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DOE OSTI2026

Understanding failure in austenitic steels: Key considerations for molten salt storage in CSP applications

Owing to their excellent properties, austenitic stainless steels are extensively used in boilers, furnaces, molten salt tanks, and other applications that are subjected to extreme mechanical loads and high-temperature conditions. Their high corrosion and creep resistance make them suitable for high-temperature operating environments. Additionally, good fatigue resistance and favorable mechanical and visual properties are essential. However, the premature failure of several components at elevated temperatures has been previously reported. Although the failure analysis of components in service is complex, processes such as cold work and welding have been identified as contributing factors to the performance degradation of these steels. This study aims to analyze the various documented failure modes and mechanisms in austenitic steels, including creep, cracking, stress relaxation cracking, and fatigue, to better understand the multi-objective design requirements for these alloys as structural materials for high-temperature molten salt tanks in Concentrating Solar Power (CSP) plants. Stabilized austenitic grades, such as AISI 347H, demonstrate superior resistance to creep and corrosion-related degradation when compared to non-stabilized grades like AISI 316L at temperatures relevant to concentrated solar power (CSP) applications. In contrast, nickel-based alloys offer enhanced corrosion resistance, albeit at a higher cost. This review underscores that creep, stress relaxation cracking, and thermo-mechanical fatigue are the predominant long-term failure risks in CSP hot tanks.

14 SOLAR ENERGY↗

DOE OSTI2026

Methods development towards automated, physics-informed, quantitative quality control of TRISO-SiC

Tristructural-isotropic (TRISO) fuel particles have been developed as a high-performance fuel for use in high-temperature gas-cooled reactor (HTGR) systems due to their high efficiency and stability under both normal and off-normal conditions. Broader deployment of this technology in advanced nuclear applications may benefit from quantitative quality assurance and quality control (QA/QC) methods that directly link TRISO properties to downstream performance. A key TRISO property is the SiC layer microstructure, which influences fission product retention during irradiation. However, existing QA/QC for the TRISO-SiC microstructure comprises only a qualitative visual inspection; therefore, there is a clear opportunity for the development of quantitative methods for TRISO QA/QC. Here, to this end, previous work has demonstrated an image processing approach to grain boundary (GB) identification and subsequent extraction of microstructural metrics; however, extensive twinning within the SiC layer complicates such analyses because twin GBs significantly influence microstructural metrics but are not expected to contribute to fission product transport. This study presents the initial development, training, and testing of an ML-based image segmentation algorithm designed to identify and remove twin GBs from standard backscattered electron micrographs, providing an industrially applicable, quantitative, and physically meaningful QA/QC approach for the TRISO-SiC microstructure. Although pixel-wise performance metrics for the twin predictions are low, the change in grain area and the number of GB pixels after twin removal predicted by the ML workflow are within 1% of the true values calculated using crystallographic data. This suggests that the model is well capable of predicting overall twin boundary structures and grain morphology, and continued advancement of this approach could enable automated, scalable, and physics-informed QA/QC for TRISO-SiC microstructures, supporting the reliable qualification of coated particle fuels for next-generation reactor systems.

Computer vision↗

DOE OSTI2025

A product data network to enable faster, easier, and better planning of building envelopes

The building envelopes contributes significantly to the energy-efficiency of the building. Building performance simulation has made it possible to compare façade technologies regarding energy demand, daylighting, thermal and visual comfort in detail. Planners, such as architects and engineers, need experience to find product data with the right quality and level of detail, and to process the data to fit the calculation and the application. In the available time, planners can compare only a limited number of products, which means that better solutions could go unnoticed. This paper presents a new concept for making product data easily accessible for building façade planning. The concept consists of a network of databases for the efficient exchange and use of optical and calorimetric data of glazing units, shading devices, and combinations of both. The paper presents the research questions, an analysis of the current challenges, six design goals for the product data network and its implementation together with a discussion. Many product data sources can be connected to many planning software applications via the specified application programming interface. When planning software connects to the product data network, the planning of building envelopes can be much faster because planners do not need to spend so much time to search and process product data manually. The planning of building envelopes can also become much easier, especially for planners with limited experience. They do not need to understand all the details about which data fits which calculation if the software company implements this. The planning of building envelopes can become much more reliable when software companies validate their use of the product data network, because the current manual process is prone to errors. The planning of building envelopes can also improve because more products can be compared in the available time, allowing better solutions to be found.

