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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Recent progress on the mesoscale modeling of architected thin-films via phase-field formulations of physical vapor deposition

Thin-film coatings can be found everywhere in modern technological applications due to desirable electrical, mechanical, chemical, and optical properties. These properties directly depend upon the thin-film’s microstructural features, which are themselves influenced by the materials and vapor-deposition processing conditions used for fabrication. As such, understanding processing-microstructure relationships is essential to designing thin-films with optimized properties, and discovering new processing conditions that allow for novel thin-films with multifunctional microstructures. Here, a short review is presented on recent developments that utilize the phase-field method to simultaneously model the vapor-deposition process and corresponding microstructure formation at the mesoscale. Also phase-field-based vapor-deposition models that simulate thin-film growth of immiscible alloy and polycrystalline systems are highlighted in addition to machine-learning-based surrogate models that can facilitate accelerated high-fidelity simulations along with materials design and exploration studies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Effect of microstructural and environmental variables on ductility of austenitic stainless steels

Austenitic stainless steels are used extensively in harsh environments, including for high-pressure gaseous hydrogen service. However, the tensile ductility of this class of materials is very sensitive to materials and environmental variables. While tensile ductility is generally insufficient to qualify a material for hydrogen service, ductility is an effective tool to explore microstructural and environmental variables and their effects on hydrogen susceptibility, to inform understanding of the mechanisms of hydrogen effects in metals, and to provide insight to microstructural variables that may improve relative performance. In this study, hydrogen precharging was used to simulate high-pressure hydrogen environments to evaluate hydrogen effects on tensile properties. Several austenitic stainless steels were considered, including both metastable and stable alloys. Room temperature and subambient temperature tensile properties were evaluated with three different internal hydrogen contents for type 304L and 316L austenitic stainless steels and one hydrogen content for XM-11. Significant ductility loss was observed for both metastable and stable alloys, suggesting the stability of the austenitic phase is not sufficient to characterize the effects of hydrogen. Internal hydrogen does influence the character of deformation, which drives local damage accumulation and ultimately fracture for both metastable and stable alloys. While a quantitative description of hydrogen-assisted fracture in austenitic stainless steels remains elusive, these observations underscore the importance of the hydrogen-defect interactions and the accumulation of damage at deformation length scales.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mass transport in a highly immiscible alloy on extended shear deformation

Forced mixing to a single phase or supersaturated solid solution (SSS) and its prerequisite microstructure evolution in immiscible systems has been a focus of research for both fundamental science and a variety of applications. Controlling the formation of SSS by shear deformation assisted processing could enable a material design beyond conventional equilibrium microstructure in immiscible systems. Here, a highly immiscible (mixing enthalpy of ~ 20 kJ·mol -1 ) Cu-50 at. % Cr binary alloy was employed to investigate the microstructure evolution and localized tendencies of SSS during severe shear deformation. The present results demonstrate distinctive microstructure refinement process in each phase and how they lead to localized SSS as a function of shear strain. Preferential dynamic recrystallization occurs in the softer Cu phase due to strain localization, leading to substantial grain refinement. The refinement of Cr phase in the top-most layer, however, is enabled by the progressive evolution of grain lamination, splitting, and fragmentation as a function of shear strain. The eventual SSS is found to be strongly dependent on the local environments that affect the dislocation activity, including the level of microstructure refinement, the interfacial orientation relationship, hardness difference, and supposed stability of oxidation. Ab initio simulations comfirm that it is more favorable to oxidize Cr than Cu at incoherent Cu/Cr interfaces which then limits the mass transport on an incoherent boundary. Our results shed light on the underpinning mechanism for non-equilibrium mass transport in immiscible systems upon severe deformation that can be applicable to a variety of processing techniques aimed at producing immiscible alloys with superior mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effect of Diphenyl Content on Viscoelasticity of Poly(dimethyl- co -diphenyl)siloxane Melt and Network

