arXiv subjects

Joseph T. McKeown

Publications and source records attributed to Joseph T. McKeown.

6 recordsLinked to original sources

arXiv2026

Microstructure evolution during rapid solidification of hypoeutectic Al-Ag alloys near absolute stability

Microsegregation-free microstructures can form by solidifying at velocities beyond the absolute stability limit ($V_{\text{abs}}$), where solute partitioning is suppressed by a stable, planar solid-liquid interface. Producing such microstructures is of considerable practical interest; however, $V_{\text{abs}}$ typically exceeds the ${\sim}1$ m/s growth rates encountered in additive manufacturing (AM). Here we demonstrate the absolute stability limit can be reached in sufficiently concentrated hypoeutectic Al-Ag alloys at growth rates well below the 1~m/s typically encountered in additive manufacturing. Dynamic Transmission Electron Microscopy (DTEM) of rapid solidification front evolution -- following laser spot melting of Al-Ag thin films -- combined with postmortem microstructural characterization, enables detailed quantitative comparison with both phase-field (PF) simulations and a sharp-interface linear stability analysis that uses a non-equilibrium, velocity-dependent phase diagram extracted from the PF model. The analysis predicts that $V_{\text{abs}}$ follows a trend similar to that of the miscibility gap, first increasing and then decreasing with Ag concentration. Predicted values of $V_{\text{abs}}$ are in good quantitative agreement with PF simulations over the entire hypoeutectic concentration range and with experiments for three concentrated alloys. These results inform the prediction and control of microstructural development in concentrated alloys near the absolute stability limit under AM conditions.

cond-mat.mtrl-sci↗

arXiv2026

Monte Carlo Simulations of Crystal Defects in Open Ensembles

Zero- and two-dimensional crystal defects form in open statistical ensembles, such as the grand canonical, that are usually inaccessible with conventional simulation techniques. This longstanding challenge is overcome with a new Hamiltonian Monte Carlo method that samples energy-biased gradual transformations. The method enables free energy calculations for nonideal point defects and the direct prediction of finite-temperature interface structures.

cond-mat.mtrl-sci↗

arXiv2025

Harnessing On-Machine Metrology Data for Prints with a Surrogate Model for Laser Powder Directed Energy Deposition

In this study, we leverage the massive amount of multi-modal on-machine metrology data generated from Laser Powder Directed Energy Deposition (LP-DED) to construct a comprehensive surrogate model of the 3D printing process. By employing Dynamic Mode Decomposition with Control (DMDc), a data-driven technique, we capture the complex physics inherent in this extensive dataset. This physics-based surrogate model emphasizes thermodynamically significant quantities, enabling us to accurately predict key process outcomes. The model ingests 21 process parameters, including laser power, scan rate, and position, while providing outputs such as melt pool temperature, melt pool size, and other essential observables. Furthermore, it incorporates uncertainty quantification to provide bounds on these predictions, enhancing reliability and confidence in the results. We then deploy the surrogate model on a new, unseen part and monitor the printing process as validation of the method. Our experimental results demonstrate that the predictions align with actual measurements with high accuracy, confirming the effectiveness of our approach. This methodology not only facilitates real-time predictions but also operates at process-relevant speeds, establishing a basis for implementing feedback control in LP-DED.

eess.SY↗

arXiv2023

A Data-Driven, Non-Linear, Parameterized Reduced Order Model of Metal 3D Printing

Directed energy deposition (DED) is a promising metal additive manufacturing technology capable of 3D printing metal parts with complex geometries at lower cost compared to traditional manufacturing. The technology is most effective when process parameters like laser scan speed and power are optimized for a particular geometry and alloy. To accelerate optimization, we apply a data-driven, parameterized, non-linear reduced-order model (ROM) called Gaussian Process Latent Space Dynamics Identification (GPLaSDI) to physics-based DED simulation data. With an appropriate choice of hyperparameters, GPLaSDI is an effective ROM for this application, with a worst-case error of about 8% and a speed-up of about 1,000,000x with respect to the corresponding physics-based data.

math.NA↗

arXiv2021

Orientation gradients in rapidly solidified pure aluminum thin films: comparison of experiments and phase-field crystal simulations

Rapid solidification experiments on thin film aluminum samples reveal the presence of lattice orientation gradients within crystallizing grains. To study this phenomenon, a single-component phase-field crystal (PFC) model that captures the properties of solid, liquid, and vapor phases is proposed to model pure aluminium quantitatively. A coarse-grained amplitude representation of this model is used to simulate solidification in samples approaching micrometer scales. The simulations reproduce the experimentally observed orientation gradients within crystallizing grains when grown at experimentally relevant rapid quenches. We propose a causal connection between formation of defects and orientation gradients.

cond-mat.mtrl-sci↗

arXiv2018

Observation of a metastable intermediate during solid-solid phase transformation in response to rapid compression

In order to probe the mechanism of solid-solid phase transformations, we have applied ultrafast shock wave compression (120 picosecond duration) and ultrashort (130 femtosecond) x-ray diffraction at the Linac Coherent Light Source (LCLS) to probe the compression-induced phase transition pathway in zirconium. Surprisingly, rather than transform from alpha-Zr to the more disordered hex-3 equilibrium omega-Zr phase, in its place we find the formation of a non-equilibrium body-centered cubic (bcc) metastable intermediate. Theoretically hypothesized for several decades, this bcc intermediate state has now been found to be dynamically stabilized under uniaxial loading at sub-nanosecond timescales. Molecular dynamics simulations of shock-wave propagation in zirconium predict this transformation via the dynamical intermediate state. In contrast with longer timescale experiments where the phase diagram alone is an adequate predictor of the crystalline structure of a material, our recent study highlights the importance of metastability and time-dependence in the kinetics of phase transformation at extreme conditions.

cond-mat.mtrl-sci↗