Nanometer scale chemistry and microstructure of CrN/AlN multilayer films
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SOC Microstructural Property Estimator
This pre-trained ML model is a tool that uses basic compositional parameters for porous solid oxide cell (SOC) electrodes - the phase fractions and mean particle/pore diameters – as inputs and uses them to estimate additional electrochemical performance parameters: active (i.e., connected) TPB density, all tortuosity factors, and phase pair specific interfacial areas. The electrode is assumed to be composed of two solid phases and a pore phase. The property calculations are performed using neural network regression models trained on a large bank of synthetic electrode microstructural data that NETL has generated using the program DREAM3D (that bank is also hosted on EDX: https://edx.netl.doe.gov/dataset/soc-synthetic-microstructure-bank). This means the generated parameters are based on training from actual measured properties from 3D microstructures, not estimated from geometric simplifications. This tool was developed and is intended to replace percolation theory calculations in models that use hypothetical electrode properties. An example use case would be running SOC performance simulations across a parametric sweep of electrode designs (e.g., varying phase fractions and particle sizes) and assessing how it impacts the electrochemical performance of the SOC. Within the parameter space of the training data (statistics of that parameter space is provided in the readme file), this model achieves sub-5% mean absolute percent errors, an order of magnitude less error than percolation theory across the same parameter space. However, be aware that this tool was developed with parametric simulations in mind, and users are encouraged to assess accuracy for their own specific use case rather than taking accuracy metrics at face value. More info, including a usage guide, is in the included readme file. This tool should be cited with the DOI number provided.
Electrode Microstructure↗
Status Report on Development of a Cask to Enable Pulsed Neutron Characterization of Irradiated Fuel
We present the design of a shielding cask that allows pulsed neutron characterization of irradiated fuel rodlets prior to their destructive examination in hot cells. The goal is to provide complementary and informative measurements that will inform subsequent hot cell PIE examinations by identifying typical and atypical regions with respect to microstructure, tomographic data, or isotope densities. Time-of-flight neutron diffraction has the potential to offer efficient, non-destructive and non-contact microstructural characterization of irradiated fuel pins with spatial resolution of 1 mm3 to 1 cm3 while for energy-resolved neutron imaging (and by extension tomography) a resolution of 100 μm was demonstrated. The potential results include crystallinity vs. amorphous volumes and microstructural information such as phase compositions and textures from the diffraction data as well as distances (e.g. pellet to cladding), cracks, and isotopic distributions of minor actinides, fission products as well as fission gas partial pressures e.g. in the plenum from energy resolved neutron imaging. The capability will identify regions of atypical behavior and provide cost effective bulk characterization of entire samples prior to destructive evaluation in hot cells. This effort is a collaboration between LANL, INL, ORNL, and UC Berkeley. A key facet of the initiative is the ability to cost effectively ship irradiated fuels from INL to the pulsed spallation neutron source at LANSCE. The irradiated fuel would be loaded in the custom designed cask (designated RaMHaM) at INL hot cells which then could be shipped in a BRR Type B shipment container between INL and LANL. No hot cell is required after the loading of the sample at INL in the pathway laid out in this report, greatly simplifying handling at LANL.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Modeling Time-Dependent Surrogates of Additive-Manufactured Nuclear Fuels Processes
Additive manufacturing (AM) technology is being increasingly adopted in a wide variety of application areas for its ability to rapidly produce, prototype, and customize designs. Recently, a hybrid AM technique was successfully developed at Idaho National Laboratory (INL) to manufacture nuclear fuels [1]. Despite the advantages, this AM technique needs optimization due to defects from a highly complex melting and sintering process. The complex metallurgical phenomena during AM processes are strongly related to parameters such as applied laser power, traveling speed, and scan style, which could lead to differences in density, residual stress, crystallographic texture, and mechanical properties. In addition, stochastic variations in laser energy interaction and associated multiscale/multiphysics phenomena cause variations in microstructure evolution and mechanical properties. Currently, researchers at INL are focusing on developing a comprehensive modeling framework, leveraging INL’s simulation tools MOOSE/MARMOT/BISON/RAVEN [2-4] to describe all steps of this AM process across multiple length scales. Although this advanced framework plays a critical role in enabling enhancements to traditional trial and error approaches for design and optimization of nuclear fuel materials, it remains computationally intense, limiting its use in sensitivity and optimization analysis. In this case, an accurate and inexpensive surrogate becomes an effective tool for providing a tractable approximation of the underlying underline physics. Surrogate models generally not based on the physics of a system are purely mathematical models used to capture the relationships between specific system inputs and outputs. Popular approaches, including neural networks [5], response surfaces [6], and subspace-based reduced order models [7], have been applied to a wide range of disciplines, such as nuclear reactor design, aerospace design and automotive design. In this summary, we employ advanced time-dependent surrogate models such as high-dimensional model representation (HDMR) [8] and physics-informed deep neural network (PINNs) [9] to accelerate the design and optimization of AM process.
