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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Software Architecture and Hardware Organization in Mu2e Solenoid Field Mapping System

Herein, the Mu2e field mapping system is designed to produce high accuracy field maps of the detector solenoid used in the experiment. The data acquisition system is mobile and uses a self-propelled mapper with rotating arms equipped with 3D Hall probes. The measurements require not only accurate magnetic field readouts, but also accurate locations of all Hall probes while measuring data. The latter is accomplished by using the laser tracker to measure positions of several retroreflectors on the field mapper during data acquisition. The measurement process requires scanning the whole space inside the large solenoid and takes many hours to complete, which necessitates its full automation. The automation software includes control of the mapper, readout of Hall and NMR probes and control of a laser tracker, including prediction of retroreflector positions and execution of quality control checks. The software architecture and data acquisition hardware of the field mapping system are described, with special attention given to control of the laser tracker and its integration with the rest of the system.

3d hall probes↗
DOE OSTI2026

Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that challenge traditional analysis pipelines. The LSST Dark Energy Science Collaboration (DESC) aims to derive robust constraints on dark energy and dark matter from these data, requiring methods that are statistically powerful, scalable, and operationally reliable. Artificial intelligence and machine learning (AI/ML) are already embedded across DESC science workflows, from photometric redshifts and transient classification to weak lensing inference and cosmological simulations. Yet their utility for precision cosmology hinges on trustworthy uncertainty quantification, robustness to covariate shift and model misspecification, and reproducible integration within scientific pipelines. This white paper surveys the current landscape of AI/ML across DESC's primary cosmological probes and cross-cutting analyses, revealing that the same core methodologies and fundamental challenges recur across disparate science cases. Since progress on these cross-cutting challenges would benefit multiple probes simultaneously, we identify key methodological research priorities, including Bayesian inference at scale, physics-informed methods, validation frameworks, and active learning for discovery. With an eye on emerging techniques, we also explore the potential of the latest foundation model methodologies and LLM-driven agentic AI systems to reshape DESC workflows, provided their deployment is coupled with rigorous evaluation and governance. Finally, we discuss critical software, computing, data infrastructure, and human capital requirements for the successful deployment of these new methodologies, and consider associated risks and opportunities for broader coordination with external actors.

Aubourg, Eric [APC, Paris] (ORCID:000000025592023X↗
DOE OSTI2024

Roadmap on data-centric materials science

Science is and always has been based on data, but the terms ‘data-centric’ and the ‘4th paradigm’ of materials research indicate a radical change in how information is retrieved, handled and research is performed. It signifies a transformative shift towards managing vast data collections, digital repositories, and innovative data analytics methods. The integration of artificial intelligence and its subset machine learning, has become pivotal in addressing all these challenges. This Roadmap on Data-Centric Materials Science explores fundamental concepts and methodologies, illustrating diverse applications in electronic-structure theory, soft matter theory, microstructure research, and experimental techniques like photoemission, atom probe tomography, and electron microscopy. While the roadmap delves into specific areas within the broad interdisciplinary field of materials science, the provided examples elucidate key concepts applicable to a wider range of topics. The discussed instances offer insights into addressing the multifaceted challenges encountered in contemporary materials research.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Atom probe tomography of segregation at grain boundaries and gas bubbles in neutron irradiated U-10 wt% Mo fuel

During neutron irradiation to fission densities > 5.2 × 10 21 fiss/cm 3 , Xe agglomerates forming gas bubbles of varying size within the U-Mo fuel matrix. Herein, segregation of fission products to Xe bubbles and grain boundaries (GB) were studied using atom probe tomography (APT). Segregation behavior was found to vary among GBs, small bubbles (<10 nm), and larger bubbles (>10 nm). Solid fission products were enriched at GBs and larger bubbles, but not at small bubbles. Finally, a denuded zone was identified adjacent to a > 10 nm Xe gas bubble and a GB.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Visualizing oxygen transport pathways during intergranular oxidation in Ni-Cr

The transport paths of O during intergranular oxidation in binary Ni-Cr were investigated. To isolate the selective oxidation of Cr, oxidation was performed with a CO/CO 2 gas mixture in which the oxygen partial pressure was kept under the NiO dissociation pressure. A combination of electron microscopy and atom probe tomography (APT) was used to study the nanometer-scale details of the passivation and penetrative intergranular oxidation processes at high-energy grain boundaries. Oxygen transport towards the terminating oxidation front is elucidated with dedicated usage of oxygen tracer exchange experiments. Secondary ion mass spectroscopy and APT support classical theories of internal oxidation, revealing preferred transport paths at the oxide/alloy interface with sub-nanometer resolution.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Building an Integrated Ecosystem of Computational and Observational Facilities to Accelerate Scientific Discovery

