This
Feature Article discusses how cluster models can be effectively
used for quantum chemistry simulations of metal-doped amorphous silicates.
These materials have been successfully used as heterogeneous catalysts
for a variety of reactions, including olefin metathesis and polymerization,
and alcohol dehydration. The amorphous surface provides a large surface
area and distorted metal sites that are very reactive. However, the
disordered microscopic nature of these silicates makes them hard to
characterize, and progress toward better catalysts relies on a trial-and-error
approach. Simulations can in principle provide insights on structure–property
relations that may lead to a rational design approach, but again the
disordered structure of the active sites makes the formulation of
reliable models difficult. Using cluster models, it is possible to
create multiple replicas of the same site with different distorted
structures and silica environments, such that one can obtain a more
realistic picture of the behavior of the material. Simulations based
on the METal-doped Amorphous SIlicate Library (METASIL), which includes
70 cluster structures for single-site Zr-, Nb-, and W-doped silica,
show very good agreement with a variety of experimental characterization
techniques. These calculations validate the models and, more importantly,
they allow to identify important structural descriptors of the active
sites as well as a number of potential issues in the interpretation
of experimental data. The Feature Article also discusses what challenges
are still open in the simulation of amorphous materials and how these
may be addressed in combination with new approaches such as machine
learning algorithms.