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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

3013 Baseline Inner Container Report: Description, Imaging, and Analysis

This report presents consolidated findings from three microscopy studies of baseline Bagless Transfer Containers (BTCs), which are the inner containers used in DOE Standard 3013-compliant plutonium storage packages. The studies were conducted by Los Alamos National Laboratory (LANL), Savannah River National Laboratory (SRNL), and DNV, a subcontractor specializing in corrosion science. The baseline BTCs examined had not been exposed to corrosive environments, serving as control samples for comparison with destructively examined (DE) containers. Additionally, the Background section provides an overview of the BTC design, including manufacturing methods, material properties, and container configurations that may influence corrosion behavior. The primary objective of the LANL and SRNL studies was to establish reference characteristics of BTCs to distinguish manufacturing artifacts from corrosion-induced features observed in DE containers. Both laboratories used advanced microscopy techniques, including Wide Area Microscopy (WAMS), Laser Confocal Microscopy (LCM), Scanning Electron Microscopy (SEM), and Focused Ion Beam (FIB), to reveal that most surface anomalies were shallow and attributable to flow-forming processes, not corrosion. Subsurface impurities, identified as non-metallic inclusions, were also observed. DNV’s investigation focused on characterizing the mechanical and chemical properties of the BTC material to support crack growth modeling. Their findings indicate higher hardness and strength but reduced ductility—consistent with flow-formed 304L stainless steel and a higher-than-expected martensite content, in contrast to manufacturer claims. Ongoing and future studies, including Electron Backscatter Diffraction (EBSD), aim to further understand the microstructural factors influencing crack initiation and propagation. The combined studies provide a crucial baseline for distinguishing corrosion effects in DE containers, contributing to the safe and reliable long-term storage of plutonium-bearing materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

SENTRA: A Modular Computational Graph Framework for Critical Mineral and Materials Supply Chains: Part I: Network Construction Latent-Quantity Estimation, and Temporal Graph Forecasting

Global supply chains for critical minerals and materials are complex, evolving networks of countries, products, production stages, and trade relationships. Existing analytical approaches are limited by fragmented data and static network representations that do not capture the dynamic production dependencies linking raw materials, intermediate products, and final goods across multiple countries. Trade and production statistics provide only a partial view of domestic production, inventories, and material flows, making it difficult to identify indirect sourcing pathways, hidden dependencies, and embedded foreign exposures. This paper introduces the Supply Chain Exposure Network Tracking and Risk Assessment (SENTRA) framework, a modular graph-based computational framework for constructing, analyzing, and forecasting dynamic supply chain networks. As the first paper in a three-part methodological series, it establishes the computational foundation of SENTRA by constructing a temporal attributed multi-relational graph whose nodes represent product–country pairs and whose edges encode observed trade and within-country value-chain relationships. Statistical estimation and constrained optimization recover latent production, final demand, and product input dependency coefficients while enforcing economic accounting constraints. Graph-derived exposure measures quantify direct, transshipment, value-chain, and multi-hop supply chain dependencies independently of the forecasting model. A temporal graph forecasting architecture based on a relational graph neural network then forecasts the evolution of the graph under mass-balance constraints with distribution-free conformal uncertainty quantification. Validation on the global aluminum supply chain shows that the learned graph representations recover economically meaningful supply chain structure, accurately forecast out-of-sample trade relationships, and produce well-calibrated prediction intervals. Subsequent papers apply this computational foundation to exposure assessment, disruption analysis, and scenario-based policy analysis, and extend the framework to multimaterial supply chain modeling and decision support.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Evidence of gas phase nucleation of nanodiamond in microwave plasma assisted chemical vapor deposition

