Water Is Cool: Advanced Phonon Dynamics in Ice Ih and Ice XI via Machine Learning Potentials and Quantum Nuclear Vibrations

Low-dimensional water, despite the relative simplicity of its constituents, exhibits a vast range of phenomena that are of central importance in natural sciences. A large number of bulk as well as nanoscale polymorphs offer engineering possibilities for technological applications such as desalinization, drug delivery, or biological interfacing. However, little is known about the stability of such structures. Therefore, in this study, we employ an array of state-of-the-art computational techniques to study the vibrational properties of ice Ih and XI in their bulk and thin film forms in order to elucidate their structural stability and dynamic behavior. An efficient workflow, consisting of quantum mechanical simulations (based on density functional theory) and machine learning interatomic potentials (MTPs) coupled to temperature-dependent effective potentials (TDEP) and classical molecular dynamics, was verified necessary to capture the temperature-dependent stabilization of the phonons in bulk ice Ih and XI. Anharmonicity and nuclear quantum effects, incorporated in an efficient way through a quantum thermal bath technique, were found crucial to dynamically stabilize low-frequency lattice modes and high-frequency vibrational stretching involving hydrogen. We have identified three novel thin film structures that retain their stability up to at least 250 K and have shed light on their phonon characteristics. In addition, our examination of the Raman spectrum of ice underscores the shortcomings of predicting vibrational properties when relying entirely on the harmonic approximation or purely anharmonic effects. The corrected redistribution of vibrational intensities is found to be achieved only upon inclusion of quantum nuclear vibrations. This was found to be even more crucial for low-dimensional thin film (2D) structures. Overall, our findings demonstrate the significance of joining advanced computational methodologies in unraveling the intricate vibrational dynamics of crystalline ice materials, offering valuable insights into their thermodynamic and structural properties. Furthermore, we suggest a procedure based on MTPs coupled to a quantum thermal bath for the computationally efficient probing of nuclear effects in ice structures, although equally applicable to any other system.