Maurer, Christoph↗

DOE OSTI2024

Accelerating Multivariate Functional Approximation Computation with Domain Decomposition Techniques⋆

Modeling large datasets through Multivariate Functional Approximations (MFA) provide an elegant way to handle many visualization and scientific analysis workflows. The process necessitates scalable data partitioning methods to compute MFA representations efficiently without compromising the accuracy or continuity of the reconstructed solution. We propose a domain -decomposed method for computing the MFA with B -spline bases, which reduces the total work per task and uses a restricted Additive Schwarz (RAS) method to converge the control point data degrees -of -freedom along subdomain boundaries. We provide an in-depth analysis of the parallel approach with domain decomposition solvers, aiming to minimize local subdomain error residuals and recover high -order continuity at subdomain interfaces with appropriate choices of knot overlaps. The communication cost, determined by the overlap regions in the RAS implementation, is optimized to recover the numerical error profile of the single subdomain case. Our proposed method stands in contrast to previous methods, which typically only recover either C 0 or at best C 1 continuity for arbitrary B -spline degree expansions, or those that require post -processing to blend discontinuities in the reconstructed data. We demonstrate the effectiveness of our approach using analytical and real -world datasets in 1D, 2D, and 3D through both strong and weak scaling studies. The performance results indicate that the overall cost of computing the approximation is directly proportional to the underlying nearest -neighbor communication implementation, and is only weakly dependent on the overlap region size that determines the size of the messages. This finding underscores the efficiency and scalability of our proposed method, making it a promising solution for handling large datasets in scientific workflows.

additive Schwarz solvers↗

DOE OSTI2024

In-situ electrochemical optical techniques in the investigation of lithium interfacial phenomena with a liquid and a solid-state electrolyte

An in-situ electrochemical optical diagnosis is the key to the investigation of electrode interface during a redox reaction. Because the morphology changes particularly, dendrite formation, dendrite shapes, solid electrolyte interface formation and gas generation can be revealed visually. The challenge of ensuring uniform current density on a flat Li anode in a liquid electrolyte was addressed and uniform Li plating was demonstrated. The dendrite shape change under different reduction current density was discussed. Here the Li dendrite shape change and the performance of Li anodes with a surface lamination of graphite and red phosphate were used as examples to demonstrate the capability of the in-situ optical cell. An in-situ electrochemical optical cell used in the investigation of the increasingly popular solid-state Li batteries has its own challenges. Due to the untransparent nature of a solid-state electrolyte, an optical investigation on a solid-state electrolyte Li battery needs to be done by exposing the cross-section of the cell. In addition, it is very difficult to assemble an optical cell with a brittle and fragile solid-state electrolyte in a glove box. A set of formation and transfer dies, and an optical cell were introduced. The Li dendrite growth at the interface can be observed in a solid-state Li cell.

25 ENERGY STORAGE↗

DOE OSTI2024

Impact of supercritical carbon dioxide on the frictional strength of and the transport through thin cracks in shale

Understanding the mechanical and transport behavior of thin (i.e. small aperture) cracks slipping under supercritical carbon dioxide (sc-CO 2 ) conditions is essential to evaluate the integrity of sealing formations with buoyant sc-CO 2 below and the success of waterless fracturing. The two major items of interest in this work are frictional strength and permeability change of the crack. We used a triaxial cell that permits in situ visualization to conduct and monitor slippage along the faces of narrow cracks subjected to triaxial stresses. Such cracks are analogs to small geological faults. We tested carbonate-rich, 1-inch diameter Wolfcamp shale samples that are saw cut 30° to vertical to create a thin crack. Friction coefficients ranged from about 0.6 to 0.8 consistent with expectations for brittle rocks. The sc-CO 2 generally did not alter friction coefficient over the time scale of experiments. From a transport perspective, saturating cracks with sc-CO 2 substantially decreased permeability of the crack by 26%–52%, while slip resulted in a variety of permeability responses. Overall, the combined impact of sc-CO 2 saturation and slip reduced fault permeability for all tests. Our observations support the notion that the sealing capacity of some caprocks improves when saturated with sc-CO 2 and that some slip of small fractures is not necessarily detrimental to caprock integrity.

