SearcharxivSearch

arXiv subjects

Timothy J. Rupert

Publications and source records attributed to Timothy J. Rupert.

At least 19 recordsLinked to original sources

Phase nucleation, coarsening and evolution pathways of a sputtered nanostructured Inconel 725 alloy during heat treatment

Physical vapor deposition enables the fabrication of nanostructured superalloys with unique defect architectures, yet their phase evolution pathways can differ significantly from those of conventionally processed alloys. In this study, the effects of solution and aging treatments on phase selection and precipitation behavior in sputtered Inconel 725 films with an initially uniform columnar nanotwinned structure were systematically investigated. Direct aging at relatively low temperatures promoted extensive {\delta}-phase precipitation at twin boundaries and defect-rich regions, which depleted Nb from the {\gamma} matrix and suppressed {\gamma}'/{\gamma}" precipitation. In contrast, high-temperature solution treatment induced recrystallization and eliminated the nanotwinned structure, significantly reducing {\delta}-phase precipitation and increasing Nb availability to enable the formation of ultrafine spherical {\gamma}'/{\gamma}" precipitates within a refined {\gamma} matrix (<1 {\mu}m). Subsequent aging treatments promoted elemental partitioning and drove the morphological evolution of {\gamma}'/{\gamma}" precipitates from spherical to lenticular forms, while {\delta} precipitation became increasingly concentrated along grain boundaries. This spatial separation of intragranular {\gamma}'/{\gamma}" and grain-boundary {\delta} phases enabled simultaneous precipitation strengthening and grain stabilization, resulting in hardness values approaching 9 GPa. As a whole, this study demonstrates that the initial templates provided by defect structures can govern phase selection and precipitation pathways, providing a strategy for tailoring microstructure and achieving synergistic strengthening in nanostructured superalloys.

cond-mat.mtrl-sci

Synergistic doping of the grain interior and grain boundary alters deformation mechanisms and enables extreme strength in nanocrystalline Ni-Cr-Y alloys

Solid solution addition and grain boundary segregation have been independently shown to enhance the strength of nanocrystalline alloys. In the present study, the interplay between these two effects is investigated in nanocrystalline Ni-Cr-Y sputtered films through systematic variation of alloying element contents with grain size kept constant. Cr is introduced into a solid solution and serves to strengthen the lattice, while Y segregates to the grain boundaries to stabilize these features. Nanoindentation is used to probe hardness, with unexpected trends and very high values observed. Cr additions led to nanocrystalline solid solution strengthening, yet saturation was observed at higher concentrations due to the emergence of grain boundary dominated processes, as evidenced by pile-up morphologies containing slip steps and grain rotation. Y enrichment was observed at the examined grain boundaries, enhancing boundary-mediated strengthening by pinning the dislocations and suppressing dislocation emission, grain boundary sliding, and grain rotation processes. With increasing Y concentration, the nanocrystalline solid solution strengthening effect induced by Cr addition becomes weaker. This phenomenon can be attributed to a reduced dislocation bowing distance caused by dopant pinning. Most notably, the strongest ternary Ni-Cr-Y alloy exhibited a hardness of 11.0 GPa, among the highest hardness values reported for single-phase nanocrystalline Ni alloys with grain sizes near 20 nm. These findings highlight how tuning grain and grain boundary chemistry offers a viable strategy to control dislocation mechanics and improve the strength of nanocrystalline metals.

cond-mat.mtrl-sci

A computational alloy design framework for the promotion of amorphous grain boundary complexions

