  Tens of Zr inter-atomic potentials (force fields) have been developed to
enable atomic-scale simulations of Zr alloys. These can provide critical
insight in the in-reactor behaviour of nuclear fuel cladding and structural
components exposed, but the results are strongly sensitive to the choice of
potential. We provide a comprehensive comparison of 13 popular Zr potentials,
and assess their ability to reproduce key physical, mechanical, structural and
thermodynamic properties of Zr. We assess the lattice parameters, thermal
expansion, melting point, volume-energy response, allotropic phase stability,
elastic properties, and point defect energies, and compare them to experimental
and ab-initio values. No potential was found to outperform all others on all
aspects, but for every metric considered here, at least one potential was found
to provide reliable results. Older embedded-atom method (EAM) potentials tend
to excel in 2-3 metrics each, but at the cost of poorer transferability. The
two highest-performing potentials overall, with complementary strengths and
weaknesses, were the 2021 angular-dependent potential of Smirnova and Starikov
(Comp. Mater. Sci. 197, 110581) and the 2019 embedded-atom method potential of
Wimmer et al (J. Nucl. Mater. 532, 152055). All potentials trained through
machine learning algorithms proved to have lower overall accuracy, and less
transferability, than simpler and computationally faster potentials available.
Point defect structures and energies is where the greatest divergence and least
accuracy is observed. We created maps that will help modellers select the most
suitable potential for a specific application, and which may help identify
areas of improvement in future potentials.