58 GEOSCIENCES↗

DOE OSTI2025

Experimental investigation of the dependence of void nucleation and growth on initial microstructure in high-purity titanium under tension

An experimental investigation of failure mechanisms in relation to the initial microstructure in high-purity titanium samples is presented. The initial microstructure of the specimens was measured in 3D using diffraction-contrast tomography (DCT). Ex-situ X-ray computed tomography (XCT) was used to visualize voids in specimens at various levels of deformation attained by interrupted tensile testing. Electron backscatter diffraction (EBSD) mapping was used to characterize the deformed microstructures per specimen. The investigation showed that the location of failures was unrelated to the formation of the first voids, but rather the nucleation and growth of cracks were from heavily deformed surface regions. The areas surrounding the failure-causing cracks had the highest propensity for void development of any area in the specimen. This facilitated crack propagation through the specimen via “linking up”. The failure of the specimens by microvoid coalescence was bolstered by “dimpled” fracture surfaces. Paint composed of gallium embedded in rubber was used to track the displacement of points along the loading direction of the specimens, to relate the location of failure to the material's initial microstructure. However, the correlation proved difficult, due to complex microstructural evolution involving voids, grain fragmentations, and profuse twinning. Nevertheless, it was shown that necking occurred near the largest grain in the gauge section of the specimens. This is likely caused by the decrease in strength of larger grains, causing strain to concentrate in their vicinity. Here, a comprehensive picture of the failure processes in high-purity titanium under axial loading is presented and discussed in the paper.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Atomic-scale investigations of Ti 3 C 2 T x MXene surfaces

The family of two-dimensional (2D) carbides and/or nitrides, also known as MXenes, has generated great excitement within the scientific community and has been proposed for a wide variety of applications since its discovery. Despite this attention, there have been only limited studies of the atomically resolved local electronic and physical structure of MXene surfaces strongly affecting the physicochemical properties of these materials. Here, in this study, we report local structural, spectroscopic, and chemical investigations of the surfaces of Ti 3 C 2 T x flakes using scanning tunneling microscopy and spectroscopy, closely coupled to theoretical studies. Terminal groups are visualized and characterized, along with surface TiO 2 clusters formed upon exposure to air. Fundamental insight into the local electronic and chemical properties associated with different terminal groups on MXenes and their oxidation products is presented.

36 MATERIALS SCIENCE↗

DOE OSTI2026

The incommensurate modulation of tetragonal tungsten bronze quantified by high resolution 4D STEM

Many members of the tetragonal tungsten bronze (TTB) family of oxides display an incommensurate periodic lattice distortion, the nature of which has been the subject of some controversy. Here we present a study of this structural modulation in the relaxor ferroelectric Ba 5 SmSn 3 Nb 7 O 30 (BSSN) by quantitative scanning transmission electron microscopy (STEM). Additionally, we characterize the modulation in BSSN by employing a fast, pixelated direct electron detector to perform high resolution phase contrast STEM imaging of the crystalline lattice. By quantitatively analyzing the images, we visualize the atomic structural correlations present in the material on both the cation and anion sublattices. This analysis reveals the incommensurate structure to have an octahedral tilting pattern and cooperative A2 site cation displacements, analogous to an Ama2 commensurate cell. Finally, we show that the modulation is composed of a structural motif with a period of 3 x $d_{1\bar{1}0}$ and modified by discommensurations, likely arise from frustrated octahedral tilting in the odd-valued periodicity.

