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At least 955 records · Page 53

Multi-scale observations of structure and chemical composition changes of portland cement systems during hydration

There is little agreement about the mechanisms and few direct observations of the transition of cement paste from a slurry to a solid. This paper uses four different imaging techniques at multiple length scales (from 15.6 nm to 1 μm) to follow the three-dimensional microstructural evolution of portland cement, and monoclinic tricalcium silicate (mC 3 S) paste over the first 16 h of hydration. Measurements of over 60,000 particles captured every 10 min were made at the micron scale. Nanoscale examinations of the structure and chemical composition are used to support this work. The results show that hydration products with an average Ca/Si > 3 form on and near the surface of the hydrating particles prior to the acceleration period that appears to control the reaction rate. These hydration products appear to change in chemical composition as more rapid dissolution of C 3 S and formation of hydration products occur during the acceleration period. The findings are used to provide insights into the origin of the induction and acceleration periods during hydration.

36 MATERIALS SCIENCE↗

High temperature oxidation of Ni alloys in CO 2 containing impurities

Next-generation power systems need structural alloys resistant to high-temperature oxidation in CO 2 containing combustion impurities. In this report we evaluate the oxidation performance of several commercial Ni alloys exposed to 95%CO 2 -4%H 2 O-1%O 2 , with/without 0.1% SO 2 , at 750°C and 1 atm. All alloys formed protective chromia layers and showed no signs of carburization or sulfidation, and minimal chromia volatilization. The microstructural evolution of the alloy surface, secondary oxidants, and minor alloy additions all played a part in promoting protective chromia formation/growth. The results show that Ni alloys are promising candidates for high-temperature portions of next-generation CO 2 -based power systems.

36 MATERIALS SCIENCE↗

Using lifetime of point defects for dislocation bias in bcc Fe

The interaction between dislocations and point defects is key to deformation processes and microstructural evolution of structural materials. In this work, we compute the lifetime of point defects to describe their interaction with dislocations. This approach can accurately account for the effects of the dislocation core and anisotropic defect dynamics to accumulatively determine the capture efficiency, sink strength, and dislocation bias at different temperatures and dislocation densities. Particularly, the absorption of point defects by straight screw and edge dislocations in a model bcc iron system is studied. The maximum swelling rates based on the obtained bias factors are in close agreement with a variety of experimental measurements, including both neutron and ion-irradiation data, especially when considering the survival fraction for point defects from displacement cascades. Further, this approach applies to many other processes and sinks, such as dislocation loops and interfaces, providing a powerful means to develop fundamental insights critical for improving radiation resistance and mechanical properties of structural materials through controlling defect interaction and evolution.

36 MATERIALS SCIENCE↗

Best of both worlds: Enforcing detailed balance in machine learning models of transition rates

The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation approaches such as molecular dynamics become prohibitive and Kinetic Monte-Carlo (kMC) algorithms, where the state-to-state evolution of the system is represented in terms of a continuous-time Markov chain, are instead frequently relied upon to efficiently predict long-time evolution. The accuracy of kMC simulations however relies on the complete and accurate knowledge of reaction pathways and corresponding kinetics. This requirement becomes extremely stringent in complex systems such as concentrated alloys where the astronomical number of local atomic configurations makes the a priori tabulation of all possible transitions impractical. Machine learning models of transition kinetics have been used to mitigate this problem by enabling the efficient on-the-fly prediction of kinetic parameters. While conventional KMC methods based on transition state theory naturally yield reversible dynamics that exactly obey the detailed balance criterion, providing strong guarantees on the properties of the stationary distribution, many recently-proposed ML-based approaches to barrier predictions provide no such guarantees. In this study, we derive conditions under which physics-informed ML architectures exactly enforce the detailed balance condition by construction, even when relying on non-extensive descriptions of states in terms of local environments around mobile defects. In conclusion, using the diffusion of a vacancy in a concentrated alloy as an example, we show that such ML architectures also exhibit superior performance in terms of prediction accuracy, demonstrating that the imposition of physical constraints can facilitate the accurate learning of barriers at no increase in computational cost.

