| Description |
Pablo Piaggi (Princeton University)
Abstract:
The vast and complex phase diagram of water, with at least 18 different ice polymorphs, is a rich playground for the study of crystallization. Moreover, the equilibrium picture provided by the phase diagram is enriched further by the possible existence of a metastable liquid-liquid critical point at deeply supercooled conditions. Over the years, considerable attention has been devoted to the study of water and ices, and a vast literature has amassed on studies of this system using molecular simulations based on empirical potentials. In spite of the many merits of empirical models, they are often not able to describe important physical effects, such as polarization and chemical reactions. A possible strategy to overcome these limitations is the use of quantum-mechanical ab initio simulations to derive the potential energy surface and use the associated forces to drive the dynamics of the nuclei. For many years, this strategy was severely hampered by the sheer computational cost of direct ab initio simulations. Recently, the use of machine learning algorithms to learn the potential energy surface has mitigated the cost of these calculations, paving the way to more realistic studies of many systems. In this talk, I will discuss recent developments on the use of first principles simulations and rare-event techniques to study the crystallization of ice polymorphs. I will first present results on the calculation of homogeneous ice nucleation rates from first principles [1]. Then, I will describe the development of a machine learning potential for the study of heterogeneous ice nucleation at feldspar minerals, one of the most potent ice nucleating particles in the atmosphere [2]. Afterwards, I will present evidence of the existence of a liquid-liquid transition in ab initio water [3], and I will discuss the exotic behavior of the melting lines of several ice polymorphs in the vicinity of the liquid-liquid critical point [4]. I will conclude the talk with some thoughts about how these techniques are revolutionizing our ability to understand and predict the crystallization of materials.
[1] Piaggi, Weis, Panagiotopoulos, Debenedetti, and Car, Proc. Natl. Acad. Sci. 119, 33 (2022) [2] Piaggi, Selloni, Panagiotopoulos, Car, and Debenedetti, arXiv:2305.10255 (2023) [3] Gartner, Piaggi, Car, Panagiotopoulos, and Debenedetti, Phys. Rev. Lett. 129, 25 (2022) [4] Piaggi, Gartner, Car, and Debenedetti, arXiv:2302.08540 (2023) |
CMSP-SISSA Atomistic Seminar: Understanding the crystallization of ice polymorphs from first principles
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