arXiv subjects

Darren C. Pagan

Publications and source records attributed to Darren C. Pagan.

At least 19 recordsLinked to original sources

arXiv2026

An Automated Magnetron Sputtering Chamber for Ferroelectric Thin Film Deposition

Optimization of next-generation materials synthesis and manufacturing processes can be accelerated by effective use of digital datasets. However, a majority of existing custom research infrastructure, including that for thin film deposition, is primarily manually operated and not compatible with this new research paradigm. Here, a template is provided for upgrading existing manual deposition chambers to enable automated and autonomous experimentation. As an example, the upgrade of an existing magnetron sputtering chamber dedicated to synthesis of wurtzite ferroelectrics is presented. Focus is placed on automation of instrumentation; system and deposition control; and synchronized and automated data collection strategies. An example use case of the system for semi-autonomous determination of process-property relationships is presented, specifically minimization of coercive field in wurtzite Al$_{1-x-y}$Sc$_x$B$_y$N thin films.

cond-mat.mtrl-sci↗

arXiv2026

Sensitivity of grain-averaged elastic strain and orientation predictions on the mesh density and boundary conditions in crystal plasticity finite element simulations

Combined high-energy X-ray diffraction microscopy (HEDM) and crystal plasticity finite element (CPFE) modeling studies have emerged as a preferred paradigm to shed insight into the evolution of elasticity and plasticity at the intragrain scale of polycrystals. In particular, far-field HEDM measures the deformation response of upwards of thousands of individual grains simultaneously in situ during mechanical loading, though measurements are primarily limited, however, to the average state of each grain -- i.e., the grain's full strain tensor, crystallographic orientation, spatial location and volume. CPFE is utilized to shed information on the intragrain deformation response, via the sub-discretization of each grain into many finite elements, though the direct point of comparison to HEDM remains the grain-averaged response. We thus seek to find the minimum simulation conditions necessary to provide consistent grain-averaged predictions in an attempt to limit computational cost. In this study, we perform a suite of simulations and systematically study the effects of mesh density and boundary conditions, and consider different materials. We discuss these results and show that accurate prediction of grain-averaged elastic strains in a given region of interest typically requires a mesh with 250 elements per grain on average and a buffer layer of at least three grains between the region of interest and the control surfaces.

cond-mat.mtrl-sci↗

arXiv2025

Integrated Experiment and Simulation Co-Design: A Key Infrastructure for Predictive Mesoscale Materials Modeling

The design of structural & functional materials for specialized applications is being fueled by rapid advancements in materials synthesis, characterization, manufacturing, with sophisticated computational materials modeling frameworks that span a wide spectrum of length & time scales in the mesoscale between atomistic & continuum approaches. This is leading towards a systems-based design methodology that will replace traditional empirical approaches, embracing the principles of the Materials Genome Initiative. However, several gaps remain in this framework as it relates to advanced structural materials:(1) limited availability & access to high-fidelity experimental & computational datasets, (2) lack of co-design of experiments & simulation aimed at computational model validation,(3) lack of on-demand access to verified and validated codes for simulation and for experimental analyses, & (4) limited opportunities for workforce training and educational outreach. These shortcomings stifle major innovations in structural materials design. This paper describes plans for a community-driven research initiative that addresses current gaps based on best-practice recommendations of leaders in mesoscale modeling, experimentation & cyberinfrastructure obtained at an NSF-sponsored workshop dedicated to this topic. The proposal is to create a hub for Mesoscale Experimentation and Simulation co-Operation (hMESO)-that will (I) provide curation and sharing of models, data, & codes, (II) foster co-design of experiments for model validation with systematic uncertainty quantification, & (III) provide a platform for education & workforce development. It will engage experimental & computational experts in mesoscale mechanics and plasticity, along with mathematicians and computer scientists with expertise in algorithms, data science, machine learning, & large-scale cyberinfrastructure initiatives.

cond-mat.mtrl-sci↗

arXiv2025

Processing-dependent Chemical Ordering in a Metallic Alloy Characterized via Non-destructive Bragg Coherent Diffraction Imaging

