Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Reliable and Practical Computational Prediction of Molecular Crystal
  Polymorphs   The ability to reliably predict the structures and stabilities of a molecular
crystal and its polymorphs without any prior experimental information would be
an invaluable tool for a number of fields, with specific and immediate
applications in the design and formulation of pharmaceuticals. In this case,
detailed knowledge of the polymorphic energy landscape for an active
pharmaceutical ingredient yields profound insight regarding the existence and
likelihood of late-appearing polymorphs. However, the computational prediction
of the structures and stabilities of molecular crystal polymorphs is
particularly challenging due to the high dimensionality of conformational and
crystallographic space accompanied by the need for relative (free) energies to
within $\approx$ 1 kJ/mol per molecule. In this work, we combine the most
successful crystal structure sampling strategy with the most accurate energy
ranking strategy of the latest blind test of organic crystal structure
prediction (CSP), organized by the Cambridge Crystallographic Data Centre
(CCDC). Our final energy ranking is based on first-principles density
functional theory (DFT) calculations that include three key physical
contributions: (i) a sophisticated treatment of Pauli exchange-repulsion and
electron correlation effects with hybrid functionals, (ii) inclusion of
many-body van der Waals dispersion interactions, and (iii) account of
vibrational free energies. In doing so, this combined approach has an optimal
success rate in producing the crystal structures corresponding to the five
blind-test molecules. With this practical approach, we demonstrate the
feasibility of obtaining reliable structures and stabilities for molecular
crystals of pharmaceutical importance, paving the way towards an enhanced
fundamental understanding of polymorphic energy landscapes and routine
industrial application of molecular CSP methods.

22
The categories of this paper are: chao-dyn
12
The categories of this paper are: nucl-th
6
The categories of this paper are: astro-ph
26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
21
The categories of this paper are: adap-org
19
The categories of this paper are: eess
16
The categories of this paper are: stat
11
The categories of this paper are: hep-lat
37
The categories of this paper are: supr-con
27
The categories of this paper are: comp-gas
1
The categories of this paper are: cs
5
The categories of this paper are: gr-qc
33
The categories of this paper are: plasm-ph
28
The categories of this paper are: alg-geom
20
The categories of this paper are: acc-phys