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At least 721 records · Page 40

Digital polycrystalline microstructure generation using diffusion probabilistic models

Accurate micromechanical simulation of polycrystalline materials requires a realistic digital representation of the grain scale microstructure. Here, this work demonstrates the use of a generative diffusion probabilistic model for synthesizing single phase polycrystalline realizations. The model performs well and is capable of producing realistic microstructures consisting of not just simple equiaxed structures but also structures exhibiting more complex spatial arrangements. Masked microstructure generation reveals that the model is context aware of morphological descriptors which may be encoded in the latent space. Training on more diverse data sets, with scaled up architectures, may enable development of future models capable of synthesizing even more complex microstructural features.

36 MATERIALS SCIENCE↗

Simulated effects of sample size and grain neighborhood on the modeling of extreme value fatigue response

Assessing the size of representative volume elements (RVEs) for fatigue-related applications is challenging. A RVE relevant to random microstructure requires a volume of material that is sufficiently large to capture the grain/phase heterogeneity that captures all statistical moments of the distribution of the driving force for fatigue crack formation at “hot spot” grains. Consequently, the large size of a microstructure RVE required to study fatigue phenomena is largely computationally intractable and difficult to explore. A more realistic objective in this work is to systematically study, as a function of the size of a statistical sample of microstructure, trends towards convergence of the simulated distribution of driving force for fatigue crack formation. Our present work accordingly leverages the recently developed open-source PRISMS-Fatigue framework to examine the trends in convergence of extreme value distributions (EVD) of Fatigue Indicator Parameters (FIPs) in progressively larger polycrystalline microstructure realizations of FCC Al alloy 7075-T6 using crystal plasticity finite element method simulations. The results are compared to the traditional method in which ensembles of statistical volume elements (SVEs) are simulated to build up statistics intended to approximate those associated with a larger volume of material. The convergence of EVDs with increase of size of a SVE of microstructure is closely related to the extent of grain nearest neighbor (NN) interactions. Accordingly, the sensitivity of the local micromechanical response at hot spot grains is quantitatively investigated by systematically varying the orientations of NN grains. Results indicate that SVEs with cubic crystallographic texture tend towards convergence of the EVD of FIPs with tens of thousands of grains while the random and rolled textures require larger volumes. Simple relationships based on microstructure parameters (e.g., Schmid Factor, grain size, NN misorientation) do not completely correlate to fatigue hot spot grains. Finally, the sensitivity of the extreme value fatigue response at hot spot grains extends to the 3rd NN when a single neighborhood grain orientation is altered.

36 MATERIALS SCIENCE↗

Dynamic Scaling Analysis of Accelerated Irradiation Testing on Additive Manufacturing Materials by Positron Annihilation

The timely applications of Additive Manufacturing (AM) materials in nuclear environments require accelerated irradiation tests, mainly ion irradiation to enable rapid prototyping. Low dose ion irradiation would cause sub-nanostructure changes by generation of lattice defects, vacancies, vacancy clusters and voids and void swelling caused by cellular dislocations. Positron Annihilation Lifetime (PAL), a novel technology, sensitive towards sub-nanostructure morphology with high accuracy (about 10-7 vacancy per atom), supported by Transition Electron Microscope (TEM) would be applied to identify the type and total size of the defects. The subsequent PAL measurements and TEM surface studies would be followed by PAL analysis that includes sophisticated trapping model. The PAS results would become an input to dynamic scaling analysis (that predicts radiation effects from low dose studies for high dose effects), which incorporate mean-field theory model. The final effect is an in-depth understanding of the microstructure evolution of AM materials under ion irradiation which can be extrapolated to the studies of neutron irradiation, since ion-irradiation takes less time and do not cause the irradiation hazard. The working hypothesis is that PAL technology, that have excellent sensitivity to low-defect concentration would help to identify ion-induced material damage on the atomic and nano-scale level, which then could be extrapolated to understand the neutron damage better.

accelerated irradiation testing↗

Evaluation of DED and LPBF Fe-based Alloys Process Application Envelopes based on Performance, Process Economics, Supply Chain Risks, and Reactor-specific Targeted Components

