Bulk Metallic Glasses XVIII: Alloy Development and Application II
Sponsored by: TMS Structural Materials Division, TMS: Mechanical Behavior of Materials Committee
Program Organizers: Peter Liaw, University of Tennessee; Yanfei Gao, University of Tennessee-Knoxville; Hahn Choo, University of Tennessee; Yunfeng Shi, Rensselaer Polytechnic Institute; Robert Maass, Federal Institute of Materials Research and Testing (BAM); Xie Xie, FCA US LLC; Gongyao Wang, Globus Medical
Tuesday 2:00 PM
March 16, 2021
Room: RM 7
Location: TMS2021 Virtual
Session Chair: Eun Park, Seoul National Univerisity; David Browne, University College Dublin
2:00 PM
Fabrication of Fe-based Metallic Glassy Microparts Through Unprecedented Processes: Rui Yamada1; Noriharu Yodoshi1; Naoyuki Nomura1; Junji Saida1; Akira Kawasaki1; 1Tohoku University
The availability/reproducibility of our own developed metallic glassy microparts fabrication process were investigated. We proposed the process where a single spherical particle is used as a raw material for fabricating microparts. Mono-dispersed [(Fe0.5Co0.5)0.75Si0.05B0.2]96Nb4 metallic glassy particles with diameters of several hundred micro meter scales were successfully prepared by a container-less quenching technique called the pulsated orifice ejection method (POEM). The glassy states of the particles prepared at the same batch were confirmed to be almost identical and it was clarified that the particles had technological advantages as raw materials for microparts. In addition, several kinds of microparts were successfully fabricated through the micro viscous flow processing, in which a single POEM particle is directly shaped into the final product. It was revealed that metallic glassy microparts with nearly the same geometric shape with almost the identical thermal/processing histories can be fabricated, verifying the availability of our proposed sequential processes.
2:20 PM Invited
Selection and Testing of Bulk Metallic Glass Alloys for Space-based Mechanisms: Andrew Murphy1; Andrew Norman2; David Browne1; 1University College Dublin; 2European Space Agency
Material selection is a critical part of design for space-based applications. Mechanisms must withstand harsh environments for long durations without maintenance, in situations where component-level failure may cause total mission failure. Bulk Metallic Glasses (BMG)s have demonstrated exceptional mechanical, optical, and magnetic properties. Many commercialization efforts have been made over the last 20 years, particularly for applications where the enhanced properties and/or more efficient processing routes result in significant performance improvements. In this work, four BMG compositions were selected based on the performance requirements of anti-backlash gears and compliant flexures, and alloy samples were fabricated. Five key material properties were selected for evaluation, namely: strength, elastic modulus, hardness, wear resistance, and fatigue life. Initial results demonstrate the suitability of BMGs for these space-mechanism applications. However, there is still a gap in terms of repeatability, predictability, and performance life that need to be overcome before widespread adoption for mission-critical systems.
2:45 PM
Measuring Metallic Glass Viscosities Over Wide Composition Ranges: Sebastian Kube1; Theo Evers1; Will Polsky1; Rodrigo Miguel Ojeda Mota1; Kevin Ryan1; Jan Schroers1; 1Yale University
Amongst the most fundamental properties of metallic glasses (MGs) are the viscosity η(T) and the fragility parameter. Measuring these is challenging and data have only been reported for few compositions and systems. Here, we present a new experimental method to measure the viscosity and fragility across wide composition ranges and for various MG systems: Using co-sputtering and silicon etching, we prepare samples of circular MG thin film membranes freely suspended on silicon chips. Applying gas pressure, these membranes are thermoplastically deformed between Tg and Tx. As the membranes expand into spherical shape, we track the deformation rate as function of the temperature and pressure difference. Using our model of spherical membrane deformation, we then compute viscosities for the full temperature range. We implement this method in a high-throughput fashion and aim to answer fundamental questions, for example how the fragility and the glass forming ability are correlated for MGs.
3:05 PM
Machine Learning from Elemental and Simulation Features for Predicting Glass Forming Ability: Dane Morgan1; Benjamin Afflerbach1; Lane Schultz1; Janine Erickson1; Dan Thoma1; John Perepezko1; Carter Francis1; Paul Voyles1; George Bokas2; Jianqi Xi1; Izabela Szlufarska1; 1University of Wisconsin-Madison; 2Siemens Industry Software
Robust accessible features that can accurately predict glass forming ability remain a grand challenge for the field of bulk metallic glasses. Here we present two approaches to this problem. First, we use machine learning to correlate a large database of measured and estimated critical cooling rates with elemental features and then predict critical cooling trends in a number of ternary metal systems. Then we demonstrate that molecular dynamics modeling can potentially be combined with readily accessible experimental data to obtain characteristic temperatures that can be correlated with critical casting diameters. Potentially useful correlations are obtained but significant uncertainties still plague these models and the open challenges will be discussed.