The mechanism of ballas-like nanodiamond formation still remains elusive, and this work attempts to analyze its formation in the framework of activation energy (Ea) of nanodiamond films grown from a H2/CH4 plasma in a 2.45 GHz chemical vapor deposition system. The Ea was calculated from the Arrhenius equation corresponding to the thickness growth rate using substrate temperature (∼1000−1300 K) in all the calculations. While the calculated values matched with the Ea for nanodiamond formation throughout the literature, these values of ∼10 kcal/mol were lower compared to ∼15–25 kcal/mol for standard single crystal diamond (SCD) formation, concluding thus far that the energetics and processes involved were different. Further, the substrate preparation and sample collection method were modified while keeping the growth parameters constant. Unseeded Si substrate was physically separated from the plasma discharge by a molybdenum disk with a pinhole drilled in it. Small quantity of a sample substance was collected on the substrate. The sample was characterized by electron microscopy and Raman spectroscopy, confirming it to be nanodiamond, thus suggesting that nanodiamond self-nucleated in the plasma and flowed to the substrate that acted as a mere collection plate. It is hypothesized then, if nanodiamond nucleates in gas phase, gas temperature has to be used in the Arrhenius analysis. The Ea values for all the nanodiamond films were re-calculated using the simulated gas temperature (∼1500−2000 K) obtained from a simple H2/CH4 plasma model, giving new values within the range characteristic to SCD formation. Based on these findings, a unified growth mechanism for nanodiamond and SCD is proposed, concluding that the rate-limiting reactions for nanodiamond and SCD formation are the same.

Materials Science↗
DOE OSTI2020

Power Prediction of Airborne Wind Energy Systems Using Multivariate Machine Learning

Kites can be used to harvest wind energy at higher altitudes while using only a fraction of the material required for conventional wind turbines. In this work, we present the kite system of Kyushu University and demonstrate how experimental data can be used to train machine learning regression models. The system is designed for 7 kW traction power and comprises an inflatable wing with suspended kite control unit that is either tethered to a fixed ground anchor or to a towing vehicle to produce a controlled relative flow environment. A measurement unit was attached to the kite for data acquisition. To predict the generated tether force, we collected input–output samples from a set of well-designed experimental runs to act as our labeled training data in a supervised machine learning setting. We then identified a set of key input parameters which were found to be consistent with our sensitivity analysis using Pearson input–output correlation metrics. Finally, we designed and tested the accuracy of a neural network, among other multivariate regression models. The quality metrics of our models show great promise in accurately predicting the tether force for new input/feature combinations and potentially guide new designs for optimal power generation.

17 WIND ENERGY↗
DOE OSTI2021

Rapid charging made practical in graphite-based lithium batteries: surface-acoustic wave turbulent electrolyte mixing to overcome diffusion limited charging rates [Final Report]

One of the key limits in rapidly recharging a lithium-ion battery is the depletion of lithium ions within the electrolyte adjacent the anode during charging and long diffusion time to overcome this depletion. It also causes dendrite formation, inefficient use of the lithium, and battery degradation over many charge-discharge cycles. Because the liquid electrolyte remains quiescent and unmixed, this depletion layer’s depth rapidly grows to match the anode-cathode separation distance at even modest charge rates. The solution proposed by PI Prof. James Friend and Co-PI Prof. Ping Liu, both from the University of California, San Diego, is to mix the electrolyte and minimize the Li+ ion concentration gradient during charging. Even in the presence of the separator, the charging rate could then be significantly increased. They propose to accomplish this using surface acoustic wave (SAW)-driven acoustic streaming, a technique employing 10-mW fingernail-sized solid-state devices from the telecommunications industry to drive turbulent mixing to submicron length scales in a manner completely compatible with the typical 20700 and 18650 cells used in electric vehicles. 0.1. Turbulent acoustic streaming mixes the electrolyte during charging—even with separator Our proposed 100-MHz SAW device used to recirculate the electrolyte is compatible with lithium- ion battery electrochemistry, as it is made in our lab of single-crystal lithium niobate. Their solution is straightforward to drive from a DC power source alongside the signal provided during battery charging. The device is only needed during charging and does not consume power dur- ing battery discharge. Uniquely, SAW generates extreme accelerations of over 1 billion meters per second squared in the fluid, driving turbulent mixing from centimeter to submicron length scales, even through the porous separator materials that tend to be used in batteries, all while avoiding interfering with the anode’s solid electrolyte interphase layer that forms during use. By employing novel fluid mechanics, the investigators are proposing a new direction for battery research away from direct use of materials science and electrochemistry. The chemistry agnostic solution may be employed in any battery chemistry that makes use of liquid electrolytes, providing a broader transformative benefit to the battery research community. They are to produce a series of prismatic and 20700-cell sized 2 Ah batteries capable of being charged and discharged at least 500 times without more than 20% loss in battery capacity, and to provide analysis tools useful to the battery research and development community for adopting this approach for other battery chemistries and configurations.

