Adhesion energy,
a measure of the strength by which two surfaces
bind together, ultimately dictates the mechanical behavior and failure
of interfaces. As natural and artificial solid interfaces are ubiquitous,
adhesion energy represents a key quantity in a variety of fields ranging
from geology to nanotechnology. Because of intrinsic difficulties
in the simulation of systems where two different lattices are matched,
and despite their importance, no systematic, accurate first-principles
determination of heterostructure adhesion energy is available. We
have developed robust, automatic high-throughput workflow able to
fill this gap by systematically searching for the optimal interface
geometry and accurately determining adhesion energies. We apply it
here for the first time to perform the screening of around a hundred
metallic heterostructures relevant for technological applications.
This allows us to populate a database of accurate values, which can
be used as input parameters for macroscopic models. Moreover, it allows
us to benchmark commonly used, empirical relations that link adhesion
energies to the surface energies of its constituent and to improve
their predictivity employing only quantities that are easily measurable
or computable.