Nonoxidative dehydrogenation
of light alkanes has seen a renewed
interest in recent years. While PtGa systems appear among the most
efficient catalyst for this reaction and are now implemented in production
plants, the origin of the high catalytic performance in terms of activity,
selectivity, and stability in PtGa-based catalysts is largely unknown.
Here we use molecular modeling at the DFT level on three different
models: (i) periodic surfaces, (ii) clusters using static calculations,
and (iii) realistic size silica-supported nanoparticles (1 nm) using
molecular dynamics and metadynamics. The combination of the models
with experimental data (XAS, TEM) allowed the refinement of the structure
of silica-supported PtGa nanoparticles synthesized via surface organometallic
chemistry and provided a structure–activity relationship at
the molecular level. Using this approach, the key interaction between
Pt and Ga was evidenced and analyzed: the presence of Ga increases
(i) the interaction between the oxide surface and the nanoparticles,
which reduces sintering, (ii) the Pt site isolation, and (iii) the
mobility of surface atoms which promotes the high activity, selectivity,
and stability of this catalyst. Considering the complete system for
modeling that includes the silica support as well as the dynamics
of the PtGa nanoparticle is essential to understand the catalytic
performances.