Differential phase contrast↗

DOE OSTI2024

Dual particle imaging: Applications in security and environmental imaging

Radiation imaging detectors have been applied in a variety of fields for detection, localization and characterization of radioactive sources. In this work, we describe a handheld detection system (H2DPI) that can simultaneously image neutrons and gamma rays, and reconstruct the energy spectra of the incident particles. This system was applied to the detection and characterization of a plutonium metal source in experiments performed at the National Criticality Experiments Research Center, where the 4.5 kg plutonium source was placed approximately 60 cm from the H2DPI. Neutron and gamma-ray images were measured that show good agreement with the known location of the source. Furthermore, the H2DPI was also used to measure the neutron spectrum, which shows the expected shape of a Watt fission spectrum, and the gamma-ray energy spectrum, which shows the energies common to plutonium metal. Finally, we describe the application of the H2DPI in augmented reality, whereby real-time neutron and gamma-ray imaging data can be streamed to the Microsoft HoloLens to allow the user to visualize the source locations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

Unsupervised anomaly detection in MeV ultrafast electron diffraction

MeV ultrafast electron diffraction (MUED) is a pump-probe technique used to study the dynamic structural evolution of materials. An ultrashort laser pulse triggers structural changes, which are then probed by an ultrashort relativistic electron beam. To overcome low signal-to-noise ratios, diffraction patterns are averaged over thousands of shots. However, shot-to-shot instabilities in the electron beam can distort individual patterns, introducing uncertainty. Improving MUED accuracy requires detecting and removing these anomalous patterns from large datasets. In this work, we developed a fully unsupervised methodology for the detection of anomalous diffraction patterns. Using a convolutional autoencoder, we calculate the reconstruction mean squared error of the diffraction patterns. Based on the statistical analysis of this error, we provide the user an estimation of the probability that the pattern is normal, which also allows a posterior visual inspection of the images that are difficult to classify. This method has been trained with only 100 diffraction patterns and tested on 1521 patterns, resulting in a false positive rate between 0.2% and 0.4%, with a training time of 10 s per image and a test time of about 1 s per image. Here, the proposed methodology can also be applied to other diffraction techniques in which large datasets are collected that include faulty images due to instrumental instabilities.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Comparative study between experimental measurements and model predictions of bubble rise velocity in molten LiCl-KCl

This research investigated the shape and rise velocities of gas bubbles (helium, nitrogen, argon, and krypton) in molten LiCl-KCl at 500 °C using a specialized optical visualization apparatus. The apparatus features a custom quartz rectangular prism cell housed in a furnace, enabling the application of the shadowgraph measurement technique. Bubbles with diameters between 0.45 and 3.2 mm were produced via a capillary, and their equivalent diameters and rise velocities were analyzed using high-resolution imaging and centroid tracking algorithms. Important non-dimensional parameters were calculated to characterize behavior. Bubbles with 0.03 < Eo < 1.32, 17 < Re < 718, and Mo order of 10 -11 were generated in the molten LiCl-KCl, revealing that bubbles with diameters less than 1.46 mm remain spherical, whereas those with larger diameters are ellipsoidal. The transition and oscillation onset for bubble shape occurred at larger diameters than those previously observed in air–water systems. Comparative analysis of the gas-molten salt data against existing air–water bubble rise velocity correlations highlighted inaccuracies in predictions, particularly across the different bubble regimes. An existing correlation was calibrated to the molten salt data to improve the bubble velocity predictions. In conclusion, this study contributes essential experimental data for the design and safety evaluation of molten salt reactors and offers insights for the optimization of sparge systems for fission product removal.

Bubble rise velocity↗

DOE OSTI2025

A methodology for decay heat characterization in molten salt reactors

Accurate decay heat prediction in molten salt reactors (MSRs) faces dual challenges: complex operational uncertainties and the need for interpretable models compatible with engineering workflows. This work presents a hybrid machine learning and segmented polynomial methodology that addresses both requirements through three key innovations. First, a modular data architecture encodes MSR-specific operational parameters (power density: 1-100 W cm -3 , humidity: 0-0.1 wt %, air ingress: 0-0.1 mol %) with uncertainty-aware temporal discretization spanning 15 orders of magnitude. Second, region-optimized machine learning models achieve 92.3 % root mean square error (RMSE) reduction over conventional polynomials while maintaining physical interpretability through automated piecewise equation generation. Third, dual front-end interfaces accelerate safety analyses — a Jupyter environment enables researchers to explore 10,000+ parameter combinations via interactive widgets, while a Streamlit web application reduces design iteration cycles through production-grade visualization tools. Operational deployment demonstrates prediction times of only a couple hundred milliseconds for 10 4 years decay profiles, enabling real-time optimization of spent fuel container designs.