The U.S. Department of Energy (DOE), Office of Nuclear Energy (NE), Advanced Materials and Manufacturing Technologies (AMMT) program aims to develop extreme-environment materials solutions for use in the deployment of advanced nuclear reactors and the sustainment of the current fleet. To achieve this objective, a combination of experiment, a computational tool, and machine learning (ML) for the design of materials is adopted for the maturation of materials for nuclear technology. Through advanced manufacturing techniques such as laser powder bed fusion (LPBF) and laser powder direct energy deposition (LP-DED), components with complex geometries can be fabricated with reduced time and effort. Such advanced manufacturing methods can also provide the opportunity to improve materials performance through optimized microstructures and mechanical properties. However, existing engineering alloys are not always well suited for fabrication with additive manufacturing (AM), as their compositions have been tuned to optimize fabrication via conventional methods. Thus, similar alloys with modified compositions that are better suited for AM can be studied for improved performance. Over the past three years, the AMMT teams from Argonne National Laboratory (ANL) and Pacific Northwest National Laboratory (PNNL) studied various known Fe-based alloys by evaluating their initial printability using LPBF, and an AMMT-developed down-selection and decision matrix reduced the number of alloys to be studied from six to three in fiscal year (FY) 2024. Additionally, in FY 2024, for parallel evaluation, these three alloys were studied using LPDED. While LPBF is better for small- to medium-sized components with high detail and internal features, LP-DED combines a material feed system to place the powder onto the exact spot where the laser will melt the material. This AM method can be easily scaled to extremely large components and provides high build rate speeds compared to those of conventional LPBF systems. Additionally, DED is a better choice for complex geometries and compositional gradients.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Tailoring plasticity mechanisms in compositionally graded hierarchical steels fabricated using additive manufacturing

Abstract While there exists in nature abundant examples of materials with site-specific gradients in microstructures and properties, engineers and designers have traditionally used monolithic materials with discrete properties. Now, however, additive manufacturing (AM) offers the possibility of creating structures that mimic some aspects of nature. One example that has attracted attention in the recent years is the hierarchical structure in bamboo. The hierarchical architecture in bamboo is characterized by spatial gradients in properties and microstructures and is well suited to accommodate and survive complex stress states, severe mechanical forces, and large deformations. While AM has been used routinely to fabricate functionally graded materials, this study distinguishes itself by leveraging AM and physical metallurgy concepts to trigger cascading deformation in a single sample. Specifically, we have been successful in using AM to fabricate steel with unique spatial hierarchies in structure and property to emulate the structure and deformation mechanisms in natural materials. This study shows an improvement in the strength and ductility of the nature-inspired “hierarchical steel” compared with conventional cast stainless steels. In situ characterization proves that this improvement is due to the sequential activation of multiple deformation mechanisms namely twinning, transformation-induced plasticity, and dislocation-based plasticity. While significantly higher strengths can be achieved by refining the chemical and processing technique, this study sets the stage to achieve the paradigm of using AM to fabricate structures which emulate the flexibility in mechanical properties of natural materials and are able to adapt to in-service conditions.

36 MATERIALS SCIENCE↗

In situ synchrotron tensile investigations on ultrasonic additive manufactured (UAM) zirconium

The microstructure evolution during room temperature uniaxial tensile straining of ultrasonic additive manufactured (UAM) zirconium was evaluated using the Advanced Photon Source (APS) facility. Miniature dog-bone tensile specimens of two orientations were cut from a UAM-fabricated zirconium bar for in situ synchrotron tensile tests. Wide-angle X-ray scattering (WAXS) scanning was used to unveil the changes in microstructure of the entire gauge regions throughout the straining. A series of WAXS data analysis methods were utilized to quantify both elastic and plastic deformation mechanisms within the strained specimens. Stress concentrations were identified during early stages of plastic deformation, which become candidate necking positions and eventually lead to failure. Additionally, fracture surface analysis implied that these stress concentration locations may be correlated to the fabrication defects, providing insightful guidance for future improvements of the UAM zirconium fabrication process.