25 ENERGY STORAGE↗
DOE OSTI2024

Development of High Temperature (>700°C) Molten Salt Pump Technology for Generation 3 Solar Power Tower Systems

Bearings are required for long-shafted pumps historically used in concentrating solar thermal power applications. For molten chloride salts, bearings for such service conditions are not commercially available, nor has a design been demonstrated to work. Therefore, a project was sponsored by the Department of Energy’s Solar Energy Technologies Office for the development and demonstration of a submerged bearing for use in chloride salt pumps. This project’s tasks covered the tribological testing of candidate materials and the design, fabrication, testing, and post-test analysis of full-scale salt-compatible bearings. This work expands upon previous work. The effects of potential particulate in the salt were investigated through tribological bench testing. Through 11 tests, the MgO particulate size and concentration in a molten chloride salt were varied, and the effects on friction, wear rate, and wear characteristics were recorded. Novel journal bearings for chloride salt service were designed and fabricated based on these results. The bearings were of a relevant scale (i.e., for a 1.5 in. pump shaft) to demonstrate the technology with respect to further scale-up. The bearings were made of Haynes 244 and Yttria Partially Stabilized Zirconia. A custom bearing test rig, salt tanks, and associated infrastructure (e.g., heaters, tanks, transfer lines, gas flow control) were designed, procured, and installed. A few issues were encountered in the system fabrication process, resulting in delay of the project schedule. The system was successfully fabricated and assembled. Heating, cover gas, and pump motor systems were integrated into the control logic. This progress of the bearing test system represents a significant step forward towards demonstrating this promising technology. Nevertheless, the project ended before testing of the full-scale bearings could be performed.

14 SOLAR ENERGY↗
DOE OSTI2025

Design Report on the MiniFuel Instrumented Test Apparatus for Understanding Radiation Effects

Most nuclear fuels irradiations at Oak Ridge National Laboratory (ORNL) over the past decade have been conducted using MiniFuel—a static capsule design employing subscale fuel specimens to collect separate-effects irradiated fuel performance data. Irradiation conditions for MiniFuel experiments are predicted pre-test using reactor physics, and thermal models are verified post-irradiation via SiC dilatometry and various spectrometry methods. Relevant fuel performance parameters are also observed post-irradiation in a hot cell, thereby providing a single data point for each parameter representing the cumulative effects of the irradiation conditions. Substantially more data can be harvested from a single test and within a shorter duration by instrumenting irradiation vehicles and measuring desired quantities in situ. This report presents the design and analysis of the MiniFuel INstrumented Irradiation Test Apparatus for Understanding Radiation Effects (MINITAURE)—an instrumented test rig based on the separate-effects MiniFuel concept that aims to capture fission gas release (FGR) and thermal conductivity degradation of fuel specimens during irradiation in the High Flux Isotope Reactor (HFIR). MINITAURE will be integrated with the Materials Irradiation Facility (MIF) located in the HFIR building outside the reactor containment. The MIF will act as the instrumentation and control center for the experiment, enabling real-time feedback from in situ sensors and control of irradiation temperatures via a gas delivery system. Two unique capsule designs were developed to capture each phenomenon: the thermal conductivity capsule, which uses a thermopile method to estimate fuel specimen thermal conductivity, and the fission gas release capsule, which will have continuous flowing gas communication to high-purity germanium detectors that are housed in the MIF for monitoring FGR. This report details the reactor physics and heat transfer modeling activities that were used to inform the experiment design and predict capsule performance. It also describes out-of-pile activities conducted to stand up this new capability and verify the measurement techniques. Modeling efforts to date have demonstrated the feasibility of the in situ measurement techniques and supported the development of the MINITAURE assembly configuration. Out-of-pile testing of the thermal conductivity measurement shows promise in capturing relative changes in thermal conductivity. However, significant errors exist in the measured absolute value, posing a need for further refinement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Building a new multiphysics workflow in MOOSE: application to tritium migration, trapping and advection in TMAP8

