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At least 145 records · Page 8

Geomechanical characterization of Rock Valley carbonates

In Rock Valley, Nevada, the USA, past earthquake sequences and shallow faulting in Paleozoic carbonates remain poorly understood. Carbonates are typically more ductile rocks that do not experience large stress drops or fracture coalescence, which contradicts previous observations in the region. As part of the Source Physics Experiment, an effort has been made to experimentally characterize the petrophysical and geomechanical properties of carbonates from Rock Valley. Well core and outcrop samples were used to determine the difference between shallow-buried Tertiary limestones and deeply buried Paleozoic limestones and dolostones. The carbonates possessed porosities between 3 and 9%, with V P and V S in the Tertiary carbonates around 2700 and 1800 m/s, respectively, and 6000 and 3100 m/s, respectively, in the Paleozoic carbonates. Microstructural characterization revealed that the Paleozoic carbonates contained significantly more pre-existing damage and alteration than the Tertiary carbonates, though the deformation varies from localized to diffuse. Unconfined Brazilian tests and triaxial tests with confining pressures between 0 and 50 MPa showed that, although samples all experienced failure, the dolostones typically failed at greater stresses and possessed greater E/ν ratios than the limestones. Furthermore, the Hoek–Brown failure criterion was used to construct failure envelopes with the compressive and tensile failure tests. Velocity, density, and porosity measurements were used to construct a hypothetical velocity-depth profile and compare the results with the theoretical petrophysical measurements. Using brittleness analysis, the likely failure conditions were determined to be low-porosity dolomitic rock for fault nucleation in the Paleozoic basement.

Brittleness↗

Multiscale Mechanisms of Twisted Carbon Nanotube Yarns Probed In Situ by Soft X-rays during Tensile Loading

Piecing together carbon nanotubes (CNTs) into assemblies has so far failed to achieve the same elite strength performance metrics as individual CNTs, highlighting a critical deficiency in understanding the effects that the processing of individual nanostructures have on the performance of their derived macroscale assemblies, thereby hindering the development of a process-structure-performance map for these materials. Here, in this work, we propose a method to decouple the distribution orientation of nanoscale tortuosity and the microscale twist of CNT dry-spun yarns under applied loads via in situ soft X-ray probing at high energy (1200 eV) and low energy (280 eV), respectively. With this decoupling enabled by in situ soft X-ray scattering, we acquired a deeper understanding of the deformation mechanisms of these yarns. We found that for untreated yarns, the twist angle of collective CNT bundles at the macroscale is more sensitive to applied stress than the nanoscale alignment distribution. We also found that increasing nominal twist densities of yarns as well as increased strengthening via plasma treatments and polymer infiltration act to decrease the yarns’ sensitivity to realignment at the nanoscale and prevent failure by the slip mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polymers used in 4 mm PV Connectors [Slides]

Polymer cracks are not a new problem in the PV industry. However, the suddenness and severity of the cracking connector model is new and concerning. Some sites are experiencing wide-spread cracking of a specific connector model. The preliminary investigation results are (1) there are potential clearance issues with the O-ring, leading to high mechanical stress; (2) potential use of lubrication yields polymer embrittlement; and (3) clear mechanical or chemical differences between the affected model and other PPE-based models using FTIR and tensile testing could not be demonstrated.

36 MATERIALS SCIENCE↗

Experimental and Numerical Characterization of High Temperature Deformation Behavior of 347H Stainless Steel

