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DOE OSTI2023

Mechanical responses of architected boron carbide-aluminum lattice composites fabricated via reactive metallic infiltration of hierarchical pore structures

The incorporation of micro and nanoscale constituents in a hierarchical order improves mechanical properties of bulk structures while inducing controlled deformation. However, these features have seldomly been applied to the fabrication of cermet materials due to manufacturing constraints. Here, overcoming previous limitations, boron carbide cermets with embedded aluminum lattices were produced using a combination of additive manufacturing and gelcasting techniques. Kelvin cell and octet truss scaffolds were printed, cast and burned out so the negative volume could be infiltrated with metal to form an architected cermet. Computed microtomography scans reveal full aluminum infiltration of the volume with high fidelity to the target architecture. Equibiaxial flexural tests showed localized crack propagation in lattice-reinforced cermets and that samples with imbedded architecture required nearly double the energy for complete failure. Overall, the addition of an internal aluminum lattice limits abrupt fracture of the composite and provides a method for tuning its mechanical response with architected ratios of metal to ceramic.

36 MATERIALS SCIENCE↗

DOE OSTI2022

AI-Enabled Discovery and Physics-Based Optimization of Energy Efficient Processing Strategies for Advanced Turbine Alloys (Final Technical Report)

In this project, the multi-organizational team of academic and industrial researchers from the University of Kentucky an aerospace and energy generation OEM partner has leveraged novel Digital Process Twin (DPT) models of process/structure interactions (i.e., process-induced surface integrity) to advance a paradigm of fully integrated computational materials engineering (ICME). Using efficient process models as the core of a digital process simulator for a reinforcement learning algorithm, the team has integrated industrial data and metrics of structure/performance/energy relationships and manufacturing-related energy metrics to optimize dynamic processing parameters for significantly improved life-cycle energy efficiency of advanced γ-TiAl low-pressure turbine (LPT) alloys, as indicated by a set of design relevant parameters (e.g., residual stresses and scrap rate). The key objective and anticipated outcome of the project was at least a 10% reduction in life-cycle embodied energy for a recently developed, γ-TiAl low-pressure turbine (LPT) alloy and nickel-based superalloy Inconel 718, through the adoption of the proposed AI-enabled process optimization approach. The final project outcomes significantly exceeded this original target, realizing manufacturing-related energy efficiency improvements of more than 130% for TiAl and up to 80% for Inconel 718. Rather than following the prevailing and highly inefficient empirical paradigm, the proposed study demonstrated the feasibility of adopting a digital, physics-based process design and optimization paradigm. The recurring need for manual intervention, rework, reinspection causes significant production bottlenecks and unnecessary expense associated with delivering the requisite component quality. The OEM partner, and turbine industry in general, expect to reap significant cost and resource savings if an AI-optimized set of parameters can be applied to specific machining operations. The technical scope of the proposed project involved the paving of a realistic path towards model-based and AI-enabled Integrated Computational Materials Engineering (ICME), and away from inefficient empirical process optimization and legacy manufacturing practices, which are no longer able to efficiently process novel high-performance turbine alloy materials. The project team will address the fundamental knowledge gap that currently exists within the ICME paradigm with respect to the process/structure/performance/energy impacts of finishing processes. While significant resources have been devoted to the ‘early stages’ of manufacturing, such as alloy design, primary and secondary processing, finishing processes have not been adequately integrated within ICME. To provide an actionable path towards model-based finishing process design (e.g., machining, burnishing, grinding, polishing), we will employ a novel AI-enabled process optimization paradigm, based on a computationally efficient, physics-based process simulator. Through limited experimental work to calibrate and validate our process simulator model via an advanced in-situ characterization technique and process optimization via reinforcement learning, the project will seek to demonstrate a viable alternative to the inefficient ‘legacy’ processing strategies, empirical testing and broad scope machining learning approaches, all of which fail to adequately consider complex process physics. The project team has identified an intermetallic γ-TiAl LPT alloy, which is currently being used as part of the OEM partner’s advanced gas turbine designs. This particular alloy poses significant manufacturing challenges during finishing operations, which limit the degree to which the current turbine design can be manufactured in an energy- and cost-efficient manner. Empirical testing and numerical modeling efforts to optimize processing parameters for γ-TiAl have not been able to resolve these manufacturing challenges, so the proposed physics-based AI-enabled optimization technology would offer a truly novel and transformative capability. The multi-organizational team of academic and industry experts from the UKY and the OEM partner will work together closely to demonstrate the analytical and experimental critical function and characteristic proof of concept of this novel approach.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2025

