Realistic phase diagram of water from "first principles" data-driven quantum simulations

Area of Science:

• Computational physics and chemistry
• Materials science
• Thermodynamics

Background:

• The thermodynamic stability of ice polymorphs has been studied since the early 1900s.
• Understanding molecular-level interactions is crucial for predicting phase behavior.
• Previous simulations lacked the realism to fully capture water's complex phase diagram.

Purpose of the Study:

• To develop a highly realistic computational model for water's phase diagram.
• To investigate the roles of enthalpic, entropic, and nuclear quantum effects on water's free-energy landscape.
• To demonstrate the capability of "first principles" data-driven simulations for complex molecular systems.

Main Methods:

• Utilized the MB-pol data-driven many-body potential for water, derived from "first principles".
• Employed advanced enhanced-sampling algorithms to accurately simulate quantum molecular motion and thermodynamic equilibria.
• Integrated these methods to achieve unprecedented realism in phase diagram simulations.

Main Results:

• Successfully simulated water's phase diagram with exceptional realism.
• Provided fundamental insights into how enthalpic, entropic, and nuclear quantum effects govern the free-energy landscape.
• Validated the power of "first principles" data-driven simulations for complex molecular modeling.

Conclusions:

• Combining advanced potentials and sampling algorithms enables realistic simulations of water's phase diagram.
• This approach deepens the understanding of molecular interactions and quantum effects in determining ice stability.
• "First principles" data-driven simulations bridge the gap between computational studies and experimental observations for complex molecular systems.