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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Modeling and Optimization of a Rotating Packed Bed Contactor with a Tetraamine-Appended Metal−Organic Framework for CO 2 Capture

A potential contactor technology for sorbent-based CO 2 capture is the rotating packed bed that contains separate sections for continuous adsorption and desorption. A heat exchanger can be embedded to remove heat in the adsorption section and add heat in the desorption section. In this work, we develop a two-dimensional (2D) model of a rotating packed bed for use in CO 2 capture applications. Mass and energy balances for the model are developed based on a Ljungström-type air preheater, which accounts for the counter-current axial flow of gas phases in separate sections of the bed and the rotation of a solid sorbent, which cycles between adsorption and desorption sections. The sorbent used for this analysis is the tetraamine-appended metal−organic framework Mg 2 (dobpdc)(3−4− 3), chosen for its stability and affinity for CO 2 at low partial pressures, such as those from a natural gas power plant source. An optimization problem is solved that considers the trade-off between maximizing the productivity of the bed and minimizing energy consumption. Maximum productivity and minimum energy are found to be 8.53 kg/h/m 3 and 3.84 MJ/kg, respectively, when these objectives are optimized independently. It is observed that the flue gas pressure and bed rotational speed are the desired operating variables to vary for model-based design of experiments to reduce uncertainty in parameter estimation, as these two variables yielded the most information content based on the Fisher information matrix.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

DECOVALEX-2023: Task A Final Report

Task A, also known as HGFrac, examines the fracturing processes that may occur in the Callovo-Oxfordian claystone (COx) in the context of the high-level (HLW) and intermediate-level long-lived (ILW-LL) radioactive waste repository in France. Understanding these processes and improving numerical models to reproduce them will aid in the design, optimization, and safety of the repository. Heat and gas fracturing are studied in two independent subtasks following a stepwise approach: laboratory tests/benchmark exercises, in-situ experiment, and finally, an application case. The in-situ heater experiment aimed to thermally induce a hydraulic fracture; temperature and pore pressure were monitored to detect any evidence of fracturing. The in-situ gas injection experiment aimed to study the effect of the stress orientation and gas injection kinetics on the gas fracturing process. The occurrence of fracturing was monitored by gas pressure measured in the injection interval. In both experiments, the excavation-induced fracture network around the heater/injection boreholes played an important role in the reduction of the compressive stress state, leading to both a tensile and shear failure response of the COx. During the first two years of the project, the research teams working on each task developed and/or proposed numerical approaches for reproducing the occurrence of fracturing in the in-situ experiments. The failure criteria were defined by reproducing the measurements from laboratory extension tests for the heat fracturing subtask. In the gas fracturing subtask, their approaches were used for simulating several benchmark exercises, and an inter-comparison between models was carried out. In both tasks, the developed approaches were compared with a simplified approach considering poro-elasticity for the mechanical behaviour of the COx. Most of the developed approaches are based on a continuous medium that takes into account variations in hydraulic properties due to mechanical degradation, such as plastic deformation or damage. Other approaches implicitly modelled weak planes or embedded discontinuities to reproduce fracture propagation. The potential for fracture initiation was also studied through of a discrete approach. In the second half of the project, the research teams mainly focused on interpretative modelling of two in-situ experiments and a blind prediction exercise to test their respective approaches. The models developed by the research teams were also applied at the repository scale to evaluate fracture initiation in a case study under vi unfavourable conditions, particularly in terms of spacing between High-Level Waste cells. The results showed that the poro-elasticity approach could be an efficient tool for understanding the main processes occurring in the COx. One example is the explicit representation of the excavation-induced fracture network around the boreholes, which yielded acceptable results compared to the measurement data. However, advanced approaches were needed to evaluate the potential increase of the excavation-induced fracture network extend and better understand fracture initiation. The stress analyses carried out by the teams revealed that hydraulic boundary conditions had a strong impact on fracture initiation in the heater experiment. Furthermore, in most cases, the results required higher pore pressure increments to reach fracturing than those measured in the experiment. This implies that the measurements may have been biased by the packer’s capacity to fully isolate the piezometric chambers, leading to lower pressures. On the contrary, there was no agreement on the fracturing mode, as some reported either shear or tensile fracturing, while others reported a combination of the two modes. In the case of gas fracturing, the research teams were limited to the comparison of a single point, which complicated their task. Nonetheless, the numerical results were able to reproduce the measurements and capture processes such as longitudinal gas flow through the excavation-induced fracture network, as suggested by some evidence in the observation piezometric chambers. The numerical models also agreed with the measurements in the sense of higher probability of developing along the injection borehole than radially towards the sound rock. The approaches developed by the research teams showed that they are capable of analysing and reproducing fracture initiation in the COx. However, areas of future work should focus on the fracture propagation and fracture aperture, which were out of the scope of this task. To this end, additional data must be gathered for the parameter characterisation and validation of the numerical models. Nonetheless, various approaches showed promising results as they were able to reproduce fracture development under certain conditions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Design of a High-Pressure Fuel System for Use with Dimethyl Ether