42 - ENGINEERING↗

DOE OSTI2026

A call to standardize metrics for monitoring baleen whales near marine construction activities

Effective monitoring is necessary to protect marine mammal species during the construction of offshore infrastructure. The tools for detecting or monitoring marine mammals span traditional (e.g., visual observers, optical cameras), to newer (e.g., passive acoustic monitoring, infrared cameras, tags), and emerging (e.g., satellite imagery, environmental DNA, dimethyl sulfide concentration) technologies. Some are better suited for use during offshore development; however, peer-reviewed literature does not typically evaluate and report on the performance of these various technologies. We define a minimum set of metrics related to efficacy (i.e., confusion matrix, precision and recall, probability of missed mitigation), detection range (i.e., maximum and reliable detection range, spatial resolution), and data delivery (i.e., detection latency, system reliability, temporal resolution) that we recommend are needed to assess the utility of monitoring technologies for this purpose. Following a literature review of relevant studies, we highlight which publications reported these metrics and used multiple technologies to compare relative performance. We also emphasize the benefits of multi-modal approaches and recommend performance assessments through modeling or large-scale collaborative field testing. These metrics will standardize data collection, reporting, and analysis; promote consistent and comparable results; and foster collaboration among developers, regulatory agencies, and scientists. This may lead to the co-development of technology that achieves multiple goals, has greater application, and can answer research questions while collecting data to fulfill permitting requirements. These metrics may also inform decisions on what systems regulatory agencies might consider using and reduce monitoring costs, which is critical to support the marine sector's rapid growth alongside marine mammal conservation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Understanding the interplay between pilot fuel mixing and auto-ignition chemistry in hydrogen-enriched environment

The diesel-piloted dual-fuel compression ignition combustion strategy is well-suited to accelerate the decarbonization of transportation by adopting hydrogen as a renewable energy carrier into the existing internal combustion engine with minimal engine modifications. Despite the simplicity of engine modification, many questions remain unanswered regarding the optimal pilot injection strategy for reliable ignition with minimum pilot fuel consumption. The present study uses a single-cylinder heavy-duty optical engine to explore the phenomenology and underlying mechanisms governing the pilot fuel ignition and the subsequent combustion of a premixed hydrogen-air charge. The engine is operated in a dual-fuel mode with hydrogen premixed into the engine intake charge with a direct pilot injection of n-heptane as a diesel pilot fuel surrogate. Optical diagnostics used to visualize in-cylinder combustion phenomena include high-speed IR imaging of the pilot fuel spray evolution as well as high-speed HCHO* and OH* chemiluminescence as indicators of low-temperature and high-temperature heat release, respectively. Three pilot injection strategies are compared to explore the effects of pilot fuel mass, injection pressure, and injection duration on the probability and repeatability of successful ignition. The thermodynamic and imaging data analysis supported by zero-dimensional chemical kinetics simulations revealed a complex interplay between the physical and chemical processes governing the pilot fuel ignition process in a hydrogen containing charge. Hydrogen strongly inhibits the ignition of pilot fuel mixtures and therefore requires longer injection duration to create zones with sufficiently high pilot fuel concentration for successful ignition. Results show that ignition typically tends to rely on stochastic pockets with high pilot fuel concentration, which results in poor repeatability of combustion and frequent misfiring. In conclusion, this work has improved the understanding on how the unique chemical properties of hydrogen pose a challenge for maximization of hydrogen’s energy share in hydrogen dual-fuel engines and highlights a potential mitigation pathway.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

Flame stabilization in DME spray flames under engine-relevant conditions characterized by OH* chemiluminescence and formaldehyde laser-induced fluorescence

