Refractory high entropy alloys (RHEAs) have gained significant attention in recent years as potential
replacements for Ni-based superalloys in gas turbine applications. Improving their properties, such as their
high-temperature yield strength, is crucial to their success. Unfortunately, exploring this vast chemical space
using exclusively experimental approaches is impractical due to the considerable cost of the synthesis,
processing, and testing of candidate alloys, particularly at operation-relevant temperatures. On the other hand,
the lack of reasonably accurate predictive property models, especially for high-temperature properties, makes
traditional Integrated Computational Materials Engineering (ICME) methods inadequate. In this paper, we
address this challenge by combining machine-learning models, easy-to-implement physics-based models, and
inexpensive proxy experimental data to develop robust and fast-acting models using the concept of Bayesian
updating. The framework combines data from one of the most comprehensive databases on RHEAs (Borg et al.,
2020) with one of the most widely used physics-based strength models for BCC-based RHEAs (Maresca and
Curtin, 2020) into a compact predictive model that is significantly more accurate than the state-of-the-art.
This model is cross-validated, tested for physics-informed extrapolation, and rigorously benchmarked against
standard Gaussian process regressors (GPRs) in a toy Bayesian optimization problem. Such a model can be
used as a tool within ICME frameworks to screen for RHEAs with superior high-temperature properties. The
code associated with this work is available at: https://codeocean.com/capsule/7849853/tree/v2.
more »
« less
Mining of lattice distortion, strength, and intrinsic ductility of refractory high entropy alloys
Severe lattice distortion is a prominent feature of high-entropy alloys (HEAs) considered a reason for many of those alloys’ properties. Nevertheless, accurate characterizations of lattice distortion are still scarce to only cover a tiny fraction of HEA’s giant composition space due to the expensive experimental or computational costs. Here we present a physics-informed statistical model to efficiently produce high-throughput lattice distortion predictions for refractory non-dilute/high-entropy alloys (RHEAs) in a 10-element composition space. The model offers improved accuracy over conventional methods for fast estimates of lattice distortion by making predictions based on physical properties of interatomic bonding rather than atomic size mismatch of pure elements. The modeling of lattice distortion also implements a predictive model for yield strengths of RHEAs validated by various sets of experimental data. Combining our previous model on intrinsic ductility, a data mining design framework is demonstrated for efficient exploration of strong and ductile single-phase RHEAs.
more » « less- PAR ID:
- 10405381
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- npj Computational Materials
- Volume:
- 9
- Issue:
- 1
- ISSN:
- 2057-3960
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Additive Manufacturing (AM) has opened new frontiers for the design of refractory high-entropy alloys (HEAs) for high-temperature applications. The thermal conductivity of the AM feedstock is among the most important thermo-physical properties that control the melting and solidification process. Despite its significance, there remains a notable gap in both computational and experimental research concerning the thermal conductivity of HEAs. Here, we use density functional theory (DFT) to systematically investigate the alloying effects on the transport properties of Ti-Cr-Mo-W-V-Nb-Ta RHEAs, including electrical and thermal conductivities and the Seebeck coefficient. The relaxation time of charge carriers is a key underlying parameter determining thermal conductivity that is exceedingly challenging to predict from first principles alone, and we thus follow the approach by Mukherjee, Satsangi, and Singh [Chem Mater 32, 6507 (2022)] to optimize the relaxation time for RHEAs. We validated thermal conductivity predictions on elemental solids, binary and ternary alloys, and RHEAs and compared them against thermodynamic (CALPHAD) predictions and our experiments with good correlations. To understand observed trends in thermal conductivity, we assessed the phase stability, electronic structure, phonon, and intrinsic- and tensile strength of down-selected RHEAs. Our electronic structure and phonon results connect well with the observed compositional trends for thermal transport in RHEAs. Our DFT assessment and CALPHAD predictions provide a unique design guide for RHEAs with tailored thermal conductivity, a critical consideration for AM and thermal-management applications.more » « less
-
null (Ed.)Hardness is an essential property in the design of refractory high entropy alloys (RHEAs). This study shows how a neural network (NN) model can be used to predict the hardness of a RHEA, for the first time. We predicted the hardness of several alloys, including the novel C0.1Cr3Mo11.9Nb20Re15Ta30W20 using the NN model. The hardness predicted from the NN model was consistent with the available experimental results. The NN model prediction of C0.1Cr3Mo11.9Nb20Re15Ta30W20 was verified by experimentally synthesizing and investigating its microstructure properties and hardness. This model provides an alternative route to determine the Vickers hardness of RHEAs.more » « less
-
more » « less
Abstract Severe distortion is one of the four core effects in single‐phase high‐entropy alloys (HEAs) and contributes significantly to the yield strength. However, the connection between the atomic‐scale lattice distortion and macro‐scale mechanical properties through experimental verification has yet to be fully achieved, owing to two critical challenges: 1) the difficulty in the development of homogeneous single‐phase solid‐solution HEAs and 2) the ambiguity in describing the lattice distortion and related measurements and calculations. A single‐phase body‐centered‐cubic (BCC) refractory HEA, NbTaTiVZr, using thermodynamic modeling coupled with experimental verifications, is developed. Compared to the previously developed single‐phase NbTaTiV HEA, the NbTaTiVZr HEA shows a higher yield strength and comparable plasticity. The increase in yield strength is systematically and quantitatively studied in terms of lattice distortion using a theoretical model, first‐principles calculations, synchrotron X‐ray/neutron diffraction, atom‐probe tomography, and scanning transmission electron microscopy techniques. These results demonstrate that severe lattice distortion is a core factor for developing high strengths in refractory HEAs.
-
Refractory high-entropy alloys (RHEAs) are strong candidates for use in high-temperature engineering applications. As such, the thermodynamic properties as a function of temperature for a variety of RHEA systems need to be studied. In the present work, thermodynamic quantities such as entropy, enthalpy, heat capacity at constant volume, and linear thermal expansion are calculated for three quaternary and three quinary single-phase, BCC RHEAs: AlMoNbV, NbTaTiV, NbTaTiZr, AlNbTaTiV, HfNbTaTiZr, and MoNbTaVW. First-principle calculations based on density functional theory are used for the calculations, and special quasirandom structures (SQSs) are used to represent the random solid solution nature of the RHEAs. A code for the finite temperature thermodynamic properties using the Debye-Grüneisen model is written and employed. For the first time, the finite temperature thermodynamic properties of all 24 atomic configuration permutations of a quaternary RHEA are calculated. At most, 1.7% difference is found between the resulting properties as a function of atomic configuration, indicating that the atomic configuration of the SQS has little effect on the calculated thermodynamic properties. The behavior of thermodynamic properties among the RHEAs studied is discussed based on valence electron concentration and atomic size. Among the quaternary RHEAs studied, namely AlMoNbV, NbTaTiZr, and NbTaTiV, it is found that the presence of Zr contributes to higher entropy. Additionally, at lower temperatures, Zr contributes to higher heat capacity and thermal expansion compared to the alloys without Zr, possibly due to its valence electron concentration. At higher temperatures, Al contributes to higher heat capacity and thermal expansion, possibly due its ductility. Among the quinary systems, the presence of Mo, W, and/or V causes the RHEA to have a lower thermal expansion than the other systems studied. Finally, when comparing the systems with the NbTaTi core, the addition of Al increases thermal expansion, while the removal of Zr lowers the thermal expansion.more » « less