42 ENGINEERING↗
3D printed carbon fiber reinforced carbon as an energy efficient alternative to graphite for EFAS tooling
As Electric Field Assisted Sintering (EFAS) gains more industrial acceptance and use, it becomes more important to develop more efficient means to implement this technology. To this aim, 3D printed continuous carbon fiber reinforced carbon (CCC) was manufactured and fabricated into tooling for EFAS systems as an alternative to traditional graphite tooling. The impact of fiber orientation on the thermal and electrical properties of the CCC was characterized. Sample material was sintered in Tokai G535 graphite tooling, under common processing conditions and compared with CCC tooling. There was nearly 50 % energy savings compared to graphite while maintaining equivalent sample density and microstructure plus keeping ram temperatures 39 % cooler. This is due to spatial control of generated heat and thermal diffusivity within the molds, by means of fiber orientation anisotropy. Finite element modeling of the tooling design supported the experimental results as well as displays the effect of optimization of this 3D printed CCC material.
36 MATERIALS SCIENCE↗
Neutron irradiation-enhanced grain growth in tungsten and tungsten alloys
Herein, to understand the microstructural stability of candidate plasma-facing materials under fusion-relevant environments, neutron irradiation of W and W-3%Re alloys with and without K and La dopants was performed in the mixed-spectrum High Flux Isotope Reactor at nominal temperatures of ~850 °C and ~1100 °C to calculated doses between 0.42 and 0.47 dpa. To the best of our knowledge, this study presents the first experimental evidence of radiation-enhanced recrystallization in W and undoped W–Re alloys at ~850 °C, conditions where thermal annealing does not cause any grain growth in a similar timescale. Potassium- or lanthanum-doped tungsten alloys showed more resistance to radiation-enhanced grain growth. We explain the acceleration of grain growth by analyzing the self-diffusion constant under atomic displacement environments. The microstructural observations of the studied W variants suggest that La doping is more effective than K doping for mitigating recrystallization. This study also found that radiation-enhanced recrystallization is an important consideration when designing and applying W to plasma-facing components in future nuclear fusion reactors.
36 MATERIALS SCIENCE↗
High spatial resolution neutron imaging of lithium-ion batteries: Correlating microstructure and lithium transport
Thick electrodes for lithium-ion batteries can increase the overall energy density, but increasing the electrode thickness introduces charge transport limitations. These limitations may be mitigated through proper electrode structuring. Here, high spatial resolution neutron imaging was used to understand the correlation between microstructure and lithium transport in lithium-ion anodes. Batteries with distinct graphite anode microstructures were produced and studied with high spatial resolution in operando neutron radiography to observe the effects of structure on transport. High spatial resolution neutron computed tomography was performed following in operando neutron radiography. X-ray computed tomography and scanning electron microscopy were used to observe the finer scale anode structure to complement neutron imaging. Solvent-free anodes containing a tightly-packed layered structure confined lithium movement close to the separator. This structure limited capacity, but supported better rate capability. Conversely, a more open pore structure in the wet cast anodes yielded higher capacity with reduced rate capability. Together, these results show that lithium distributions can be controlled by the macroscopic structure of the electrodes, the microstructural pore network, and the microscale active areas that support electrochemical reactions. Furthermore, multimodal imaging applying the complementary strengths of neutron and X-ray methods is shown as a tool for advancing battery design.
25 ENERGY STORAGE↗
Additive manufacturing of nickel-based superalloys: A state-of-the-art review on process-structure-defect-property relationship
Fusion-based additive manufacturing (AM) has significantly grown to fabricate Nickel-based superalloys with design freedom across multiple length scales. Several phenomena such as feedstock/energy source/melt pool interactions, solidification and phase transformations occur during fusion-based AM processes of Nickel-based superalloys, which determine the ultimate microstructure and mechanical performance of the built parts. In this review, here we elaborate a comprehensive discussion on AM Nickel-based superalloys and influential factors including feedstock characteristics (powder morphology, chemistry, contamination, flowability, recycling) and AM processing (parameters, and powder spreading/wall/balling/spattering effects) on their microstructure (micro-segregation, phases formations and grain structures), defect generation (sub-surface/internal defects, microcracks, surface roughness, and residual stress). Furthermore, the mechanical properties of AM Nickel-based superalloys such as tensile, creep and fatigue at room/elevated temperatures are analyzed in accordance with the initial, and post processing effects. Additionally, the commonly utilized modeling approaches in literature to predict the microstructure and mechanical behavior of these alloys are highlighted. Finally, the current challenges and mitigation approaches for future research are identified considering the gaps in the AM Nickel-based superalloys.