Polydimethylsiloxane (PDMS) is one of the most widely used polymeric materials for sealants, adhesives, lubricants, and thermal as well as electrical insulation. At low temperatures, however, PDMS is subject to crystallization that can cause deterioration in mechanical function. A common way to suppress such crystallization is through the incorporation of phenylsiloxane into the backbone of polysiloxane. Nevertheless, the introduction of phenyl components, even in small quantities, could potentially change the properties of the siloxane in a significant way. In this work, a series of mechanical tests and finite element simulations were performed to study the macroscale viscoelasticity of two poly(dimethyl-co-diphenyl)siloxane formulations in order to understand the effects of a few percent diphenyl contents on the viscoelasticity of the polysiloxane material. Here, we utilized the small-angle X-ray scattering to investigate the microscopic structures of the copolymers and broadband dielectric spectroscopy and rheology to probe the chain dynamics at the microscale. The results of these characterizations were used to inform the finite element simulations. We found that the degree of cross-linking does not significantly alter the microstructure but can profoundly affect the viscoelastic response of the copolymer networks. The corresponding hysteretic behavior is interpreted in terms of reptation-like motion and relaxation of the effective free chains in the cured polymer network. The relaxation of the copolymer chains is slowed significantly by even a small increase in the molar ratio of the diphenyl component.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Modeling laser interactions with aluminum and tantalum targets using a hybrid atomistic-continuum model

A hybrid atomistic-continuum method can model the microstructure evolution of metals subjected to laser irradiation. This method combines classical molecular dynamics (MD) simulations with the two-temperature model (TTM) to account for the laser energy absorption and heat diffusion behavior. Accurate prediction of the temperature evolution in the combined MD-TTM method requires reliable accuracy in electron heat capacity, electron thermal conductivity, and electron–phonon coupling factor across the temperatures generated. This study uses the electronic density of states (DOS) obtained from first-principle calculations. The calculated electron temperature-dependent parameters are used in MD-TTM simulations to study the laser metal interactions in FCC and BCC metals and the phenomenon of laser shock loading and melting. This study uses FCC Al and BCC Ta as model systems to demonstrate this capability. When subjected to short pulsed laser shocks, the dynamic failure behavior predicted using temperature-dependent parameters is compared with the experimentally reported single-crystal and nanocrystalline Al and Ta systems. The MD-TTM simulations also investigate laser ablation and melting behavior of Ta to compare with the ablation threshold reported experimentally. In conclusion, this manuscript demonstrates that integrating the temperature-dependent parameters into MD-TTM simulations leads to the accurate modeling of the laser–metal interaction and allows the prediction of the kinetics of the solid–liquid interface.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Modeling of flash sintering of ionic ceramics

A fundamental understanding of the influence of defects in ionic ceramics at the atomic, microstructural, and macroscopic levels, before, during, and after the flash sintering event is key to the development of ceramic processing operations that lead to fast, low cost, and environmentally safe fabrication of materials. The observed phenomenology of the flash process encompasses multiple time and length scales and have resulted on a wide variety of what sometimes appears to be contradictory explanations. Here, this article summarizes the latest developments on the modeling and simulation of flash sintering, specifically those related to the understanding of the equilibrium and kinetic properties and the corresponding microstructural evolution of ionic ceramics. Challenges and opportunities in the development of theoretical analyses that include unidentified multiphysical effects are discussed, as they pertain to the processing of technologically relevant ceramic materials for advanced structures and devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

High-pressure phase transitions in a laser directed energy deposited Fe-33Cu Alloy