Future scientific discoveries will rely on flexible ecosystems that incorporate modern scientific instruments, high performance computing resources, parallel distributed data storage, and performant networks across multiple, independent facilities. In addition to connecting physical resources, such an ecosystem presents many challenges in logistics and accessibility, especially in orchestrating computations and experiments that span across leadership computing systems and experimental instruments. Past efforts have typically been application-specific or limited to interfaces for computing resources. This paper proposes a general framework for integrating computation resources and instrument operations, addressing challenges in code development/execution, data staging and collection, software stack, control mechanisms, resource authorization and governance, and hardware integration. We also describe a demonstration use case wherein a Bayesian optimization algorithm running on an edge computing resource guides a scanning probe microscope to autonomously and intelligently characterize a material sample. This science edge ecosystem framework will provide a blueprint for federating multi-institutional, disparate resources and orchestrating scientific workflows across them to enable next-generation discoveries.

Somnath, Suhas↗
DOE OSTI2022

AtomAI framework for deep learning analysis of image and spectroscopy data in electron and scanning probe microscopy

Over the past several decades, electron and scanning probe microscopes have become critical components of condensed matter physics, materials science and chemistry research. At the same time, the infrastructure for establishing a connection between microscopy observations and materials behaviour over a broader parameter space is lacking. In this work, we introduce AtomAI, an open-source software package bridging instrument-specific Python libraries, deep learning and simulation tools into a single ecosystem. AtomAI allows direct applications of deep neural networks for atomic and mesoscopic image segmentation converting image and spectroscopy data into class-based local descriptors for downstream tasks such as statistical and graph analysis. For atomically resolved imaging data, the output is types and positions of atomic species, with an option for subsequent refinement. AtomAI further allows the implementation of a broad range of image and spectrum analysis functions, including invariant variational autoencoders for disentangling structural factors of variation and im2spec type of encoder–decoder models for mapping structure–property relationships. Finally, our framework allows seamless connection to the first principles modelling with a Python interface on the inferred atomic positions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

High-precision inversion of dynamic radiography using hydrodynamic features

While radiography is routinely used to probe complex, evolving density fields in research areas ranging from materials science to shock physics to inertial confinement fusion and other national security applications, complications resulting from noise, scatter, complex beam dynamics, etc. prevent current methods of reconstructing density from being accurate enough to identify the underlying physics with sufficient confidence. In this work, we show that using only features that are robustly identifiable in radiographs and combining them with the underlying hydrodynamic equations of motion using a machine learning approach of a conditional generative adversarial network (cGAN) provides a new and effective approach to determine density fields from a dynamic sequence of radiographs. In particular, we demonstrate the ability of this method to outperform a traditional, direct radiograph to density reconstruction in the presence of scatter, even when relatively small amounts of scatter are present. Our experiments on synthetic data show that the approach can produce high quality, robust reconstructions. We also show that the distance (in feature space) between a testing radiograph and the training set can serve as a diagnostic of the accuracy of the reconstruction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Ion Channel Laser Based on Direct Laser Acceleration of a Shaped Beam Driver (Final Technical Report)

The main focus of our research was to understand the synergies between an electron bunch and a laser pulse when the two co-propagate through the plasma. We have clearly demonstrated using theoretical and computational modeling that the propagation distance of both the bunch and the laser pulse could be extended. The ability of the combined bunch/pulse system to extend the propagation distance and the size of the plasma bubble enables highly-efficient sources of relativistic electrons. As pointed out by the Plasma Decadal Study, such electron sources can be used for generating extremely bright x-rays for a variety of applications can serve as probes and diagnostics for other plasma experiments: high energy density (HED) sciences, inertial confinement fusion (ICF), and potentially Fusion Materials and Technology (FM&T). Development of advanced diagnostics of plasma-based accelerators is yet another key area identified by recent reports. Even broader security and medical applications of compact accelerator-based radiation sources, such as very high energy electron (VHEE) sources for FLASH radiobiology, have been identified by a recent multi-agency panel. A number of key technical issues were considered and successfully resolved during the course of the grant. Those include: beam loading effect of both the driver and witness bunches on the wake, laser channeling by the bunch, and the direct laser acceleration (DLA) of the driver bunch by the laser pulse. To demonstrate clear synergy, we were able to ascertain that the total energy gain of a witness bunch in the wake of the combined bunch/laser complex is large than the sum of the energy gains in the wake of the laser pulse alone, and the driver bunch alone. We have also demonstrated that not only the energy gain is improved, but the energy spread is not sacrificed. To carry out these simulations, we have to develop a range of in-house computational tools, including a fully-3D code WAND-PIC.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Effect of dose rate on the phase stability of a CrFeNiMn alloy

