Abstract
The properties of a material depend on how its atoms are arranged, and predicting these arrangements from first principles is a longstanding challenge. Orbital-free density functional theory provides a quantum-mechanical model based solely on the electron density, not individual wave functions. The resulting speedups make it attractive for random structure searching, whereby random configurations of atoms are relaxed to local minima in the energy landscape. We use this strategy to map the low-energy crystal structures of Li, Na, Mg, and Al at zero pressure. For Li and Na, our searching finds numerous close-packed polytypes of almost-equal energy, consistent with previous efforts to understand their low-temperature forms. For Mg and Al, the searching identifies the expected ground state structures unambiguously, in addition to revealing other low-energy structures. This new role for orbital-free density functional theory—particularly as continued advances make it accurate for more of the periodic table—will expedite crystal structure prediction over wide ranges of compositions and pressures.
Highlights
Materials physicists have long sought efficient methods for predicting the structures of atoms in materials
In the Supporting Information, we provide some analogous results obtained with the local density approximation (LDA)[40] and PBEsol[41] functionals
We applied the dimensionality reduction method Stochastic Hyperspace Embedding And Projection (SHEAP) to produce two-dimensional visualizations of the structural data.[53]. In these SHEAP maps, individual structures are represented by circles colored according to structure energy, with areas proportional to number of occurrences in the search
Summary
Materials physicists have long sought efficient methods for predicting the structures of atoms in materials. One fruitful strategy combines density functional theory (DFT)[4−7] and random structure searching.[1,8] The former provides reliable estimates of the energy (or enthalpy) of an arrangement of atoms, while the latter explores possible configurations. The procedure begins with randomly generated structures, perhaps having preselected symmetries or constrained by simple heuristics, which are relaxed to local minima (or stationary points) in the energy landscape. This approach, while pragmatic and effective, is limited by the computational expense of conventional Kohn−Sham density functional theory (KSDFT).[5] For example, metals requiring dense Brillouin zone sampling pose a challenge because poor sampling leads to overly rugged landscapes. Faster DFT calculations would facilitate study of numerous materials of practical interest, such as complex phases of intermetallic alloys
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