The AFLOW Fleet for Materials Discovery

Toher, Cormac; Oses, Corey; Hicks, David; Gossett, Eric; Rose, Frisco; Nath, Pinku; Usanmaz, Demet; Ford, Denise C.; Perim, Eric; Calderón, Camilo E.; Plata, José J.; Lederer, Yoav; Jahnátek, Michal; Wang, Shidong; Xue, Junkai; Rasch, Kevin; Chepulskii, Roman V.; Taylor, Richard; Gomez, Geena; Shi, Harvey; Supka, Andrew; Orabi, Rabih Al Rahal Al; Gopal, Priya; Cerasoli, Frank; Liyanage, Laalitha; Wang, Haihang; Siloi, Ilaria; Agapito, Luis A.; Nyshadham, Chandramouli; Hart, Gus L. W.; Carrete, Jesús; Legrain, Fleur; Mingo, Natalio; Zurek, Eva; Isayev, Olexandr; Tropsha, Alexander; Sanvito, Stefano; Hanson, Robert M.; Takeuchi, Ichiro; Mehl, Michael J.; Kolmogorov, Aleksey N.; Yang, Kesong; D'Amico, Pino; Calzolari, Arrigo; Costa, Marcio; Gennaro, Riccardo De; Nardelli, Marco Buongiorno; Fornari, Marco; Levy, Ohad; Curtarolo, Stefano

doi:10.1007/978-3-319-42913-7_63-1

Cited by 15 publications

(13 citation statements)

References 66 publications

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“…All the ab-initio data are freely available to the public as part of the AFLOW online repository and can be accessed through AFLOW.org following the REST-API interface [45] and AFLUX search language [10].…”

Section: Discussionmentioning

confidence: 99%

Coordination corrected ab initio formation enthalpies

et al. 2019

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The correct calculation of formation enthalpy is one of the enablers of ab-initio computational materials design. For several classes of systems (e.g. oxides) standard density functional theory produces incorrect values. Here we propose the "Coordination Corrected Enthalpies" method (CCE), based on the number of nearest neighbor cation-anion bonds, and also capable of correcting relative stability of polymorphs. CCE uses calculations employing the Perdew, Burke and Ernzerhof (PBE), Local Density Approximation (LDA) and Strongly Constrained and Appropriately Normed (SCAN) exchange correlation functionals, in conjunction with a quasiharmonic Debye model to treat zero-point vibrational and thermal effects. The benchmark, performed on binary and ternary oxides (halides), shows very accurate room temperature results for all functionals, with the smallest mean absolute error of 27 (24) meV/atom obtained with SCAN. The zero-point vibrational and thermal contributions to the formation enthalpies are small and with different signs -largely cancelling each other.

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Section: Discussionmentioning

confidence: 99%

Coordination corrected ab initio formation enthalpies

et al. 2019

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“…The EFA is calculated using the AFLOW-POCC module 17 implemented in the AFLOW Framework for Materials Discovery 68 . For each disordered composition, a set of representative ordered supercells is resolved.…”

Section: Calculation Of the Entropy-forming Abilitymentioning

confidence: 99%

Discovery of high-entropy ceramics via machine learning

et al. 2020

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Although high-entropy materials are attracting considerable interest due to a combination of useful properties and promising applications, predicting their formation remains a hindrance for rational discovery of new systems. Experimental approaches are based on physical intuition and/or expensive trial and error strategies. Most computational methods rely on the availability of sufficient experimental data and computational power. Machine learning (ML) applied to materials science can accelerate development and reduce costs. In this study, we propose an ML method, leveraging thermodynamic and compositional attributes of a given material for predicting the synthesizability (i.e., entropy-forming ability) of disordered metal carbides. The relative importance of the thermodynamic and compositional features for the predictions are then explored. The approach's suitability is demonstrated by comparing values calculated with density functional theory to ML predictions. Finally, the model is employed to predict the entropy-forming ability of 70 new compositions; several predictions are validated by additional density functional theory calculations and experimental synthesis, corroborating the effectiveness in exploring vast compositional spaces in a highthroughput manner. Importantly, seven compositions are selected specifically, because they contain all three of the Group VI elements (Cr, Mo, and W), which do not form room temperature-stable rock-salt monocarbides. Incorporating the Group VI elements into the rock-salt structure provides further opportunity for tuning the electronic structure and potentially material performance.

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“…To demonstrate dynamic stability, the phonon dispersion curves were computed for both phases using DFT perturbation theory to compute the dynamical matrices with the phonon dispersion curves computed with Phonopy 46 . For the

normalζ

‐Hf 3 N 2 phase, we computed the dispersion curves along the Γ‐Y‐F‐H‐Z‐I‐X‐Γ‐Z path and the G‐Y‐F‐L‐I‐I 1 ‐Z‐G‐X‐X1‐Y‐M‐G‐N‐Z‐F 1 path for

normalη

‐Hf 12 N 7 as determined by AFLOW 47 . These phonon dispersion curves are shown in Figure 4 and exhibit positive frequencies for all simulated paths, demonstrating dynamic stability.…”

Section: Resultsmentioning

confidence: 99%

A computational examination of the zeta and eta phases in the hafnium nitrides

Weinberger

Thompson

2020

J Am Ceram Soc

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The hafnium nitrides are an interesting class of ceramics that have shown promise in a diversity of applications that include high temperature coatings, 1,2 uses in electronics, 3 solar cells, 4 and even hydrogen storage. 5 Despite decades of research and the wide applications of these materials, the stability of the phases that comprise the hafnium-nitrogen (Hf-N) system are still debated. 6-10 For the advancement of these materials in these and other emerging technologies, it is particularly important to concretely establish and understand the equilibrium phase diagram in the Hf-N system. One of the earliest phase equilibrium diagrams for the Hf-N system was described by Toth. 11 As with many ultrahigh temperature ceramics, this system has a rocksalt phase, δ-HfN, which can be found at nitrogen concentrations between 39 and 52 at.%, depending on temperature. In contrast to the transition metal carbides which also form the rocksalt structure, 12,13 δ-HfN is able to retain the rocksalt structure for a modest nonmetal-rich composition. 7,10 Thus, δ-HfN can be regarded as a strongly nonstoichiometric compound. With the depletion of nitrogen, Rudy 14 originally reported two specific subnitride phases, the-Hf 3 N 2−x (originally called the ε-Hf 3 N 2) and ζ-Hf 4 N 3−x phases. The former eta phase was identified to have a 9R metal atom stacking sequence, that is (hhc) 3 or ABABCBCAC. The latter zeta phase has a similar metal atom stacking sequence given as (hhcc) 3 or ABABCACABCBC, which is equivalent to the structure identified by Yvon and Parthe as the ζ-V 4 C 3−x phase. 15,16 The compositions of the eta and zeta phases were only identified for single samples at chemistries of HfN 0.56 and HfN 0.65 , respectively. However, Rudy was not able to identify either a composition range for the phases (and thus they were assumed to be line compounds) nor establish if or how much the nitrogen atoms were ordered in either structure. Rudy further identified the upper decomposition temperatures for these respective phases to be approximately 2000°C (eta) and 2300°C (zeta).

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The AFLOW Fleet for Materials Discovery

Cited by 15 publications

References 66 publications

Coordination corrected ab initio formation enthalpies

Coordination corrected ab initio formation enthalpies

Discovery of high-entropy ceramics via machine learning

A computational examination of the zeta and eta phases in the hafnium nitrides

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