The transient and quasi-steady flame structures of Dimethyl Ether (DME) fuel sprays, produced by a single-hole injector (Spray D), were investigated using Planar Laser-Induced Fluorescence (PLIF) and chemiluminescence imaging in a constant-volume chamber under Engine Combustion Network (ECN) Spray A conditions (900 K ambient temperature, 60 bar ambient pressure, 1500 bar injection pressure, and 22.8 kg/m 3 ambient density). Low-temperature chemical reaction zones were visualized using formaldehyde (CH 2 O) PLIF with 355 nm excitation, while high-temperature flame regions were captured via chemiluminescence imaging of excited-state hydroxyl radicals (OH*). Both transient and quasi-steady flame structures clearly show the transition from CH 2 O to OH*, highlighting the progression from low- to high-temperature combustion, while the position of the flame is displaced for DME compared to reference hydrocarbon n-dodecane. Homogeneous reactor calculations with detailed chemistry and using adiabatic mixing for initial temperature show that CH 2 O peaks are significantly higher for DME at the same equivalence ratio, with a higher heat-release during the cool-flame regime with respect to the fuel heating value. Thus, the cool-flame dynamic as a precursor to high-temperature combustion and flame stabilization exhibit distinct behavior for DME relative to conventional hydrocarbons, and these phenomena are effectively resolved through the soot-free nature of DME and the high-speed, time-resolved diagnostics.

CH2O laser-induced fluorescence↗

DOE OSTI2024

Gamma, electron beam and X-ray irradiation effects on polymers in an advanced bone cement mixer device

The medical device industry has been investigating ways to increase the use of alternatives to cobalt-60 gamma radiation and ethylene-oxide gas sterilization, such as electron beam (E-beam) and X-ray radiation, due to regulatory and market pressures. One impediment to switching to E-beam or X-ray technology for sterilization is the lack of data on the effects of these radiation sources on medical device polymers. To provide such data this work considers irradiation and testing of a common single-use medical bone cement mixing system, the Stryker Advanced Cement Mixer (ACM®), that is composed of seven polymer materials. The ACM® devices considered here were processed to sterilization-relevant doses (15, 25, 50, and 70 kGy) using three radiation technologies: gamma, E-beam, and X-ray. The system and its polymer components were tested for product functionality, as well as mechanical and visual properties to determine how exposure effects may be influenced by radiation technology and dose level. We found that although there were instances of statistically significant differences in effects between the gamma-irradiated products and those irradiated with E-beam and X-ray, those effects were negligible in terms of retained functionality of the product and retained mechanical properties of the polymer components. Overall, results of this study demonstrate that, for of the effects studied, E-beam and X-ray are viable alternatives to cobalt-60 gamma radiation for sterilization of the polymer-based device investigated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Plant-microbial interplay for organic nitrogen mediated by functional specificity of root compartments

The organic form of nitrogen (N) is a critical intermediate in mutualistic and competitive root-microbial interactions, mediated by extracellular enzymes. Visualization of the hotspots of organic N and proteolytic activity might be valuable for revealing root functional specificity in N acquisition and transformation at the level of individual roots and compartments. For the first time, we used time-lapse amino-mapping and zymography to co-localize and map the spatial distribution of amino-N and leucine aminopeptidase (LAP) activity in the soil and different root parts of maize (Zea mays L.). Amino-N distribution was mainly associated with seminal roots and root tips, where it overlapped with LAP activity hotspots. In the lateral roots and bulk soil, however, LAP activity was decoupled from amino-N. Distinct functional traits revealed themselves as the highest amino-N content and LAP activity in seminal root tips and as the largest relative extent of the rhizosphere in lateral root tips. Co-localized amino-N and LAP activities highlighted different nutrient acquisition strategies mediated by root-microbe interactions, depending on the root compartment. Seminal roots and their tips appeared to adopt mutualistic strategies, potentially attracting root-associated microorganisms through releasing oligo- and polypeptides. In contrast, lateral roots, with amino-N detected only at their tips, demonstrated stronger N competition, relying on the enzyme activity of the rhizosphere microbial community for N acquisition. These insights emphasized the role of root functional specialization in shaping plant-microbe interactions, offering pathways to enhance nutrient use efficiency.

Maize (Zea mays L.)↗