The paper documents the modeling and experimental work on a common rail fuel injection system for Dimethyl Ether, a potential diesel substitute with a low carbon intensity signature. The DME fuel system is deployed on a light duty 2.2L compression ignition engine. The paper describes the injector optimization to shift to higher flows to account for the lower heating value and density of the DME when compared to diesel. The type of the injection system used for the DME application is an advanced rendering of the Common rail noted for a one-piece piston-needle injector construction and a solenoid driven spill valve featuring a pressure balanced poppet. A dedicated high-pressure fuel pump designed to pressurize DME is used. The design results in a fast acting open and close injection event, reduced leakage, with reduced cavitation in the fuel injector volume. Design parameters for system optimization included fill and spill orifices, needle lift, bias spring, and injector hole size. The design model provides good correlation of the instantaneous rates of injection with experiments across a wide range of pressure and injection timings. Proposed performance milestones for the design included similar DME injection duration to the diesel counterpart for same fuel energy injected into the cylinder to retain high engine cycle efficiency. Here, the dedicated DME design provided reduced hydraulic delays of 50%. Tests demonstrated sustained operation at pressures of 1000 bar, with capability to reach 1500bar. Durability tests showed no cavitation-deterioration over a 200-hour test cycle by means of spray imaging and hardware inspection.

De Ojeda, William [WM International Engineering, L↗
DOE OSTI2024

Portable Acceleration of CMS Computing Workflows with Coprocessors as a Service

Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Development of a coupled experimental–computational approach for engineering optimization of spout-fluidized bed particle coating systems

The design of spout-fluidized bed (SFB) coating systems for nuclear particle fuels typically relies on trial-and-error processes, comprising iterative and time-consuming coating deposition experiments and post-deposition characterization. At an engineering scale, this approach to guided SFB system design is inefficient, highlighting the need for streamlined experimental methodologies which can correlate fluidization conditions to downstream coating outcomes. In this study, we combine time-resolved particle image velocimetry (PIV) with CFD–DEM simulations to benchmark hydrodynamic behavior in a 3D spout-fluidized bed. By exploiting easily accessible optical measurements of particle motion at the bed wall and within the spouting region, we obtain quantitative velocity fields that can be directly compared with model predictions of the occluded bed region, without resorting to complex imaging and characterization techniques such as X-ray or magnetic resonance tomography. Experimental benchmarking reveals strong agreement between CFD–DEM and PIV in the spout and annulus regions, while discrepancies near the wall highlight areas for future model development. Here, the proposed integrated experimental–numerical framework will enable a direct connection between measured variables and numerically predicted fluidization performance of dense, surrogate nuclear particle fuel feedstock such that experimental SFB component design can be rapidly evaluated, informing design decisions for nozzle geometry and operating conditions. Future work will extend this framework by correlating quantified fluidization metrics across nozzle geometries and operating conditions with the resulting coating morphology, microstructure, and uniformity. Establishing these correlations will enable predictive links between hydrodynamic performance and coating quality, providing a rational, scalable basis for optimizing SFB design prior to coating deposition.

