Potential energy landscape of a coarse grained model for water: ML-BOP

Neophytou, Andreas; Sciortino, Francesco

doi:10.1063/5.0197613

The Journal of Chemical Physics

2024

DOI: 10.1063/5.0197613

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Potential energy landscape of a coarse grained model for water: ML-BOP

Andreas Neophytou,

Francesco Sciortino

Abstract: We quantify the statistical properties of the potential energy landscape for a recently proposed machine learning coarse grained model for water, machine learning-bond-order potential [Chan et al., Nat. Commun. 10, 379 (2019)]. We find that the landscape can be accurately modeled as a Gaussian landscape at all densities. The resulting landscape-based free-energy expression accurately describes the model properties in a very wide range of temperatures and densities. The density dependence of the Gaussian landsc… Show more

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2024

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Cited by 4 publications

References 64 publications

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Potential energy landscape formalism for quantum molecular liquids

Eltareb,

Zhou,

Lopez

et al. 2024

Commun Chem

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The potential energy landscape (PEL) formalism is a powerful tool within statistical mechanics to study the thermodynamic properties of classical low-temperature liquids and glasses. Recently, the PEL formalism has been extended to liquids/glasses that obey quantum mechanics, but applications have been limited to atomistic model liquids. In this work, we extend the PEL formalism to liquid/glassy water using path-integral molecular dynamics (PIMD) simulations, where nuclear quantum effects (NQE) are included. Our PIMD simulations, based on the q-TIP4P/F water model, show that the PEL of quantum water is both Gaussian and anharmonic. Importantly, the ring-polymers associated to the O/H atoms in the PIMD simulations, collapse at the local minima of the PEL (inherent structures, IS) for both liquid and glassy states. This allows us to calculate, analytically, the IS vibrational density of states (IS-VDOS) of the ring-polymer system using the IS-VDOS of classical water (obtained from classical MD simulations). The role of NQE on the structural properties of liquid/glassy water at various pressures are discussed in detail. Overall, our results demonstrate that the PEL formalism can effectively describe the behavior of molecular liquids at low temperatures and in the glass states, regardless of whether the liquid/glass obeys classical or quantum mechanics.

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Potential energy landscape formalism for quantum molecular liquids

Eltareb,

Zhou,

Lopez

et al. 2024

Commun Chem

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Liquid–liquid transition and ice crystallization in a machine-learned coarse-grained water model

Dhabal,

Kumar,

Molinero

2024

Proc. Natl. Acad. Sci. U.S.A.

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Mounting experimental evidence supports the existence of a liquid–liquid transition (LLT) in high-pressure supercooled water. However, fast crystallization of supercooled water has impeded identification of the LLT line T LL ( p ) in experiments. While the most accurate all-atom (AA) water models display a LLT, their computational cost limits investigations of its interplay with ice formation. Coarse-grained (CG) models provide over 100-fold computational efficiency gain over AA models, enabling the study of water crystallization, but have not yet shown to have a LLT. Here, we demonstrate that the CG machine-learned water model Machine-Learned Bond-Order Potential (ML-BOP) has a LLT that ends in a critical point at p c = 170 ± 10 MPa and T c = 181 ± 3 K. The T LL ( p ) of ML-BOP is almost identical to the one of TIP4P/2005, adding to the similarity in the equation of state of liquid water in both models. Cooling simulations reveal that ice crystallization is fastest at the LLT and its supercritical continuation of maximum heat capacity, supporting a mechanistic relationship between the structural transformation of water to a low-density liquid (LDL) and ice formation. We find no signature of liquid–liquid criticality in the ice crystallization temperatures. ML-BOP replicates the competition between formation of LDL and ice observed in ultrafast experiments of decompression of the high-density liquid (HDL) into the region of stability of LDL. The simulations reveal that crystallization occurs prior to the coarsening of the HDL and LDL domains, obscuring the distinction between the highly metastable first-order LLT and pronounced structural fluctuations along its supercritical continuation.

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Medium-density amorphous ice unveils shear rate as a new dimension in water’s phase diagram

de Almeida Ribeiro,

Dhabal,

Kumar

et al. 2024

Proc. Natl. Acad. Sci. U.S.A.

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Recent experiments revealed a new amorphous ice phase, medium-density amorphous ice (MDA), formed by ball-milling ice I h at 77 K [Rosu-Finsen et al. , Science 379 , 474–478 (2023)]. MDA has density between that of low-density amorphous (LDA) and high-density amorphous (HDA) ices, adding to the complexity of water’s phase diagram, known for its glass polyamorphism and two-state thermodynamics. The nature of MDA and its relation to other amorphous ices and liquid water remain unsolved. Here, we use molecular simulations under controlled pressure and shear rate at 77 K to produce and investigate MDA. We find that MDA formed at constant shear rate is a steady-state nonequilibrium shear-driven amorphous ice (SDA), that can be produced by shearing ice I h , LDA, or HDA. Our results suggest that MDA could be obtained by ball-milling water glasses without crystallization interference. Increasing the shear rate at ambient pressure produces SDAs with densities ranging from LDA to HDA, revealing shear rate as a new thermodynamic variable in the nonequilibrium phase diagram of water. Indeed, shearing provides access to amorphous states inaccessible by controlling pressure and temperature alone. SDAs produced with shearing rates as high as 10 6 s −1 sample the same region of the potential energy landscape than hyperquenched glasses with identical density, pressure, and temperature. Intriguingly, SDAs obtained by shearing at ~10 8 s −1 have density, enthalpy, and structure indistinguishable from those of water “instantaneously” quenched from room temperature to 77 K over 10 ps, making them good approximants for the “true glass” of ambient liquid water.

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Potential energy landscape of a coarse grained model for water: ML-BOP

Cited by 4 publications

References 64 publications

Potential energy landscape formalism for quantum molecular liquids

Potential energy landscape formalism for quantum molecular liquids

Liquid–liquid transition and ice crystallization in a machine-learned coarse-grained water model

Medium-density amorphous ice unveils shear rate as a new dimension in water’s phase diagram

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