Wide‐Field Bond Quality Evaluation Using Frequency Domain Thermoreflectance with Deep Neural Network Feature Reconstruction

Heterogeneous integration of microelectronic components provides a pathway to improve circuit/component performance; however, this comes with assembly challenges, in particular due to complex interfaces via subsurface bump bonds. The ability of these bonds to transmit electrical signals and conduct heat to the carrier substrate limits component performance. In this work, hyperspectral frequency‐domain thermoreflectance (FDTR) imaging is demonstrated as a robust technique for evaluating the quality of subsurface indium bump bonds in a surrogate microelectronic sample. By performing microscale FDTR imaging with coarse motion image stitching, thermal phase maps that cover a 4 mm by 4 mm field‐of‐view with subsurface feature sensitivity at depths greater than 50 µm are obtained. The resulting FDTR hyperspectral data contains more than three million pixels and reveal the quality of subsurface microbump arrays. Wide‐field analysis of bonded versus gap regions is enabled by deep neural network feature reconstruction, that after training, rapidly provides an interpretable representation of bond quality. Utility of noisy higher frequency FDTR phase maps, i.e., near the computationally predicted sensing depth limit, results in an average prediction error of 11%. Taken together, FDTR with neural network‐based analysis demonstrates subsurface bond monitoring at length scales relevant for heterogeneously integrated microelectronics.

FDTR↗

DOE OSTI2023

Spherical powders: Control over the size and morphology of powders for additive manufacturing and enriched stable isotope nuclear targets

Metal powders are a fundamental starting point for fabricating many types of nuclear targets. Elemental powder properties can differ drastically between batches, even when using the same method. Therefore, the variation in morphology and the size of metal powders can cause variable quality and produce inconsistent results with what are otherwise proven target manufacturing techniques. Additive manufacturing has additional requirements for higher quality and more uniform feedstock. The production of spheroidized powders with uniform, reproducible properties and a narrow size distribution represents unexplored opportunities for experiments. These opportunities include experimenting with solid metals that can now flow like liquids, new options for powder handling and dispensing, and new target fabrication methods using additive manufacturing. The Stable Isotope Materials and Chemistry Group at Oak Ridge National Laboratory obtained an AMAZEMET rePowder ultrasonic metal atomization tool for creating limited batches of fully dense, free flowing, spherical powders with a narrow size distribution of extremely rare materials. Early results are presented with materials that were produced. The team explores the anticipated limits of this instrument with extremely rare materials (e.g., enriched stable isotopes) and highlights research into new fabrication techniques that provide additional options benefitting the international nuclear target community.

Zach, Mike↗

DOE OSTI2026

An overview of 3D field optimization for control of transport and edge instabilities on KSTAR

An international team from several laboratories and universities has made key advances over the last few years in the control of plasma transport and edge instabilities with applied 3D fields in the KSTAR tokamak to optimize long pulse operation scenarios. This overview begins with the optimization of both core and edge resonant magnetic perturbations (RMP) to improve fast ion confinement to avoid excessive limiter heat loads due to fast ion losses and successful modeling of the experimental results. Integrated and advanced plasma control techniques with machine learning (ML) and adaptive control were then used to optimize the 3D field spectrum in real-time to control edge localized modes (ELMs) while avoiding core locked modes that could disrupt the plasma. Accelerating the offline model of 3D fields with a surrogate ML model can optimize ELM suppression in the edge while limiting the impact of the applied RMP fields deeper in the plasma core in real-time. In addition, the impact of the 3D fields on the divertor heat load has been modeled and compared with experimental measurements. An analysis of a multi-machine database including KSTAR has been performed to better understand the metrics for the observed RMP thresholds for ELM suppression and the resulting plasma performance. Predictive modeling of the operational space for ELM suppression and density pumpout due to RMP has shown the importance of magnetic islands in the plasma edge and their impact on plasma turbulence. This research has culminated in the development of successful long pulse operational scenarios on KSTAR while attempting to overcome challenges of the new tungsten divertor.