CFD/DEM↗
DOE OSTI2024

Demonstration of low-mode shape control in indirect-drive double shell implosions at the NIF

Double shell inertial confinement fusion is a concept for achieving robust thermonuclear burn that uses dense metal shells to compress deuterium-tritium (DT) fuel to fusion conditions. Double shell implosions are typically indirectly driven and involve a target that consists of a low-Z ablator, a foam layer, and a high-Z pusher surrounding the DT fuel. The goal of the campaign is to achieve a volumetric burn as radiation losses from the DT fuel are trapped by the opaque high-Z shell. The overall performance of double shell implosions relies on the efficient collisional transfer of kinetic energy between layers. The efficiency of this transfer (and therefore the overall performance of a given implosion) is degraded by the presence of low-mode asymmetries. P2 asymmetries are often observed in spatially resolved 2D radiographs of nominal double shell implosions. This work discusses three such experiments: one with an oblate P2 asymmetry, one with a prolate P2 asymmetry, and one with an approximate spherical symmetry. After performing a shape analysis of the oblate and prolate implosions to quantify asymmetries, these experimental results were compared with the results of hydrodynamic simulations for the two experiments. Differences between the experiment and simulation were then used to design an approximately spherical implosion by altering the incident laser cone fraction. Radiographs from the experiment that implemented the modified cone fraction show evidence of an implosion that is approximately spherical until bang time. This design is intended to serve as a point design for future studies that will seek to optimize various aspects of the double shell target.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

A&L Annual Report: Kapton Strength

Exploding Foil Initiator (EFI) systems function by launching a polymer flyer (often referred to as a slapper) at a high explosive (HE) pellet, which is intended to shock-initiate the HE. Flyer characteristics (e.g., shape, planarity, etc.) are extremely important in this respect, governing their ability to initiate the HE. Polymer models currently used in these systems are largely unvalidated, potentially compromising the integrity of magneto-hydrodynamic (MHD) predictions of EFI function. An improved EFI MHD modelling capability is expected to: (1) expedite optimization of EFI-based initiation system design, (2) enable consideration of EFI-related aging and corresponding lifetime predictions, and (3) potentially minimize the number of costly experiments required to certify EFI designs. To address this knowledge gap, several years ago we began a computational project to develop a higher-fidelity model for Kapton, a Polyimide copolymer most commonly employed as the flyer material in EFI devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Enabling Next Generation Reaction Injection Molding (RIM) for Lightweight Structures

Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this project, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. This optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption. This research has been performed in collaborations with McClarin Composites. The research outcome has been submitted to the Journal of Manufacturing Processes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Simulation-driven design optimization of reaction injection molding (RIM) process for polydicyclopentadiene (pDCPD): Minimizing cycle time, defects, and warpage

Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this study, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. In conclusion, this optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption.

42 ENGINEERING↗
DOE OSTI2025

Conceptual Design of a Water Tank Critical Facility for SPARC

Critical experiments, sometimes referred to zero-power reactors, are crucial tools in developing and validating nuclear physics predictions and thus an indispensable capability to ensure criticality safety during all parts of the nuclear fuel cycle and in reducing uncertainties in reactor physics predictions toward optimizing nuclear energy production. The System Physics Advanced Reactor Facility (SPARC) project was recently initiated to enable large-scale criticality experiments using a horizontal split table machine well suited toward solid core materials systems (fuel, moderator, reflector). The facility selected for this mission was a former pool-type research reactor building and thus also well suited toward a second critical experiment capability able to house full-size light-water reactor (LWR) fuel bundles. A conceptual design study was undertaken to review past water tank critical experiments used for LWR physics experiments and to develop an early engineering design for a new critical assembly tank (CAT). The work described here shows that a relatively simple CAT concept can be constructed and deployed in the SPARC facility to meet the urgent demands for new critical experiments on advanced LWR fuel bundles designs. The SPARC facility layout is conducive to the receipt and upending of LWR fuel bundles using existing containers and equipment from the LWR industry. The facility’s overhead crane can then be used to handle fuel bundles and place them in a vertical storage rack or in the CAT for critical experiments, both of which fit within the building’s “open basement” alongside other equipment planned for SPARC and the horizontal split table. A slightly lower area in the basement can serve as a large drain tank so that fail-safe valves drain the CAT reactor tank for safe shutdown. Neutronic configurations were determined where a 3 × 3 array of fuel bundles can be surrounded by full-length “loose rods” to adjust reactivity so that critical is achieved when the bundles are fully submerged. Viable configurations were determined for both pressurized- and boiling-water-reactor-type fuel bundles. This design concept was used to develop an early planning basis for establishing the CAT capability alongside the otherwise planned SPARC project in order to help streamline the process. Recent presidential executive orders have highlighted the need to achieve power uprates in LWR plants and the CAT capability will be a crucial element of these initiatives. Based on the work described herein, it is recommended that an earnest and timely project begin in order to establish this urgently needed capability.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Two-level overlapping additive Schwarz preconditioner for training scientific machine learning applications