This study investigates how temperature affects the plasticity and thermal creep behavior of 347H stainless steel under uniaxial tension. The research combined experimental testing with advanced computational modeling. Two types of experiments were conducted: uniaxial tensile tests at temperatures from 100°C to 750°C using strain rates of ~10⁻⁴ s⁻¹, and creep tests at temperatures between 600°C and 750°C under various stress levels. These experimental results were used to develop and validate a new integrated mechanistic model that can predict material behavior under any loading condition while accounting for both stress and temperature effects. The model was implemented using a polycrystalline microstructure simulation framework based on elasto-viscoplastic Fast Fourier Transform (EVPFFT). It incorporates three key deformation mechanisms: thermally activated dislocation glide, dislocation climb, and vacancy diffusional creep. The model accounts for internal stress distribution within single crystals and considers how precipitates and solute atoms (both interstitial and substitutional) affect dislocation movement. After validation against experimental data, the model was used to generate Ashby-Weertman deformation mechanism maps for 347H steel, providing new insights into how microstructure influences the activation of different creep mechanisms.

Joy, Jobin K.↗

Anisotropic Tensile Properties of a 14YWT Nanostructured Ferritic Alloy: On the Role of Cleavage Fracture

Two plates of nanostructured ferritic alloy NFA-1 were processed by ball milling atomized Fe-14Cr-3W-0.4Ti-0.2Y (wt.%) with FeO powders, canning, and hot-extrusion at 850 °C, followed by annealing and multipass cross-rolling at 1000 °C. This produces a severe (001) brittle cleavage texture on planes running parallel to the plate faces. In the first plate (P1), pre-existing microcracks (MCs) formed on the cleavage planes during cross-rolling. The second plate (P2) contained far fewer, if any, MCs. Here, we compare the tensile data for out-of-plane (S) and in-plane (L) tensile axis orientations, at temperatures from −196 °C to 800 °C. We also assess the tensile property differences between P1 and P2, and the effect of specimen size. The L-orientation strength and ductility were excellent; for example, the room temperature (RT) yield stress, σy ≈ 1042 ± 102 MPa, and the total elongation, εt ≈ 12.9 ± 1.5%. In contrast, the S-orientation RT σy ≈ 708 ± 57 MPa, and εt ≤ 0.2%. These differences were due to cleavage on the brittle (001) planes. Cleavage leads to beneficial delamination toughening, but is deleterious to deformation processing and through-wall heat transfer. Therefore, it is important to quantitatively characterize the pronounced NFA-1 strength anisotropy due to severe crystallographic texturing and cleavage fracture.

Crystallography↗

Structure and Sulfur: Tuning the Viscoelastic and Surface Properties of Natural Keratin Fibers

Natural keratin fibers, such as wool, possess a complex hierarchical structure that governs their mechanical properties and surface energy. However, the extent to which these characteristics are influenced by combined contributions of structural variations (e.g., fiber diameter, intermediate filament (IF) packing) and chemical composition (e.g., disulfide bond density) remains poorly understood. In this study, we investigate wool fibers from five sheep breeds (Merino, Polwarth, Cheviot, Eider, and Devon) to elucidate how these factors influence viscoelasticity and surface interactions. Using a multimodal approach integrating interfacial and bulk characterization methods, including inverse gas chromatography (IGC), atomic force microscopy-infrared spectroscopy (AFM-IR), X-ray photoelectron spectroscopy (XPS), uniaxial tensile testing, and synchrotron small-angle X-ray scattering (SAXS), we show that the nanometer-thick 18-methyleicosanoic acid (18-MEA) layer is consistently present across all wool types and plays a key role in governing hydrophobicity and surface heterogeneity. A controlled isothermal treatment at 200 °C, designed to cleave disulfide bonds, results in a nearly 40% reduction in specific surface area across all fiber types, accompanied by a significant decrease in tensile strength and 80% reduction in elongation at break for Merino and Devon wool, but limited influence on the mechanical properties of Eider fibers. Furthermore, rate-dependent tensile testing within the elastic regime reveals distinct viscoelastic responses among the fiber types, suggesting that the sulfur-rich protein matrix surrounding IFs and its structure contribute actively to stress partitioning. Altogether, when combined with conclusions from SAXS measurements of IF spacing, our work offers compelling insights into the role of the keratin-associated protein (KAP) matrix in shaping wool fiber mechanics. Differences in mechanical behavior among wool types, despite similar IF spacing or sulfur content, highlight the importance of matrix composition and cross-linking density, suggesting that the molecular architecture of the KAP network may be a dominant factor in determining fiber performance.

