The presence of a second critical point in water has been a topic of intense investigation for the last few decades. The molecular origins underlying this phenomenon are typically rationalized in terms of the competition between local high-density (HD) and low-density (LD) structures. Their identification often requires designing parameters that are subject to human intervention. Herein, we use unsupervised learning to discover structures in atomistic simulations of water close to the liquid-liquid critical point (LLCP). Encoding the information on the environment using local descriptors, we do not find evidence for two distinct thermodynamic structures. In contrast, when we deploy nonlocal descriptors that probe instead heterogeneities on the nanometer length scale, this leads to the emergence of LD and HD domains rationalizing the microscopic origins of the density fluctuations close to criticality.

Beyond Local Structures in Critical Supercooled Water through Unsupervised Learning / Donkor, Edward Danquah; Offei-Danso, Adu; Rodriguez, Alex; Sciortino, Francesco; Hassanali, Ali. - In: THE JOURNAL OF PHYSICAL CHEMISTRY LETTERS. - ISSN 1948-7185. - 15:15(2024), pp. 3996-4005. [10.1021/acs.jpclett.4c00383]

Beyond Local Structures in Critical Supercooled Water through Unsupervised Learning

Sciortino, Francesco;
2024

Abstract

The presence of a second critical point in water has been a topic of intense investigation for the last few decades. The molecular origins underlying this phenomenon are typically rationalized in terms of the competition between local high-density (HD) and low-density (LD) structures. Their identification often requires designing parameters that are subject to human intervention. Herein, we use unsupervised learning to discover structures in atomistic simulations of water close to the liquid-liquid critical point (LLCP). Encoding the information on the environment using local descriptors, we do not find evidence for two distinct thermodynamic structures. In contrast, when we deploy nonlocal descriptors that probe instead heterogeneities on the nanometer length scale, this leads to the emergence of LD and HD domains rationalizing the microscopic origins of the density fluctuations close to criticality.
2024
liquid-liquid transition, rsupercooled water, structural indicators
01 Pubblicazione su rivista::01a Articolo in rivista
Beyond Local Structures in Critical Supercooled Water through Unsupervised Learning / Donkor, Edward Danquah; Offei-Danso, Adu; Rodriguez, Alex; Sciortino, Francesco; Hassanali, Ali. - In: THE JOURNAL OF PHYSICAL CHEMISTRY LETTERS. - ISSN 1948-7185. - 15:15(2024), pp. 3996-4005. [10.1021/acs.jpclett.4c00383]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1722814
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