Here, additively manufactured Fe-Cu alloys contain both equilibrium face-centered cubic (FCC) and metastable body-centered cubic (BCC) crystal structure Cu precipitates depending on their size. However, the stability of these nanoscale precipitates under extreme conditions such as high pressures has not been reported. This study investigates the phase transformations and microstructural stability of laser directed energy deposition (DED-LB) made Fe67Cu33 alloy (nominal composition in at.%) under high static pressure deformation using in-situ synchrotron X-ray diffraction under pressure, postmortem high-resolution scanning transmission electron microscopy (HR-STEM), and molecular dynamics (MD) simulations. In-situ XRD results reveal a reversible phase transformation from BCC to the hexagonal close-packed (HCP) structure in the Fe grains at an onset pressure of 16.4 GPa, significantly higher than reported in the literature for pure Fe. Although no high-pressure phase transition was observed in the FCC Cu grains through XRD, HR-STEM analysis uncovers a phase transition to the HCP structure in nanoscale metastable BCC Cu precipitates within the BCC Fe matrix. After decompression, the Fe matrix reverted back to the BCC structure with periodic lath martensite, while regions of the nanoscale BCC Cu precipitates retained the metastable HCP structure. MD simulations support the BCC → HCP transition in the embedded nanoscale coherent Cu precipitates, consistent with the classical Burgers mechanism. Thus, by leveraging in-situ XRD observation, postmortem high-resolution S/TEM microscopy, and MD simulations, this study offers profound insights into the distinctive phase transformations induced by high pressure in DED-LB Fe67Cu33 alloy, which is distinguished by its hierarchical microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Design of novel refractory equiatomic multi-principal elemental alloys based on Mo-Nb-Ti system for Gen IV reactor applications

Excellent irradiation damage resistance demonstrated by multi-principal elemental alloys (MPEAs) has sparked significant interest among researchers, prompting exploration into their vast compositional space, to validate their suitability for nuclear applications. A combined approach of thermodynamic and empirical parameters calculations alongside CALPHAD (CALculation of PHAse Diagrams) for phase formation predictions enable high-throughput material selection for sophisticated applications like nuclear, overcoming laborious and time-consuming experiments. Key thermodynamic and empirical parameters for eight novel equiatomic MPEAs, based on seven low thermal neutron cross section refractory elements, for predicting phase formation were calculated, and equilibrium and non-equilibrium simulations in CALPHAD were employed to comprehensively model the systems. Pseudo binary phase diagram simulations showed that Zr, V or equiatomic CrV additions to the base MoNbTi alloy (MoNbTi-Zr, MoNbTi-V and MoNbTi-CrV alloys) favor the formation of isomorphous body-centered cubic (BCC) phase at high temperatures, while Cr, Al, equiatomic ZrV, or equiatomic CrAl additions (MoNbTi-Cr, MoNbTi-Al, MoNbTi-ZrV or MoNbTi-CrAl alloys) limit the solubility of them. Equilibrium CALPHAD simulations at 750 oC were consistent with XRD results on MoNbTi, MoNbTiZr and MoNbTiCr alloys, and partially for others. Notably, elemental segregation observed in the backscattered electron (BSE) scanning electron microscopy (SEM) images of the alloys was accurately simulated through non-equilibrium Scheil solidification calculations in CALPHAD, further verified by experiments. The precipitation of TiCr2 Laves phase in Cr containing MoNbTiCr and MoNbTiCrAl was accurately predicted while discrepancies were noted in MoNbTiCrV. The equilibrium simulations also provided insights into phase compositions at specific temperatures offering a pathway for tailoring the desired microstructure and properties of these systems. Empirical parameters calculations successfully predicted random solid solution in the base MoNbTi alloy, and with an exception in MoNbTiV and MoNbTiAl, predicted intermetallic precipitation in the rest, especially, Laves phase precipitation in Cr containing alloys.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Effects of irradiation temperature on the microstructure and deuterium retention in γ-LiAlO 2 pellets

This report presents the experimental findings obtained from November 2023 to September 2024. The study aims to investigate the effects of temperature on the microstructure, deuterium (D) retention, and lithium (Li) loss in γ-LiAlO 2 pellets subjected to sequential He + and D + ion irradiation to a high dose. Sequential ion irradiation has been a key method in our previous studies to simulate the behavior of γ-LiAlO 2 under neutron irradiation. In addition to dose and dose rate, irradiation temperature is a critical factor influencing microstructural and compositional changes. LiAl 5 O 8 precipitates have been observed in γ-LiAlO 2 pellets irradiated with reactor neutrons at ~300°C. These precipitates also form during ion irradiation at an elevated temperature of 500°C, but not at 300°C. In our ion irradiation experiments, the dose rate is typically three orders of magnitude higher than that of neutron irradiation, leading to a more rapid damage production. To better emulate the microstructural features in neutron-irradiated pellets using ion irradiation, a higher irradiation temperature is needed to accelerate the diffusion of point defects and enhance defect recovery rates, thereby compensating for the effects of the higher dose rate. The microstructural changes observed are the result of competing processes occurring during ion irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties

