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DOE OSTI2025

The effect of grain boundary yield and disconnections on grain boundary fracture strength

During high-temperature interfacial strain, e.g., creep or sintering, grain boundaries will sample non-equilibrium states associated with the non-equilibrium disconnections that mediate strain. This work tests the hypothesis that those non-equilibrium states should affect the mechanical properties of the grain boundary. High-temperature bicrystal tensile strain experiments performed on Sc-doped ZrO 2 as a function of strain rate enable the observation of fracture before and after grain boundary yield. Yielded boundaries exhibit a median fracture strength ≈ 50 % lower than those that did not yield. Molecular dynamics simulations performed on boundaries with and without interstitial-type disconnection loops indicate that the presence of those loops reduce the failure stress.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A Database of Stress-Strain Properties Auto-generated from the Scientific Literature using ChemDataExtractor

Abstract There has been an ongoing need for information-rich databases in the mechanical-engineering domain to aid in data-driven materials science. To address the lack of suitable property databases, this study employs the latest version of the chemistry-aware natural-language-processing (NLP) toolkit, ChemDataExtractor, to automatically curate a comprehensive materials database of key stress-strain properties. The database contains information about materials and their cognate properties: ultimate tensile strength, yield strength, fracture strength, Young’s modulus, and ductility values. 720,308 data records were extracted from the scientific literature and organized into machine-readable databases formats. The extracted data have an overall precision, recall and F-score of 82.03%, 92.13% and 86.79%, respectively. The resulting database has been made publicly available, aiming to facilitate data-driven research and accelerate advancements within the mechanical-engineering domain.

Kumar, Pankaj↗

DOE OSTI2025

High Strength and Fracture Resistance of Reduced-Activity W-Ta-Ti-V-Zr High-Entropy Alloy for Fusion Energy Applications

Refractory high-entropy alloys (HEAs) are promising candidates for next-generation nuclear applications, particularly fusion reactors, due to their excellent high-temperature mechanical properties and irradiation resistance. Here, the microstructure and mechanical behavior were investigated for an equimolar WTaTiVZr HEA, designed from a palette of low-activation elements. The as-cast alloy exhibited a dendritic microstructure composed of W-Ta rich dendrites and Zr-Ti-V rich inter-dendritic regions, both possessing a body-centered cubic (BCC) crystal structure. Room temperature bulk compression tests showed ultra-high strength of around 1.6 GPa and plastic strain ~6%, with fracture surfaces showing cleavage facets. The alloy also demonstrated excellent high-temperature strength of ~650 MPa at 500 °C. Scratch-based fracture toughness was ~38 MPa√m for the as-cast WTaTiVZr HEA compared to ~25 MPa√m for commercially used pure tungsten. This higher value of fracture toughness indicates superior damage tolerance relative to commercially used pure tungsten. These results highlight the alloy’s potential as a low-activation structural material for high-temperature plasma-facing components (PFCs) in fusion reactors.

Physics↗

DOE OSTI2025

Evaluating the bond strength and fracture mechanisms of cold-sprayed zinc coating on AZ91 magnesium substrate via a combined experimental and computational approach

Magnesium (Mg) alloys are ideal candidates for automotive applications due to their high strength to weight ratio, castability, recyclability etc., however, they lack corrosion and oxidation resistance. Solid-state deposition techniques, such as cold spray, have been demonstrated to enhance their corrosion resistance as it relies on the severe plastic deformation of powder particles upon impact with the substrate to form a metallurgical bond with the substrate and within the coating. At cold sprayed interfaces, a heterogeneous microstructure is formed that includes some porosity, oxides and intermetallics which can significantly affect coating performance. Thus, establishing a direct correlation between the interface microstructure and its properties can aid in designing optimal cold spray parameters. In this study, we investigated the microstructure and mechanical properties of a zinc (Zn) coating deposited on a high pressure die cast (HPDC) AZ91 Mg substrate via high resolution scanning transmission electron microscopy, in situ micro-tensile testing, and finite element method (FEM) modeling. Micro-tensile pillars fabricated using the plasma focused ion beam (PFIB) successfully isolates the coating-substrate interface within the gauge length. The average bond strength of Zn-Mg interface was determined to be ∼140 MPa with failure occurring partially at the interface and mostly into the coatings. A detailed microstructural characterization revealed evidence of a strong metallurgical bonding at the Zn-Mg interface and formation of the C14 MgZn 2 laves phase interlayer resulting in a mixed mode of fracture during the micro-tensile experiments. FEM modeling reveals the stress distribution along the interfaces and suggests that a MgZn 2 layer thickness between 200–400 nm is optimum to increase the bond strength and minimize the triaxiality. Such a site-specific interfacial analysis with correlative computational modeling provides crucial insight into the overall performance of cold spray interfaces.