3D fields↗

DOE OSTI2023

Super-resolution computational saturated absorption microscopy

Imaging beyond the diffraction limit barrier has attracted wide attention due to the ability to resolve previously hidden image features. Of the various super-resolution microscopy techniques available, a particularly simple method called saturated excitation microscopy (SAX) requires only simple modification of a laser scanning microscope: The illumination beam power is sinusoidally modulated and driven into saturation. SAX images are extracted from the harmonics of the modulation frequency and exhibit improved spatial resolution. Unfortunately, this elegant strategy is hindered by the incursion of shot noise that prevents high-resolution imaging in many realistic scenarios. Here, we demonstrate a technique for super-resolution imaging that we call computational saturated absorption (CSA) in which a joint deconvolution is applied to a set of images with diversity in spatial frequency support among the point spread functions (PSFs) used in the image formation with saturated laser scanning fluorescence microscopy. CSA microscopy allows access to the high spatial frequency diversity in a set of saturated effective PSFs, while avoiding image degradation from shot noise.

Murray, Gabe (ORCID:0000000295655485)↗

DOE OSTI2025

Evaluation of current density measurement methods for high-current, low-beta electron beams

Recent current density measurements with a low-beta electron beam (β=0.5-0.75) are strongly affected by electron scatter and Cherenkov limits. These invasive measurements are heavily influenced by the electron energy and the intercepting material properties: density, index of refraction, and atomic number. We evaluate various measurement methods, including x-ray scintillation and Cherenkov emission. To optimize the x-ray scintillation technique for this energy regime, metal foils of differing atomic number (Z) and thickness were placed upstream of a scintillation screen. We have selected Cherenkov emitters, based on a material refractive index, in order to differentiate the contributions from electron scatter and produced fluorescence, Cherenkov emission, and total internal reflection. The observed distributions for both approaches are verified through MCNP6®. Additionally, the simulations provide insight as to what physical processes dominate the measured distribution. We conclude by determining the limits and optimal measurement range for each measurement technique.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Assessing the technical aspects of ocean-alkalinity-enhancement approaches

Ocean alkalinity enhancement (OAE) is an emerging strategy that aims to mitigate climate change by increasing the alkalinity of seawater. This approach involves increasing the alkalinity of the ocean to enhance its capacity to absorb and store carbon dioxide (CO 2 ) from the atmosphere. This chapter presents an overview of the technical aspects associated with the full range of OAE methods being pursued and discusses implications for undertaking research on these approaches. Various methods have been developed to implement OAE, including the direct injection of alkaline liquid into the surface ocean; dispersal of alkaline particles from ships, platforms, or pipes; the addition of minerals to coastal environments; and the electrochemical removal of acid from seawater. Each method has its advantages and challenges, such as scalability, cost effectiveness, and potential environmental impacts. The choice of technique may depend on factors such as regional oceanographic conditions, alkalinity source availability, and engineering feasibility. This chapter considers electrochemical methods, the accelerated weathering of limestone, ocean liming, the creation of hydrated carbonates, and the addition of minerals to coastal environments. In each case, the technical aspects of the technologies are considered, and implications for best-practice research are drawn. The environmental and social impacts of OAE will likely depend on the specific technology and the local context in which it is deployed. Therefore, it is essential that the technical feasibility of OAE is undertaken in parallel with, and informed by, wider impact assessments. While OAE shows promise as a potential climate change mitigation strategy, it is essential to acknowledge its limitations and uncertainties. Further research and development are needed to understand the long-term effects, optimize techniques, and address potential unintended consequences. OAE should be viewed as complementary to extensive emission reductions, and its feasibility may be improved if it is operated using energy and supply chains with minimal CO 2 emissions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Redefining precision interferometry and spectroscopy with high-performance optical interference coatings