Of current importance for alloy design is controlling chemical ordering through processing routes to optimize an alloy's mechanical properties for a desired application. However, characterization of chemical ordering remains an ongoing challenge, particularly when nondestructive characterization is needed. In this study, Bragg coherent diffraction imaging is used to reconstruct morphology and lattice displacement in model Cu$_3$Au nanocrystals that have undergone different heat treatments to produce variation in chemical ordering. The magnitudes and distributions of the scattering amplitudes (proportional to electron density) and lattice strains within these crystals are then analyzed to correlate them to the expected amount of chemical ordering present. Nanocrystals with increased amounts of ordering are found to generally have less extreme strains present and reduced strain distribution widths. In addition, statistical correlations are found between the spatial arrangement of scattering amplitude and lattice strains.

cond-mat.mtrl-sci↗

arXiv2025

Orientation reconstruction of transformation $α$ titanium alloys via polarized light microscopy: methodology and assessment

Emerging microstructural characterization methods have received increased attention owing to their promise of relatively inexpensive and rapid measurement of polycrystalline surface morphology and crystallographic orientations. Among these nascent methods, polarized light microscopy (PLM) is attractive for characterizing alloys comprised of hexagonal crystals, but is hindered by its inability to measure complete crystal orientations. In this study, we explore the potential to reconstruct quasi-deterministic orientations for titanium microstructures characterized via PLM by considering the Burgers orientation relationship between the room temperature $α$ (HCP) phase fibers measured via PLM, and the $β$ (BCC) phase orientations of the parent grains present above the transus temperature. We describe this method -- which is capable of narrowing down the orientations to one of four possibilities -- and demonstrate its abilities on idealized computational samples in which the parent $β$ microstructure is fully, unambiguously known. We further utilize this method to inform the instantiation of samples for crystal plasticity simulations, and demonstrate the significant improvement in deformation field predictions when utilizing this reconstruction method compared to using results from traditional PLM.

cond-mat.mtrl-sci↗

arXiv2025

Deconvoluting Thermomechanical Effects in X-ray Diffraction Data using Machine Learning

X-ray diffraction is ideal for probing sub-surface state during complex or rapid thermomechanical loading of crystalline materials. However, challenges arise as the size of diffraction volumes increases due to spatial broadening and inability to deconvolute the effects of different lattice deformation mechanisms. Here, we present a novel approach to use combinations of physics-based modeling and machine learning to deconvolve thermal and mechanical elastic strains for diffraction data analysis. The method builds on a previous effort to extract thermal strain distribution information from diffraction data. The new approach is applied to extract the evolution of thermomechanical state during laser melting of an Inconel 625 wall specimen which produces significant residual stress upon cooling. A combination of heat transfer and fluid flow, elasto-plasticity, and X-ray diffraction simulations are used to generate training data for machine-learning (Gaussian Process Regression, GPR) models that map diffracted intensity distributions to underlying thermomechanical strain fields. First-principles density functional theory is used to determine accurate temperature-dependent thermal expansion and elastic stiffness used for elasto-plasticity modeling. The trained GPR models are found to be capable of deconvoluting the effects of thermal and mechanical strains, in addition to providing information about underlying strain distributions, even from complex diffraction patterns with irregularly shaped peaks.

cond-mat.mtrl-sci↗

arXiv2024

Depth-Resolved Characterization of Centrifugal Disk Finishing of Additively Manufactured Inconel 718