36 MATERIALS SCIENCE↗

Electron microscopy data on irradiation effects in glassy carbon, nuclear graphite, pyrolytic carbon, and carbon fibers

Glassy carbon, a monoatomic allotrope of carbon, is a candidate material for components in fission nuclear power systems due to its radiation tolerance. This article presents comprehensive electron microscopy data revealing the effects of neutron and electron irradiation on glassy carbon. For comparison, additional data are provided for pyrolytic graphite and carbon fibers, materials that exhibit similar structural behavior under irradiation. In situ electron irradiation experiments further illustrate the real-time microstructural evolution of glassy carbon during exposure. The dataset is organized into five parts: (1) transmission electron microscopy (TEM) micrographs of as-received and neutron-irradiated glassy carbon; (2) TEM micrographs of neutron-irradiated graphite; (3) TEM micrographs of unirradiated and irradiated carbon–carbon composites; (4) TEM micrographs of pyrolytic carbon specimens in both conditions; (5) scanning transmission electron microscopy (STEM) micrographs of as-received and neutron-irradiated glassy carbon and (6) in situ electron irradiation data of a glassy carbon particle. These datasets provide valuable insights into radiation-induced structural changes in carbon-based materials relevant to nuclear applications.

36 MATERIALS SCIENCE↗

A microstructural signature of the coesite-quartz transformation: New insights from high-pressure experiments and EBSD

Ultra-high pressure (UHP) metamorphism is difficult to identify in continental crust as few petrological barometers are suitable for dominantly felsic lithologies. In such cases, burial to extreme depths is commonly identified through the preservation of coesite, a high-pressure polymorph of SiO 2 that typically forms at depths exceeding ∼ 100 km (i.e., > 2 GPa pressure). Unfortunately, coesite readily transforms to quartz upon exhumation, meaning that UHP terranes may often be overlooked. While some studies have suggested that quartz may inherit an orientation signature indicative of former coesite, both the specific nature of this signature and the conditions favouring its development remain uncertain. Here, to address this problem, we combine electron backscatter diffraction analysis of natural and experimental samples to explore microstructural evolution across the coesite-quartz phase transformation. We demonstrate that neighbouring domains of quartz commonly feature an 84 ± 4° rotation of [c] axes around the pole of a common {m} plane. This orientation relationship is a product of epitaxy, whereby the {$11\bar{2}2$} Japan twin plane in quartz nucleates on the (010) plane in coesite. In supercell simulations, the nucleation of Japan twins can be explained by the energetically favourable alignment of quartz tetrahedra on parental coesite tetrahedra. Through experiments, we demonstrate that this signature emerges over a broad range of conditions, regardless of the availability of nucleation sites (e.g., grain boundaries) or the density of crystal lattice defects (e.g., dislocations). Overall, our work provides a quantitative and unambiguous tool for identifying UHP terranes from quartz in isolation.

Coesite↗

Bayesian strategies for uncertainty quantification of the thermodynamic properties of materials

Reliable models of the thermodynamic properties of materials are critical for industrially relevant applications that require a good understanding of equilibrium phase diagrams, thermal and chemical transport, and microstructure evolution. The goal of thermodynamic models is to capture data from both experimental and computational studies and then make reliable predictions when extrapolating to new regions of parameter space. These predictions will be impacted by artifacts present in real data sets such as outliers, systematic errors, and unreliable or missing uncertainty bounds. Such issues increase the probability of the thermodynamic model producing erroneous predictions. We present a Bayesian framework for the selection, calibration, and quantification of uncertainty of thermodynamic property models. The modular framework addresses numerous concerns regarding thermodynamic models including thermodynamic consistency, robustness to outliers, and systematic errors by the use of hyperparameter weightings and robust Likelihood and Prior distribution choices. Furthermore, the framework’s inherent transparency (e.g. our choice of probability functions and associated parameters) enables insights into the complex process of thermodynamic assessment. We introduce these concepts through examples where the true property model is known. Additionally, we demonstrate the utility of the framework through the creation of a property model from a large set of experimental specific heat and enthalpy measurements of Hafnium metal from 0 to 4900K.