High-performance optical interference coatings have transformed precision interferometry and spectroscopy by enabling unparalleled control over light–matter interactions. This review explores recent innovations in ion-beam sputtered amorphous dielectric, as well as substrate-transferred crystalline coatings, and their impact on systems at the forefront of precision metrology. These state-of-the-art coating techniques generate multilayers with ultralow optical losses, yielding mirrors with exceptional reflectivity. Refinements in their noise performance push the ultimate limits of sensitivity, resolution, and stability in demanding laser-based metrology applications. These technologies underpin the most advanced timekeeping and spatial measurement tools, enabling high-finesse reference cavities for the world’s most precise optical atomic clocks and low-noise reflective test masses for km-baseline gravitational-wave detectors. Emerging hybrid designs combining these techniques expand access to the mid-infrared spectral region, enabling the first ultralow-optical-loss coatings in the 3000–5000 nm wavelength range for enhanced spectroscopy and trace-gas detection. We highlight how these technologies redefine coating performance metrics and set new benchmarks in quantum science, fundamental physics, and precision optical sensing.

Cole, Garrett D. [University of Arizona, Tucson, A↗

DOE OSTI2025

High‐Temperature Single‐Photon Emission From Covalently Functionalized van der Waals Heterostructures

Two-dimensional (2D) transition metal dichalcogenides (TMDs) such as tungsten diselenide (WSe 2 ) are attractive nanomaterials for quantum information applications due to single-photon emission (SPE) from intrinsic atomic defects. Defect and strain engineering techniques have been developed to produce high purity, deterministically placed SPE in WSe 2 . However, a major challenge in the application of these techniques is the low temperature required to observe defect-bound TMD exciton emission, typically limiting SPE to T < 30 K. SPE at higher temperatures either loses purity or requires integration into complex devices such as optical cavities. Here, 2D heterostructure engineering and molecular functionalization are combined to achieve high purity (>90%) SPE in strained WSe 2 persisting to over T = 90 K. Covalent diazonium functionalization of graphite in layered WSe 2 /graphite heterostructures maintains high purity up to T = 90 K and single-photon source integrity up to T = 115 K. This method preserves the best qualities of SPE from WSe 2 while increasing working temperature to more than three times the typical range. This work demonstrates the versatility of surface functionalization and heterostructure design to synergistically improve the properties of quantum emission and offers new insights into the phenomenon of SPE from 2D materials.

2D materials↗

DOE OSTI2026

Neutron Grating Interferometry at the High Flux Isotope Reactor

Neutron imaging is a non-destructive probe that can spatially resolve bulk materials’ internal features/structures. Neutron imaging spatial resolution is driven by detector technology, i.e., pixel size, and is currently on the order of 10–20 µm. This limitation can be alleviated by the use of neutron grating interferometry – an advanced neutron imaging technique – that enables simultaneous access to three contrast mechanisms: attenuation, differential phase, and small-angle neutron scattering. Recently, a Talbot-Lau neutron grating interferometry has been implemented at the Multimodal Advanced Radiography Station at the High Flux Isotope Reactor. In this work, the design, setup and performance of the grating apparatus are presented.