X-ray scattering↗

The role of specimen size and grain boundary characteristics in the yield strength of tungsten in microtensile tests

To effectively use the measured properties from small-scale tensile tests for bulk material performance predictions, it is essential to understand the threshold of specimen size-effect strengthening and the interaction between dislocations and microstructures within miniaturized specimens. This study uses pure tungsten to investigate the size effect in terms of specimen size, grain size, and grain boundary characteristics relative to the yield strength of tungsten at room temperature. We evaluate the transition from miniaturized specimen properties to bulk properties and the deformation behavior through small-scale tensile tests of three specimen sizes (large: 80 × 100 × 233 µm³; medium: 7 × 7 × 18 µm³; and small: 2 × 2 × 5 µm³). The testing results reveal that the small and medium specimens exhibit high yield strength with ductile behavior, while the large specimens exhibit brittle failure, consistent with the room temperature strength of tungsten, indicating bulk behavior. We further explore the specimen size-effect sensitivity to yield stress and the scaling relationship between yield strength and the number of grains involved in the deformation. A power-law relationship with the exponent value of approximately -0.5 was found in the yield strength–grain number scaling, implying the Hall-Petch like behavior. A minimum of 7–17 effective grain boundaries across the tensile gauge dimension is required to accurately measure bulk properties.

36 - MATERIALS SCIENCE↗

Atomic Energy Accuracy of Neural Network Potentials: Harnessing Pretraining and Transfer Learning

Machine learning-based interatomic potentials (MLIPs) have transformed the prediction of potential energy surfaces (PESs), achieving accuracy comparable to ab initio calculations. However, atomic energy predictions, often assumed to lack physical meaning, remain underexplored. In this study, we demonstrate that inaccuracies in atomic energy predictions reduce the robustness and transferability of Neural Network Potentials (NNPs) and atomic energy error can be masked in total energy predictions due to error cancellation. Here, we validate this finding using challenging configurations involving deformation and failure under tensile loading. By pretraining atomic energy predictions using empirical potentials and applying transfer learning with density functional theory (DFT) data, we achieve notable improvements in the accuracy of total energy, forces, and stress predictions. Furthermore, this approach enhances the robustness and transferability of NNPs, emphasizing the importance of atomic energy predictions in developing high-quality and reliable MLIPs.

Active Learning↗

Geophysical Signatures of Crack Network Coalescence in Rocks at Multiple Length Scales

