High-throughput prediction of finite-temperature properties using the quasi-harmonic approximation

Nath, Pinku; Plata, José J.; Usanmaz, Demet; Orabi, Rabih Al Rahal Al; Fornari, Marco; Nardelli, Marco Buongiorno; Toher, Cormac; Curtarolo, Stefano

doi:10.1016/j.commatsci.2016.07.043

Cited by 57 publications

(64 citation statements)

References 59 publications

(61 reference statements)

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“…Ab initio computational approaches for determining ΔGf(T), which involve calculating the vibrational contribution to G(T) as a function of volume, 13 have benefited from recent advances that reduce their computational cost. 14,15 However, despite these advances, calculating the vibrational entropy of phonons quantum mechanically is still computationally demanding, with computed G(T) available for fewer than 200 compounds in the Phonon database at Kyoto University (PhononDB). 16 Highly populated and widely used materials databases currently tabulate 0 or 298 K enthalpies of formation, ΔHf, which neglect the effects of temperature and entropy on stability.…”

Section: Introductionmentioning

confidence: 99%

Physical descriptor for the Gibbs energy of inorganic crystalline solids and temperature-dependent materials chemistry

et al. 2018

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The Gibbs energy, G, determines the equilibrium conditions of chemical reactions and materials stability. Despite this fundamental and ubiquitous role, G has been tabulated for only a small fraction of known inorganic compounds, impeding a comprehensive perspective on the effects of temperature and composition on materials stability and synthesizability. Here, we use the SISSO (sure independence screening and sparsifying operator) approach to identify a simple and accurate descriptor to predict G for stoichiometric inorganic compounds with ~50 meV atom−1 (~1 kcal mol−1) resolution, and with minimal computational cost, for temperatures ranging from 300–1800 K. We then apply this descriptor to ~30,000 known materials curated from the Inorganic Crystal Structure Database (ICSD). Using the resulting predicted thermochemical data, we generate thousands of temperature-dependent phase diagrams to provide insights into the effects of temperature and composition on materials synthesizability and stability and to establish the temperature-dependent scale of metastability for inorganic compounds.

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Section: Introductionmentioning

confidence: 99%

Physical descriptor for the Gibbs energy of inorganic crystalline solids and temperature-dependent materials chemistry

et al. 2018

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“…7,86 Qualitatively, all the three frameworks have high linear correlation with experiments (Pearson, r); AAPL and QHA-APL are also very effective in rank ordering the compounds (Spearman, ρ).…”

Section: Validation With Experimentsmentioning

confidence: 99%

“…86 The magnitude of the displacement is 0.015 Å. Electronic self-consistent field iterations for static calculations are stopped when the difference of energy between the last two steps is less than 10 −5 meV.…”

Section: Phonon Calculationsmentioning

confidence: 99%

An efficient and accurate framework for calculating lattice thermal conductivity of solids: AFLOW—AAPL Automatic Anharmonic Phonon Library

et al. 2017

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One of the most accurate approaches for calculating lattice thermal conductivity, κ ' , is solving the Boltzmann transport equation starting from third-order anharmonic force constants. In addition to the underlying approximations of ab-initio parameterization, two main challenges are associated with this path: high computational costs and lack of automation in the frameworks using this methodology, which affect the discovery rate of novel materials with ad-hoc properties. Here, the Automatic Anharmonic Phonon Library (AAPL) is presented. It efficiently computes interatomic force constants by making effective use of crystal symmetry analysis, it solves the Boltzmann transport equation to obtain κ ' , and allows a fully integrated operation with minimum user intervention, a rational addition to the current high-throughput accelerated materials development framework AFLOW. An "experiment vs. theory" study of the approach is shown, comparing accuracy and speed with respect to other available packages, and for materials characterized by strong electron localization and correlation. Combining AAPL with the pseudo-hybrid functional ACBN0 is possible to improve accuracy without increasing computational requirements.

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“…A high throughput combinatorial method for fast and robust prediction of lattice thermal conductivity is presented. Using the QHA-APL implementation [35], we can compute different definitions for the Debye temperature and the Grüneisen parameter. These values can be used in a combinatorial approach with the Slack equation to obtain different values of κ l (θ a , γ).…”

Section: Discussionmentioning

confidence: 99%

“…Phonon calculations were carried out using the automatic phonon library, APL, as implemented in the AFLOW package, using VASP to obtain the IFCs via the finite-displacement approach [35]. The magnitude of this displacement is 0.015 Å.…”

Section: Phonon Calculationsmentioning

confidence: 99%

High throughput combinatorial method for fast and robust prediction of lattice thermal conductivity

et al. 2017

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The lack of computationally inexpensive and accurate ab-initio based methodologies to predict lattice thermal conductivity, without computing the anharmonic force constants or time-consuming ab-initio molecular dynamics, is one of the obstacles preventing the accelerated discovery of new high or low thermal conductivity materials. The Slack equation is the best alternative to other more expensive methodologies but is highly dependent on two variables: the acoustic Debye temperature, θ a , and the Grüneisen parameter, γ. Furthermore, different definitions can be used for these two quantities depending on the model or approximation. In this article, we present a combinatorial approach to elucidate which definitions of both variables produce the best predictions of the lattice thermal conductivity, κ l . A set of 42 compounds was used to test accuracy and robustness of all possible combinations. This approach is ideal for obtaining more accurate values than fast screening models based on the Debye model, while being significantly less expensive than methodologies that solve the Boltzmann transport equation.

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High-throughput prediction of finite-temperature properties using the quasi-harmonic approximation

Cited by 57 publications

References 59 publications

Physical descriptor for the Gibbs energy of inorganic crystalline solids and temperature-dependent materials chemistry

Physical descriptor for the Gibbs energy of inorganic crystalline solids and temperature-dependent materials chemistry

An efficient and accurate framework for calculating lattice thermal conductivity of solids: AFLOW—AAPL Automatic Anharmonic Phonon Library

High throughput combinatorial method for fast and robust prediction of lattice thermal conductivity

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