In this work we introduce a novel two-level overlapping additive Schwarz preconditioner for accelerating the training of scientific machine learning applications. The design of the proposed preconditioner is motivated by the nonlinear two-level overlapping additive Schwarz preconditioner. The neural network parameters are decomposed into groups (subdomains) with overlapping regions. In addition, the network’s feed-forward structure is indirectly imposed through a novel subdomain-wise synchronization strategy and a coarse-level training step. Through a series of numerical experiments, which consider physicsinformed neural networks and operator learning approaches, we demonstrate that the proposed two-level preconditioner significantly speeds up the convergence of the standard (LBFGS) optimizer while also yielding more accurate machine learning models. Moreover, the devised preconditioner is designed to take advantage of model-parallel computations, which can further reduce the training time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Active learning path-dependent properties using a cloud-based materials acceleration platform

Solid state materials are central to many modern technologies in which a given material may be exposed to a variety of environments. The material properties often vary with the sequence of environments in an irreversible manner, resulting in a quintessential path-dependency in experimental observables. While sequential learning techniques have been effectively deployed for accelerating learning of state properties of materials, they often use a consistent environment path in all experiments. To elevate such techniques for making optimal decisions in experimental investigations of path-dependent properties, we introduce an iterated expected information gain acquisition function that optimizes over entire experimental trajectories. This approach is implemented within a cloud-based Materials Acceleration Platform architecture utilizing an event-driven stateful broker coupled with remote HELAO (Hierarchical Experimental Laboratory Automation and Orchestration) instances and an AI science manager. The platform's efficacy was demonstrated through a case study optimizing multi-step spectro-electrochemical experiments to identify optically stable potential windows in (Co–Ni–Sb)O z metal oxides. The system successfully integrated AI-driven experiment design, remote laboratory automation, and cloud-based data infrastructure, validating the platform's capability for managing complex, adaptive, path-dependent workflows in materials discovery.

Guevarra, Dan [California Institute of Technology ↗
DOE OSTI2025

Static characterization of a highly optimized streak tube design incorporating a steering slot anode and an aberration-corrected Einzel lens

The BHx streak tube, under development at the Laboratory for Laser Energetics, incorporates a series of novel electron-optics elements to enable high fidelity measurements for high-energy-density physics experiments. The system is engineered to support a 25-mm active photocathode region compatible with sub-picosecond temporal resolution and with 70% internal photoelectron throughput. It exhibits negligible geometric distortion on a flat output screen, making it well suited for variety of measurements, such as ultrafast x-ray spectroscopy. Here, this paper presents characterization data from a prototype unit tested with an ultraviolet laser in a static deflection (non-swept) mode and shows good agreement with the predictions from numerical modeling, including focusing performance and geometric distortion measurements. Key design elements have been demonstrated and de-risked, laying the foundation for dynamic deflection testing. The anticipated improvements in data fidelity are expected to impact the fields as diverse as inertial confinement fusion, laboratory astrophysics, and materials science.

High energy density physics↗
DOE OSTI2025

Rapid Bayesian High Entropy Alloy Designs Fabricated via Wire Arc Additive Manufacturing

