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In this work we assess and extend strategies for calculating surface tension of complex liquids from molecular dynamics simulations: the mechanical route and the instantaneous liquid interface (ILI) approach. The former employs the connection between stress tensor and surface tension, whereas the latter involves computation of instantaneous density field. Whereas the mechanical route is general, the ILI method involves system-dependent parameters restricting its original application to liquid water only. Here we generalize the approach to complex molecular liquids using atomic van der Waals radii. The performance of the approaches is evaluated on two liquid systems: acetonitrile and water–methanol mixture. In addition, we compare the effect of the computational models for interaction potentials based on semi-empirical electronic structure theory and classical force fields on the estimate of the surface tension within both stress tensor and ILI approaches.

Simulations based on electronic structure theory naturally include polarization and have no transferability problems. In particular, Kohn–Sham density functional theory (KS-DFT) has become the method of reference for ab initio molecular dynamics simulations of condensed matter systems. However, the high computational cost often poses strict limits on the affordable system size as well as on the extension of sampling (number of configurations). In this work, we propose an improvement to the subsystem density functional theory approach, known as the Kim–Gordon (KG) scheme, thus enabling the sampling of configurations for condensed molecular systems keeping the KS-DFT level accuracy at a fraction of computer time. Our scheme compensates the known KG shortcomings of the electronic kinetic energy term by adding a simple correction and can match KS-DFT accuracy in energies and forces. The computationally cheap correction is determined by means of a machine learning procedure. The proposed KG scheme is applied within a linear scaling self-consistent field formalism and is assessed by a series of molecular dynamics simulations of liquid water under different conditions. Although system-dependent, the correction is transferable between system sizes and temperatures.

The nature of the bulk hydrated electron has been a challenge for both experiment and theory due to its short lifetime and high reactivity, and the need for a high-level of electronic structure theory to achieve predictive accuracy. The lack of a classical atomistic structural formula makes it exceedingly difficult to model the solvated electron using conventional empirical force fields, which describe the system in terms of interactions between point particles associated with atomic nuclei. Here we overcome this problem using a machine-learning model, that is sufficiently flexible to describe the effect of the excess electron on the structure of the surrounding water, without including the electron in the model explicitly. The resulting potential is not only able to reproduce the stable cavity structure but also recovers the correct localization dynamics that follow the injection of an electron in neat water. The machine learning model achieves the accuracy of the state-of-the-art correlated wave function method it is trained on. It is sufficiently inexpensive to afford a full quantum statistical and dynamical description and allows us to achieve accurate determination of the structure, diffusion mechanisms, and vibrational spectroscopy of the solvated electron.

Sampling potential energy surfaces (PES) is pivotal for understanding chemical structure, energetics and reactivity and is of special importance for complex condensed‐phase systems. Until recently such simulations based on electronic structure theory have been performed only by density functional theory and semiempirical methods. Many‐body electronic structure methods, almost routinely used for molecules, have been practically unavailable for sampling PES in the condensed‐phase. This has changed during the last few years, as efficient algorithms and software implementations for the evaluation of electronic energies and forces on atoms have been developed, allowing for geometry optimization, molecular dynamics and Monte‐Carlo simulations, which was previously unthinkable. Herein, we introduce the theory and software developments and overview the applications in the field, the most encouraging results being obtained for aqueous chemistry. Requiring state‐of‐the‐art computer resources PES sampling with many‐body electronic structure methods in the condensed phase provides high‐quality benchmarks and will gradually become more available due to fast progress in reduced scaling algorithms and computational technologies.

Aqueous solvated electron (eaq–), a key species in radiation and plasma chemistry, can efficiently reduce CO2 in a potential green chemistry application. Here, the mechanism of this reaction is unravelled by condensed-phase molecular dynamics based on the correlated wave function and an accurate density functional theory (DFT) approximation. Here, we design and apply the holistic protocol for solvated electron’s reactions encompassing all relevant reaction stages starting from diffusion. The carbon dioxide reduction proceeds via a cavity intermediate, which is separated from the product (CO2–) by an energy barrier due to the bending of CO2 and the corresponding solvent reorganization energy. The formation of the intermediate is caused by solvated electron’s diffusion, whereas the intermediate transformation to CO2– is triggered by hydrogen bond breaking in the second solvation shell of the solvated electron. This picture of an activation-controlled eaq– reaction is very different from both rapid barrierless electron transfer and proton-coupled electron transfer, where key transformations are caused by proton migration.

CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid,molecular, and biological systems. It is especially aimed at massively parallel and linear-scaling electronic structure methods and state-of-the-artab initiomolecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithmsimplemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient andaccurate electronic structure simulations. The emphasis is put on density functional theory and multiple post–Hartree–Fock methods usingthe Gaussian and plane wave approach and its augmented all-electron extension.