Structure Discovery in Atomic Force Microscopy Imaging of Ice

The interaction of
water with surfaces is crucially important in
a wide range of natural and technological settings. In particular,
at low temperatures, unveiling the atomistic structure of adsorbed
water clusters would provide valuable data for understanding the ice
nucleation process. Using high-resolution atomic force microscopy
(AFM) and scanning tunneling microscopy, several studies have demonstrated
the presence of water pentamers, hexamers, and heptamers (and of their
combinations) on a variety of metallic surfaces, as well as the initial
stages of 2D ice growth on an insulating surface. However, in all
of these cases, the observed structures were completely flat, providing
a relatively straightforward path to interpretation. Here, we present
high-resolution AFM measurements of several water clusters on Au(111)
and Cu(111), whose understanding presents significant challenges due
to both their highly 3D configuration and their large size. For each
of them, we use a combination of machine learning, atomistic modeling
with neural network potentials, and statistical sampling to propose
an underlying atomic structure, finally comparing its AFM simulated
images to the experimental ones. These results provide insights into
the early phases of ice formation, which is a ubiquitous phenomenon
ranging from biology to astrophysics.