36 MATERIALS SCIENCE↗
Methodology of Atomic Force Microscopy Visualization of Electrode–Electrolyte Interfaces
Electrochemical atomic force microscopy (EC-AFM) provides unprecedented insights into the microstructure of electrode–electrolyte interfaces during electrochemical reactions. However, performing EC-AFM measurements has many challenges, for example, drift, contamination, and probe degradation. We present solutions to these experimental issues through electrochemical cell design and carefully chosen experimental parameters. The possibility that the probes can react with the interface during scanning, generating false-positive electrochemical dynamics, is discussed as an example of the challenge of high-fidelity EC-AFM measurement. Here, we demonstrate this effect in highly ordered pyrolytic graphite and show that we could use electrochemical control of the AFM probe to enable high-fidelity in situ AFM visualization of solid–liquid interfaces during electrochemical reactions.
Electrochemical cells↗
Summary of BISON Development and Validation Activities - NEAMS FY15 Report
The objective of the NEAMS ToolKit is to develop a “pellet-to-plant” simulation capability useful for predicting performance and safety for a broad range of nuclear reactor power systems. The NEAMS ToolKit has been organized into a Fuels Product Line (FPL) and a Reactor Product Line (RPL) and is modular in design. Within the FPL, a multiscale approach has been adopted in which simulations of fuel performance at the engineering scale are informed by material property and irradiation performance models developed from mesoscale simulations of microstructural evolution. The focus in this report is on development and validation of the engineering-scale fuel performance analysis tool within the FPL, which is BISON. This summary report contains an overview of work performed under the work package enti- tled “FY2015 NEAMS INL-Engineering Scale Fuel Performance & Interface with RPL Tools.” A first chapter identifies the specific FY-15 milestones, providing a basic description of the asso- ciated work and references to related detailed documentation. Where applicable, a representative technical result is provided. A second chapter summarizes major additional accomplishments including 1) a BISON validation paper, 2) a multiphysics coupling paper, 3) application of BI- SON to Reactivity Insertion Accident analysis and 4) use of BISON for uncertainity analysis in fuel modeling. A final chapter outlines FY-16 future work.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Sphere-by-Sphere Manufacturing of 3D Microscale Granular Materials
Two of the central challenges in the mechanical design of components in nuclear systems are the dissipation of energy from external shocks and the localization of energy in energetic materials. This research seeks to address these problems by developing a patterned granular microstructure that can be optimized to direct or impede the transfer of energy carried by stress waves. Such structures require the development of a manufacturing technique that can yield perfectly ordered lattices. Two branches of research are detailed here: the development of a sphere-by-sphere additive manufacturing technique, and the development of a framework for modeling the technique in order to guide future improvements. Proof of concept of the method is demonstrated, and recommendations for future work are made.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Physics-Based Modeling and Simulation of Self-Reacting Friction Stir Welding Using Computational Fluid Dynamics
A physics-based model was developed to simulate the behavior of material in a self-reacting friction stir welding (SR-FSW) process for the joining of metals. This steady-state model builds upon fundamental computational fluid dynamic (CFD) principles within Ansys Fluent to solve the discretized equations. The effective viscosity is calculated using a viscoplastic model using a Sheppard-Wright formulation of flow stress. Numerous advancements have been made in the incorporated physics including (1) temperature-dependent material properties; (2) locally adaptable flow and thermal boundary conditions; and (3) adapting material properties in nugget in response to microstructural changes. Simulation strategies to accelerate computation and improve numerical stability include adapting the mesh refinement and solver relaxation factors during simulation. The result is a highly robust and computationally efficient model capable of providing the material flow and temperature history across the domain. As material history determines the local microstructure and ultimately weld strength, an accurate and detailed physics-based model has the potential to accelerate SR-FSW process development. The model is highly adaptable to changes in process parameters, tool design, or alloy.