Bond strength↗

DOE OSTI2024

Microstructural characterization and equibiaxial flexural strength of CeO 2 and Ti-doped CeO 2

In this study, the synthesis of CeO 2 and titanium dioxide (TiO 2 ) doped CeO 2 (TDC) monoliths are investigated, and their fracture strength is assessed using an equibiaxial flexure testing technique at room temperature. Pellets were synthesized using conventional powder processing and sintering methods to produce the desired characteristics. The TiO 2 dopant concentration was optimized at 0.1 wt % TiO 2 to obtain dense, solid-solution pellets with an enhanced grain microstructure. A ball-on-ring fixture was used to obtain the TRS and Weibull parameters of over 30 pellets for CeO 2 and 0.1 wt % TDC to compare fracture behavior. The TRS of CeO 2 pellets ranged from 88 to 160 MPa and the TRS of 0.1 wt % TDC pellets ranged from 102 to 171 MPa, both being consistent with published values. Weibull parameters, such as characteristic strength and Weibull modulus, were extracted as 129 MPa and 8.5 for CeO 2 and 150 MPa and 9.3 for 0.1 wt % TDC, respectively. Although Hertzian contact damage was observed on compressive surfaces, failure initiation occurred on the tensile surfaces of both types of samples. Fracture surface analysis for CeO 2 indicated a predominantly intergranular fracture while 0.1 wt % TDC had a predominantly transgranular fracture mode. Finally, the TRS of 0.1 wt % TDC resulted in increased Weibull parameters when compared to CeO 2 , indicating sample chemistry and microstructure impact mechanical behavior for these samples.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Fracture Behavior Considerations for the TRISO Particle Matrix

To assess whether matrix fracture would result in an unacceptable loss of containment or confinement in TRISO fuel particles, it is crucial to evaluate the micro-tensile strength, fracture toughness, and irradiation effects on matrix materials. Current data must be comprehensive and validated for modeling fractures under various conditions. Relevant material properties surrounding matrix fracture will be discussed during the presentation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties

This project developed machine learning (ML) methods, lab data sets, and field data to advance geothermal exploration and geothermal energy production. The work had three focus areas. One involved the development of ML methods to use microearthquakes (MEQs) for imaging geothermal reservoir properties and improving subsurface characterization – most importantly the evolution of permeability within the evolving reservoir. This part of the work included development of ML approaches for automated MEQ location, focal mechanism determination and identification of earthquake precursors. The second area focused on using MEQ signals generated by geothermal exploration and production to predict the relationship between fluid injection and seismicity. Here, we extended to reservoir scale our success in using ML to predict laboratory earthquakes and fault zone stress state. The third focus area was on lab experiments. Here, we developed new ML models for lab earthquake prediction and identification of precursors to failure to improve earthquake forecasting and early warning in geothermal settings. Major outcomes of our work include ML models that learn from MEQ signals during geothermal exploration and production to predict induced seismicity. MEQs occur naturally in connection with drilling and energy production. We developed ML methods to use the seismic waves from these events to characterize the elastic, hydraulic and poromechanical properties of reservoirs. Our work illuminated fracture geometry and the evolution of fracture permeability by incorporating seismic coda wave analysis and ML methods to relate fluid injection and seismicity. We significantly expanded laboratory earthquake prediction to include methods that use both passive measurements of microearthquakes within the lab fault zones and also active source acoustic measurements of fault zone elastic properties. These methods can now predict fault zone stress state, time to failure and the magnitude of lab earthquakes. Our work showed that repetitive stick- slip failure events during frictional sliding (the lab equivalent of earthquakes) are preceded by a cascade of micro-failure events that radiate energy in a manner that foretells unstable failure – manifest as laboratory MEQs. We documented a mapping between fracture properties and statistical attributes of elastic radiation. We extended existing works to geothermal reservoir scale and developed ML methods to determine reservoir permeability, fracture properties, and their evolution during geothermal energy production. An attractive feature of ML algorithms is their ability to handle big datasets and reveal patterns and correlations that may remain invisible to conventional analyses. Our work connected data from field, laboratory and intermediate scales to study permeability, stress, strength, fracture stiffness and geometry. At the field scale we used data from the Newberry Volcano field site, UtahFORGE, EGS Collab, and also the Bedretto underground research lab in Switzerland. These data sets are bridging the gap between the lab scale, theory, and reservoir scale. Our work produced plain language summaries to improve public understanding of DOE research. We also developed openly distributed ML and seismicity datasets for use by all researchers and we published connections between induced seismicity in geothermal areas and reservoir properties including permeability, fracture properties, and stress state. Our models are designed for the large data sets of induced seismicity typically associated with geothermal sites. We produced labeled event catalogs and used them on geothermal data to assess how ML can facilitate geothermal production and exploration. All datasets are available on the GDR Productivity: The project produced 32 publications in peer reviewed journals (two are in review). It supported the work of 6 PhD students, 40 conference presentations, 6 keynote talks at national meetings, and mentoring and professional development for 4 postdoctoral fellows.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Thermo-Mechanical Phase-Field Modeling of Fracture in High-Burnup UO2 Fuels Under Transient Conditions