The main goal of the research project was to identify the geophysical signatures of fracture growth in natural rocks by utilizing novel geophysical techniques. The research objectives were to (a) investigate the potential for geophysical methods to determine when cracks initiate, the types and locations of propagated cracks, and the coalescence of networks of cracks in natural rocks at multiple scales, (b) determine how damage at the microscale evolved into damage at the macroscale and then link the microscopic and macroscopic observations, (c) quantify crack coalescence in rocks under realistic stress conditions using coupled mechanical-geophysical-optical visualization, and (d) identify the precursors in geophysical signals to crack coalescence. The following research thrusts were explored to achieve the research objectives: (1) uniaxial compression testing of rock specimens with and without a set of pre‐existing flaws and (2) triaxial compression testing of natural rock specimens. These thrusts allowed for exploring fracturing in rocks under realistic in situ environments and at multiple scales. This project provided educational opportunities for nine graduate and undergraduate students and resulted in 27 peer-reviewed publications. This first research thrust focused on investigating the micromechanics of fractures in rocks through uniaxial compression testing combined with advanced geophysical and imaging techniques, specifically acoustic emission (AE) monitoring, ultrasonic imaging, and 2-dimensional Digital Image Correlation (2D-DIC). By examining damage processes under time-independent and time-dependent loading conditions, insights into damage localization, crack initiation, and fracturing mechanisms were gained. It was observed that the AE signals and the strain-based measurements directly reflect the state of damage in the rock specimen and could be used to identify the cracking levels, such as the crack initiation (CI) and crack damage (CD), and the mode of deformation. A novel calibration apparatus was developed to enhance the accuracy of AE sensors, allowing for the estimation of key parameters such as magnitude, source dimension, stress drop, and radiated seismic energy associated with the fractures. The findings highlighted significant variations in the temporal evolution of AE source parameters during the primary, secondary, and tertiary stages of creep, identifying tensile cracking as the primary deformation mode. The second research thrust focused on enhancing the understanding of fracturing processes in natural rocks through triaxial compression testing, real-time AE monitoring, and ultrasonic monitoring. We investigated the impact of various factors such as fracture propagation regimes, injection parameters, rock types, and pre-existing conditions on the hydraulic fracture (HF) behavior using scaled true-triaxially loaded specimens of Barre granite and Lyons sandstone. Custom sensor housing facilitated concurrent active and passive monitoring to analyze hydro-mechanical responses and microseismicity associated with different HF scenarios. A coupled investigation of passive microseismicity and active signal attributes permitted a detailed comprehension of the various HF processes (aseismic deformation, fracture initiation and propagation, fluid permeation, and leak-off) and their dependence on the specific rock type. The findings of this research demonstrated the effectiveness of AE monitoring techniques in providing valuable insights into the impact of various factors on the behavior and dynamics of HF processes. The advancements in monitoring techniques, offering a more thorough and precise approach, represent a significant step towards optimizing HF practices and ensuring sustainable resource extraction.

58 GEOSCIENCES↗

Efficient mapping between void shapes and stress fields using Deep Convolutional Neural Networks with sparse data

Establishing fast and accurate structure-to-property relationships is an important component in the design and discovery of advanced materials. Physics-based simulation models like the finite element method (FEM) are often used to predict deformation, stress, and strain fields as a function of material microstructure in material and structural systems. Such models may be computationally expensive and time intensive if the underlying physics of the system is complex. This limits their application to solve inverse design problems and identify structures that maximize performance. In such scenarios, surrogate models are employed to make the forward mapping computationally efficient to evaluate. However, the high dimensionality of the input microstructure and the output field of interest often renders such surrogate models inefficient, especially when dealing with sparse data. Deep convolutional neural network (CNN) based surrogate models have shown great promise in handling such high-dimensional problems. In this paper, a single ellipsoidal void structure under a uniaxial tensile load represented by a linear elastic, high-dimensional and expensive-to-query, FEM model. We consider two deep CNN architectures, a modified convolutional autoencoder framework with a fully connected bottleneck and a UNet CNN, and compare their accuracy in predicting the von Mises stress field for any given input void shape in the FEM model. Additionally, a sensitivity analysis study is performed using the two approaches, where the variation in the prediction accuracy on unseen test data is studied through numerical experiments by varying the number of training samples from 20 to 100.

surrogate modeling; convolutional neural networks;↗

TEM Approaches for Microstructure-Informed Prediction of Mechanical Properties in Structural Alloys