Process Modeling↗
Overview of C/C-SiC Composite Development for the Orion Launch Abort System
Past and present efforts by the authors to further understanding of the ceramic matrix composite (CMC) material used in the valve components of the Orion Launch Abort System (LAS) Attitude Control Motor (ACM) will be presented. The LAS is designed to quickly lift the Orion Crew Exploration Vehicle (CEV) away from its launch vehicle in emergency abort scenarios. The ACM is a solid rocket motor which utilizes eight throttleable nozzles to maintain proper orientation of the CEV during abort operations. Launch abort systems have not been available for use by NASA on manned launches since the last Apollo ]Saturn launch in 1975. The CMC material, carbon-carbon/silicon-carbide (C/C-SiC), is manufactured by Fiber Materials, Inc. and consists of a rigid 4-directional carbon-fiber tow weave reinforced with a mixed carbon plus SiC matrix. Several valve and full system (8-valve) static motor tests have been conducted by the motor vendor. The culmination of these tests was the successful flight test of the Orion LAS Pad Abort One (PA ]1) vehicle on May 6, 2010. Due to the fast pace of the LAS development program, NASA Marshall Space Flight Center assisted the LAS community by performing a series of material and component evaluations using fired hardware from valve and full ]system development motor tests, and from the PA-1 flight ACM motor. Information will be presented on the structure of the C/C-SiC material, as well as the efficacy of various non ]destructive evaluation (NDE) techniques, including but not limited to: radiography, computed tomography, nanofocus computed tomography, and X-ray transmission microscopy. Examinations of the microstructure of the material via scanning electron microscopy and energy dispersive spectroscopy will also be discussed. The findings resulting from the subject effort are assisting the LAS Project in risk assessments and in possible modifications to the final ACM operational design.
Allen, Lee R.↗
Microstructural Analysis of Additively Manufactured 304L Stainless Steel Oxide Dispersion Strengthened Alloy
Selective laser melting (SLM) is one of the additive manufacturing (AM) process that utilizes laser for selectively melting and fusing of a thin layer of powder. This technique allows manufacturing a part directly from computer-aided design (CAD) models by dividing the part into a set of two-dimensional slices, which are built sequentially on top of another. Here, SLM technology enables manufacturing of complex geometries, such as parts with inner cooling channels which could be difficult or time consuming to make by conventional manufacturing processes.
36 MATERIALS SCIENCE↗
Chapter 4: Physically informed deep learning networks for simulating microstructure evolution of 3D polycrystals
As discussed in the previous chapter, high energy diffraction microscopy (HEDM) is used to study the micromechanical evolution of a material during in situ loading. HEDM experiments have been used to verify crystal plasticity (CP) simulations [119, 91, 90, 120], for experimental planning, material design, and to further analyze experimental results. However, Fast Fourier transform-based CP (CP-FFT) or finite element-based CP (CP-FE) methods are often too slow to be used in real-time during an experiment. CP-FFT is faster than CP-FE simulations due to the absence of meshing, but can still take hours to simulate the response of a single volume depending on the size and number of strain steps [127]. Reducing computation time would create a larger exploration space in planning and design, and enable faster analysis of experimental results and real-time feedback during an experiment. This research expands upon previous works to develop a workflow for predicting the full-field evolution of a 3D polycrystal. The workflow is simplified from previous works to predict only orientation and elastic strain tensors (from which stress tensors are calculated). The network is physically informed through loss functions and network architecture for a more robust model. The orientation predictions are informed about the cubic crystal symmetry of the material by incorporating disorientation and misorientation information into the network architecture and loss. The Von Mises stress is used to enforce the correct stress-strain trends in the strain tensor predictions. Additional total strain steps from the elastic and elastoplastic region are included to better capture the stress-strain evolution at smaller total strain steps. Material and hardening parameters are additional inputs into the networks to further inform the network and to study the network’s ability to predict different materials other than those used for training.
36 MATERIALS SCIENCE↗
Friction Stir Weld Inspection Through Conductivity Imaging Using Shaped Field MWM(TM)-Arrays
Friction Stir Welds (FSW) of A1 2195-T8 and A1 2219-T8, provided by Lockheed Martin Michoud Operations, were inspected for lack-of-penetration (LOP) defects using a custom designed MWM-Array, a multi-element eddy-current sensor. MWM electrical conductivity mapping demonstrated high sensitivity to LOP as small as 0.75 mm (0.03 in.), as confirmed by metallographic data that characterized the extent of LOP defects. High sensitivity and high spatial resolution was achieved via a 37-element custom designed MWM-Array allowing LOP detection using the normalized longitudinal component of the MWM measured conductivity. This permitted both LOP detection and correlation of MWM conductivity features with the LOP defect size, as changes in conductivity were apparently associated with metallurgical features within the near-surface layer of the LOP defect zone. MWM conductivity mapping reveals information similar to macroetching as the MWM-Array is sensitive to small changes in conductivity due to changes in microstructure associated with material thermal processing, in this case welding. The electrical conductivity measured on the root side of FSWs varies across the weld due to microstructural differences introduced by the FSW process, as well as those caused by planar flaws. Weld metal, i.e., dynamically recrystallized zone (DXZ), thermomechanically affected zone (TMZ), heat-affected zone (HAZ), and parent metal (PM) are all evident in the conductivity maps. While prior efforts had met with limited success for NDE of dissimilar alloy, A12219 to A12195 FSW, the new custom designed multi-element MWM-Array achieved detection of all LOP defects even in dissimilar metal welds.