Amorphous grain boundary complexions have been shown to be radiation tolerant interfaces that can also reduce grain boundary embrittlement, marking them as favorable microstructural features. However, the incorporation of these features into new alloy systems is often a slow and arduous process based on trial and error. Here, a computational framework for alloy design is presented which enables the selection of dopants that promote the formation of amorphous grain boundary complexions. This framework is primarily built on density functional theory calculations and is demonstrated for W-rich binary and ternary alloys, which represent a promising target for fusion energy materials. Our framework first evaluates the grain boundary segregation tendency of dopants and then the energy penalty for amorphization alongside targeted interfacial energy comparison, with the end goal of identifying the best dopants. For a W base, Y and some transition metals such as Co and Ni are found to significantly lower these energetic barriers. Electronic structure analysis, local lattice distortion, and charge density distributions are calculated and used to provide mechanistic explanations for these dopant selections. Finally, the framework is validated by comparing with experimental literature for W alloys and a refractory complex concentrated alloy, showing a strong correlation between our dopant selections and low sintering onset temperatures that have been attributed to activated sintering. As a whole, this work establishes a transferable pipeline for designing alloys with grain-boundary complexions across diverse alloy systems.

cond-mat.mtrl-sci

Stress field modification near linear complexions increases the effective obstacle size and strengthening effect

Linear complexions are stable defect states that form along dislocations and recent experiments have demonstrated strengthening effects exceeding classical precipitation hardening predictions, motivating a detailed study of nanoscale strengthening mechanisms. Here, molecular dynamics simulations in Al-Cu and Ni-Al face-centered cubic alloys are used to demonstrate distinct plasticity mechanisms associated with linear complexions. Both nanoparticle array and platelet array complexions exhibit appreciable strengthening. In addition to direct interactions with the particles, stress field modification in nearby regions can restrict dislocation motion as well. Finally, the relative particle-dislocation orientation is found to have a large effect, with the strongest resistance observed when the dislocation stress field aligns with the original complexion nucleation condition. As a whole, these findings provide mechanistic insight into the strengthening observed experimentally and establish design principles for linear complexion-induced strengthening in structural alloys.

cond-mat.mtrl-sci

Irradiation-Driven Recrystallization in Fusion-Grade Tungsten: A Mesoscale, Microstructure-Aware Model

Tungsten (W) is the leading candidate material for plasma-facing components in fusion reactors, yet its upper operational temperature is limited by premature grain growth and recrystallization processes. Irradiation adds further complications by generating defect clusters and transmutation products that alter both the driving forces and kinetics of grain boundary motion. In this work, we develop a physics-based, multiscale framework that couples crystal plasticity, stochastic cluster dynamics, and discrete grain boundary dynamics to model the co-evolution of plastic deformation, irradiation damage, and grain growth in fusion-grade tungsten polycrystals. The approach enables simulations on realistic microstructures with arbitrary grain size and misorientation distributions, without recourse to mean-field simplifications. The model captures (i) the spatial heterogeneity of dislocation density distribution during hot working; (ii) irradiation-induced defect accumulation under fusion conditions, and (iii) the buildup of chemical and elastic driving forces for grain boundary migration and microstructural evolution. Parametric studies demonstrate the dominant influence that temperature has on thermally activated grain-boundary mobility, a weaker dependence on prior strain, and a pronounced retardation of recrystallization by rhenium segregation arising from neutron transmutation. Under fusion energy irradiation conditions, our framework predicts a substantial reduction of the effective recrystallization temperature relative to unirradiated microstructures, while Re production restores and even elevates this limit. By providing quantitative projections of recrystallization kinetics and in-service recrystallization temperatures, this work establishes a predictive tool for assessing the lifetime and operational envelope of W-based plasma-facing materials under fusion conditions.

cond-mat.mtrl-sci

Extraction of a structural short-range order descriptor from nanobeam electron diffraction patterns using a transfer learning approach

