High-throughput materials screening algorithm based on first-principles density functional theory and artificial neural network for high-entropy alloys

Abstract

This work introduced the high-throughput phase prediction of PtPd-based high-entropy alloys via the algorithm based on a combined Korringa-Kohn-Rostoker coherent potential approximation (KKR-CPA) and artificial neural network (ANN) technique. As the first step, the KKR-CPA was employed to generate 2,720 data of formation energy and lattice parameters in the framework of the first-principles density functional theory. Following the data generation, 15 features were selected and verified for all HEA systems in each phase (FCC and BCC) via ANN. The algorithm exhibited high accuracy for all four prediction models on 36,556 data from 9139 HEA systems with 137,085 features, verified by R2 closed to unity and the mean relative error (MRE) within 5%. From this dataset comprising 5002 and 4137 systems of FCC and BCC phases, it can be realized based on the highest tendency of HEA phase formation that (1) Sc, Co, Cu, Zn, Y, Ru, Cd, Os, Ir, Hg, Al, Si, P, As, and Tl favor FCC phase, (2) Hf, Ga, In, Sn, Pb, and Bi favor BCC phase, and (3) Ti, V, Cr, Mn, Fe, Ni, Zr, Nb, Mo, Tc, Rh, Ag, Ta, W, Re, Au, Ge, and Sb can be found in both FCC and BCC phases with comparable tendency, where all predictions are in good agreement with the data from the literature. Thus, the combination of KKR-CPA and ANN can reduce the computational cost for the screening of PtPd-based HEA and accurately predict the structure, i.e., FCC, BCC, etc.

A review on high-throughput development of high-entropy alloys by combinatorial methods

“…This method maps the quantummechanical many-electron Schrodinger equation onto an effective one-electron problem using electron density as a key variable. This mapping also requires the use of the exchange-correlation functional of the electron density which is not known for most systems and must be approximated either with the local density approximation (LDA) [96,97] or the generalized gradient approximation (GGA) [98][99][100] . Once these fundamental functions are calculated, the overall energy of the system can be calculated and used to determine the energy of formation for the possible phases of the system.…”

“…The use of combining MD simulations with ML techniques was also explored by Zhang et al to explore the non-equiatomic compositions within the Fe-Co-Cr-Ni-Mn alloy system [124] . In this case, the deformation of 100 compositions with a single-crystal structure was simulated in three different crystallographic directions, [100], [110], and [111]. The simulated stress-strain responses of these compositions are shown in Figure 8A.…”

High-Throughput First-Principles Prediction of Interfacial Adhesion Energies in Metal-on-Metal Contacts

“…Moreover in recent times, alongside the fundamental combination of theory and experiments on specific problems, high-throughput density functional theory (DFT) approaches are used in materials design and discovery. − Increasingly complex DFT-based high-throughput workflows have been developed, screening molecular adsorption energies and sites on intermetallic surfaces in view of electrochemical catalysis applications, looking for novel 2D superconductors, predicting lattice parameters and formation energies of high-entropy alloys, and identifying promising metal–organic frameworks for heterogeneous catalysis. , However, in this quickly developing framework, a systematic study of mechanical and tribological properties of solid–solid heterointerfaces has not been addressed yet. Most probably this is due to the inherent difficulties that this kind of system poses and to the fact that the community of references (the tribology, metallurgy, and mechanical manufacturing communities) most of the time relies on classical macroscopic engineering models.…”

First‐Principles Density Functional Theory and Machine Learning Technique for the Prediction of Water Adsorption Site on PtPd‐Based High‐Entropy‐Alloy Catalysts

“…The 56 PtPd XYZ HEAs with the elements of Ru, Rh, Ag, Au, Fe, Co, Ni, and Cu ( X ≠ Y ≠ Z ) are considered because our previous screening work demonstrated that these selected HEAs are thermodynamically formed as an FCC structure. [ 43 ] The adsorption energy and electronic properties of all 56 HEA surfaces are discussed. Finally, the analysis results provide the suitable HEA formula for H 2 O activation during the WGSR.…”