This study presents a novel multiphysics phase-field fracture model to analyze high-burnup uranium dioxide (UO2) fuel behavior under transient reactor conditions. Fracture is treated as a stochastic phase transition, which inherently accounts for the random microstructural effects that lead to variations in the value of fracture strength. Moreover, the model takes into consideration the effects of temperature and burnup on thermal conductivity. Therefore, the model is able to predict crack initiation, propagation, and complex morphologies in response to thermal gradients and stress distributions. Several simulations were conducted to investigate the effects of operational and transient conditions on fracture behavior and the resulting cracking patterns. High-burnup fuels exhibit reduced thermal conductivity, elevating temperature gradients and resulting in extensive radial and circumferential cracks. Transient heating rates and temperatures significantly affect fracture patterns, with higher heating rates generating steeper gradients and more irregular crack trajectories. This approach provides critical insights into fuel integrity during accident scenarios and supports the safety evaluation of extended burnup limits.

Chemistry↗

DOE OSTI2025

Ion Size Effects on the Thermodynamic, Kinetic, and Mechanical Properties during Ion Exchange in Solid-State Electrolytes

Ion exchange offers a pathway to impose residual compressive stresses to mitigate the electro-chemo-mechanical cracking of solid-state electrolytes such as lithium lanthanum zirconium oxide. This study uses a coupled multiscale framework (integrating density functional theory (DFT), molecular dynamics (MD), and continuum modeling) to examine how exchange ion size influences stress, diffusion, fracture toughness, and electronic properties. Larger isovalent ions (Na + , Ag + , K + ) were exchanged with Li + , with DFT confirming their preference for octahedral 96h sites and a linear relationship between ion size and chemical free expansion coefficient. MD simulations reveal stress and concentration effects on exchange ion diffusivity at elevated temperatures, with Na + and Ag + maintaining favorable mobility while K + showing concentration-dependent clustering. Continuum modeling predicts the range of fracture strength improvements and the required ion exchange concentration profile. It was shown that a 5% surface exchange concentration can induce ∼0.6 GPa of surface compressive stress using Na + and ∼1.0 GPa of surface compressive stress using Ag + . On the other hand, larger ion exchange species may penalize Li + diffusivity by increasing the activation volume and activation energy. Interestingly, Na + has a negligible penalty on Li-ion diffusivity. The room temperature Li + ion diffusivity is reduced by ∼40% with Ag + ion exchange. Electronic band structure analysis shows no size-dependent change in the bandgap, though Ag + introduces localized defect states near the valence band maximum. This study highlights ion size as a key factor in optimizing LLZO properties, offering a framework to improve the solid-state battery performance.

Jagad, Harsh D. [Brown Univ., Providence, RI (Unit↗

DOE OSTI2026

Emergence of Diverse Failure Patterns in Weathering‐Induced Landslides: Insights From Particle Finite Element Simulations

Weathering is a fundamental driver of landslide evolution over geological timescales. Despite its ubiquity and importance, quantifying how weathering drives the progressive destabilization of rock slopes remains challenging. In this work, we develop a unified computational framework based on the particle finite element method to investigate the evolution of weathering‐induced landslides, from long‐term weathering to short‐term slope failure and runout dynamics. The framework integrates key processes, including weathering front propagation, time‐dependent strength degradation, rupture surface development, and post‐failure runout dynamics. Through numerical simulation experiments, we elucidate how interactions among weathering characteristics (type, intensity, and rate law), bedrock strength, fracture distribution, and slope geometry govern the failure modes and kinematics of weathering‐induced landslides. Simulations show that matrix‐dominated weathering leads to shallow translational failures, whereas fracture‐dominated weathering produces deep‐seated rotational and compound landslides. Pre‐existing fractures and slope morphology also strongly influence the movement of destabilized landmasses, affecting the failure pattern (e.g., kinematic mode and rupture surface geometry) and post‐failure behavior (e.g., runout velocity). We further demonstrate that the failure time and volume of weathered slopes are governed by the competition between gravitational driving forces and cohesive resisting forces during progressive destabilization. These findings provide new insights into the fundamental mechanisms that drive the emergence of diverse failure patterns of weathering‐induced landslides with important implications for landslide hazard assessment.