Fusion devices are anticipated to produce and consume several kilograms of tritium per year. This rare fuel resource is both highly mobile and radioactive, making tracking inventories a priority for operation and safety. The fusion safety program at the Idaho National Laboratory has been developing the Tritium Migration and Analysis Program (TMAP), of which the latest version is a MOOSE-based application. TMAP8 is verified against its predecessors and possesses additional multi-dimensional tritium migration modeling capabilities. As we extend its capabilities towards both whole device (in multiple dimensions) and whole plant (with multiple components) simulations, the syntax of inputs must become compact, descriptive, compatible with quality assurance processes, and as error-proof as achievable. The new Physics system developed MOOSE can set up equations and instantiating them on plant components. The system permits the automatic definition of complex discretization with a consistency between object parameters achieved programmatically. The Physics system can currently instantiate the equations for heat conduction and Navier Stokes weakly compressible flow. In MOOSE-terms, it automates the definition of kernels, boundary conditions, and several core and helper materials and fields. As part of this effort, Physics classes were developed for tritium migration, trapping and advection within either a multi-dimensional Navier Stokes fluid dynamics simulation, or a 1D thermal hydraulics piping system. In this presentation, we will showcase the new syntax, its application to several verification and validation cases which were already studied using the classical TMAP8 syntax, and a demonstration of the new coupling capabilities for the migration of tritium into blanket coolant channels and the subsequent advection into the coolant loop.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Use of computer vision for analysis of image datasets from high temperature plasma experiments

Great strides have been made in improving the quality of x-ray radiographs in high energy density plasma experiments, enabled in part by innovations in engineering and manufacturing of integrated circuits and materials. As a consequence, the radiographs of today are filled with a great deal of detail, but few of these features are extracted in a systematic way. Analysis techniques familiar to plasma physicists tend toward brittle 1D lineout or Fourier transform type analyses. The techniques applied to process our data have not kept pace with improvements in the quality of our data. Fortunately, the field of computer vision has a wealth of tools to offer, which have been widely used in industrial imaging and, more recently, adopted in biological imaging. We demonstrate the application of computer vision techniques to the analysis of x-ray radiographs from high energy density plasma experiments, as well as give a brief tutorial on the computer vision techniques themselves. These tools robustly extract 2D contours of shocks, boundaries of inhomogeneities, and secondary flows, thereby allowing for increased automation of analysis, as well as direct and quantitative comparisons with simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

The Effect of Flow on CO2 Corrosion of Self-Healing Metallic Coatings

Internal corrosion is an issue that affects natural gas pipelines, a significant part of the United States’ energy infrastructure. Over time, this corrosion has worn away longstanding pipelines due to the original construction materials used for the lines and impurities in the gas and liquid streams flowing through them. The main impurities in natural gas are H2O, CO2, H2S, and O2. One of the leading causes of corrosion is the CO2 dissolved in water, giving rise to carbonic acid formation, which can further dissolve the steel pipe. The National Energy Technology Laboratory (NETL) has been studying different solutions to this problem. One potential answer is a self-healing sacrificial metallic coating applied by a novel cold spray technique. This study explored the impact of flow on corrosion with this coating and carbon steel when exposed to a saturated CO2 environment by simulating the pipeline flow profile in a small-scale lab setting. The samples were evaluated using multiple electrochemical techniques that found corrosion rates and were backed up with surface analysis to conclude the behavior of the corrosion mechanisms. The cold spray coating exhibited steel corrosion protection under flow conditions. This study has significantly advanced our understanding of CO2 corrosion, particularly in the context of natural gas pipelines and coating design.

