Materials Design and Processing Optimization for Advanced Manufacturing: From Fundamentals to Application: Materials Design and Processing Optimization: Session IV
Sponsored by: TMS Structural Materials Division, TMS: Alloy Phases Committee
Program Organizers: Wei Xiong, University of Pittsburgh; Dana Frankel, Apple Inc; Gregory Olson, Massachusetts Institute of Technology

Tuesday 4:00 PM
March 1, 2022
Room: 253B
Location: Anaheim Convention Center

Session Chair: Le Zhou, Marquette University; Xiaoxiang Yu, Novelis Inc.


4:00 PM  
Variation in Density, Phase Constituents, Microstructure, Surface Roughness and Modulus/Hardness Observed from LPBF Parametric Study of Ti – 6 wt.% Al – 4 wt.% V Alloy: Asif Mahmud1; Jeongmin Woo1; Holden Hyer1; Ji-Yoon Kim2; Thinh Huynh1; Abhishek Mehta1; Kee-Ahn Lee2; Yongho Sohn1; 1University of Central Florida; 2Inha University
    Ti6Al4V alloy has a wide range of applications from aerospace to prosthetics, potentially requiring variation in physical and mechanical properties controlled by the laser powder bed fusion (LPBF) parameters. A wide range of volumetric energy density (VED), varied by independently changing laser power and scan speed of LPBF, was examined to document the changes in density, phase constituents, microstructure, surface roughness and modulus. VED associated with alloy density greater than 99.5% was found around 70 J/mm3 with phase constituents of acicular α’ phase, surface roughness of 10 µm, and elastic modulus of 118 GPa. Excessive VED yielded keyhole porosity, smoother surface down to 5 µm, α’/α and β phases, and higher modulus. VED lower than optimized was related to lack of fusion flaws, rough surface up to 37 µm, acicular α’ phase, and lower modulus. Changes in these characteristics are discussed with respect to LPBF parameters and solidification/cooling behavior.

4:20 PM  
Towards Laser Powder Bed Process Optimization: An Approach for Fast Process-microstructure Predictions: Mason Jones1; Jean-Pierre Delplanque1; 1University of California Davis
    This work investigates the feasibility of a fast method for predicting part scale microstructural characteristics of objects produced using the laser powder bed fusion process. Traditional predictive computational models for this process are at present too slow to be used for effective optimization of process parameters. The proposed approach uses a fast physics-based surrogate thermal model and identified thermal characteristics to predict selected microstructural characteristics. Verification of this method will be enabled by a custom SPPARKS kinetic Monte Carlo (KMC) application capable of using the temperature field predicted by the thermal model for predictions of the microstructure. The development of this KMC application and its validation using available experimental data will also be discussed.

4:40 PM  Invited
Additive Manufacturing of High-performance Compositionally Complex Metal Alloys: Wen Chen1; Shahryar Mooraj1; 1University of Massachusetts-Amherst
     The increasing demands for materials require increasingly complex compositions and microstructures, which meanwhile bring grand challenges in processing and understanding of microstructure-property relationships in these materials since many microstructural features are interconnected by conventional processing routes. To overcome these challenges, I will present some recent work in our group on fabrication of compositionally complex metal alloys by additive manufacturing, which enables the access of engineered hierarchical microstructures with excellent mechanical properties. Specifically, I will discuss the potential of using laser additive manufacturing and direct ink writing based 3D printing techniques to fabricate some compositionally complex metal alloys such as metallic glass composites and high-entropy alloys with heterogeneous microstructures by tailoring the additive manufacturing process protocol towards superior mechanical performance.