Free energy predictions for crystal stability and synthesisability

Abstract

What is the likelihood that a hypothetical material - the combination of a composition and crystal structure - can be formed? Underpinning the reliability of predictions for local or global...

Reply to Comment on “Environmental Stability of Crystals: A Greedy Screening”

“…Remaining challenges for decomposition prediction include a strategy for when the relevant data concerning a decomposition product is not available in the database, and thus cannot be looked up (e.g., an underexplored region of composition or a highly competitive noncrystalline phase), as well a more complete description of the atomic chemical potentials at finite temperatures and pressures. 3 These require further developments, including effective search and optimization strategies where an exact solution is no longer possible. In conclusion, the linear optimization approach for the identification of oxidation products described by Ai and Schrier shows that there are viable alternatives to being greedy when seeking solutions to materials stability and design problems.…”

“…Ai and Schrier did well to leverage experience in other fields, including mathematics, allowing more efficient algorithms that can be transferred and adapted to materials chemistry needs. Other approaches to the heuristic greedy search, including direct methods proposed by the authors or a bloom filter-based search, may be more appropriate as materials databases expand in number of entries and approach those of proteomics. Remaining challenges for decomposition prediction include a strategy for when the relevant data concerning a decomposition product is not available in the database, and thus cannot be looked up (e.g., an underexplored region of composition or a highly competitive noncrystalline phase), as well a more complete description of the atomic chemical potentials at finite temperatures and pressures . These require further developments, including effective search and optimization strategies where an exact solution is no longer possible. …”

Exploring the High-Temperature Stabilization of Cubic Zirconia from Anharmonic Lattice Dynamics

“…19,20 This has paved the way for modeling of finite temperature phonon dispersions, lattice thermal conductivities, as well as free energy calculations beyond the harmonic approximation. 13,16,21 II. COMPUTATIONAL METHODS II.A.…”

“…Ultimately, the stability of a given phase is determined from its free energy, Δ G , in relation to its competing phases. , Stability in the solid state is often determined from the internal energy or enthalpy based on density functional theory (DFT) calculations, but when comparing phase stability at different temperatures, entropic contributions must be taken into account. normalΔ G = normalΔ H true︸ enthalpy − T false( normalΔ S vib + normalΔ S other false) true︸ entropy The main source of entropy in an crystalline solid is usually of vibrational origin, which can to a first approximation be determined using the (quasi-)harmonic approximation to describe the vibrational degrees of freedom. However, when dynamic instabilities are present in the phonon dispersion, which is often the case for high temperature phases, the harmonic approximation breaks down and the vibrational entropy becomes ill-defined .…”

“…11 Ultimately, the stability of a given phase is determined from its free energy, ΔG, in relation to its competing phases. 12,13 Stability in the solid state is often determined from the internal energy or enthalpy based on density functional theory (DFT) calculations, but when comparing phase stability at different temperatures, entropic contributions must be taken into account.…”