Surface characteristics are a major contributor to the in-service performance, particularly fatigue life, of additively manufactured (AM) components. Centrifugal disk finishing (CDF) is one of many rigid media, abrasive machining processes employed to smooth the surfaces and edges of AM components. Within the general family of abrasive machining processes currently applied to AM, CDF is moderate in terms of material removal rate and the inertial forces exerted. How CDF alters the underlying microstructure of the processed surface is currently unknown. Here we employ white light profilometry and high-energy X-ray diffraction to characterize surface finish, crystallographic texture, and anisotropic distributions of residual microscale strain as a function of depth in CDF-finished Inconel 718 manufactured with laser powder bed fusion. Surfaces are finished using both unimodal and bimodal finishing media size distributions. We find that CDF will remove surface crystallographic textures (here a {111} fiber texture) from AM components, but generally not alter the bulk texture (here a cube texture). CDF is also found to impart significant amounts of residual microscale strain into the first 100 $μ$m from the sample surface as evidenced by an approximately 50% increase in diffraction peak widths at 20 $μ$m from the surface in comparison to 120 $μ$m.

physics.app-ph↗

arXiv2024

The influence of substantial intragranular orientation gradients on the micromechanical response of heavily-worked material

In this study, we employ high-energy X-ray characterization to examine the role of relatively large amounts of intragranular lattice misorientation -- present after many thermomechanical processes -- on the micromechanical response of Al-7085 with a modified T7452 temper. We utilize near-field high energy X-ray diffraction microscopy (HEDM) to measure three-dimensional (3D) spatial orientation fields, facilitated by a novel method that utilizes grain orientation envelopes measured using far-field HEDM to enable reconstruction of grains with intragranular orientation spreads greater than 20°. We then assess the consequences of consideration of intragranular orientation fields on the predicted deformation response of the sample through 3D micromechanical simulations of the forged Al-7085. We construct two virtual polycrystalline specimens for use in simulations: the first a faithful representation of the HEDM reconstruction, the second a microstructure with no intragranular misorientation (i.e., grain-averaged orientations). We find significant differences in the predicted deformation mechanism activation, distribution of stress, and distribution of plastic strain between simulations containing intragranular misorientation and those with grain-averaged orientations, indicating the necessity for consideration of intragranular orientation fields for accurate predictions. Further, the influence of elastic anisotropy is discussed, along with the effects of intragranular misorientation on fatigue life through the calculation and analysis of fatigue indicator parameters.

cond-mat.mtrl-sci↗

arXiv2024

Revisiting first-principles thermodynamics by quasiharmonic approach: Application to study thermal expansion of additively-manufactured Inconel 625

An innovative method is developed for accurate determination of thermodynamic properties as a function of temperature by revisiting the density functional theory (DFT) based quasiharmonic approach (QHA). The present methodology individually evaluates the contributions from static total energy, phonon, and thermal electron to free energy for increased efficiency and accuracy. The Akaike information criterion with a correction (AICc) is used to select models and model parameters for fitting each contribution as a function of volume. Using the additively manufactured Inconel alloy 625 (IN625) as an example, predicted temperature-dependent linear coefficient of thermal expansion (CTE) agrees well with dilatometer measurements and values in the literature. Sensitivity and uncertainty are also analyzed for the predicted IN625 CTE due to different structural configurations used by DFT, and hence different equilibrium properties determined.

cond-mat.mtrl-sci↗

arXiv2023

An In Situ Study of the Role of Pressure on Fe Recrystallization and Grain Growth during Thermomechanical Processing

Elevated pressures are encountered in many metal forming processes that can alter microstructural evolution rates. Here we measure rate changes with pressure in recrystallization and grain growth in Fe through adaptation of synchrotron-compatible multi-anvil presses, originally designed for study of the mantle. Recrystallization and grain growth are monitored in situ using high-energy X-ray diffraction. Principal component analysis applied to the diffraction images is used to quantify evolution rates, with increasing pressure significantly slowing the process.

cond-mat.mtrl-sci↗

arXiv2023

Combining Synchrotron X-ray Diffraction, Mechanistic Modeling, and Machine Learning for In Situ Subsurface Temperature Quantification during Laser Melting