Predicting the mechanical performance of structural alloys from their evolving microstructure remains a major challenge in materials science, particularly for nuclear structural materials, where irradiation-induced defects span multiple types and length scales and interact through complex mechanisms. The dispersed barrier hardening (DBH) [1] and Friedel–Kroupa–Hirsch (FKH) [2,3] models have been widely used to evaluate the hardening contributions of individual obstacles and to estimate tensile strength from quantified microstructures; however, when multiple size-dependent obstacles coexist and evolve, predicting temperature-dependent tensile strength becomes significantly more complex, and a fully consistent hardening model is still lacking. Transmission electron microscopy (TEM) plays a central role in refining hardening models and enabling predictive assessments of tensile strength evolution by providing quantitative characterization of dislocations, irradiation-induced defects (e.g., dislocation loops and cavities), precipitates, and grain structure (Fig. 1.). These experimentally measured defect densities are incorporated into physically based hardening models with size- and shape- dependent obstacle strengths [4], using root-sum-square superposition for obstacles of comparable strength and linear superposition for dissimilar ones [5]. In addition, recent advances in TEM [6-8], including high-resolution imaging, 4D-STEM strain mapping, EDS/EELS elemental analysis, and flash-polishing-based TEM specimen preparation and extraction-replica methods (Fig. 2), further improve the accuracy of microstructural quantification. By comparison with prior studies as well as our own results, we show that when TEM-derived microstructural information is carefully integrated with physically grounded hardening models, yield strength (or irradiation-induced hardening) measured at room temperature can be predicted with good quantitative agreement across multiple alloy classes. In-situ TEM combined with high-temperature mechanical testing represents an important next step for refining hardening models by directly probing dislocation–obstacle interactions across varying irradiation doses and temperatures [9]. Because the barrier strength factor (α) depends on both temperature and obstacle size, it should not be treated as a constant fitting parameter; rather, it must be explicitly evaluated to achieve physically meaningful predictions of mechanical behaviour at operating temperatures. This presentation therefore discusses why all strengthening contributions (e.g., Peierls stress, solid-solution strengthening, voids, bubbles, dislocation loops, dislocation lines, and grain boundaries) must be considered collectively, why appropriate superposition methods are essential when obstacles possess different barrier strength factors, how hardness measurements can be meaningfully related to tensile properties, and how TEM-derived microstructural information can be systematically incorporated into hardening models. More broadly, it outlines a pathway toward microstructure-informed prediction of mechanical properties and supports the goal of establishing science-based tools for evaluating structural materials in extreme environments [10].

Lin, Yan-Ru [ORNL] (ORCID:0000000339991473)↗

Uncertainty quantification for competing failure mechanisms in unidirectionally reinforced carbon–carbon composites

Microstructure-informed finite element models play a key role in the carbon–carbon composite design process. Variability in manufacturing process parameters and experimental limitations introduce model parameter uncertainty. This study quantifies the effect of model parameter uncertainty on transverse tensile fracture behavior and proposes a methodology to predict the failure mode based on competing microscale damage mechanisms. Finite element simulations incorporate fiber–matrix interface debonding with cohesive zones and matrix damage with a smeared crack band approach in a unidirectional carbon–carbon composite. Results from a variance-based global sensitivity analysis identifies interfacial and matrix damage parameters as the primary source of variability in fracture behavior. Sobol’ indices indicate that matrix and cohesive zone strengths contribute 94% of the variance in the effective ultimate stress. A local analysis elucidates the relationship between these constituent strength parameters and failure mode by estimating the probability of cohesive, matrix, and mixed-mode dominated failure. Based on the results for 4000 simulations, 93% exhibit mixed-mode or interfacial dominated failure, which underscores the crucial role of fiber–matrix interface debonding in the transverse tensile failure of carbon–carbon composites. These uncertainty quantification results facilitate more efficient model calibration and provide a framework for microstructure-informed failure predictions in the face of manufacturing-induced uncertainty.

36 MATERIALS SCIENCE↗

Epoxy Coating of Biofiber: An Effective Modifier of Biofiber Physical and Flow Properties for Improved Tensile Behavior of Biofiber-Reinforced Biocomposite