36 MATERIALS SCIENCE↗

Towards data-driven constitutive modelling for granular materials via micromechanics-informed deep learning

The analytical description of path-dependent elastic-plastic responses of a granular system is highly complicated because of continuously evolving microstructures and strain localisation within the system undergoing deformation. This study offers an alternative to the current analytical paradigm by developing micromechanics-informed machine-learning based constitutive modelling approaches for granular materials. A set of critical variables associated with the constitutive behaviour of granular materials are identified through an incremental stress-strain relationship analysis. Depending on the strategy to exploit the priori micromechanical knowledge, three different training strategies are explored. The first model uses only the measurable external variables to make stress predictions; the second model utilises a directed graph to link all the external strain sequences and internal microstructural evolution variables into a single prediction model comprised of a series of sub-mappings, and the third model explicitly integrates the physically important non-temporal properties with external strain paths into training through an enhanced Gated Recurrent Unit (GRU). These three models show satisfactory agreement with unseen test specimens based on multi-directional loading cases. The basic features and potential applications of each model are explained. Lastly, the key factors for constitutive training and limitations of the current work are also discussed in detail.

36 MATERIALS SCIENCE↗

Microstructure characterization and elastic-plastic self-consistent simulation studies of anisotropic deformation of β -tin

Uniaxial compression tests of 99.9% pure polycrystalline $β$-tin (Sn) were conducted at various strain rates (10 -3 /s, 10 -1 /s and 1/s) and temperatures (294 K and 193 K) to understand the effects of these variables on the stress–strain response, microstructure evolution, and stress relaxation behavior. Multiple Sn specimens were subjected to complex compressive loading/unloading/reloading paths at different strain rates. Specimens initially compressed at higher strain rates showed strain rate-dependent texture evolution and more pronounced relaxation upon reloading, as compared to those pre-strained at lower rates at room temperature (RT). Compression tests conducted at low temperature (193 K) revealed increased strength, similar to the enhanced strength observed when the strain rate was increased at RT. Neutron diffraction was employed to characterize the initial and final bulk textures of the RT specimens. Electron backscatter diffraction was utilized to examine the crystallographic grain orientation and morphology, thereby identifying the signatures of dislocation-mediated deformation, grain refinement, recrystallization, and twinning behaviors. Elastic-plastic self-consistent simulations were performed to investigate the deformation modes responsible for the strain rate-dependent macroscopic stress–strain response and texture evolution. Effects of crystallographic orientation on stress relaxation behavior was also examined. In conclusion, the model predictions are in reasonable agreement with experimental observations.

36 MATERIALS SCIENCE↗

Thermodynamic and kinetic analysis of the melt spinning process of Fe-6.5 wt.% Si alloy

Here, the microstructural evolution of Fe-6.5 wt.% Si alloy during rapid solidification was studied over a quenching rate of 4 × 10 4 K/s to 8 ×10 5 K/s. The solidification and solid-state diffusional transformation processes during rapid cooling were analyzed via thermodynamic and kinetic calculations. The Allen-Cahn theory was adapted to model the experimentally measured bcc_B2 antiphase domain sizes under different cooling rates. The model was calibrated based on the experimentally determined bcc_B2 antiphase domain sizes for different wheel speeds and the resulting cooling rates. Good correspondence of the theoretical and experimental data was obtained over the entire experimental range of cooling rates. Along with the asymptotic domain size value at the infinite cooling rates, the developed model represents a reliable extrapolation for the cooling rate > 10 6 K/s and allows one to optimize the quenching process.

36 MATERIALS SCIENCE↗

Grain growth and Hall-Petch relationship in a refractory HfNbTaZrTi high-entropy alloy

Understanding the effect of temperature variation on the microstructural evolution is particularly important to refractory high-entropy alloys (RHEAs), given their potential high-temperature applications. Here, we experimentally investigated the grain-growth behavior of the HfNbTaZrTi RHEAs during recrystallization at temperatures from 1,000 to 1,200 °C for varied durations, following cold rolling with a 70% thickness reduction. Following the classical grain-growth kinetics analysis, two activation energies are obtained: 205 kJ/mol between 1,000 and 1,100°C, and 401kJ/mol between 1,100 and 1,200°C, which suggests two mechanisms of grain growth. Moreover, the yield strength – grain size relation was found to be well described by the Hall-Petch relation in the form of σ y = 942 + 270D -0.5 . It was revealed that the friction stress, 942 MPa, in the HfNbTaZrTi HEA is higher than that of tungsten alloys, which indicates the high intrinsic stress in the BCC-RHEA. Further, the coefficient, 270 MPa/μm -1/2 , is much lower than that in the 316 stainless steel and Al 0.3 CoCrFeNi HEAs, which indicates low grain-boundary strengthening.