Laser melting, such as that encountered during additive manufacturing (AM), produces extreme gradients of temperature in both space and time, which in turn influence microstructural development in the material. Qualification and model validation of the process itself and resulting material produced necessitates the ability to characterize these temperature fields. However, well-established means to directly probe material temperature below the surface of an alloy while it is being processed are limited. To address this gap in characterization capabilities, we present a novel means to extract subsurface temperature distribution metrics, with uncertainty, from in situ synchrotron X-ray diffraction measurements to provide quantitative temperature evolution during laser melting. Temperature distribution metrics are determined using Gaussian Process Regression supervised machine learning surrogate models trained with a combination of mechanistic modeling (heat transfer and fluid flow) and X-ray diffraction simulation. Trained surrogate model uncertainties are found to range from 5% to 15% depending on the metric and current temperature. The surrogate models are then applied to experimental data to extract temperature metrics from an Inconel 625 nickel superalloy wall specimen during laser melting. Maximum temperatures of the solid phase in the diffraction volume through melting and cooling are found to reach the solidus temperature as expected, with mean and minimum temperatures found to be several hundred degrees less. The extracted temperature metrics near melting are determined to be more accurate due to the lower relative levels of mechanical elastic strains. However, uncertainties for temperature metrics during cooling are increased due to the effects of thermomechanical stress.

cond-mat.mtrl-sci↗

arXiv2022

Graph Neural Network Modeling of Grain-scale Anisotropic Elastic Behavior using Simulated and Measured Microscale Data

Here we assess the applicability of graph neural networks (GNNs) for predicting the grain-scale elastic response of polycrystalline metallic alloys. Using GNN surrogate models, grain-averaged stresses during uniaxial elastic tension in Low Solvus High Refractory (LSHR) Ni Superalloy and Ti 7wt%Al (Ti-7Al), as example face centered cubic and hexagonal closed packed alloys, are predicted. A transfer learning approach is taken in which GNN surrogate models are trained using crystal elasticity finite element method (CEFEM) simulations and then the trained surrogate models are used to predict the mechanical response of microstructures measured using high-energy X-ray diffraction microscopy (HEDM). The performance of using various microstructural and micromechanical descriptors for input nodal features to the GNNs is explored through comparisons to traditional mean-field theory predictions, reserved full-field CEFEM data, and measured far-field HEDM data. The effects of elastic anisotropy on GNN model performance and outlooks for extension of the framework are discussed.

cond-mat.mtrl-sci↗

arXiv2022

Non-destructive Depth-Resolved Characterization of Residual Strain Fields in High Electron Mobility Transistors using Differential Aperture X-ray Microscopy

Localized residual stress and elastic strain concentrations in microelectronic devices often affect the electronic performance, resistance to thermomechanical damage, and, likely, radiation tolerance. A primary challenge for characterization of these concentrations is that they exist over sub-$μ$m length-scales, precluding their characterization by more traditional residual stress measurement techniques. Here we demonstrate the use of synchrotron X-ray -based differential aperture X-ray microscopy (DAXM) as a viable, non-destructive means to characterize these stress and strain concentrations in a depth-resolved manner. DAXM is used to map two-dimensional strain fields between source and drain in a gallium nitride (GaN) layer within high electron mobility transistors (HEMTs) with sub-$μ$m spatial resolution. Strain fields at various positions in both pristine and irradiated HEMT specimens are presented in addition to a preliminary stress analysis to estimate the distribution of various stress components within the GaN layer. $γ$-irradiation is found to significantly reduce the lattice plane spacing in the GaN along the sample normal direction which is attributed to radiation damage in transistor components bonded to the GaN during irradiation.

physics.app-ph↗

arXiv2022

The influence of alloying on slip intermittency and the implications for dwell fatigue in titanium

Dwell fatigue, the reduction in fatigue life experienced by titanium alloys due to holds at stresses as low as 60% of yield, has been implicated in several uncontained jet engine failures. Dislocation slip has long been observed to be an intermittent, scale-bridging phenomenon, similar to that seen in earthquakes but at the nanoscale, leading to the speculation that large stress bursts might promote the initial opening of a crack. Here we observe such stress bursts at the scale of individual grains in situ, using high energy X-ray diffraction microscopy in Ti-7Al-O alloys. This shows that the detrimental effect of precipitation of ordered Ti_3Al is to increase the magnitude of rare pri and bas slip bursts associated with slip localisation. In contrast, the addition of trace O interstitials is beneficial, reducing the magnitude of bas slip bursts and increasing the homogeneity between basal and prismatic slip. This is further evidence that the formation of long paths for easy basal plane slip localisation should be avoided when engineering titanium alloys against dwell fatigue.