Amorphous solids exhibit structural short-range order despite lacking long-range crystalline order, with this structural descriptor found to be important for determining mechanical properties. Nanobeam electron diffraction offers a potential route for experimental characterization of structural short-range order, yet efforts to date have been primarily qualitative in nature. In this work, machine learning approaches based on transfer learning are used to enable quantitative analysis of nanobeam electron diffraction data from amorphous solids. A ResNet-18 model is trained on simulated diffraction patterns taken from different locations within simulated metallic glasses and amorphous grain boundary complexions in the Cu-Zr alloy system that were created with hybrid molecular dynamics and Monte Carlo simulations. The disorder parameter is found to be a superior target structural descriptor compared to traditional Voronoi indices for this task. The model achieves a low validation mean absolute error across diffraction patterns corresponding to different interaction volumes, demonstrating excellent performance and potential transferability. Testing was performed using other simulated nanobeam electron diffraction data as well as experimental nanobeam electron diffraction patterns, showing that the model can reliably capture spatial variations in local structural state. As a whole, this framework is able to overcome the challenges in the quantitative experimental characterization of structural short-range order, enabling improved characterization of amorphous solids and the exploration of structure-property relationships.

cond-mat.mtrl-sci

Thicker amorphous grain boundary complexions reduce plastic strain localization in nanocrystalline Cu-Zr

Amorphous grain boundary complexions have been shown to increase the plasticity of nanocrystalline alloys as compared to ordered grain boundaries. Here, the effect of an important structural descriptor, amorphous complexion thickness, on the plasticity and failure modes of nanocrystalline Cu-Zr is studied with in-situ compression testing, with over 50 micropillars tested. Two model materials were created that differ only in their complexion thickness, with one having a thicker complexion population than the other. The sample with thinner complexions was more likely to experience non-uniform plastic deformation in the form of localized plastic flow or shear banding. In contrast, the sample with thicker complexions displayed more homogeneous plasticity and higher damage tolerance; thicker amorphous complexions suppress localization by absorbing defects. This work demonstrates that increasing complexion thickness can be beneficial for stable plastic flow in nanocrystalline alloys, by improving resistance to strain localization and premature failure.

cond-mat.mtrl-sci

Local chemical order suppresses grain boundary migration under irradiation in CrCoNi

Complex concentrated alloys with intrinsic chemical heterogeneity are promising candidates for nuclear applications, where local chemical order can strongly influence defect evolution under irradiation. Grain boundaries also contribute to radiation damage mitigation by serving as defect sinks, yet this interaction can alter interfacial structure, typically leading to destabilization and grain growth. This study investigates how chemical ordering influences grain boundary migration and stability during successive radiation events in CrCoNi. Using atomistic simulations, bicrystals were equilibrated to induce segregation-enhanced chemical order, followed by prolonged irradiation at 1100 K. Our results show that grain boundaries in random CrCoNi begin to migrate after only a few collision cascades, whereas those in the ordered alloy remain immobile until the chemical order is sufficiently disrupted. Single-cascade simulations reveal key mechanistic differences, where cascades near chemically ordered interfaces produce smaller damage volumes and reduced atomic displacement due to enhanced Frenkel pair combination within the cascade core. This limits both the residual defect population and the energetic driving force for interfacial rearrangement. Subsequent simulations of irradiated interfaces show that interstitial absorption induces a structural transition that modifies the segregation morphology at and near the grain boundary, demonstrating a dynamic coupling between ordering stability and defect evolution. These findings offer new insights into the role of local chemical order on defect-interface interactions under extreme conditions and highlight pathways for designing radiation-tolerant materials for next-generation nuclear systems.

cond-mat.mtrl-sci

Modulation of structural short-range order due to chemical patterning in multi-component amorphous interfacial complexions

