and study our Sun, in details that could neither be done with the largest neutrino detectors on Earth nor other types of space-craft measurements that are not using neutrino detection. Our goal in this NIAC Phase-2 was to take the detector simulation ideas and construct a prototype for testing in the lab with tagged sources to evaluate and demonstrate that the performance in the simulations are borne out by a prototype.
Neutrino↗