Here we introduce a denoising diffusion algorithm to discover microstructures with nonlinear fine-tuned properties. Denoising diffusion probabilistic models are generative models that use diffusion-based dynamics to gradually denoise images and generate realistic synthetic samples. By learning the reverse of a Markov diffusion process, we design an artificial intelligence to efficiently manipulate the topology of microstructures to generate a massive number of prototypes that exhibit constitutive responses sufficiently close to designated nonlinear constitutive behaviors. To identify the subset of microcstructures with sufficiently precise fine-tuned properties, a convolutional neural network surrogate is trained to replace high-fidelity finite element simulations to filter out prototypes outside the admissible range. Results of this study indicate that the denoising diffusion process is capable of creating microstructures of fine-tuned nonlinear material properties within the latent space of the training data. More importantly, this denoising diffusion algorithm can be easily extended to incorporate additional topological and geometric modifications by introducing high-dimensional structures embedded in the latent space. Numerical experiments are conducted on the open-source mechanical MNIST data set (Lejeune, 2020). Consequently, this algorithm is not only capable of performing inverse design of nonlinear effective media, but also learns the nonlinear structure–property map to quantitatively understand the multiscale interplay among the geometry, topology, and their effective macroscopic properties.

42 ENGINEERING↗
DOE OSTI2022

USE OF TWO-PISTON SPLAT QUENCHING TO INVESTIGATE & CHARACTERIZE THE IMPACT OF COMPOSITIONAL VARIATIONS ON RAPID SOLIDIFICATION MICROSTRUCTURES & SUB-MICROSCALE FEATURES IN STAINLESS STEEL ALLOY.

The objective of this dissertation was to use two-piston splat quenching (SQ) to investigate the impact of compositional modifications on the solidification and microstructure of rapidly solidified austenitic stainless steels (SS) and to demonstrate the ability of SQ to quickly and effectively simulate rapid solidification conditions similar to those found in powder bed fusion (PBF) additive techniques. PBF techniques like laser powder bed fusion (LPBF) are being implemented across a breadth of research and industrial applications to create parts with complex geometries and performance capabilities while pushing the current limits of processing conditions and understanding of material systems. In this work, SQ was used to experimentally produce rapid solidification in 20+ unique austenitic SS compositions with systematic variations of the chrome and nickel equivalency ratio (Cr/Nieq) through targeted compositional modifications. From the targeted change of Cr, Ni, and Mo concentrations in rapidly solidified SS alloys, the ferrite solidification mode was found to be the primary solidification mode at significantly lower Cr/Nieq than previously predicted for RS. Also, decreasing concentrations of Fe at a constant Cr/Nieq ratio (i.e., different Fe isopleths), or increased Mo concentrations at a constant Cr/Nieq ratio were found to suppress the ferrite to austenite massive transformation when compared to alloys with lower concentrations at the same Cr/Nieq. Using an established empirical relationship between cell size and cooling rate, the SQ technique was estimated to produce cooling rates between 106 and 108 K/s. Thermal gradients were extracted from 2-D heat transfer simulations of the SQ solidification event and used with these cooling rates to produce solidification rate estimates for SQ which were between 0.4-1.6m/s. The primary solidification mode was observed to be the determining factor in which elements segregated to the cell boundaries during RS, for which Cr and Mo were the main elements to segregate during primary austenite solidification and Ni during primary ferrite solidification. Finally, the solidification rates and conditions produced by SQ experiments resulted in similar microstructures, features, and microsegregation to what was found in LPBF samples of the same feedstock.