Wang, Liang [Eidgenoessische Technische Hochschule↗

DOE OSTI2024

Ability of x‐ray computed tomography to resolve critical flaw size in laser‐based, paste stereolithography ceramic printing of alumina

Abstract Complex alumina parts were printed using vat photopolymerization (VPP), which is a stereolithography‐based additive manufacturing (AM) technique used to shape ceramic preforms, or green parts. The critical flaw size was determined using classical fracture mechanics techniques. The strength and fracture toughness were measured and compared to flaws detected in x‐ray computed tomography (XCT or CT) distributions as well as the fracture surfaces. The strength was lower compared traditionally made alumina, and that is due to layering effects, slurry defects, and printing defects. The critical flaw size from fracture mechanics was 206 µm. XCT has high enough resolution to detect the critical flaw size and much smaller features, where the average flaw size observed in CT scans was around 80–100 µm. The fracture surfaces indicate that flaws causing failure are larger than that of the critical flaw size (∼300 µm), but fracture surfaces do not show definitive features compared to traditionally made ceramics. Since XCT can observe flaws smaller than the critical flaw size, this method can be used as a screening technique.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A workflow for simulating variability in strength and ductile fracture of laser-welded materials with porosity defects using non-local damage and adaptive remeshing

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Phung, Brian Ruskin [Sandia National Laboratories ↗

DOE OSTI2024

Utah FORGE 5-2565: Evolution of Permeability and Strength Recovery of Shear Fractures Under Hydrothermal Conditions - 2024 Annual Workshop Presentation

This is a presentation on the Evolution of Permeability and Strength Recovery of Shear Fractures Under Hydrothermal Conditions by United States Geological Survey, presented by Tamara Jeppson. This video slide presentation, by the USGS, discusses the determination of how thermal, hydrologic, mechanical, and chemical (THMC) processes affect the sustainability of fracture networks in geothermal reservoirs. This includes (1) the qualification of rates of change of fracture properties, (2) the parameterization of modes of reaction, (3) the development of micromechanical and empirical fracture models, and (4) extended THMC models for laboratory- and reservoir-scale models. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 15, 2024.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

ULTIMATE Phase I project: Development of Niobium-based alloys for Turbine Applications

Current Ni-based alloys used in turbine blade applications are operating at 1100°C which is approximately 90% of the solidus of Ni-based alloys. Further increases in temperature can be achieved only through the use of alloys with higher solidus temperatures such as refractory alloys which include Mo, Nb, W, Ta alloys. Niobium has a unique combination of physical properties that include a high melting point (2468°C), lowest density (8.57 g/cc), and the lowest modulus amongst refractory alloys, a good thermal conductivity that increases from 45 W/mK at room temperature to 62 W/mK at 1093°C, good ductility with fabricability using traditional techniques, high strength, good creep resistance, and general chemical inactivity. Hence niobium alloys offer many advantages for use at the desired temperature of 1300°C. One of the major deterrents to the use of niobium and its alloys at high temperatures is achieving good oxidation resistance. In addition, achieving balanced properties of room temperature strength, ductility, fracture toughness, high temperature strength, and creep resistance required for 1300°C operation at a density of 9 g/cm 3 is extremely challenging since the addition of W which is a potent strengthener increases the density of the alloy. This project seeks to enable the development of a tri-layered turbine blade that can operate continuously at 1300°C with the core of the turbine blade providing good creep resistance, the second layer providing improved oxidation resistance over the core layer, and the third layer being an environmental barrier providing oxidation resistance. The objective of this Phase 1 project was to use computational modeling and advanced characterization tools to develop two classes of Nb alloys which could be used as the core layer and the transition layer. The first class of alloys developed in this project was a Nb-alloy designed to serve as the turbine blade core with excellent room temperature strength, ductility, and high temperature strength and creep resistance required for 1300°C operation. These alloys were designed to contain sufficient solute solution strengthening elements (W, Mo) but constrained by the density of alloy, along with the addition of elements such as Zr, Hf, Ta, C, and N to achieve a combination of primary and secondary carbide precipitation. A total of 38 “creep-resistant” alloys were designed and cast during the duration of the project. Processing techniques were developed to keep the oxygen contents as low as possible with typical oxygen contents less than 250 ppm. One alloy with a density of < 9.5 g/cc was successful in meeting the Phase 2 intermediate project mechanical property milestone requirements of room temperature ductility greater than 1.0%, 1200°C creep strain of less than 3% at 150 MPa and 100 hours in vacuum, and with solidus temperature greater than 1500ᵒC. The second class of alloys was designed to be a Nb-rich alloy with improved oxidation resistance when compared to the core layer and was designed specifically to be compatible with the core layer and the outer environmental barrier coating. This Nb- alloy will be specifically designed to be microstructurally stable at these temperatures when in contact with the core alloy and provide protection against catastrophic failure of the barrier coating. Two alloys were cast and processed but further development was discontinued to focus on the development of the creep resistant alloy.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Development of Niobium-based alloys for Turbine Applications: 20/CJ000/08/09 (ULTIMATE Phase I project)

