Tight-Binding Approximation-Enhanced Global Optimization

Solving
and predicting atomic structures from first-principles
methodologies is limited by the computational cost of exploring the
search space, even when relatively inexpensive density functionals
are used. Here, we present an efficient approach where the search
is performed using density functional tight-binding, with an automatic
adaptive parametrization scheme for the repulsive pair potentials.
We successfully apply the method to the genetic algorithm optimization
of bulk carbon, titanium dioxide, palladium oxide, and calcium hydroxide,
and we assess the stability of the unknown crystal structure of palladium
hydroxide.