Biocomposites combine renewable, plant-based fibers with degradable polymers and are an attractive option for sustainable, lightweight, and cost-effective materials with a low carbon footprint, especially for large-scale additive manufacturing. One of the major challenges in the widespread adoption of biocomposites is that their mechanical performance is significantly inferior to that of synthetic composites. Surface treatment is a common and effective technique to improve the mechanical properties of the biofibers used in biocomposites. This study aims to investigate the physical and flow properties of surface-treated biofibers, as well as the tensile properties of their PLA-based biocomposite, to gain insights into how surface treatment changes the fiber‘s characteristics and biocomposite‘s mechanical properties. Surface treatment was created using a two-component epoxy system by reacting poly(bisphenol A-co-epichlorohydrin) glycidyl end-capped (PBG) and dicyandiamide (DICY). The treatment was tested on two different biofibers (loblolly pine and corn stover fibers) with three different PBG/DICY molar ratios (0.25, 0.5, and 2). Results showed that surface-treated fibers improved the tensile strength and Young‘s modulus of the biocomposites. Loblolly pine biocomposites from fibers treated with a PBG/DICY ratio of 0.25 exhibited the best tensile properties. The surface treatment resulted in a more loosely dispersed fiber bulk structure, as evidenced by less fiber agglomeration into smaller particle sizes, higher fiber sphericity, and lower loose bulk density. This can enhance stress distribution and the overall mechanical performance of the biocomposites. Additionally, surface-treated fibers exhibited better dynamic flow properties.

36 MATERIALS SCIENCE↗

Macro-level mechanical interlocking: A rapid joining approach for additively manufactured compression molded composite panels

Composite joining typically involves multiple steps, such as drilling and surface treatment, as part of the manufacturing process, which leads to low throughput and long cycle times. In the present study, we demonstrated a macro-level mechanical interlocking (MI) based, rapid joining technique to assemble additively manufactured compression molded (AMCM) panels, enabling the production of parts larger than the mold dimensions. Composite panels made of 20 wt% short carbon fiber reinforced acrylonitrile butadiene styrene (CF/ABS) were joined using MI features of various geometries, namely tree (TR), dovetail (Dov), rectangle 2 (Rect2), and rectangle 1 (Rect1), and their in-plane strength was evaluated. The resultant strength of the tested MI joints reached up to 74 % of the baseline tensile strength (i.e., the ‘no joint’ case). Observations from optical and scanning electron microscopy revealed inadequate polymer diffusion between the adherends, indicating that the joint strength was primarily derived from mechanical interlocking. Additionally, the fracture surfaces exhibited stress-whitening marks, which were characterized using differential scanning calorimetry (DSC). The increase in melting enthalpy suggested local stretching of polymer chains due to MI. Finite element analysis (FEA) indicated that the Rect1 MI feature, which generated the lowest stress concentration, outperformed the others in terms of joint strength, achieving 42 MPa. As a demonstration of the MI joining method, a battery box tray measuring 108 cm × 34 cm using a mold with an effective dimension of 36 cm × 34 cm successfully manufactured, resulting in a part with an area three times larger than the mold. In conclusion, this study presents a promising approach to improving composite joining techniques while minimizing production complexities.

In-plane joining↗

Fiber orientation and porosity in large-format extrusion process: The role of processing parameters

Controlling fiber orientation and porosity in short-fiber thermoplastic composites is important for enhancing mechanical, electrical and thermal properties in large-format additive manufacturing. This study employs a factorial design of experiments (DoE) to assess the effects of nozzle diameter (5.08 mm–10.16 mm), temperature (230–250 °C), and extruder screw speed (150–280 rpm) on flow rate, shear rate, porosity, fiber orientation, fiber length and tensile strength in 20 % carbon fiber-filled acrylonitrile butadiene styrene. ANOVA results show that screw speed significantly impacts flow rate, while nozzle diameter and temperature have lesser effects. Shear rate increases with smaller nozzles and higher speeds. Porosity decreases from 5.58 % with a 10.16 mm nozzle to 3.11 % with a 5.08 mm nozzle at 150 rpm due to increased shear rates, which induce shear thinning, reducing viscosity and facilitating gas escape. Larger nozzles (10.16 mm) produce larger, more heterogeneous pores, while smaller nozzles (5.08 mm) yield smaller, uniform pores. Beads produced with the 5.08 mm nozzle exhibit longer fiber lengths due to reduced residence time, lower shear stress, and better alignment. Fiber orientation improves with smaller nozzles due to higher shear rates but decreases with higher screw speeds (280 rpm) due to shorter residence times. The highest fiber alignment (A xx ∼ 0.65) and low porosity (∼3%) were achieved with a 5.08 mm nozzle at 150 rpm, while equivalent additive manufacturing-compression molding samples exhibited better tensile strength (∼93 MPa) under these conditions. In conclusion, these findings emphasize the importance of optimizing processing parameters to enhance fiber alignment and reduce porosity for improved mechanical performance.