We report CrFeNi-based multi-principal element alloys (MPEAs) are being considered for nuclear applications because of their potentially superior mechanical properties and irradiation resistance. While the alloys appear stable against phase decomposition during ion irradiation performed at high dose rate, previous electron irradiation and thermal annealing studies suggested that some of them may be susceptible to phase decomposition. Therefore, to clarify the role of dose rate during ion irradiation on phase decomposition, a CrFeNiMn alloy was irradiated using Fe ions at 500 °C with an intermediate dose rate of 10 -4 dpa/s. Transmission electron microscopy and atom probe tomography observations revealed a high number density of NiMn precipitates, cavities, and dislocation loops, which had not previously been observed after ion irradiation at higher dose rates.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Lattice Parameter Evolution during the β-to-α and β-to-ω Transformations of Iron- and Aluminum-Modified Ti-11Cr(at.%)

β-titanium (β-Ti) alloys are useful in diverse industries because their mechanical properties can be tuned by transforming the metastable β phase into other metastable and stable phases. Relationships between lattice parameter and β-Ti alloy concentrations have been explored, but the lattice parameter evolution during β-phase transformations is not well understood. In this work, the β-Ti alloys, Ti-11Cr, Ti-11Cr-0.85Fe, Ti-11Cr-5.3Al, and Ti-11Cr-0.85Fe-5.3Al (all in at.%), underwent a 400 °C aging treatment for up to 12 h to induce the β-to-ω and β-to-α phase transformations. Phase identification and lattice parameters were measured in situ using high-temperature X-ray diffraction. Phase compositions were measured ex situ using atom probe tomography. During the phase transformations, Cr and Fe diffused from the ω and α phases into the β matrix, and the β-phase lattice parameter exhibited a corresponding decrease. The decrease in β-phase lattice parameter affected the α- and ω-phase lattice parameters. The α phase in the Fe-free alloys exhibited α-phase c/a ratios close to those of pure Ti. A larger β-phase composition change in Ti-11Cr resulted in larger ω-phase lattice parameter changes than that for Ti-11Cr-0.85Fe. This work illuminates the complex relationship between diffusion, composition, and structure for these diffusive/displacive transformations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Development of Automated Atom Probe Tomography capability to study the influence of applied voltage and laser power on the final apparent composition of the analyzed specimen

This study presents the development and implementation of an autonomous Bayesian optimization (BO) framework for controlling and optimizing experimental parameters in Atom Probe Tomography (APT). Using commercial silicon needle samples as a benchmark system, we demonstrate that BO can efficiently navigate the complex parameter space of voltage and laser power to achieve target charge state ratios (specifically Si + /(Si + +Si 2+ )) with minimal experimental evaluations. Our implementation integrates Gaussian Process modeling with the CAMECA atom probe control framework, enabling autonomous adjustment of experimental conditions in real-time. Results show that the algorithm successfully converges to target ratios under different scenarios: maintaining a reference ratio, increasing the ratio (favoring Si 1+ ), and decreasing the ratio (favoring Si 2+ ). The system adapts to specimen evolution during analysis, compensating for changes in apex geometry while maintaining optimization targets. This work establishes a proof of concept for AI-driven optimization in APT, addressing the traditional challenges of manual parameter tuning and paving the way for applications to more complex materials where compositional accuracy is critical.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Phase instabilities in austenitic steels during particle bombardment at high and low dose rates

