arXiv subjects

James Hanagan

Publications and source records attributed to James Hanagan.

3 recordsLinked to original sources

arXiv2026

Element-Specific Solute Trapping and Grain Structure Evolution during Laser Powder Bed Fusion of Multicomponent Alloys

Under the rapid solidification conditions of laser powder bed fusion (LPBF), solute trapping manifests in an element-specific manner, altering nonequilibrium partitioning, constitutional undercooling, and grain selection behavior in multicomponent alloys. Here, we elucidate the mechanisms by which element-specific solute trapping governs nucleation behavior and grain structure evolution during LPBF demonstrated on a SS316L. This requires quantitative description of nonequilibrium multicomponent thermodynamics and grain evolution across broad LPBF solidification conditions, which is achieved through a CALPHAD-informed Gaussian Process Regression (GPR)-assisted Phase-Field (PF) approach. The predicted transitions in grain morphology and grain size are validated against EBSD measurements under multiple LPBF processing conditions. Results demonstrate that increasing solidification rate drives a composition-dependent transition from solute diffusion-controlled nucleation to solute trapping-controlled grain growth, where nonequilibrium solute redistribution intensified by solute trapping suppresses equiaxed grain formation despite high cooling rates. Quantitative decomposition of multicomponent undercooling further reveals distinct element-specific sensitivities to solute trapping, where C, Cr, and Mo remain dominant contributors to the overall undercooling, while the undercooling contribution of low-partitioning elements such as S and P are strongly suppressed relative to their equilibrium values under rapid solidification conditions. These results reveal how element-specific solute trapping governs grain selection in multicomponent alloys, providing a mechanistic basis for alloy design under nonequilibrium solidification conditions.

cond-mat.mtrl-sci↗

arXiv2025

Compositionally Grading Alloy Stacking Fault Energy using Autonomous Path Planning and Additive Manufacturing with Elemental Powders

Compositionally graded alloys (CGAs) are often proposed for use in structural components where the combination of two or more alloys within a single part can yield substantial enhancement in performance and functionality. For these applications, numerous design methodologies have been developed, one of the most sophisticated being the application of path planning algorithms originally designed for robotics to solve CGA design problems. In addition to the traditional application to structural components, this work proposes and demonstrates the application of this CGA design framework to rapid alloy design, synthesis, and characterization. A composition gradient in the CoCrFeNi alloy space was planned between the maximum and minimum stacking fault energy (SFE) as predicted by a previously developed model in a face-centered cubic (FCC) high entropy alloy (HEA) space. The path was designed to be monotonic in SFE and avoid regions that did not meet FCC phase fraction and solidification range constraints predicted by CALculation of PHAse Diagrams (CALPHAD). Compositions from the path were selected to produce a linear gradient in SFE, and the CGA was built using laser directed energy deposition (L-DED). The resulting gradient was characterized for microstructure and mechanical properties, including hardness, elastic modulus, and strain rate sensitivity. Despite being predicted to contain a single FCC phase throughout the gradient, part of the CGA underwent a martensitic transformation, thereby demonstrating a limitation of using equilibrium CALPHAD calculations for phase stability predictions. More broadly, this demonstrates the ability of the methods employed to bring attention to blind spots in alloy models.

cond-mat.mtrl-sci↗

arXiv2024

Performance-driven Computational Design of Multi-terminal Compositionally Graded Alloy Structures using Graphs

The spatial control of material placement afforded by metal additive manufacturing (AM) has enabled significant progress in the development and implementation of compositionally graded alloys (CGAs) for spatial property variation in monolithic structures. However, cracking and brittle phase formation have hindered CGA development, with limited research extending beyond materials design to structural design. Notably, the high-dimensional alloy design space (systems with more than three active elements) remains poorly understood, specifically for CGAs. As a result, many prior efforts take a trial-and-error approach. Additionally, current structural design methods are inadequate for joining dissimilar alloys. In light of these challenges, recent work in graph information modeling and design automation has enabled topological partitioning and analysis of the alloy design space, automated design of multi-terminal CGAs, and automated conformal mapping of CGAs onto corresponding structural geometries. In comparison, prior gradient design approaches are limited to two-terminal CGAs. Here, we integrate these recent advancements, demonstrating a unified performance-driven CGA design approach on a gas turbine blade with broader application to other material systems and engineering structures.

cond-mat.mtrl-sci↗