Purpose: This project seeks to demonstrate a new high-throughput (rapid) alloy design technique applied to creating new high entropy alloys (HEAs) for extreme environments. High entropy alloys shift the design paradigm from being focused on a single principal element (e.g. nickel-based alloys) to target alloys that include high atomic fractions (X >10%) of multiple elements. These HEA materials can exhibit sluggish diffusion and enhanced corrosion resistance, ideal for potential applications in advanced ultra supercritical (A-USC) steam cycles for power generation. Scope: The addition of multiple elements in high atomic fractions creates an enormous design space that cannot easily be investigated by traditional material design strategies such as designed of experiments (DOE). This project utilizes a Bayesian machine learning algorithm that has been modified to work with calculation of phase diagrams (CALPHAD) software. This Bayesian algorithm reduces manual inputs and increase the likelihood of achieving an optimal solution. Compositional inputs to this algorithm will be assessed using existing material property models for high temperature strength and corrosion resistance. The target for alloy performance will be a 15% (~100 ⁰C) increase in allowable service temperature beyond heat-resistant stainless steels while maintaining or improving alloy cost and corrosion resistance. Haynes 230 was selected as a baseline, which is 57 wt% Ni with 22 wt% Cr 14 wt% W, and 2 wt% Mo as solid solution strengtheners. In addition to rapid design via Bayesian machine learning, the alloys were rapidly fabricated using a multi-wire arc additive manufacturing (mWAAM) technique which allows for precise control of alloy composition and assessing of alloy design “windows” to study composition effects. Build speeds for wire-arc additive processes are among the highest for additive technologies enabling rapid and reliable sample fabrication when compared to conventional methods such as arc button melting. The mWAAM samples will be rapidly characterized via instrumented indentation for room temperature modulus and strength and for elevated temperature strength via hot hardness tests. After being screened with hardness testing, potential alloys will be further evaluated with conventional microscopy techniques including scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to assess agreement with modeling results. The most promising compositions will also be evaluated by printing full sized tensile specimens for mechanical behavior tests at elevated temperatures. Results: Bayesian machine learning of a single performance function was initially used to optimize five performance metrics: 1) single phase stability, 2) yield strength, 3) creep resistance (low diffusion coefficient), 4) freezing range (weldability), and 5) material cost. The single performance function was suboptimal as assumptions had to be made about the results while formulating the optimization. A goal-oriented Bayesian optimization strategy (Hanaoka, 2021) was implemented with CALPHAD for use with the five metrics above. This multi-objective Bayesian optimization (MOBO) enabled the design of NiCrCoFe alloys with V and W additions. A base composition of NiCoCr was selected as Ni provides a stable FCC matrix, Cr aids corrosion/oxidation resistance, and Co is a solid-solutions strengthener that also improves creep by increasing the activation energy. Fe helps reduce diffusion coefficients and cost. Finally, V and W were selected for their reasonable solubility and high atomic misfit to aid in solid solution strengthening. Cracking of the mWAAM specimens was an early issue, and the Easton solidification cracking model (Easton et al., 2014a) was selected for addition to the MOBO function. High performing alloys fabricated by mWAAM included Ni 28 Cr 25 Co 26 Fe 15 V 8 and Ni 62 Cr 18 Co 1 Fe 3 W 15 . It was observed that even after adapting the mWAAM process for W, the W did not fully dissolve. To fully evaluate the Ni 62 Cr 18 Co 1 Fe 3 W 15 composition, a cored wire (80-20 NiCr sheath/powder core) was manufactured and printed via WAAM, and HIP’ing was utilized to homogenize and densify the printed alloy. The V and W alloys produced met metrics 1 (solid solution), 4 (solidification cracking), and 5 (cost). However, an unmodeled mechanism of thermal stress cracking was identified in the WAAM produced materials, perhaps exacerbated by the lack of grain boundary strengthening elements (B, C). Conclusions & Recommendations: A high-throughput (rapid) alloy design technique was applied to designing and manufacturing new high entropy alloys (HEAs) for extreme environments utilizing MOBO and mWAAM. The developed process was rapid and effective in addressing the mechanisms included in the model. The lack of grain boundary strengthening element additions (e.g., B, C) was a simplification that likely produced thermal stress cracking that turned into a large part of the investigation. Additions on the order of 0.005 wt% B and 0.05 wt% C likely would have minimized thermal stress grain boundary cracking. Overall, the high throughput design strategy is promising for rapid design of metrics-driven alloys for advanced ultra supercritical (A-USC) steam cycles for power generation. The MOBO and mWAAM process could be commercialized to accelerate metrics-driven alloy design. In addition, the cored-wire process utilized for scale-up is a promising high-volume process for WAAM alloy development and scale-up.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Metalloproteins in an Era of Modern Crystallography and Why the Beamline Matters

The Structural Molecular Biology (SMB) macromolecular crystallography (MC) group at the Stanford Synchrotron Radiation Lightsource (SSRL) have developed state-of-the-art capabilities tailored for metalloenzyme structural analysis. Metalloproteins sit at the center of biology’s most audacious chemistry. From multi-electron redox catalysis to radical rearrangements and light-driven transformations, metal sites give proteins access to reaction landscapes that would otherwise be inaccessible under ambient conditions. Yet their study presents a fundamental paradox for MC studies: the very X-rays we use to reveal atomic structure can alter the electronic states we seek to understand. As the field moves beyond static snapshots toward mechanistic insight, success increasingly depends on our ability to maintain metal centers in their native state throughout the experiment. The SSRL SMB-MC beamlines integrate a suite of capabilities specifically designed to address these challenges. By combining in situ spectroscopic verification, intelligent dose management, controlled reaction initiation, optimized anomalous diffraction, and real-time crystallographic diffraction analysis, these tools enable researchers to interrogate metalloproteins with unprecedented rigor. This article explores how these complementary approaches are reshaping our ability to capture metalloprotein chemistry, and what this means for mechanistic studies at synchrotron beamlines.

