Before revision: Such machine learning potentials (MLPs) promised to thread the gap between density functional theory, a highly-accurate but computationally-intensive simulation program, and empirically-derived or intuitively-approximated potentials, which were far computationally lighter but substantially less accurate.
After revision: Such machine learning potentials promised to fill the gap between density functional theory, a highly-accurate but computationally-intensive simulation program, and empirically-derived or intuitively-approximated potentials, which were far computationally lighter but substantially less accurate.