carbon steel↗
DOE OSTI2023

Electron Target Cooling Analyses of the KIPT ADS Using MCNP and Ansys Fluent

This study presents multiphysics analyses of the electron target cooling system of the accelerator-driven system (ADS) of the Kharkiv Institute of Physics and Technology (KIPT) using MCNP and Fluent computer programs. MCNP has been used to transport electrons, gammas, and neutrons, and to calculate the energy deposition in the target materials. The MCNP mesh-tally data have been imported into Fluent by a C subroutine that has been compiled and linked to Fluent as a user-defined function.The KIPT ADS is located in Ukraine and was in operation until February 2022. The Fluent model is based on the computer-aided design files from the manufacturing process of the target assembly. Here, the Fluent results for the reference case match very well the literature results obtained by STAR-CCM+ during the design phase. Other cases that differ from the reference one have been analyzed; in these cases, it is assumed a malfunction of the electron accelerator or of the water cooling system. The target cooling system operates normally for all the analyzed cases except when the inlet water mass flow rate is decreased. The transient analysis showed that the target cooling system can operate for 180 s with full power when the inlet water mass flow rate is decreased down by 75%.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Effect of Solvent Motion on Ion Transport in Electrolytes

We use concentrated solution theory to derive an equation governing solvent velocity in a binary electrolyte when a current passes through it. This equation, in combination with the material balance equation, enables the prediction of electrolyte concentration profiles and species velocities as a function of space and time. This framework is used to predict ion velocities in Li-Li symmetric cells containing a mixture of lithium bis(trifluoromethanesulfonyl)imide and poly(ethylene oxide) (LiTFSI/PEO), for which the cation transference number relative to the solvent velocity, ${t}_{+}^{0},$ can be either positive or negative, depending on salt concentration. Accounting for the solvent motion is increasingly important at higher concentrations. Especially for negative ${t}_{+}^{0},$ if solvent velocity is set to zero, the cation velocity, based on the electrode-electrolyte interface reference frame, is pointed opposite to the current flow. However, when solvent motion is taken into account, the cation velocity, based on the same reference frame, is in the same direction as the current. This analysis demonstrates the importance of accounting for solvent velocity rigorously in seemingly simple systems such as symmetric cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Hypersonic Jets of Detonation Products in the Hydrodynamic Collapse of Macroscopic Voids

Localizing the energetic output from detonation waves has been a long-standing challenge in applied detonation physics. Here, energy localization is achieved via machined millimeter scale voids in pressed samples of PBX 9501, an HMX (1,3,5,7-Tetranitro-1,3,5,7-tetrazocane)-based plastic bonded explosive. A main mechanism of energy localization in these systems, the formation of hydrodynamic jets of dense product gases, is characterized experimentally using a semicylindrical geometry in witness plate impact experiments and streak imaging of the jet propagating into the air. The distance at which the jet is optimally developed is identified and the supersonic flow structure in the vicinity of this feature is explored using hydrocode simulations. This analysis found that most of the kinetic energy of the hydrodynamic jet arises from pressure gradients induced by geometrically mediated squeeze flow lateral to the direction of detonation propagation. This work presents a new development in the control of energetic output from detonation waves and applications to detonation wave shaping are discussed.

42 ENGINEERING↗
DOE OSTI2021

Impact of exposure to brine/CO 2 on the mechanical and transport properties of the Mt. Simon Sandstone