Amorphous interfacial complexions have been shown to restrict grain growth and improve damage tolerance in nanocrystalline alloys, with increased chemical complexity stabilizing the complexions themselves. Here, we investigate local chemical composition and structural short-range order in Cu-rich, multi-component nanocrystalline alloys to understand how dopants self-organize within these amorphous complexions and how local structure is altered. High resolution scanning transmission electron microscopy and elemental analysis are used to study both grain boundaries and interphase boundaries, with chemical partitioning observed for both. Notably, the amorphous-crystalline transition region is observed to be enriched in certain dopant species and depleted of others as compared to the interior of the amorphous complexions. This chemical patterning can be explained in terms of the elemental preference for ordered or disordered grain boundary environments. As only a qualitative measure of structural short-range order can be obtained with nanobeam electron diffraction for these specimens, atomistic simulations with a custom-built machine learning interatomic potential are then used to probe how dopant patterning affects local structural state. Increased grain boundary chemical complexity is found to result in a more disordered complexion structure, with segregation to the amorphous-crystalline transition regions driving changes in local structure that are sensitive to dopant ratios. As a whole, the intimate connection between local chemistry and order in amorphous interfacial complexions is demonstrated, opening the door for microstructural engineering within the amorphous complexions themselves.

cond-mat.mtrl-sci

Enhanced strain rate sensitivity due to platelet linear complexions in Al-Cu

Platelet array linear complexions have been predicted in Al-Cu, with notable features being dislocation faceting and climb into the precipitate, both of which should impact plasticity. In this study, we examine the strain rate dependence of strength for platelet linear complexions using atomistic simulations, with classical precipitate strengthening through particle cutting and particle bowing used as baseline comparisons. Dislocation segments with edge character must climb down from the platelet structures prior to the commencement of glide, introducing a significant time-dependent barrier to plastic deformation. Consequently, the strain rate sensitivity of strength for the platelet linear complexions system was found to be up to five times higher than that of classical precipitation strengthening mechanisms.

cond-mat.mtrl-sci

Bulk nanocrystalline Al-Mg-Y alloys with amorphous grain boundary complexions display high strength and compressive plasticity

Although nanocrystalline alloys regularly exhibit high strengths, their use in structural applications often face challenges due to sample size limitations, unstable microstructures, and the limited ability to plastically deform. The incorporation of amorphous grain boundary complexions has been proposed to address these issues, by simultaneously stabilizing nanocrystalline grain structures for scale-up processing and improving alloy toughness. In the present study, the mechanical behavior of bulk nanocrystalline Al-Mg-Y is examined with macroscale compression testing, probing a length scale that is relevant to real-world structural applications. Bulk samples were fabricated via a simple powder metallurgy approach, with different pressing temperatures and times employed for consolidation in order to investigate microstructural and property evolution. All of the specimens contained primary face-centered cubic Al and secondary Al4C3 and Al3Y phases, with the Al3Y particles exhibiting two populations of small equiaxed and larger elongated particles. Appreciable plasticity was measured along with high ultimate stresses over 800 MPa due to the presence of amorphous grain boundary complexions. Microstructural characterization of fracture surfaces revealed that the area fraction of dimpled regions increased with longer hot-pressing time. Most importantly, the elongated Al3Y particles formed regular cellular patterns with increasing hot-pressing time, delaying shear localization and significantly enhancing plasticity. The hierarchy present in the microstructure of the Al-Mg-Y alloy, from amorphous grain boundary complexions to secondary phases, gives rise to excellent bulk mechanical properties, which are attractive for structural applications.

cond-mat.mtrl-sci

Grain boundaries amplify local chemical ordering in complex concentrated alloys

Local chemical ordering strongly influences the behavior of complex concentrated alloys, yet its characterization remains challenging due to the nanoscale dimensions and scattered spatial distribution of the ordered domains. Here, we study chemical ordering near grain boundaries, demonstrating they can act as microstructural anchor points that amplify chemical order and drive the formation of compositional nanopatterns. Atomistic simulations reveal the development of composition waves with ordering vectors normal to the boundary plane in two distinct material systems, CrCoNi and NbMoTaW. These waves manifest as periodic enrichment-depletion patterns that reflect the underlying chemical ordering tendencies of each system, but with amplified contrast that extends several nanometers into the grain interior before gradually decaying. By examining multiple grain boundary orientations and alloys, we show that both the interfacial segregation profile and the crystallographic terminating plane govern the extent and character of this amplification. This interplay between boundary-dictated directional ordering and the diffuse, untemplated chemical domain evolution within the grain advances our understanding of interface-mediated ordering phenomena and suggests new opportunities for experimentally detecting local chemical order in complex concentrated alloys.