36 MATERIALS SCIENCE↗

Grain Boundary Phases in NbFeSb Half‐Heusler Alloys: A New Avenue to Tune Transport Properties of Thermoelectric Materials

Abstract Many thermoelectric materials benefit from complex microstructures. Grain boundaries (GBs) in nanocrystalline thermoelectrics cause desirable reduction in the thermal conductivity by scattering phonons, but often lead to unwanted loss in the electrical conductivity by scattering charge carriers. Therefore, modifying GBs to suppress their electrical resistivity plays a pivotal role in the enhancement of thermoelectric performance, zT . In this work, different characteristics of GB phases in Ti‐doped NbFeSb half‐Heusler compounds are revealed using a combination of scanning transmission electron microscopy and atom probe tomography. The GB phases adopt a hexagonal close‐packed lattice, which is structurally distinct from the half‐Heusler grains. Enrichment of Fe is found at GBs in Nb 0.95 Ti 0.05 FeSb, but accumulation of Ti dopants at GBs in Nb 0.80 Ti 0.20 FeSb, correlating to the bad and good electrical conductivity of the respective GBs. Such resistive to conductive GB phase transition opens up new design space to decouple the intertwined electronic and phononic transport in thermoelectric materials.

36 MATERIALS SCIENCE↗

Using machine-learning to understand complex microstructural effects on the mechanical behavior of Ti-6Al-4V alloys

Structural materials properties are highly dependent on their microstructure. Their microstructure is in turn affected by multiple fabrication and thermo-mechanical treatment parameters, all of which conform a highly-dimensional parametric space with often hidden correlations that are difficult to extract by experimentation alone. This is particularly true for alloys of the dual-phase Ti-6Al-4V family, with their greatly complex and rich microstructures, which combine several intrinsic length scales associated with multiple grain and subgrain structures, grains with different crystal lattices (α and β phases), and complex chemistry. In this paper we use a comprehensive set of machine learning techniques to develop predictive tools relating the yield strength and hardening rate of these alloys to a set of input parameters covering extensive ranges. The data generator is a finite-element crystal plasticity model for polycrystal deformation that takes into account slip anisotropy and employs standard dislocation evolution models for the α and β phases of Ti-based alloys. Our dataset includes over two thousand independent simulations and is used to train the machine learning models, which are then used to establish correlations between microstructural parameters and the alloys’ mechanical response. Our results point to the most influential parameters affecting yield strength and hardening rate, information that can then be used to guide experimental synthesis and characterization efforts to save time and resources.

36 MATERIALS SCIENCE↗

Degradation of solid oxide electrolysis cells: Phenomena, mechanisms, and emerging mitigation strategies—A review

Solid oxide electrolysis cell (SOEC) is a promising electrochemical device with high efficiency for energy storage and conversion. However, the degradation of SOEC is a significant barrier to commercial viability. In this review article, the typical degradation phenomena of SOEC are summarized, with great attention into the anodes/oxygen electrodes, including the commonly used and newly developed anode materials. Meanwhile, mechanistic investigations on the electrode/electrolyte interfaces are provided to unveil how the intrinsic factor, oxygen partial pressure , and the electrochemical operation conditions, affect the interfacial stability of SOEC. At last, this paper also presents some emerging mitigation strategies to circumvent long-term degradation, which include novel infiltration method, development of new anode materials and engineering of the microstructure.

36 MATERIALS SCIENCE↗

From classical thermodynamics to phase-field method

Phase-field method is a density-based computational method at the mesoscale for modeling and predicting the temporal microstructure and property evolution during materials processes. The focus of this article is on connecting the most common phase-field equations to the very basic first and second laws of classical thermodynamics through rudimentary irreversible thermodynamics. It briefly discusses the relations of the continuum phase-field equations to their counter parts at the microscopic and atomic levels. It attempts to clarify the contributions of long-range elastic, electrostatic, and magnetic interactions to domain structure evolution during structural, ferroelectric, and ferromagnetic phase transformations by separating order parameter changes due to the presence of quasi-static fields and those arising from phase transformations. A few examples are presented to demonstrate the possibility of employing the phase-field method to provide guidance to designing materials for optimum properties or discovering novel mesoscale phenomena or new materials functionalities. Here, the article ends with a brief perspective on a number of potential future directions on the development and applications of phase-field method beyond its traditional applications to structural alloys.

