Nonadiabatic effects
that arise from the concerted motion of electrons
and atoms at comparable energy and time scales are omnipresent in
thermal and light-driven chemistry at metal surfaces. Excited (hot)
electrons can measurably affect moleculeâmetal reactions by
contributing to state-dependent reaction probabilities. Vibrational
state-to-state scattering of NO on Au(111) has been one of the most
studied examples in this regard, providing a testing ground for developing
various nonadiabatic theories. This system is often cited as the prime
example for the failure of electronic friction theory, a very efficient
model accounting for dissipative forces on metal-adsorbed molecules
due to the creation of hot electrons in the metal. However, the exact
failings compared to experiment and their origin from theory are not
established for any system because dynamic properties are affected
by many compounding simulation errors of which the quality of nonadiabatic
treatment is just one. We use a high-dimensional machine learning
representation of electronic structure theory to minimize errors that
arise from quantum chemistry. This allows us to perform a comprehensive
quantitative analysis of the performance of nonadiabatic molecular
dynamics in describing vibrational state-to-state scattering of NO
on Au(111) and compare directly to adiabatic results. We find that
electronic friction theory accurately predicts elastic and single-quantum
energy loss but underestimates multiquantum energy loss and overestimates
molecular trapping at high vibrational excitation. Our analysis reveals
that multiquantum energy loss can potentially be remedied within friction
theory whereas the overestimation of trapping constitutes a genuine
breakdown of electronic friction theory. Addressing this overestimation
for dynamic processes in catalysis and surface chemistry will likely
require more sophisticated theories