cond-mat.mtrl-sci

A Machine Learning Framework for the Prediction of Grain Boundary Segregation in Chemically Complex Environments

The discovery of complex concentrated alloys has unveiled materials with diverse atomic environments, prompting the exploration of solute segregation beyond dilute alloys. Data-driven methods offer promising for modeling segregation in such chemically complex environments, and are employed in this study to understand segregation behavior of a refractory complex concentrated alloy, NbMoTaW. A flexible methodology is developed that uses composable computational modules, with different arrangements of these modules employed to obtain site availabilities at absolute zero and the corresponding density of states beyond the dilute limit, resulting in an extremely large dataset containing 10 million data points. The artificial neural network developed here can rely solely on descriptions of local atomic environments to predict behavior at the dilute limit with very small errors, while the addition of negative segregation instance classification allows any solute concentration from zero up to the equiatomic concentration for ternary or quaternary alloys to be modeled at room temperature. The machine learning model thus achieves a significant speed advantage over traditional atomistic simulations, being four orders of magnitude faster, while only experiencing a minimal reduction in accuracy. This efficiency presents a powerful tool for rapid microstructural and interfacial design in unseen domains. Scientifically, our approach reveals a transition in the segregation behavior of Mo from unfavorable in simple systems to favorable in complex environments. Additionally, increasing solute concentration was observed to cause anti-segregation sites to begin to fill, challenging conventional understanding and highlighting the complexity of segregation dynamics in chemically complex environments.

cond-mat.mtrl-sci

Frustrated metastable-to-equilibrium grain boundary structural transition in NbMoTaW due to segregation and chemical complexity

Grain boundary structural transitions can lead to significant changes in the properties and performance of materials. In multi-principal element alloys, understanding these transitions becomes complex due to phenomena such as local chemical ordering and multi-component segregation. Using atomistic simulations, we explore a metastable-to-equilibrium grain boundary structural transition in NbMoTaW. The transition, characterized by structural disordering and reduced free volume, shows high sensitivity to its local chemical environment. Most notably, the transition temperature range of the alloy is more than twice that of a pure metal. Differences in composition between coexisting metastable and equilibrium structures highlight the change in local site availability due to structural relaxation. Further examination of grain boundaries with fixed chemical states at varying temperatures reveals that the amount of segregation significantly influences the onset temperature yet has minimal effect on the transition width. These insights underscore the profound effects of chemical complexity and ordering on grain boundary transitions in complex concentrated alloys, marking a meaningful advancement in our understanding of grain boundary behavior at the atomic level.

cond-mat.mtrl-sci

Human Perception-Inspired Grain Segmentation Refinement Using Conditional Random Fields

Automated detection of grain boundaries (GBs) in electron microscope images of polycrystalline materials could help accelerate the nanoscale characterization of myriad engineering materials and novel materials under scientific research. Accurate segmentation of interconnected line networks, such as GBs in polycrystalline material microstructures, poses a significant challenge due to the fragmented masks produced by conventional computer vision (CV) algorithms, including convolutional neural networks. These algorithms struggle with thin masks, often necessitating post-processing for effective contour closure and continuity. Previous approaches in this domain have typically relied on custom post-processing techniques that are problem-specific and heavily dependent on the quality of the mask obtained from a CV algorithm. Addressing this issue, this paper introduces a fast, high-fidelity post-processing technique that is universally applicable to segmentation masks of interconnected line networks. Leveraging domain knowledge about grain boundary connectivity, this method employs conditional random fields and perceptual grouping rules to refine segmentation masks of any image with a discernible grain structure. This approach significantly enhances segmentation mask accuracy by correctly reconstructing fragmented GBs in electron microscopy images of a polycrystalline oxide. The refinement improves the statistical representation of the microstructure, reflected by a 51 % improvement in a grain alignment metric that provides a more physically meaningful assessment of complex microstructures than conventional metrics. This method enables rapid and accurate characterization, facilitating an unprecedented level of data analysis and improving the understanding of GB networks, making it suitable for a range of disciplines where precise segmentation of interconnected line networks is essential.