Zhang, Yuxuan [ORNL] (ORCID:0000000200831408)↗

DOE OSTI2023

Search for supersymmetry in final states with a single electron or muon using angular correlations and heavy-object identification in proton-proton collisions at $ \sqrt{s} $ = 13 TeV

A search for supersymmetry is presented in events with a single charged lepton, electron or muon, and multiple hadronic jets. The data correspond to an integrated luminosity of 138 fb –1 of proton-proton collisions at a center-of-mass energy of 13 TeV, recorded by the CMS experiment at the CERN LHC. The search targets gluino pair production, where the gluinos decay into final states with the lightest supersymmetric particle (LSP) and either a top quark-antiquark ($\text{t}\bar{\text{t}}$ pair, or a light-flavor quark-antiquark ($\text{q}\bar{\text{q}}$ pair and a virtual or on-shell W boson. The main backgrounds, $\text{t}\bar{\text{t}}$ pair and W+jets production, are suppressed by requirements on the azimuthal angle between the momenta of the lepton and of its reconstructed parent W boson candidate, and by top quark and W boson identification based on a machine-learning technique. The number of observed events is consistent with the expectations from standard model processes. Limits are evaluated on supersymmetric particle masses in the context of two simplified models of gluino pair production. Exclusions for gluino masses reach up to 2120 (2050) GeV at 95% confidence level for a model with gluino decay to a $\text{t}\bar{\text{t}}$ pair (a $\text{q}\bar{\text{q}}$ pair and a W boson) and the LSP. For the same models, limits on the mass of the LSP reach up to 1250 (1070) GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Real-time damage characterization for GFRCs using high-speed synchrotron X-ray phase contrast imaging

Here, we report the application of high-speed synchrotron X-ray phase contrast imaging (PCI) in real-time damage characterization for glass fiber reinforced composites (GFRCs) subjected to dynamic loading. Dynamic single-edge notched bending (DSENB) experiments on pre-notched S-2 GFRCs were performed on a modified Kolsky compression bar. During loading, the synchrotron X-ray beam penetrated through the composite specimen from the side to detect damage evolution inside the material. Entire dynamic events were recorded by a high-speed camera as image sequences.0° and 90° unidirectional and cross-ply composites were investigated. An optical imaging technique was also employed to capture similar dynamic events in comparison with the radiographic imaging. It is demonstrated that high-speed X-ray PCI had sufficient phase contrast to characterize a crack initiation at a 20-μm spatial resolution within 920 ns and track the crack geometry during propagation, thereby providing reliable data to quantify the dynamic damage resistance of GFRCs. Furthermore, being capable of recognizing microscopic damage-related features at a sub-10-μm resolution, high-speed X-ray PCI provided fundamental material failure mechanisms to reveal the essential of macroscale structural failure of composites. It can also track the damage evolution inside and between individual plies of laminated composites. However, current high-speed X-ray PCI technique only supports in-situ observation and the high timing and spatial resolutions are limited within a field of view of ~2.5 mm in square, preventing its application in the three-dimensional and larger-area damage detection for GFRC structures.

42 ENGINEERING↗

DOE OSTI2024

Circularly Polarized Attosecond Pulses Enabled by an Azimuthal Phase and Polarization Grating

High-harmonic generation (HHG) is an extreme nonlinear optical process that can map the properties of an infrared driving laser beam onto short wavelength attosecond pulse trains. However, current techniques for generating circularly polarized high harmonics for probing magnetic materials and chiral systems have limitations: two-color collinear counter-rotating driving lasers result in a low cutoff photon energy, while single-color non-collinear counter-rotating schemes suffer from low conversion efficiency. In this work, we generate circularly polarized attosecond pulse trains by using a structured laser driver which has a rotating polarization and phase grating along the azimuthal coordinate. Furthermore, our experimental and numerical results demonstrate the production of left and right circularly polarized harmonics, which naturally separate upon propagation. Our approach uses a single laser color in a collinear geometry, that can be scaled for high efficiency. Simulations show this scheme can extend into the soft x-ray region when driven by mid-infrared driving lasers, while preserving the same high phase-matching cutoff photon energy as for linearly-polarized high harmonics.

attosecond science↗

DOE OSTI2025

A Probabilistic Model for Global EMIC Wave Activity Using Van Allen Probes Observations