Hasenbusch, Zachary↗
DOE OSTI2022

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↗
DOE OSTI2021

Microstructural Model for Creep-Fatigue Interaction in Grade 91 Steel

This report describes the completion of a crystal plasticity finite element simulation framework for creep-fatigue deformation and damage in Grade 91 steel. In addition to a description of the framework and a set of verification calculations, the report details an initial set of simulations applying the framework to examine low cycle fatigue and creep-fatigue interaction in Grade 91 at 600° C. Grade 91 is a likely material for future advanced microreactors and creep-fatigue will be a limiting structural damage mechanism, particularly for mobile reactors or load following systems. The framework described here could provide a better understanding of creep-fatigue damage mechanisms and directly examine creep, fatigue, and creep-fatigue interaction for Grade 91 at realistic component service conditions. This in turn could lead to improved design methods and component life estimation approaches, leading to more efficient and economical component designs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Meshfree simulation and prediction of recrystallized grain size in friction stir processed 316L stainless steel

Friction stir processing (FSP) is a promising solid-phase microstructural modification technique that can repair and enhance damaged stainless steel surfaces exposed to harsh environments. The quality of the repaired material is closely correlated to the recrystallized grain size in the stir zone (SZ), which is influenced by the thermomechanical conditions dictated by FSP process parameters. Thus, establishing a reliable relationship between these parameters and recrystallized grain size in the SZ is crucial for optimizing repair quality. However, existing experimental approaches often rely on indirect temperatures measured far from the SZ, along with rough strain rate estimations, which are imprecise and time-consuming. Meanwhile, existing mesh-based modeling methods usually face numerical challenges when dealing with the large material deformations inherent in FSP. Here, to address these issues, this study introduces a meshfree process model for FSP based on the smoothed particle hydrodynamics (SPH) method, aimed at predicting process conditions under different parameters. The model is validated using experimental data from 11 combinations of tool traverse and rotation speeds on 316 L stainless steel. Correlations between process parameters, material flow, temperature, strain, strain rate, and recrystallized grain size are revealed through SPH simulations and electron backscatter diffraction (EBSD) imaging. The results show that in situ SZ temperatures range from 1071 to 1322°C, which exceed the tool temperature by over 300°C. Furthermore, SZ temperature, strain rate, and grain size increase monotonically with higher tool temperature and faster traverse speed. A relationship is then established between the model-predicted Zener-Hollomon parameter and the recrystallized grain size based on EBSD data, expressed as ln(d) = -0.364 ln(Z) + 14.673. Finally, this relationship exhibits satisfactory accuracy with errors of less than 26.9% in predicting grain sizes at various SZ locations, which offers valuable insights for optimizing FSP repair processes for 316 L stainless steel.

316L stainless steel↗
DOE OSTI2024

Discerning the effect of various irradiation modes on the corrosion of Zircaloy-4

Using proton irradiation, this study investigates the individual influence of several factors on the corrosion kinetics of Zircaloy-4 in a hydrogenated water environment simulating a Pressurized Water Reactor (PWR). Using both simultaneous irradiation-corrosion and autoclave corrosion, we separately examine: (i) the effect of pre-irradiation on modifying the structure of the material, (ii) the impact of irradiation on creating defects in the growing oxide layer during corrosion, and (iii) the influence of irradiation on increasing the corrosion potential through radiolysis during corrosion. To replicate neutron-irradiated microstructure, two proton pre-irradiation schedules were employed: Schedule 1 (isothermal irradiation at 350 °C to 5 dpa) to simulate high-temperature PWR conditions, and Schedule 2 (two-step process: irradiation to 2.5 dpa at -10 °C followed by 2.5 dpa at 350 °C) to simulate lower temperature PWR and Boiling Water Reactor (BWR) conditions. Long-term autoclave corrosion testing over 360 days at 320 °C revealed no significant difference between unirradiated samples and those pre-irradiated according to either schedule, with all samples exhibiting sub-cubic kinetics within the pre-transition regime. Irradiated samples underwent Simultaneous Irradiation Corrosion (SIC) tests, corroding in 320 °C water while being irradiated with protons. Corrosion was found to accelerate in all SIC-tested samples relative to autoclave conditions, with the greatest increase observed in non-pre-irradiated samples. Pre-irradiation with either schedule resulted in a slower corrosion rate compared to non-pre-irradiated regions under SIC conditions. The degree of radiolysis observed in the SIC tests surpassed typical PWR conditions, approaching levels found in BWRs. Radiolysis products were identified as the primary contributors to accelerated corrosion, corroborated by radiolysis bar tests. Furthermore, these findings underscore the intricate interactions between irradiation, corrosion, and water chemistry in determining Zircaloy-4 corrosion kinetics within nuclear reactor environments.