When sandstone rocks are exposed to CO 2 -saturated brine, their transport and mechanical properties can, potentially, change due to chemical reactions as a result of such exposure. This paper investigates changes in the flow-through characteristics, porosity, and the mechanical properties of Mt. Simon Sandstone samples caused by such exposure to brine/CO 2 . A core, extracted from the Mt. Simon formation, was first characterized for its porosity and relevant transport properties, and it was then aged for over 500 hr in CO 2 -saturated brine at formation-relevant pressure, temperature, and confining stress conditions. The deformation of the sample was measured in situ during aging via strain gauges attached to the core's surface. Following the aging experiment, the sample's porosity and transport properties were again analyzed. Our experiments show that both the porosity and permeability of the Mt. Simon sandstone sample increase due to exposure to brine/CO 2 , with the impact on permeability being more significant. The deformation measurements employing strain gauges indicate a weakening of the core material. Analysis of the composition of the brine at the conclusion of the testing reveals changes, specifically, an increase in the concentration of several of the cations. These changes are indicative of mineral/clay dissolution, consistent with the porosity, permeability, and strain gauge measurements.

58 GEOSCIENCES↗
DOE OSTI2022

Topology optimization of an airfoil fin microchannel heat exchanger using artificial intelligence

High-performance microchannel heat exchangers are needed to supply heat for power conversion for nuclear microreactors. An airfoil fin microchannel design, constructed of Alloy 617 with helium as the working fluid, is analyzed and optimized using a design of experiments with artificial intelligence techniques. The use of airfoil fins offers the potential to reduce pressure drop across the heat exchanger, as compared to other types of channel configurations. A framework for topology optimization of airfoil fin printed circuit heat exchangers (PCHEs) has been developed that can be readily extended to different fin sizes and shapes, as well as different inlet and operating conditions, materials of construction, and working fluids. An optimization procedure is developed that employs computational fluid dynamics for a set of design points identified using Latin hypercube sampling. Computational fluid dynamics is used to analyze a simplified two-channel configuration where five design parameters are varied – inlet angle, fin scale, extent of staggering, transverse and longitudinal pitches. Two methods (a 5D polynomial and a regression neural network) are compared for generating surrogate models and the resulting response surface approximation is input to a genetic algorithm that is used to identify a set of optimal parameters. The optimal geometries are found across six channel Reynolds numbers ranging from 1000 to 5000, since inlet conditions affect flow through the heat exchanger. Additionally, a set of optimal designs that maximizes heat transfer and minimizes pressure drop is identified, and a thermal stress analysis is performed on the optimal design. Correlations for the Nusselt number and Darcy friction factor are developed that can be useful for thermal hydraulic analyses using system codes. Thermal stresses are analyzed and a brief discussion of the status of code cases of PCHEs for nuclear applications is given. Testing and thermomechanical modeling is needed to facilitate future code compliance of PCHEs for high pressure and high temperature applications.

42 ENGINEERING↗
DOE OSTI2025

CASM Monte Carlo: Calculations of the thermodynamic and kinetic properties of complex multicomponent crystals

Monte Carlo techniques play a central role in statistical mechanics approaches that connect macroscopic thermodynamic and kinetic properties to the electronic structure of a material. This paper describes the implementation of Monte Carlo techniques for the study of multicomponent crystalline materials within the Clusters Approach to Statistical Mechanics (CASM) software suite, and demonstrates their use in model systems to calculate free energies and kinetic coefficients, study phase transitions, and construct phase diagrams from first principles. Many crystal structures are complex, with multiple sublattices occupied by differing sets of chemical species, along with the presence of vacancies or interstitial species. This imposes constraints on concentration variables, the form of thermodynamic potentials, and the values of kinetic transport coefficients. The framework used by CASM to formulate thermodynamic potentials and kinetic transport coefficients accounting for arbitrarily complex crystal structures is presented and demonstrated with examples of increasing complexity. Additionally, an overview of the capabilities of the CASM software specific to Monte Carlo methods is given, and a new CASM software package is introduced, casm-flow, which helps automate the setup, submission, management, and analysis of Monte Carlo simulations.

