  Finding the possible stopping sites for muons inside a crystalline sample is
a key problem of muon spectroscopy. In a previous work, we suggested a
computational approach to this problem, using Density Functional Theory
software in combination with a random structure searching approach using a
Poisson sphere distribution. In this work we test this methodology further by
applying it to three organic molecular crystals model systems: durene,
bithiophene, and tetracyanoquinodimethane (TCNQ). Using the same sets of random
structures we compare the performance of Density Functional Theory software
CASTEP and the much faster lower level approximation of Density Functional
Tight Binding provided by DFTB+, combined with the use of the 3ob-3-1 parameter
set. We show the benefits and limitations of such an approach and we propose
the use of DFTB+ as a viable alternative to more cumbersome simulations for
routine site-finding in organic materials. Finally, we introduce the Muon
Spectroscopy Computational Project software suite, a library of Python tools
meant to make these methods standardized and easy to use.