Pressurized Water Reactor↗
DOE OSTI2023

Machine-learning-based, online estimation of ceramic’s microstructure upon the laser spot brightness during laser sintering

The ceramic microstructure strongly influences its properties. During manufacturing, the online monitoring of microstructure is critical to ensure the desired material properties. So far, the microstructure on the relevant scale is usually characterized offline using scanning electron microscopy (SEM), which is time and cost-consuming. In this work, we demonstrate a cost-effective, machine learning (ML)-based approach to simulate the SEM micrographs in real-time from the laser spot brightness. We experimentally observed a strong correlation between the laser spot brightness and the corresponding microstructure at the exact locations. The brightness values obtained from thermal emission images and the corresponding SEM micrographs were used in the training datasets. The ML algorithm was a style-based conditional generative adversarial network (CGAN). After training, the ML model could generate high-fidelity microstructure images within 0.1 seconds based on in-situ captured brightness at the laser sintering spot. We used the average grain sizes as the metric to evaluate the accuracy of the ML-predicted micrographs. Here, the ML-predicted microstructures were in good agreement, with less than 5% in difference from the real SEM images. In conclusion, we demonstrate the cost-effective, online microstructure estimation during laser sintering with a simple setup (a camera, a regular computer, and the ML model).

08 HYDROGEN↗
DOE OSTI2022

Effects of composition and canister centerline cooling on microstructure, phase distribution, and chemical durability of dehalogenated iron phosphate waste forms

This paper discusses the effects of composition and canister centerline cooling (CCC) on the microstructures, phase distribution, and chemical durability of dehalogenated iron phosphate waste forms starting from chloride-based salt simulants including KCl (Simple-1), NdCl3 (Simple-2), SrCl2 (Simple-3), LaCl3 (Simple-4), LiCl (Simple-5), CsCl (Simple-6), as well as a complex simulant containing LiCl, KCl, NaCl, CsI, SrCl2, CeCl3, and NdCl3 called ERV2. The simulants represent salt constituents present in salt wastes from electrorefiners used for electrochemical reprocessing. These salts are reacted with ammonium dihydrogen phosphate (ADP) resulting in a NH4Cl (dechlorination) byproduct that is captured and phosphate product containing oxides of the salt cations. This product is further stabilized using Fe2O3 through vitrification at higher temperatures. The results presented herein describe the properties of CCC-treated materials following dechlorination and vitrification including phase identification and quantification, elemental distributions, and chemical durabilities. The chemical durability in the CCC-cooled samples are lower durability than quenched materials for the ERV2 samples. The phases formed upon CCC cooling are very complex compositionally and microstructurally.

iron phosphate glass, iron phosphate waste forms, ↗
DOE OSTI2023

Microstructural Pattern Formation during Far-from-Equilibrium Alloy Solidification

We introduce a new phase-field formulation of rapid alloy solidification that quantitatively in- corporates non-equilibrium effects at the solid-liquid interface over a very wide range of interface velocities. Simulations identify a new dynamical instability of dendrite tip growth driven by solute trapping at velocities approaching the absolute stability limit. They also reproduce the formation of the widely observed banded microstructures, revealing how this instability triggers transitions between dendritic and microsegregation-free solidification. Predicted band spacings agree quantita- tively with observations in rapidly solidified Al-Cu thin films.

36 MATERIALS SCIENCE↗