Cluster expansion↗
DOE OSTI2026

Uncertainty-Aware Machine Learning for Small-Angle X-ray Scattering Analysis in Autonomous Experimentation

Small-angle X-ray scattering (SAXS) is a powerful high-throughput characterization tool for probing nanoscale structure in native sample environments, providing real-time morphological information such as nanoparticle size and shape during synthesis. However, automated SAXS data analysis for extracting meaningful structural parameters is non-trivial and remains a bottleneck in closed-loop experimentation towards autonomous materials discovery, which demands fast, reliable, and uncertainty-aware data analysis. Here, we develop a machine-learning approach for automated SAXS analysis tailored to closed-loop nanoparticle synthesis. A Random Forest (RF) regression model is trained on 100,000 synthetic SAXS curves generated from polydisperse spherical nanoparticles with realistic background contributions. Using normalized one-dimensional SAXS intensity profiles as input, the RF model directly predicts nanoparticle radius, size polydispersity, and background parameters, while the ensemble standard deviation across trees provides built-in uncertainty quantification (UQ). On synthetic data, we show that combining fit-quality metrics (R 2 , MAE) with thresholds on prediction uncertainty reliably identifies accurate parameter estimates without access to ground truth. We then apply the trained model to 365 experimental SAXS profiles of citrate-reduced gold nanoparticles synthesized using an automated droplet-flow microreactor with in situ SAXS at a synchrotron beamline, classifying the results into high- and low-confidence subsets based on UQ metrics. Finally, we integrate RF-based SAXS analysis into a simulated closed-loop optimization campaign using Gaussian process Bayesian optimization to minimize nanoparticle polydispersity, benchmarking against conventional automated Levenberg–Marquardt fitting. The RF-guided campaign exhibits substantially faster convergence and lower relative opportunity cost (∼0.07 vs ∼0.3), demonstrating that uncertainty-aware machine-learning SAXS analysis significantly enhances the efficiency and robustness of autonomous nanomaterials synthesis workflows.

Bayesian optimization↗
DOE OSTI2026

Refining a Novel Process Monitoring Method to Safeguard Continuously Cycling Designs Using Isotopic Ratios

In advanced reactor (AR) designs, a common feature is continuous chemical processing and circulation of the nuclear material. This work bridges a significant measurement gap in safeguarding reactors with circulating fuel or continuous refueling by leveraging and building on the isotope ratio method first developed by our team under an FY21 Advanced Reactors International Safeguards Engagement (ARISE) project (Uribe et al. 2021). In circulating fuel designs, the radioisotope inventory changes from traditional effects (e.g., radioactive decay, fission) but also includes material transport due to pressure and temperature gradients. Such designs may also require regular or continuous additions or removals during operation, which significantly increases the rate of inventory change compared to traditional pressurized water reactor (PWR)s. Thus, directly tracking the nuclear inventory is ineffective since the isotopes are continuously added and removed. The isotope ratio method instead focuses on detecting changes to the input and output flows of radioisotopes. Previous work showed that for well-chosen pairs of isotopes, the isotopic ratio provides a sensitive and lasting indicator of deviation from normal conditions (e.g., startup, shutdown, diversion). The isotope ratio method is a process monitoring method with potential for application in for forward-looking approaches to International Atomic Energy Agency (IAEA) safeguards. The original process monitoring method was developed for a specific case—the decay tank of a thorium-fueled molten salt breeder reactor. In this expanded work, we explored other types of reactors and processes with nonstationary (e.g., flowing) nuclear material, which are difficult to safeguard with traditional methods because of the transient nature of the systems. The goal of the present work is to generalize the isotope ratio method for use in processes with continuously flowing nuclear material. All continuous processes have an average time for isotopes to be replaced in the system. The isotope ratio method works by choosing radioisotopes with half-lives both above and below the processing time. The present work seeks to explore which isotopes are suitable for the method by simulating the nuclear inventory, radioisotope emissions, and detector responses for several classes of advanced reactors. While the method can in principle be applied to other processes (e.g., enrichment or reprocessing facilities), the present work limits scope to ARs with continuously flowing fuel. Section 2 details the mathematics supporting the isotope ratio method, and Section 3 introduces the representative ARs selected for this work. Section 4 discusses how each reactor was analyzed, and Section 5 showcases the results for each representative reactor. Finally, Section 6 provides concluding remarks and suggests pathways for further analysis.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