cond-mat.mtrl-sci

Enhanced radiation damage tolerance of amorphous interphase and grain boundary complexions in Cu-Ta

Amorphous interfacial complexions are particularly resistant to radiation damage and have been primarily studied in alloys with good glass-forming ability, yet recent reports suggest that these features can form even in immiscible alloys such as Cu-Ta under irradiation. In this study, the mechanisms of damage production and annihilation due to primary knock-on atom collisions are investigated for amorphous interphase and grain boundaries in a Cu-Ta alloy using atomistic simulations. Amorphous complexions, in particular amorphous interphase complexions that separate Cu and Ta grains, result in less residual defect damage than their ordered counterparts. Stemming from the nanophase chemical separation in this alloy, the amorphous complexions exhibit a highly heterogeneous distribution of atomic excess volume, as compared to a good glass former like Cu-Zr. Complexion thickness, a tunable structural descriptor, plays a vital role in damage resistance. Thicker interfacial films are more damage-tolerant because they alter the defect production rate due to differences in intrinsic displacement threshold energies during the collision cascade. Overall, the findings of this work highlight the importance of interfacial engineering in enhancing the properties of materials operating in radiation-prone environments and the promise of amorphous complexions as particularly radiation damage-tolerant microstructural features.

cond-mat.mtrl-sci

Dislocation breakaway from nanoparticle array linear complexions: Plasticity mechanisms and strength scaling laws

Linear complexions are stable defect states, where the stress field associated with a dislocation induces a local phase transformation that remains restricted to nanoscale dimensions. As these complexions are born at the defects which control plasticity in metals, it is crucial to understand their impact on subsequent mechanical properties. In this work, atomistic modeling is used to understand how dislocation mechanics are altered by the presence of nanoparticle array linear complexions in a Ni-Al alloy. Molecular dynamics simulations are used to identify the critical shear stress needed to drive dislocation breakaway, first for nanoparticle arrays formed by Monte Carlo/molecular dynamics methods to represent realistic configurations and subsequently for simplified models that allow the effects of particle spacing and size to be varied in a controlled manner. A combined bowing and progressive unpinning mechanism is uncovered, leading to the demonstration of a new strength scaling law that differs in keys ways from classical Orowan bowing.

cond-mat.mtrl-sci

Grain incompatibility determines the local structure of amorphous grain boundary complexions

Amorphous grain boundary complexions lack long-range crystalline order but are not featureless, as distinct gradients in structural short-range order have been reported through their thickness. In this work, we test the hypothesis that the distribution of short-range order is determined by the confining crystals using atomistic simulations of both Cu-Zr bicrystals and a random polycrystal. Voronoi polyhedra with structures similar to that of perfect face-centered cubic serve as signatures of high structural order and are only found at the amorphous-crystalline transition regions. The density of the ordered structural motifs within a specific amorphous-crystalline transition region is found to not be directly determined by the orientation and symmetry of the grain which touches it, but rather by the incompatibility between the two confining grains. Ordered polyhedra density is found to be inversely related to grain incompatibility, meaning that large incompatibilities between the confining crystals lead to less order in the amorphous-crystalline transition region. The finding that the entire grain-film-grain system must be considered to understand local structure unequivocally demonstrates that amorphous complexions are not simply a collection of independent phases which happen to nucleate at a grain boundary. Rather, an amorphous grain boundary complexion is a single entity that finds a local equilibrium configuration.

cond-mat.mtrl-sci