Crystal Structure Prediction of Molecular Crystals from First Principles: Are we there yet?

TL;DR

This paper demonstrates that combining advanced structure search algorithms with improved van der Waals interaction modeling in DFT enables accurate prediction of glycine's known and unknown crystal phases, marking progress in molecular crystal structure prediction.

Contribution

It shows that recent algorithmic and theoretical advances can resolve all known glycine phases and identify a previously unresolved phase without empirical input.

Findings

Successfully predicted all known glycine phases

Resolved the structure of the previously unknown ζ phase

Identified remaining challenges in predicting the α phase

Abstract

Accurate molecular crystal structure prediction is a fundamental goal in academic and industrial condensed matter research and polymorphism is arguably the biggest obstacle on the way. We tackle this challenge in the difficult case of the repeatedly studied, abundantly used aminoacid Glycine that hosts still little-known phase transitions and we illustrate the current state of the field through this example. We demonstrate that the combination of recent progress in structure search algorithms with the latest advances in the description of van der Waals interactions in Density Functional Theory, supported by data-mining analysis, enables a leap in predictive power: we resolve, without prior empirical input, all known phases of glycine, as well as the structure of the previously unresolved $\zeta$ phase after a decade of its experimental observation [Boldyreva et al. \textit{Z. Kristallogr.} \textbf{2005,} \textit{220,} 50-57]. The search for the well-established $\alpha$ phase instead reveals the remaining challenges in exploring a polymorphic landscape.