Goldfine, Neil↗
Designing Advanced Ceramic Waste Forms for Electrochemical Processing Salt Waste
This report describes the scientific basis underlying the approach being followed to design and develop “advanced” glass-bonded sodalite ceramic waste form (ACWF) materials that can (1) accommodate higher salt waste loadings than the waste form developed in the 1990s for EBR-II waste salt and (2) provide greater flexibility for immobilizing extreme waste salt compositions. This is accomplished by using a binder glass having a much higher Na 2 O content than glass compositions used previously to provide enough Na+ to react with all of the Cl– in the waste salt and generate the maximum amount of sodalite. The phase compositions and degradation behaviors of prototype ACWF products that were made using five new binder glass formulations and with 11-14 mass% representative LiCl/KCl-based salt waste were evaluated and compared with results of similar tests run with CWF products made using the original binder glass with 8 mass% of the same salt to demonstrate the approach and select a composition for further studies. About twice the amount of sodalite was generated in all ACWF materials and the microstructures and degradation behaviors confirmed our understanding of the reactions occurring during waste form production and the efficacy of the approach. However, the porosities of the resulting ACWF materials were higher than is desired. These results indicate the capacity of these ACWF waste forms to accommodate LiCl/KCl-based salt wastes becomes limited by porosity due to the low glass-to-sodalite volume ratio. Three of the new binder glass compositions were acceptable and there is no benefit to further increasing the Na content as initially planned. Instead, further studies are needed to develop and evaluate alternative production methods to decrease the porosity, such as by increasing the amount of binder glass in the formulation or by processing waste forms in a hot isostatic press. Increasing the amount of binder glass to eliminate porosity will decrease the waste loading from about 12% to 10% on a mass basis, but this will not significantly impact the waste loading on a volume basis. It is likely that heat output will limit the amount of waste salt that can be accommodated in a waste canister rather than the salt loading in an ACWF, and that the increase from 8 mass% to about 10 mass% salt loadings in ACWF materials will be sufficient to optimize these waste forms. Although the waste salt composition used in this study contained a moderate amount of NaCl, the test results suggest waste salts with little or no NaCl can be accommodated in ACWF materials by using the new binder glass, albeit at waste loadings lower than 8 mass%. The higher glass contents that will be required for ACWF materials made with salt wastes that do not contain NaCl are expected to result in much lower porosities in those waste forms.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Characterization of the degradation of gamma-irradiated elastomers using Raman spectroscopy
This report presents key findings from Raman spectroscopic analysis of gamma-irradiated rubber samples extracted from a laminated lead-damped rubber (LDR) seismic isolation device. The samples were exposed to gamma radiation from a 60Co source in a Foss Therapy Services gamma irradiator, reaching absorbed doses up to 1600 kGy. A distinct threshold near 400 kGy was identified, beyond which significant spectral changes were observed. Two Raman peaks - at approximately 425 cm-1 and 2440 cm-1 - were tracked as a function of dose using Gaussian fitting. The 425 cm-1 peak, attributed to sulfur–sulfur (S–S) bond stretching (resulting from vulcanization of the rubber), exhibited a dose-dependent upshift, indicating radiation-induced crosslinking within the sulfur-based polymer network. Conversely, the 2440 cm-1 peak, likely associated with vibrational modes of additives or impurities, showed a downward shift with increasing dose, suggesting chain scission and degradation of non-rubber constituents. These results provide first-of-a-kind insights into the microstructural evolution of elastomers under high-dose gamma irradiation and establish a preliminary dose threshold for significant degradation. Future work will incorporate multi-modal characterization—including Fourier Transform Infrared (FTIR) spectroscopy, scanning electrom microscopy (SEM) of the rubber surface morphology, thermogravimetric analysis (TGA) to determine changes in thermal stability, and mechanical testing—to correlate molecular-level changes with macroscopic performance of these elastomers as damping media in seismic isolation devices. These findings are expected to provide regulatory guidance and design criteria for qualifying low-damping rubber seismic isolators in advanced nuclear reactor applications.
36 - MATERIALS SCIENCE↗