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From Potentials to Properties: Data-Driven Many-Body Simulations of Water and Aqueous Systems.

Francesco Paesani1,2,3,4, Richa Rashmi1, Henry Agnew1

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Data-driven many-body potential energy functions (PEFs) enhance water simulations. The MB-nrg formalism provides accurate insights into aqueous systems, advancing physical chemistry research.

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Area of Science:

  • Physical Chemistry
  • Computational Chemistry
  • Materials Science

Background:

  • Water's complex behavior across phases and environments challenges current models.
  • Accurate simulations are crucial for understanding aqueous systems.

Purpose of the Study:

  • To review the impact of data-driven many-body potential energy functions (PEFs) on simulating water and aqueous systems.
  • To highlight the MB-nrg formalism's role in advancing physical chemistry.

Main Methods:

  • Development of data-driven many-body potential energy functions (PEFs) within the many-body energy (MB-nrg) formalism.
  • Utilizing "gold standard" electronic structure data.
  • Bridging quantum chemistry and statistical mechanics.

Main Results:

  • MB-pol and MB-nrg PEFs enable simulations with unprecedented predictive power.
  • Enhanced understanding of hydrogen bonding, spectroscopy, isotope effects, and phase stability in aqueous systems.
  • Accurate simulations across gas, liquid, and solid phases.

Conclusions:

  • The MB-nrg formalism offers a robust foundation for realistic molecular simulations.
  • Data-driven PEFs provide new opportunities for addressing long-standing questions in physical chemistry.
  • Quantum-mechanical accuracy is maintained across length and timescales.