Disruption of phase stability by energetic particle bombardment is a major challenge in designing advanced radiation-tolerant alloys and ion beam processing of nanocomposites. Particularly, ballistic dissolution susceptibility of different solute nanocluster species in alloys is poorly understood. Here, low dose rate neutron irradiations were conducted on a Fe-Cr-Ni based austenitic steel in the BOR-60 reactor (9.4 × 10 -7 dpa/s, 318 °C) followed by accelerated dose rate ion irradiations at multiple temperatures ( 10 -3 dpa/s, 380 – 420 °C). Using atom probe tomography, the stability of radiation-enhanced Cu-rich and radiation-induced Ni-Si-Mn-rich nanoclusters was evaluated. During neutron irradiation, Cu-rich clusters nucleated with their core concentrations progressively increasing with dose, while Ni-Si-Mn-rich clusters formed and evolved into G-phase precipitates. Ion irradiations dramatically altered the nanoclusters. Cu-rich clusters were ballistically dissolved, but Ni-Si-Mn-rich clusters remained stable and coarsened with dose at 400 and 420 °C, highlighting that different nanocluster species in a single microstructure can have innately distinct ballistic dissolution susceptibilities. Solute-specific recoil rates were incorporated into the Heinig precipitate stability model, which shows that in addition to radiation-enhanced diffusion, recovery from ballistic dissolution depends on solute concentration gradient near cluster interfaces. Finally, the combined experimental-modeling study quantified the critical temperatures and damage rates where ballistic dissolution dominates for each cluster species.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Measurements of the thermal conductivity of reference liquids using a modified transient hot-wire needle probe

Many power generation processes feature some type of working fluid that plays a critical role in the transfer of heat throughout the system. To optimize thermal efficiencies, an accurate characterization of the temperature-dependent thermal conductivity of the fluid is needed. Herein, this study develops a time-domain Modified Transient Hot-wire Needle Probe to overcome phenomena that have impaired traditional measurement techniques when the fluid is both corrosive and at an elevated temperature. First, the physical design of the instrument is presented to demonstrate features that limit interference from corrosion, electrical conduction, and convective and radiative heat transfer. Next, a governing equation for 1D (radial) heat conduction is fully developed using the thermal quadrupoles technique. A finite-element study is performed for validation. A sensitivity analysis is done to assess the time-dependent influence of critical parameters in the governing equation for several samples. Finally, thermal conductivity measurements are presented for seven different liquid substances by fitting the thermal model to experimental data across a range of temperatures. Reference correlations are included for comparison. The sample thermal conductivity and ambient temperature of the experimental conditions range from 0.125–16.5$\frac{W}{m·K}$ and 10–400°C, respectively. The total uncertainty, comprised of both the experimental design and fitting process, of all measurements is quantified.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Evidence of Xe-incorporation in the bubble superlattice in irradiated U-Mo fuel

For years, researchers have reported competing ideas on the formation of fission gas bubble super lattices in metallic fuels, which was postulated to be comprised of elemental xenon (Xe) atoms. However, the chemical and physical arrangement of these elements within this gas bubble superlattice has not been verified. In this contribution, Xe was chemically profiled using atomic resolution scanning transmission electron microscopy (STEM) and atom probe tomography (APT) techniques in irradiated uranium-molybdenum (U-Mo) fuels. These complementary techniques provide conclusive evidence of Xe presence in bubble superlattice up to fission densities of 4.5×10 21 fissions/cm 3 and provide quantitative assessment of Xe content within the bubble superlattice. Based on the results of simultaneous imaging and spectroscopy using STEM, the chemical composition of the Xe bubble superlattice present in fission densities less than 4.5x10 21 fissions/cm 3 in U-Mo fuel was measured and found to be up to 8±1.3 atomic %. APT data complements STEM findings on Xe distribution in irradiated U-Mo fuel sample. APT showed a chemical composition of 0.7±0.1 atomic%. Finally, this study concludes by providing conclusive evidence that Xe is not only present within an atomically arranged bubble superlattice but provides fundamental insight the physical state of Xe in low enriched U-Mo monolithic fuel.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Rapid assessment of structural and compositional changes during early stages of zirconium alloy oxidation

A multimodal chemical imaging approach has been developed and applied to detail the dynamic, atomic-scale changes associated with oxidation of a zirconium alloy (Zircaloy-4). Scanning transmission electron microscopy, a gas-phase reactor chamber attached to an atom probe tomography instrument, and synchrotron-based X-ray absorption near-edge spectroscopy were employed to reveal morphology, composition, crystal, and electronic structure changes that occur during initial stages of oxidation at 300 °C. Oxidation was carried out in 10 mbar O 2 gas for short exposure times of 1 and 5 min. A multilayered oxide film with a cubic ZrO adjacent to the oxide/metal interface, a nanoscopic transition region with a graded composition of ZrO 2-x (where 0 < x < 1), and tetragonal ZrO 2 in the outermost oxide were formed. Partitioning of the major alloying element (tin) to the oxide/metal interface and heterogeneously within the oxide accompanied the development of the layered oxide. Our work provides a rapid, high-throughput approach for detailed characterisation of initial stages of zirconium alloy oxidation at an accelerated time scale, with implications for several other alloy systems.

36 MATERIALS SCIENCE↗