36 MATERIALS SCIENCE↗

Heterogenous activation of dynamic recrystallization and twinning during friction stir processing of a Cu-4Nb alloy

An interplay between high degree of shear deformation and deformation-induced heating occurs during friction stir processing (FSP) of metals. In medium-to-low stacking fault energy Cu alloys, this can lead to a complex spatially heterogenous activation of dynamic recrystallization (DRX) and twinning mechanisms. Within the Cu-Nb system, the presence of Nb is further expected to influence the DRX mechanism of the Cu matrix. However, the microstructural changes induced by the co-deformation of Nb during FSP are still not well understood. So, this study uses a combination of multimodal microstructural characterization, solution thermodynamics-based predictions, and computational crystal plasticity simulation to reveal the various microstructural evolution mechanisms that can occur during FSP of a Cu-4at.%Nb binary model alloy. The formation of softer DRX zones, and harder shear localization regions are revealed using electron backscatter diffraction, transmission electron microscopy, atom probe tomography, and crystal plasticity modeling.

36 MATERIALS SCIENCE↗

A comparative study of solute trapping in Fe-(33–45 at%) Cu alloys manufactured by laser directed energy deposition

The high cooling rates in laser directed energy deposition (DED-LB) of alloys lead to substantial amounts of solute trapping as solute atoms cannot diffuse away from the solid/liquid interface before it advances. In some concentrated alloys, this results in supersaturated solid phases that form nanoscale hierarchical microstructures when the solute atoms precipitate out during reheating from subsequent laser passes. We choose the Iron-Copper (Fe-Cu) binary alloy as model system as it is chemically homogeneous in the liquid phase and has negligible solid solubility at room temperature. Two alloys with nominal compositions in atomic (at.) %, Fe67Cu33 and Fe55Cu45, were manufactured using DED-LB. Scanning transmission electron microscopy (STEM), energy dispersive spectroscopy (EDS) and wavelength dispersive spectroscopy (WDS) were used to characterize the nanostructures and heterogeneous chemical compositions. A non-equilibrium solute partitioning model was used to compute the supersaturated chemistries of the constituent phases and validated with experimentally measured compositions. The measured phase compositions of the two alloys were very similar, at roughly 12 at.% Cu and 4 at.% Fe in the α(bcc)-Fe and ε(fcc)-Cu phases respectively, despite having different processing parameters and mechanical behavior. This indicates that the total thermal history, that depends on both the processing parameters and laser scan pattern, plays a stronger role on the final microstructure evolution than just the initial quantity of trapped solute. In addition, we find that current non-equilibrium solute partitioning models applied on the continuum scale fall short of predicting accurate quantitative phase compositions in concentrated alloys, although the qualitative trends are captured correctly.

36 MATERIALS SCIENCE↗

Tusas: A fully implicit parallel approach for coupled phase-field equations

In this study, we develop a fully-coupled, fully-implicit approach for phase-field modeling of solidification in metals and alloys. Predictive simulation of solidification in pure metals and metal alloys remains a significant challenge in the field of materials science, as microstructure formation during the solidification process plays a critical role in the properties and performance of the solid material. Our simulation approach consists of a finite element spatial discretization of the fully-coupled nonlinear system of partial differential equations at the microscale, which is treated implicitly in time with a preconditioned Jacobian-free Newton-Krylov method. The approach is algorithmically scalable as well as efficient due to an effective preconditioning strategy based on algebraic multigrid and block factorization. We implement this approach in the open-source Tusas framework, which is a general, flexible tool developed in C++ for solving coupled systems of nonlinear partial differential equations. The performance of our approach is analyzed in terms of algorithmic scalability and efficiency, while the computational performance of Tusas is presented in terms of parallel scalability and efficiency on emerging heterogeneous architectures. We demonstrate that modern algorithms, discretizations, and computational science, and heterogeneous hardware provide a robust route for predictive phase-field simulation of microstructure evolution during additive manufacturing.