36 MATERIALS SCIENCE↗

Robust Interfacial Effect in Multi-interface Environment through Hybrid Reconstruction Chemistry for Enhanced Energy Storage

Electrochemical-oxidation-driven reconstruction has emerged as an efficient approach for developing advanced materials, but the reconstructed microstructure still faces challenges including inferior conductivity, unsatisfying intrinsic activity, and active-species dissolution. In this report we present hybrid reconstruction chemistry that synergistically couples electrochemical oxidation with electrochemical polymerization (EOEP) to overcome these constraints. During the EOEP process, the metal hydroxides undergo rapid reconstruction and dynamically couple with polypyrrole (PPy), resulting in an interface-enriched microenvironment. We observe that the interaction between PPy and the reconstructed metal center (i.e., Mn > Ni, Co) is strongly correlated. Theoretical calculation results demonstrate that the strong interaction between Mn sites and PPy breaks the intrinsic limitation of MnO 2 , rendering MnO 2 with a metallic property for fast charge transfer and enhancing the ion-adsorption dynamics. Operando Raman measurement confirms the promise of EOEP-treated Mn(OH) 2 (E-MO/PPy) to stably work under a 1.2 V potential window. The tailored E-MO/PPy exhibits a high capacitance of 296 F g –1 at a large current density of 100 A g –1 . Here our strategy presents breakthroughs in upgrading the electrochemical reconstruction technique, which enables both activity and kinetics engineering of electrode materials for better performance in energy-related fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of microstructure and temperature on nuclear graphite oxidation using the 3D Random Pore Model

This work compared the 3D Random Pore Model (3D-RPM) with experimental and characterization data to systematically study the effect of nuclear graphite microstructure and air oxidation temperature. It is well known that oxidation-induced weight loss at elevated temperatures degrades graphite structure and properties; however, a fundamental understanding of the role of graphite microstructure is still unclear. In this work, three diverse grades of nuclear graphite—IG-110, NBG-18, and PCEA—were examined and tested at air oxidation temperatures of 600, 650, 700, and 750 °C following ASTM D7542. Here, the 3D-RPM reproduced the microstructure and temperature dependence of mass loss curves for these grades. For the first time, measurements and modeling were combined to show how bulk density and the amount and spatial distribution of open and closed porosity affects oxidation. IG-110 was less dense and had an open pore network that is finer and more uniformly spread, and showed fastest oxidation. PCEA porosity was less uniform and showed less oxidation, while NBG-18 was more dense, had the least fine and uniform porosity, and showed the slowest oxidation. In general, oxidation proceeds faster if open porosity is more uniformly distributed and can incrementally access closed pore surface area with more ease.

36 MATERIALS SCIENCE↗

Materials science research in microgravity

There are several important attributes of an extended duration microgravity environment that offer a new dimension in the control of the microstructure, processing, and properties of materials. First, when gravitational effects are minimized, buoyancy driven convection flows are also minimized. The flows due to density differences, brought about either by composition or temperature gradients will then be reduced or eliminated to permit a more precise control of the temperature and the composition of a melt which is critical in achieving high quality crystal growth of electronic materials or alloy structures. Secondly, body force effects such as sedimentation, hydrostatic pressure, and deformation are similarly reduced. These effects may interfere with attempts to produce uniformly dispersed or aligned second phases during melt solidification. Thirdly, operating in a microgravity environment will facilitate the containerless processing of melts to eliminate the limitations of containment for reactive melts. The noncontacting forces such as those developed from electromagnet, electrostatic, or acoustic fields can be used to position samples. With this mode of operation, contamination can be minimized to enable the study of reactive melts and to eliminate extraneous crystal nucleation so that novel crystalline structures and new glass compositions may be produced. In order to take advantage of the microgravity environment for materials research, it has become clear that reliable processing models based on a sound ground based experimental experience and an established thermophysical property data base are essential.

