Environmental Degradation of Multiple Principal Component Materials: Design, Modeling, Simulation, and Machine Learning
Sponsored by: TMS Structural Materials Division, TMS: Corrosion and Environmental Effects Committee
Program Organizers: Wenjun Cai, Virginia Polytechnic Institute and State University; XiaoXiang Yu, Novelis Inc.; Vilupanur Ravi, California State Polytechnic University Pomona; Christopher Weinberger, Colorado State University; Elizabeth Opila, University of Virginia; Bai Cui, University of Nebraska Lincoln; Mark Weaver, University of Alabama; Bronislava Gorr, Karlsruhe Institute of Technology (KIT); Gerald Frankel, Ohio State University; ShinYoung Kang, Lawrence Livermore National Laboratory; Srujan Rokkam, Advanced Cooling Technologies, Inc.

Wednesday 8:30 AM
March 22, 2023
Room: Sapphire 410A
Location: Hilton

Session Chair: Chris Weinberger, Colorado State University; Lin Li, University of Alabama


8:30 AM  Invited
Atomistic Exploration of Light-weight Refractory High Entropy Alloys by Promoting Short-range Chemical Order Using a Machine Learning Potential: Yao Yi1; Xiaoxiang Yu2; Qiang Zhu3; Lin Li1; 1University of Alabama; 2Novelis Global Research Center; 3University of Nevada, Las Vegas
    Refractory high-entropy alloys (RHEAs) emerge as promising high-temperature structural materials due to their remarkable strength. However, the heavy-weight elements, such as W, in the RHEAs could hinder their space application that requires reduced payload weight. Here, atomistic simulations using a machine learning potential are used to explore various non-equiatomic MoTaNbW quinary alloys, focusing on the influence of composition on the chemical short-range order (CSRO), dislocation, and mechanical strength. Annealing the chemically random cells using the Monte Carlo approach reveals that the Mo-Ta pair is favored in all the selected alloys, and an increase in Nb concentration promotes the Mo-Ta pairs and the MoTa B2 unit structure. The enhanced CSRO leads to an increase in diffuse antiphase boundary energies and the critical stress to move the dislocations. In combination with a solid solution strengthening model, the simulation results predict a promising direction in exploring the compositional space of light-weight RHEAs.

8:50 AM  
Enabling Oxidation-resistant Refractory Complex, Concentrated Alloys via a Machine Learning for Accelerated Materials Discovery Framework: Michael Titus1; Sharmila Karumuri1; Saswat Mishra1; Vincent Mika1; Collin Scott1; Austin Hernandez1; Nimish Awalgaonkar1; Kenneth Sandhage1; Ilias Bilionis1; Alejandro Strachan1; 1Purdue University
    Refractory complex, concentrated alloys (RCCAs) are refractory-based alloys comprising four or more elements with near equimolar compositions, and some of these alloys can exhibit superior oxidation resistance compared to traditional refractory-based alloys. In this work, we will present a new machine learning for accelerated materials discovery (ML-AMD) framework that utilizes multi-fidelity and multi-cost experiments with physics-based modeling. This framework includes the integration of an oxidation database containing mass gain data from single- and multiple-component alloys, CALPHAD-based thermodynamic predictions of phase equilibria, first-principles-based predictions of oxide formation, and limited experiments with machine learning and active learning algorithms to accelerate the discovery process. This framework already led to the discovery of new ultra-high strength Al-based solid-solution BCC RCCAs, exceeding strengths found in literature. A new oxidation database of RCCAs and preliminary analysis will be presented, and recent efforts in optimizing oxidation resistance in RCCAs will be shown.

9:10 AM  Invited
High-Throughput Computation of Short-Range Order Types in MPEA Alloys: Christopher Wolverton1; 1Northwestern University
    Short-range order (SRO) in multicomponent alloys is complicated by the number of components, e.g., the number of Warren-Cowley SRO parameters for an M-component alloy is M(M-1)/2. Computational tools such as cluster expansion and machine-learned interatomic potential simulations, can be used to obtain SRO parameters, but these methods are too computationally expensive to survey a wide range of compositions in a high-throughput manner. In an effort to find high-throughput descriptors of SRO, we analyze the connection between SRO and LRO/phase diagrams for multicomponent alloys, and also investigate whether multicomponent SRO can be inferred from lower order (e.g., binary, ternary) information. We find that SRO cannot be determined from considerations of LRO alone, but the two can even qualitatively disagree. Based on energetics of ordered, disordered, and coherent phase separated states, we determine simple energetic descriptors of SRO, allowing us to classify SRO types in a variety of MPEA systems.

9:30 AM  
Modeling Element-resolved Dissolution of Compositionally Complex Alloys in Aqueous Environments: Kang Wang1; Bi-Cheng Zhou1; 1University of Virginia
    Theoretical modeling of dissolution during aqueous corrosion is challenging due to the intertwined processes of electrochemical/chemical reactions, mass/charge transport and migration of metal/electrolyte interface. The additional compositional degrees of freedom in compositionally complex alloys (CCAs) further complicate this issue. Previous modeling efforts generally focus on the overall dissolution rate, while the role of individual alloy element leading to selective dissolution of multicomponent alloys is rarely considered. Here, we apply the principles of nonequilibrium thermodynamics to model the kinetics at the metal/electrolyte interface and incorporate the multiple internal dissipation processes of alloy elements by the maximum entropy production principle. Coupled with realistic thermodynamic and kinetic databases, the dissolution kinetics and corresponding predominant reaction mechanisms for 304 stainless steel and Ni38Fe20Cr22Mn10Co10 CCA are analyzed. With enhanced capability for element-resolved dissolution kinetics, the current work brings corrosion theories primarily for simple metals closer to real-life applications for multicomponent alloys in aqueous environments.

9:50 AM  
Modelling the Interactions of Zirconium Hydrides: Alireza Tondro1; Brooke Bidyk1; Ivan Ho1; Hamidreza Abdolvand1; 1University of Western Ontario
    Hydrogen embrittlement is one of the major concerns in zirconium alloys. Formation of zirconium hydrides significantly accelerates the degradation of zirconium alloys used in the core of nuclear reactors. Zirconium hydrides usually form in different directions and configurations. This work studies the development of stress fields due to the interaction of hydrides and their subsequent effects on redistribution of hydrogen atoms. The effects of hydride distance for different hydride configurations are investigated in a CANDU pressure tube using a coupled diffusion-crystal plasticity finite element approach. It is shown that, due to alignment of growth directions of hydrides, stress fields in the vicinity of two parallel hydrides interact more significantly compared to those of perpendicular hydrides. Also, the effects of hydride length and width are studied where it is shown that hydrides with a width of 1 μm propagate faster than those having lower and higher widths.