Imaging surface structure and premelting of ice Ih with atomic resolution.

Ice surfaces are closely relevant to many physical and chemical properties, such as melting, freezing, friction, gas uptake and atmospheric reaction1-8. Despite extensive experimental and theoretical investigations9-17, the exact atomic structures of ice interfaces remain elusive owing to the vulnerable hydrogen-bonding network and the complicated premelting process. Here we realize atomic-resolution imaging of the basal (0001) surface structure of hexagonal water ice (ice Ih) by using qPlus-based cryogenic atomic force microscopy with a carbon monoxide-functionalized tip. We find that the crystalline ice-Ih surface consists of mixed Ih- and cubic (Ic)-stacking nanodomains, forming 19 × 19 periodic superstructures. Density functional theory reveals that this reconstructed surface is stabilized over the ideal ice surface mainly by minimizing the electrostatic repulsion between dangling OH bonds. Moreover, we observe that the ice surface gradually becomes disordered with increasing temperature (above 120 Kelvin), indicating the onset of the premelting process. The surface premelting occurs from the defective boundaries between the Ih and Ic domains and can be promoted by the formation of a planar local structure. These results put an end to the longstanding debate on ice surface structures and shed light on the molecular origin of ice premelting, which may lead to a paradigm shift in the understanding of ice physics and chemistry.

Harvesting Energy from Changes in Relative Humidity Using Nanoscale Water Capillary Bridges.

We show that nanoscale water capillary bridges (WCB) formed between patchy surfaces can extract energy from the environment when subjected to changes in relative humidity (RH). Our results are based on molecular dynamics simulations combined with a modified version of the Laplace-Kelvin equation, which is validated using the nanoscale WCB. The calculated energy density harvested by the nanoscale WCB is relevant, ≈1700 kJ/m3, and is comparable to the energy densities harvested using available water-responsive materials that expand and contract due to changes in RH.

Machine learning-aided atomic structure identification of interfacial ionic hydrates from AFM images.

Relevant to broad applied fields and natural processes, interfacial ionic hydrates have been widely studied by using ultrahigh-resolution atomic force microscopy (AFM). However, the complex relationship between the AFM signal and the investigated system makes it difficult to determine the atomic structure of such a complex system from AFM images alone. Using machine learning, we achieved precise identification of the atomic structures of interfacial water/ionic hydrates based on AFM images, including the position of each atom and the orientations of water molecules. Furthermore, it was found that structure prediction of ionic hydrates can be achieved cost-effectively by transfer learning using neural network trained with easily available interfacial water data. Thus, this work provides an efficient and economical methodology that not only opens up avenues to determine atomic structures of more complex systems from AFM images, but may also help to interpret other scientific studies involving sophisticated experimental results.

Advances in Atomic Force Microscopy: Imaging of Two- and Three-Dimensional Interfacial Water.

Interfacial water is closely related to many core scientific and technological issues, covering a broad range of fields, such as material science, geochemistry, electrochemistry and biology. The understanding of the structure and dynamics of interfacial water is the basis of dealing with a series of issues in science and technology. In recent years, atomic force microscopy (AFM) with ultrahigh resolution has become a very powerful option for the understanding of the complex structural and dynamic properties of interfacial water on solid surfaces. In this perspective, we provide an overview of the application of AFM in the study of two dimensional (2D) or three dimensional (3D) interfacial water, and present the prospect and challenges of the AFM-related techniques in experiments and simulations, in order to gain a better understanding of the physicochemical properties of interfacial water.

Energy Stored in Nanoscale Water Capillary Bridges between Patchy Surfaces.

We perform molecular dynamics (MD) simulations of a water capillary bridge (WCB) expanding between two identical chemically heterogeneous surfaces. The model surfaces, based on the structure of silica, are hydrophobic and are decorated by a hydrophilic (hydroxylated silica) patch that is in contact with the WCB. Our MD simulations results, including the WCB profile and forces induced on the walls, are in agreement with capillarity theory even at the smallest wall separations studied, h = 2.5-3 nm. Remarkably, the energy stored in the WCB can be relatively large, with an energy density that is comparable to that harvested by water-responsive materials used in actuators and nanogenerators.