Perepezko, John H.↗

Using phase boundary mapping to resolve discrepancies in the Mg 2 Si–Mg 2 Sn miscibility gap

Mg 2 Si–Mg 2 Sn compositions within the Mg–Si–Sn materials system have potential as inexpensive, efficient thermoelectrics. These compositions lie specifically along the pseudobinary line with compositions of Mg 2 Si 1-x Sn x . The alloying and possible nanostructuring within the miscibility gap could further increase the thermoelectric figure of merit (zT) for these materials. However, the solubility limits of the miscibility gap differ greatly in the literature. Such a discrepancy could be a result of differing Mg-compositions due to excess magnesium added during sample annealing. To define these limits better and explain the change in proposed solubility limits based on magnesium content, the three-phase regions on either side of the pseudobinary phase region are phase boundary mapped and defect energy calculations are performed. This study presents a new understanding of the Mg–Si–Sn ternary phase diagram around the pseudobinary phase region. The solubility limits on either side of the pseudobinary should be essentially identical between the Mg-rich and Mg-poor three-phase regions unless the system temperature is brought above about 565 °C, at which eutectic liquid Mg 0.9 Sn 0.1 forms. This creates a second Mg-rich three-phase region which intersects the pseudobinary with a lower Sn solubility. Thus, samples prepared along the pseudobinary line are not well-defined thermodynamically when excess magnesium is added. Excess Mg can push the system into a new three phase region with Mg 2 Si 1-x Sn x composition different from that of the true miscibility gap. This understanding presents new guidelines for evaluating the miscibility gap and assists strategies for microstructure engineering and thermoelectric material processing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Materials Challenges and Opportunities for Energy Generation, Conversion, Delivery, and Storage (Applied Energy Tri-Laboratory Consortium Workshop Report)

This report documents the outcomes of the Tri-Laboratory Materials Workshop that was held July 31 and August 1, 2019 to begin addressing the needs, opportunities, and challenges associated with the development, fabrication, and testing of the needed materials and components for integrated hybrid energy systems (i.e., incorporating nuclear, fossil, and renewables for electric and thermal applications). This was accomplished by assembling the research program leads and principal investigators at Idaho National Laboratory (INL), National Energy Technology Laboratory (NETL), and National Renewable Energy Laboratory (NREL), who support the research and development of new technology and system integration. The team then identified and prioritized key materials development needs. This effort was intended to enhance communications and synergy among the Tri-Lab partners. Advanced functional and structural materials are central to transformative energy technologies for energy generation, conversion, delivery, and storage. With that in mind, the workshop focused on identifying and assessing the foundational materials research needs at both the basic and applied levels. Materials challenges include the ability to withstand harsh environments, such as high temperatures and pressures, corrosion, oxidation, or irradiation while maintaining flexible mission profiles and long service lifespans. Advanced energy system material challenges and needs range from materials for the capture, upgrading/concentration, storage, and delivery of low-grade heat to materials for high temperature environments that involve liquid metals, molten salt, and very high temperature gas heat delivery and storage systems. Material improvements are needed for hybrid energy systems due to accelerated corrosion and stress-fatigue failure of materials and equipment, which results from increased frequency and amplitude of thermal, mechanical, and electrical cycling of systems components. Multifunctional materials are needed for high temperature solid-oxide fuel cells, advanced electrochemical reactors, and in-process separation. Relative to materials manufacturing, application of advanced additive and subtractive methods need to be understood to develop both thin-layer homogenous materials and materials of graded composition. Materials modeling and machine learning will be critical to accelerate the design and production of power electronics, and nuclear reactor materials and fuel, as well as to gain an understanding of beneficial materials phenomena or deleterious microstructure evolution. There is also a need for standardized models, computational structures, data reporting protocols and modeling tools across the three laboratories. This would allow consistent results, analysis, and data sharing. Combining computational capabilities between the three laboratories (e.g., hardware, software) would greatly increase computational capabilities and throughput. The workshop identified the need for laboratories to anticipate and address problems that will occur during scale-up. Laboratory work must connect with industry to ensure that research focuses on processes that are scalable and marketable. Industry input and perspective are essential to guide laboratory research to meet these requirements and deploy new technology in industrial demonstrations. Another aspect of scale-up is the integration of multiple systems since new challenges often arise at the subsystem interfaces. Establishing a scale-up manufacturing demonstration/pilot plant, potentially as an industrial user facility, would be beneficial to the laboratories and industry. That modular scale-up manufacturing demonstration/pilot plant would allow researchers to find and resolve interface problems that cannot be identified by focusing only on individual parts. Communication exchanges among the organizers, attendees, and workshop survey responses indicate that the workshop was successful in achieving its goal to identify key technology gaps and research needs. Strong positive feedback was received on the sharing of ideas, capabilities, talent, and passion to move forward on the materials-related action items.