Maggiolo, Ailiena O. [SLAC National Accelerator La↗
DOE OSTI2025

NuFast-LBL

NuFast is designed to calculate all nine neutrino oscillation probabilities in matter for long-baseline accelerator (e.g. NOvA, T2K, DUNE, HK) and reactor experiments (e.g. JUNO) very quickly, using the algorithms optimized for realistic oscillation scenarios. NuFast is provided in Fortran, C++, and Python, although no particular guarantees are made that the Python code is "fast".

Denton, PeterB. [Brookhaven National Laboratory (B↗
DOE OSTI2025

TEX-Chlorine Assemblies: Highly Enriched Uranium Plates with Sodium Chloride Absorbers Using Polyethylene Moderator and Polyethylene Reflector

This evaluation documents highly enriched uranium (HEU) experimental critical configurations with polyethylene moderators and sodium chloride absorbers conducted as part of the United States Nuclear Criticality Safety Program’s Thermal/Epithermal eXperiments (TEX) program. HEU-MET-MIXED-021 provides the benchmark evaluation of five TEX experiments designed to establish baseline configurations with HEU Jemima plates moderated by high density polyethylene (HDPE). The TEX-HEU experiments were designed to cover five different fission energy regimes by varying the thickness of the interstitial HDPE moderator, with varying fractions of thermal, intermediate, and fast fissions, and to be easily modified to accommodate test materials of interest. HEU-MET-INTER-013 documents the first TEX-HEU variation, incorporating hafnium in seven different experimental configurations. This evaluation covers an additional variant that incorporates absorber plates of compacted high-purity sodium chloride salt. These experiments were motivated by a criticality safety need for validation data for uranium purification by means of electrorefining with chloride salts, especially thermal and intermediate energy configurations resulting from moderator upset conditions, and their design was optimized by matching sensitivity profiles from application cases. All three experimental configurations are judged to be acceptable as benchmark cases. The main parameter varied between the configurations is the thickness of the polyethylene moderators and the sodium chloride absorbers between the HEU plates. Varying the thickness of the polyethylene tunes the neutron energy spectrum between majority thermal (Case 1 and 2) and intermediate (Case 3). The fission fractions, presented in Table 1, are determined calculationally. Case 3 is cross listed as HEU-MET-INTER-014.

42 ENGINEERING↗
DOE OSTI2025

Design Overview of a High-Pressure Helium Flow Visualization Apparatus for Blanket Cooling Studies

Cooling of the fusion blanket first wall remains a significant challenge given the adverse conditions of heat and particle flux encountered near the plasma. Helium emerges as an attractive cooling candidate because of its chemical and neutronic inertness and separability from hydrogenic species (e.g. tritium). Because of the low thermal mass of helium, optimization of these coolant channels is warranted to provide high heat transfer performance at low pumping costs. Increasingly, computational fluid dynamics (CFD) simulations are employed to model and optimize these flow channels, and accompanying experimental data are needed to validate the predictions of these models. To provide the aforementioned experimental data, a high-pressure helium flow visualization upgrade has been designed for the Helium Flow Loop Experiment facility. This apparatus was built to American Society of Mechanical Engineers boiler and pressure vessel standards to withstand operating pressure of 4 MPa and mated to high-pressure glass windows. Seedless flow visualization is performed via high-speed background oriented schlieren (BOS), with image correlation used for time-resolved two-dimensional velocimetry at frequencies in excess of 60 kHz. Rectangular flow channel test articles are additively manufactured via laser powder bed fusion and installed into this visualization apparatus, with one-sided heating supplied by resistive heaters. In conclusion, the chosen test geometries were informed by prior CFD simulations, and the helium flow structures observed via BOS (detachment, recirculation, etc.) will be used for the validation of these accompanying models, in support of the design and optimization of blanket cooling channel configurations.

Helium flow↗