Electromagnetic ion cyclotron (EMIC) waves play a key role in radiation belt dynamics through resonant interactions. However, their low occurrence probability, high variability, and spatial intermittency pose challenges for accurate modeling. In this study, we present a machine learning (ML)-based global EMIC wave model built on the entire data set from the Van Allen Probes mission. To capture the distinct statistical characteristics of wave occurrence and amplitude, the model is separated into two modules: an occurrence model trained using ML techniques, and a wave amplitude model sampled from observed probability distributions. The input parameters are limited to real-time or predictable variables to ensure practical applicability. Our model shows strong performance across the entire test set and demonstrates improved predictive capability over a baseline random occurrence model, particularly during quiet geomagnetic conditions. Evaluation during both quiet and active periods confirms the model's ability to represent the clustered and intermittent nature of EMIC wave activity. Furthermore, the model provides global estimates of wave power, enabling integration with radiation belt electron data and showing signatures consistent with wave-induced scattering. We found a good correlation between the global wave activity from the model and relativistic electron observation by Van Allen Probes, regardless of the availability of in situ wave observations. The modular structure of the model also allows for straightforward expansion for additional wave properties, such as wave frequency, which can be modeled independently. This flexible, event-sensitive approach offers a promising framework for data-driven radiation belt simulations and space weather applications.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Artificial generation of representative single Li-ion electrode particle architectures from microscopy data

Accurately capturing the architecture of single lithium-ion electrode particles is necessary for understanding their performance limitations and degradation mechanisms through multi-physics modeling. Information is drawn from multimodal microscopy techniques to artificially generate LiNi 0.5 Mn 0.3 Co 0.2 O 2 particles with full sub-particle grain detail. Statistical representations of particle architectures are derived from X-ray nano-computed tomography data supporting an ‘outer shell’ model, and sub-particle grain representations are derived from focused-ion beam electron backscatter diffraction data supporting a ‘grain’ model. A random field model used to characterize and generate the outer shells, and a random tessellation model used to characterize and generate grain architectures, are combined to form a multi-scale model for the generation of virtual electrode particles with full-grain detail. This work demonstrates the possibility of generating representative single electrode particle architectures for modeling and characterization that can guide synthesis approaches of particle architectures with enhanced performance.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Absolute electron density fluctuation reconstruction for two-dimensional hydrogen beam emission spectroscopy

Scrape-off layer (SOL) and edge plasma turbulence significantly contribute to the radial particle and heat transport, lowering the plasma confinement and increasing the heat load on the plasma facing components. SOL turbulence is predominantly intermittent, which manifests in the occurrence of isolated density filaments or blobs. Filaments propagate radially outward toward plasma facing components, limiting their lifetime by erosion and sputtering. To characterize this phenomenon in detail, few diagnostic techniques are available. Beam emission spectroscopy is a diagnostic capable of measuring plasma turbulence in both SOL and edge plasmas. Due to the finite lifetime of the excitation states during the beam–plasma interaction and the misalignment between the optics and the magnetic field, spatial smearing is introduced in the measurement. In this paper, a novel method is introduced to overcome this hindering effect by inverting the fluctuation response matrix on an optimally smoothed signal. We show that this method is fast and provides significantly more accurate absolute density fluctuation reconstruction than the direct inversion technique. Here, the presented method is usable for all types of beam emission diagnostics where the spatial resolution is higher than the combined smearing of the atomic physics and the observation.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Random magnetic field and the Dirac Fermi surface

In this paper, we study a single two-dimensional Dirac fermion at finite density, subject to a quenched random magnetic field. At low energies and sufficiently weak disorder, the theory maps onto an infinite collection of 1D chiral fermions (associated to each point on the Fermi surface) coupled by a random vector potential. This low-energy theory exhibits an exactly solvable random fixed line, along which we directly compute various disorder-averaged observables without the need for the usual replica, supersymmetry, or Keldysh techniques. We find the longitudinal dc conductivity in the collisionless $\hbar$ω/k B T→∞ limit to be nonuniversal and to vary continuously along the fixed line.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