Design of experiments↗

Analysis Of Fracture Location on Tensile Graphite Samples

The main standard for testing the ultimate tensile strength of graphite is ASTM C749. Commercial entities have raised concerns about samples breaking outside of the gauge section, particularly in the radius or head of the sample. When this occurs, the data gathered from the samples is unusable and increases the cost of testing as more samples will need to be machined. This study investigates the locations and frequency of sample breakage for four different grades of graphite using a custom-made measurement scale. The four grades include two fine-grain (2114 and IG-110) and two medium/coarse-grain (NBG-17 and PCEA). Our results show that fine-grain grades are more susceptible to breaking outside the gauge section, with almost 30% of the samples from grade 2114 breaking outside this region. Additionally, the radius being too small causes stress concentrations near the ends of the gauge section resulting in a bimodal distribution of the fracture locations.

36 - MATERIALS SCIENCE↗

Tradeoffs and Variability of Mechanical Properties in Cold Worked 21-9-6 Stainless Steel Bars

Sub-standard yield stress in a batch of 21-9-6 stainless steel (Nitronic 40) bars was observed while other batches passed requirements. This material requires enhanced property uniformity due to its application in critical components and therefore has tighter restrictions on alloying elements. Using tensile testing, this study investigates the distribution of yield and ductility across bar geometry for three lots of material and is corroborated alongside Vickers microhardness profiles.

Estrada, Micah Garnet Watson↗

Report on the Integration of Experimental and Modeling Data for Initial Equivalence Study of Mechanical Performance in Irradiated LPBF 316 Stainless Steel

To ensure the rapid development, deployment, and use of advanced nuclear technologies, faster qualification approaches are needed. Typically, the primary pathway uses traditional data packages consistent with the American Society of Mechanical Engineers Boiler and Pressure Vessel Code, which does not consider the environmental effects the material will experience such as corrosion and radiation damage. Examining radiation effects requires a significant amount of space in US facilities at the Advanced Test Reactor and the High Flux Isotope Reactor (HFIR) and suffers from natural gradients in temperature and neutron flux profiles. Ion irradiation may enable rapid assessment of radiation-induced damage to a material and is proposed as part of an accelerated materials qualification framework through the Advanced Materials and Manufacturing Technologies program. To enhance the utility of ion irradiation as an examination tool, this report provides the initial assessment of engineering-relevant properties of microstructures produced from ion irradiation in the near-surface volume. Nanoindentation, Vickers hardness, and known tensile properties were brought together with simple mathematical models and experimental data for an initial equivalence study of the mechanical performance of irradiated laser powder bed fusion (LPBF) 316 stainless steels across length scales. Direct observation of the calculated ion irradiation yield stress and measured neutron irradiation yield stress at 2 dpa showed that both datasets exhibit the same trend with irradiation temperature and overlap within an acceptable band of stress values. Ion irradiations at 10 dpa serve as a prediction of properties to compare to postirradiation examination of HFIR-irradiated LPBF 316H further in the program. This work is a significant demonstration of the Licensing Approach with Ions and Neutrons, which uses ion irradiations to generate mechanical property information more rapidly than through neutron irradiations.

36 MATERIALS SCIENCE↗