36 MATERIALS SCIENCE↗

DOE OSTI2025

Micro-structural features and material properties impact on adhesive metal joints via computational modeling and machine learning

The quality of structural bonding in practical applications depends on various factors arising from materials, pre-processing conditions, and manufacturing. Understanding how these factors influence bonding performance and determining their relative importance are of significant interest. Thus, this study evaluates the effects of microstructural features and material properties on the structural strength of adhesively-bonded metal joints at the submillimeter scale, utilizing a combination of Finite Element Modeling (FEM) and Machine Learning (ML) with Gradient Boosting Regression (GBR). The microstructural features include adhesive thickness, internal voids within the adhesive, adherend-adhesive interfacial voids, void size and volume fraction, and surface roughness. The material properties include the constitutive behavior of the adhesive, as well as the adherend-adhesive interfacial strength and fracture energy. The changes in structural strength and morphologies of the bonded metal structures with respect to different microstructural features and material properties were clarified by FEM. By further leveraging ML-GBR, the sequence of importance of these factors affecting bonding performance across various scenarios was summarized. This work provides valuable insights into the development of improved structural bonding for adhesive joints in industries such as automotive , aerospace, and beyond.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Graph neural networks for mechanical property prediction of 2D fiber composites

This work investigates the ability of graph neural networks (GNNs) to homogenize 2D fiber composite microstructures. We use different inhomogeneity and anisotropy indices to motivate and show that the Volume Elements (VEs) used in ML methods should ideally be far from their Representative Volume Element (RVE) size limit and, consequently, are notably anisotropic. Hence, training only the isotropic limit properties may not be acceptable. Another aspect is the need to normalize elastic stiffness values for ML, especially when high elastic contrast ratios are encountered between composite phases or in the material set. We introduce a normalization technique based on the mean-field method (MFM) to handle such high contrast ratios and train for the entire stiffness tensor. We show that the proposed GNN approaches exhibit high accuracy and efficiency compared to traditional methods and convolutional neural networks, utilizing unstructured graphs constructed from microstructure topology. Our model successfully predicts the stiffness tensor, peak strength under bulk damage, and brittle fracture initiation strength across diverse microstructure configurations while maintaining high accuracy even for extreme material contrasts and volume fractions. We also present a method to improve prediction accuracy for small dataset sizes using Voronoi partitioning.

Brittle strength↗

DOE OSTI2025

Statistical fracture behavior of doped UO 2 using a ball-on-ring equibiaxial flexure test method

Metal oxide dopants, such as titanium and chromium oxides, have garnered considerable attention for their potential to increase grain size (≥ 30 µm) in UO 2 fuel, purportedly enhancing fission gas retention during reactor operation. Fuel performance is significantly impacted by fuel fracture behavior, so it is important to understand the effects of enhanced grain size and dopant content on UO 2 fuel fracture. UO 2 pellets were doped with 0.1 wt% TiO 2 and 0.3 wt% Cr 2 O 3 to alter density and grain size. Inductively coupled plasma mass spectroscopy measured dopant levels pre- and post-sintering. X-ray diffraction revealed lattice changes and microstrain via Rietveld refinement. Field emission scanning electron microscopy determined grain sizes of approximately 30 µm for TiO 2 doping and 7 µm for Cr 2 O 3 doping. Transverse rupture strength tests were performed on over 30 samples per dataset to obtain characteristic strength and Weibull modulus. Results indicate no statistical difference in fracture strength between 0.1 wt% TiO 2 doped UO 2 and undoped UO 2 , while 0.3 wt% Cr 2 O 3 doped UO 2 exhibited a 20% decrease in fracture strength. Doped UO 2 samples also showed reduced Weibull modulus compared to undoped UO 2 , suggesting increased scatter in fracture strength. This study's findings suggest that titanium and chromium oxide doping in UO 2 , regardless of grain size, induce residual stresses, decreasing fracture strength and increasing variability in fracture behavior.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