The
sensitivity of NMR to the local environment, without the need for
any long-range order, makes it an ideal tool for the characterization
of disordered materials. Computational prediction of NMR parameters
can be of considerable help in the interpretation and assignment of
NMR spectra of solids, but the statistical representation of all possible
chemical environments for a solid solution is challenging. Here, we
illustrate the use of a symmetry-adapted configurational ensemble
in the simulation of NMR spectra, in combination with solid-state
NMR experiments. We show that for interpretation of the complex and
overlapped lineshapes that are typically observed, it is important
to go beyond a single-configuration representation or a simple enumeration
of local environments. The ensemble method leads to excellent agreement
between simulated and experimental spectra for Y2(Sn,Ti)2O7 pyrochlore ceramics, where the overlap of signals
from different local environments prevents a simple decomposition
of the experimental spectral lineshapes. The inclusion of a Boltzmann
weighting confirms that the best agreement with experiment is obtained
at higher temperatures, in the limit of full disorder. We also show
that to improve agreement with experiment, in particular at low dopant
concentrations, larger supercells are needed, which might require
alternative simulation approaches as the complexity of the system
increases. It is clear that ensemble-based modeling approaches in
conjunction with NMR spectroscopy offer great potential for understanding
configurational disorder, ultimately aiding the future design of functional
materials.