97 MATHEMATICS AND COMPUTING↗

Engineering grain boundary anisotropy to elucidate grain growth behavior in alumina

Current grain growth models have evolved to account for the relationship between grain boundary energy/mobility anisotropy and the five degrees of grain boundary character. However, the role of grain boundary networks on overall growth kinetics remains poorly understood. To experimentally investigate this problem, a highly textured Al 2 O 3 was fabricated by colloidal casting in a strong magnetic field to engineer a unique spatial distribution of grain boundary character. Microstructural evolution was quantified and compared to an untextured sample. From this comparison, a prevalence of (0001)/(0001) terminated grain boundaries with anisotropic networks were identified in the textured sample. These boundaries and their networks were found to be driving grain growth at a faster rate than predicted by models. These findings will allow better modelling of grain growth in real systems by experimentally exploring the impact thereon of grain boundary plane anisotropy and relative energy/mobility differences between neighboring boundaries.

36 MATERIALS SCIENCE↗

High pressure effects on EBC systems in high temperature environments

Environmental barrier coatings (EBCs) are designed to protect SiCfiber/SiCmatrix ceramic matrix composites (CMCs) in turbine engines by mitigating wear in high-temperature water vapor environments. The failure of EBCs is frequently attributed to the accelerated oxidation of the silicon bond coating layer when exposed to high-temperature steam, leading to the formation of a thickened thermally grown oxide (TGO). TGO growth increases interfacial stress, weakens adhesion, and results in coating spallation. Understanding the impact of high-temperature oxidation of EBC systems is essential for developing accurate lifespan models for turbine components, although pressurized oxidation testing is extremely sparse in the open literature. In this work, oxidation tests were performed on rare earth silicate EBCs coated onto SiC substrates under increased pressure conditions. The coated specimens were tested at 1100°C, 1200°C, and 1300°C at both 1 atm and 10 atm total pressure in steam environments. Subsequent characterization focused on the microstructural evolution of the EBC/Si/SiC system. The experimental findings indicated that TGO behavior is dependent on high-pressure conditions, with elevated pressure leading to an increase in oxide scale thickness and modifications in its morphology.

Ardrey, Kristyn [ORNL] (ORCID:0000000184407796)↗

Activation of dislocations in Mg with solute Y

Mg-Y cast alloy shows excellent ductility (elongation to failure > 15%) compared with pure Mg and commercial Mg cast alloys. By monitoring the microstructure evolution during an in situ tensile test of a Mg-2.5 wt%Y alloy, we identify the activation of prismatic slip, which is rare in Mg. Synchrotron X-ray micro-beam Laue diffraction (μ-Laue) and transmission electron microscopy revealed the morphology of prismatic slip bands and individual dislocations. Density functional theory and molecular dynamics calculations indicate that solute Y can significantly reduce the stacking fault energy (SFE) along direction on prismatic plane in Mg lattice and thus facilitate the nucleation of dislocations during deformation. The presence of free dislocations in the Mg lattice can also lead to nucleation of {10–12} twins even under unfavorable geometric conditions.

36 MATERIALS SCIENCE↗

Experimental characterization and atomistic simulation of grain boundary segregation in Mg-Y alloys

As a rare earth solute element in Mg alloys, Y has the beneficial effects of increasing both the strength and the ductility as well as weakening the crystallographic texture. To achieve a more fundamental understanding on how Y addition affects the microstructural evolution and mechanical properties, the Y segregation behavior at grain boundaries was investigated in Mg-1wt.%Y and Mg-7wt.%Y alloys at different conditions. The segregation intensity and its dependence on the grain boundary misorientation angle were experimentally characterized and computationally predicted. Strong segregation at grain boundaries was observed in both low and high Y-containing alloys. Y segregation was found to remain in alloy Mg-7Y after high-temperature annealing heat treatment at 540 °C. No direct correlation between the Y segregation intensity and the grain boundary misorientation angle could be established based on either the experimental characterization or the atomistic simulation with a spectral model. We thus conclude that grain boundary segregation of Y is independent of grain boundary misorientation angle.

Grain boundary↗