Computational Thermodynamics and Kinetics: Phase Stability I and II
Sponsored by: TMS Functional Materials Division, TMS Materials Processing and Manufacturing Division, TMS Structural Materials Division, TMS: Chemistry and Physics of Materials Committee
Program Organizers: Vahid Attari, Texas A&M University; Sara Kadkhodaei, University of Illinois Chicago; Eva Zarkadoula, Oak Ridge National Laboratory; Damien Tourret, IMDEA Materials Institute; James Morris, Ames Laboratory
Monday 8:30 AM
February 28, 2022
Location: Anaheim Convention Center
Session Chair: Prashant Singh, Ames Lab; Mira Todorova, Max-Planck-Institute
Stability of Immiscible Nanocrystalline Alloys in Compositional and Thermal Fields: Joseph Monti1; Emily Hopkins2; Fadi Abdeljawad3; Khalid Hattar1; Brad Boyce1; Remi Dingreville1; 1Sandia National Laboratories; 2Johns Hopkins University; 3Clemson University
Alloying is often employed to stabilize nanocrystalline materials against microstructural coarsening via kinetic or thermodynamic stabilization mechanisms. The interplay between these mechanisms depends on grain-boundary character and on any imposed compositional and thermal fields that further promote or inhibit grain growth. We study the stability of immiscible nanocrystalline alloys in homogeneous and heterogeneous compositional and thermal fields by using a multi-phase-field formulation for anisotropic grain growth with grain-boundary character-dependent segregation properties. Our results demonstrate the role of grain-boundary heterogeneity on solute-induced stabilization. We show that increasing the solute concentration progressively slows grain growth via both stabilization mechanisms, while increasing the temperature generally weakens thermodynamic stabilization effects due to entropic contributions. Finally, we demonstrate as a proof-of-concept that spatially-varying compositional and thermal fields can be used to construct dynamically-stable, graded, nanostructured materials. We compare our model predictions to experimental results of microstructures in Pt-Au nanocrystalline alloys.
Ab Initio Simulations on the Pure Cr Lattice Stability at 0K: Verification with the Fe-Cr and Ni-Cr Binary Systems: Songge Yang1; Yi Wang2; Zi-kui Liu2; Yu Zhong1; 1Worcester Polytechnic Institute; 2Pen State University
Significant discrepancies have been observed and discussed on the lattice stability of Cr between the ab initio and CALPHAD approaches. In the current work, we carefully examined the possible structures for pure Cr and reviewed the history back from how Kaufman originally determined the Gibbs energy of FCC-Cr in the 1970s. The reliability of Cr lattice stability derived by both approaches was discussed. It is concluded that the CALPHAD Cr lattice stability has large uncertainty. Meanwhile, we cannot claim the ab initio value is error-free as FCC-Cr is a unstable phase under ambient conditions. As both approaches have their limitations, the present work propose to integrate the ab initio results into the CALPHAD platform for the development of the next generation CALPHAD database. The Fe-Cr and Ni-Cr binary systems were chosen as case studies demonstrating the capability to adopt the ab initio Cr lattice stability directly into the CALPHAD modeling.
9:10 AM Invited
NOW ON-DEMAND ONLY – Role of Alloying on Tunability of Martensitic Phase Transformation in Multi-principal Element Alloys: Prashant Singh1; Sezer Picak2; Aayush Sharma1; A.V. Smirnov1; Y.I. Chumlyakov3; Raymundo Arroyave4; Ibrahim Karaman4; Duane D. Johnson1; 1Ames Laboratory; 2Texas A&M University ; 3Tomsk State University; 4Texas A&M University
Multi-principal element alloys (MPEAs) are an intriguing class of materials where chemical disorder can control structure and property relations. Employing density-functional theory methods, we tune thermodynamic stability between f.c.c. and h.c.p. phases in Fe-Mn-Co-Cr-based MPEAs and correlate the free-energy difference and stacking-fault energy directly with martensitic transformation and chemical short-range order. The predicted transformation in FexMn80-xCo10Cr10 at x=40at.% was supported by large-scale molecular dynamic simulations and confirmed by precision experiments. These results provide direct understanding of transformation-induced/twinning-induced plasticity (TRIP/TWIP) in this MPEA. Our approach establishes quantitative theory-guided design for the next-generation alloys with superior structure-property relations and provides unique insights for controlling transformation at the electronic level in technologically relevant alloys.
Compositional Patterning in Irradiated Polycrystalline Alloys: Robert Averback1; Pascal Bellon1; Qun Li1; 1University of Illinois at Urbana-Champaign
Irradiation can induce the self-organization of phase-separating alloy systems into bulk nanoscale compositional patterns (CP) owing to the competition between finite-range ballistic mixing with thermodynamically-driven decomposition. Here we investigate whether CP can also take place at grain boundaries (GBs), or simultaneously in the bulk and at GBs. We address these questions with a multi-order parameter phase-field model for a model polycrystalline phase-separating binary alloy, which includes an irradiation-induced finite-range gaussian mixing. Varying the difference of the heat of mixing between the GB and bulk phases, and the difference between the solute and solvent Gibbs free energies in the GB phase, it is shown that CP at GBs as well as dual CP structure can take place by selecting appropriate alloy compositions and irradiation intensities. We also illustrate that patterning under irradiation can be rationalized by mapping it onto a Swift-Hohenberg free energy with effective, competing atomic interactions.
10:00 AM Break
Semiclassical Monte Carlo Simulation of the Heisenberg Model With Near-quantum Accuracy: Flynn Walsh1; Lin-Wang Wang1; Robert Ritchie1; Mark Asta1; 1Lawrence Berkeley National Laboratory
Magnetic interactions play an important role in the thermodynamics of many technologically important materials. However, most conventional simulations of magnetism, such as classical Monte Carlo sampling of the Heisenberg model, fail to reproduce basic experimental results due to the neglect of spin quantization. Alternatively, a semiclassical approach is motivated through a rigorous comparison of the classical and quantum Heisenberg models. It is found that explicitly quantizing spins in accordance with the local quantum environment vastly improves simulation accuracy while requiring no parameters besides spin quantum numbers. This method is demonstrated by calculating various magnetic properties (heat capacity, magnetization, etc.) for ferromagnets and antiferromagnets in good agreement with experiment and quantum methods over a wide range of temperatures.