cond-mat.mtrl-sci↗

arXiv2021

Analysis of a Three-Dimensional Slip Field in a Hexagonal Ti Alloy from in-situ High-Energy X-ray Diffraction Microscopy Data

Here we analyze a three-dimensional distribution of crystallographic slip measured in-situ during the uniaxial deformation of hexagonal Ti-7Al. The slip field is reconstructed using a novel methodology that combines spatially resolved lattice orientation fields and grain-averaged stresses measured using high-energy X-ray diffraction microscopy (HEDM) with crystal plasticity. Analysis is performed to explore lattice orientation dependence, stress dependence, and connectivity (network relationships) of grains experiencing elevated amounts of slip. Elevated slip is found to be primarily associated with a single large network of connected grains, and within this network, a clustered group of grains oriented favorably for slip are found to have outsized structural importance. The effect of different rate sensitivities of families of slip systems on reconstructed slip activity is also discussed.

cond-mat.mtrl-sci↗

arXiv2020

Three-Dimensional In Situ Texture Development and Plasticity Accumulation in the Cyclic Loading of an alpha-Ti Alloy

High-energy synchrotron x-rays are used to track grain rotations and the micromechanical evolution of a hexagonal Ti-7Al microstructure as it is cyclically loaded below its macroscopic yield stress. The evolution of the grains through 200 cycles reveals a continual change in von Mises stress and orientation across the entire specimen indicating a slow accumulation of plasticity even though the sample was cycled below its macroscopic yield. Grain reorientation is consistent with the development of a tension texture despite the negligible magnitude of (macroscopic) plastic strain. It is observed that grains in a "hard" orientation (c-axis close to the loading direction) retain more residual stress on their slip systems upon unloading than the grains in a "soft" orientation.

cond-mat.mtrl-sci↗

arXiv2020

Grain-Resolved Temperature-Dependent Anisotropy in Hexagonal Ti-7Al Revealed by Synchrotron X-Ray Diffraction

Hexagonal metals have anisotropic coefficients of thermal expansion causing grain-level internal stresses during heating. High energy x-ray diffraction microscopy, a non-destructive, in situ, micromechanical and microstructural characterization technique, has been used to determine the anisotropic coefficients of thermal expansion (CTEs) for Ti-7Al. Two samples of polycrystalline $α$-phase Ti-7Al were continuously heated from room temperature to 850 $^\circ$C while far-field HEDM scans were collected. The results showed a change in the ratio of the CTEs in the 'a' and 'c' directions which explains discrepancies found in the literature. The CTE additionally appears to be affected by the dissolution of $α_2$ precipitates. Analysis of the grain-resolved micromechanical data also shows reconfiguration of the grain scale stresses likely due to anisotropic expansion driving crystallographic slip.

cond-mat.mtrl-sci↗

arXiv2018

Three-dimensional in situ characterization of phase transformation induced austenite grain refinement in nickel-titanium

Near-field and far-field high-energy diffraction microscopy and microcomputed tomography X-ray techniques were used to study a bulk single crystal nickel-titanium shape memory alloy sample subjected to thermal cycling under a constant applied load. Three-dimensional in situ reconstructions of the austenite microstructure are presented, including the structure and distribution of emergent grain boundaries. After one cycle, the subgrain structure is significantly refined, and heterogeneous Σ3 and Σ9 grain boundaries emerge. The low volume and uneven dispersion of the emergent Σ boundaries across the volume show why previous transmission electron microscopy investigations of Σ grain boundary formation were inconsistent.

cond-mat.mtrl-sci↗