36 MATERIALS SCIENCE↗

Corrosion evaluation of Ti–6Al–4V manufactured by electron beam melting in Ringer’s physiological solution: an in vitro study of the passive film

We report that electrochemical characteristics and semiconducting behavior of additively manufactured electron beam melted (EBM) and wrought (WR) Ti–6Al–4V (Ti-G5) are compared in Ringer’s physiological solution. X-ray diffraction (XRD) and field emission scanning electron microscopy (FE-SEM) confirmed the α+β structure of the tested materials, with two different microstructure types of “bimodal” and “basket-weave” for WR and EBM, respectively. Potentiodynamic polarization (PDP) revealed that the corrosion current density for EBM (i corr =0.27±0.06 μA cm -2 ) is less than the WR (i corr =0.70±0.05 μA cm -2 ). Moreover, potentiostatic polarization (PS) that was employed to form the passive layers at three different potentials of 300, 500, and 700 mV Ag/AgCl , showed that the passive films on the EBM sample are thinner. This finding was confirmed by electrochemical impedance spectroscopy (EIS). Furthermore, through Mott–Schottky (M–S) analysis, donor densities on WR passive films were found to be ~1.5 times larger than EBM. Although PS and EIS confirmed that the passive layer on EBM is thinner, it provides higher corrosion resistance than WR. The passive layer on both samples were found to have n-type characteristics with a duplex structure.

36 MATERIALS SCIENCE↗

Tuning the fluid wetting dynamics on gold microstructures using photoactive compounds

This work demonstrates how photoactive compounds can be used to tune the surface chemistry, surface free energy, and the wetting velocity of fluids on Spiropyran functionalized surfaces with different surface microstructures. Evidence of this photowetting effect is based on data showing: (1) the cyclic changes in the static, advancing, and receding contact angles $\theta$ CA for multiple UV$\rightleftarrows$vis photoswitching cycles with both smooth and microstructured surfaces and (2) the changes in the fluid wicking velocity (via UV$\rightleftarrows$vis photoswitching) on different Spiropyran functionalized hemiwicking surfaces. X-ray photoelectron spectroscopy is used to determine the efficiency of photoswitching caused by the quality of the Spiropyran functionalization. Reversible photoisomerization of Spiropyran generates a gradient in surface free energy, resulting in a similar change in contact angle ($\theta$ CA ) in the photoswitchable surfaces. In conclusion, by incorporating these changes into the Owens-Wendt and Van Oss surface energy models, the energy of smooth Au surfaces can also be predicted for both UV and visible light irradiations, where reversible contact angle variations of $\Delta$$\theta$ CA ≈ 5–10° are achieved with both water and water-ethanol mixtures due to the conversion of SP to merocyanine, which corresponds to a total free energy change of ~13% on the photoswitchable surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Parallelized Carbon Oxidation and Surface Recession Model in Direct-Simulation Monte Carlo Code, SPARTA

Ablative thermal protection system (TPS) materials for spacecraft are composites that often consist of a carbon-based reinforcement and a polymeric matrix. During Earth re-entry, they endure high-temperature oxidation and surface recession. Oxidation is an important mechanism for ablation, sometimes leading to the weakening, spallation, or failure of the oxidized fibers at the surface and in the char layer. However, more details are required including accurate material properties of the fiber microstructure, whether the fibers recede homogenously or localized at pits, and the role of pyrolysis outgassing in order to evaluate the role oxidation plays in the degradation and failure mechanisms of these materials. In this work, we demonstrate a parallelizable oxidation-driven ablation model developed for detailed, large-scale simulations in the DSMC code SPARTA. We also develop robust algorithms which handle the conservation of the surface state after an ablation step. Finally, we verify our model for both simple and more complex chemistry as well as microstructures with reaction statistics, oxidation depth calculations, and detailed visualization of oxidation-induced material recession at the microscale.

V Arias↗