A Benchmark Protocol for DFT Approaches and Data-Driven Models for Halide-Water Clusters

Abstract

Dissolved ions in aqueous media are ubiquitous in many physicochemical processes, with a direct impact on research fields, such as chemistry, climate, biology, and industry. Ions play a crucial role in the structure of the surrounding network of water molecules as they can either weaken or strengthen it. Gaining a thorough understanding of the underlying forces from small clusters to bulk solutions is still challenging, which motivates further investigations. Through a systematic analysis of the interaction energies obtained from high-level electronic structure methodologies, we assessed various dispersion-corrected density functional approaches, as well as ab initio-based data-driven potential models for halide ion–water clusters. We introduced an active learning scheme to automate the generation of optimally weighted datasets, required for the development of efficient bottom-up anion–water models. Using an evolutionary programming procedure, we determined optimized and reference configurations for such polarizable and first-principles-based representation of the potentials, and we analyzed their structural characteristics and energetics in comparison with estimates from DF-MP2 and DFT+D quantum chemistry computations. Moreover, we presented new benchmark datasets, considering both equilibrium and non-equilibrium configurations of higher-order species with an increasing number of water molecules up to 54 for each F, Cl, Br, and I anions, and we proposed a validation protocol to cross-check methods and approaches. In this way, we aim to improve the predictive ability of future molecular computer simulations for determining the ongoing conflicting distribution of different ions in aqueous environments, as well as the transition from nanoscale clusters to macroscopic condensed phases.

Quantum molecular simulations of micro-hydrated halogen anions

“…Computational calculations were carried out using our own codes [55][56][57] for both nuclear classical MD and PIMD simulations, while otherwise, we explicitly reference the corresponding software. Potential optimizations were performed using an evolutionary programming (EP) algorithm, 58 while in all cases the DENEB software package 59 was employed to generate initial guess configurations and input files, as well as to organize both input and output data files.…”

“…60 The dispersion contribution is obtained as a sum of damped Tang-Toennies terms, with the dispersion C 6 coefficients between anion and water atoms adjusted to those computed from DFT/LC-ωPBE calculations using the XDM (exchange-hole dipole moment) model, 69 as implemented in postg code, 70 while the repulsive term is represented as a sum of Born-Mayer functions over all atoms, fitted to CCSD(T)-F12b energies of the anion–H 2 O system subtracting the electrostatic and dispersion energy contributions, via an active learning scheme. 55…”

“…Following previous studies on halide-water clusters, 55,57,60,61 we have recently reported four families of data-driven PESs, namely i-TTM2, i-TTM3, i-TTM4, and i-MBpol depending on which TTM water model [62][63][64][65] we choose to describe the waterwater interactions in X À (H 2 O) N systems. Ultimately, a variety of many-body water potential models are available in the literature incorporating explicitly 2-body, 3-body, and even 4-body terms fitted to ab initio data with the remaining n-body terms described by classical induction.…”

“…60 The dispersion contribution is obtained as a sum of damped Tang-Toennies f ðR; dÞ C 6 R 6 terms, with the dispersion C 6 coefficients between anion and water atoms adjusted to those computed from DFT/LC-oPBE calculations using the XDM (exchange-hole dipole moment) model, 69 as implemented in postg code, 70 while the repulsive term is represented as a sum of Born-Mayer functions over all atoms, fitted to CCSD(T)-F12b energies of the anion-H 2 O system subtracting the electrostatic and dispersion energy contributions, via an active learning scheme. 55 In Fig. 1 we presented one-dimensional views of the anionwater potentials as a function of the f angle (C 2v axis of water molecule and -R joining oxygen and anion atoms) for planar H 2 O-fixed configurations (see upper panel) optimizing the R distance, along the OH of the ion-hydrogen bond keeping the R distance fixed at its equilibrium values (see the middle panel), and as a function of R (see the lower panel).…”

“…Thus, the present work is directed at studying the energetics and structuring of different finite-size halide-water clusters, through path-integral molecular dynamics (PIMD) simulations, employing the recently developed data-driven i-TTM4 potential models. 55 Comparisons with results from classical molecular dynamics (MD) simulations were also presented in order to investigate the impact of temperature over quantum zero-point contributions in both energies and structures.…”