Global Free-Energy Landscapes as a Smoothly Joined Collection of Local Maps.

Enhanced sampling techniques have become an essential tool in computational chemistry and physics, where they are applied to sample activated processes that occur on a time scale that is inaccessible to conventional simulations. Despite their popularity, it is well known that they have constraints that hinder their application to complex problems. The core issue lies in the need to describe the system using a small number of collective variables (CVs). Any slow degree of freedom that is not properly described by the chosen CVs will hinder sampling efficiency. However, the exploration of configuration space is also hampered by including variables that are not relevant for the activated process under study. This paper presents the Adaptive Topography of Landscape for Accelerated Sampling (ATLAS), a new biasing method capable of working with many CVs. The root idea of ATLAS is to apply a divide-and-conquer strategy, where the high-dimensional CVs space is divided into basins, each of which is described by an automatically determined, low-dimensional set of variables. A well-tempered metadynamics-like bias is constructed as a function of these local variables. Indicator functions associated with the basins switch on and off the local biases so that the sampling is performed on a collection of low-dimensional CV spaces that are smoothly combined to generate an effectively high-dimensional bias. The unbiased Boltzmann distribution is recovered through reweighing, making the evaluation of conformational and thermodynamic properties straightforward. The decomposition of the free-energy landscape in local basins can be updated iteratively as the simulation discovers new (meta)stable states.

Iterative Unbiasing of Quasi-Equilibrium Sampling.

Atomistic modeling of phase transitions, chemical reactions, or other rare events that involve overcoming high free energy barriers usually entails prohibitively long simulation times. Introducing a bias potential as a function of an appropriately chosen set of collective variables can significantly accelerate the exploration of phase space, albeit at the price of distorting the distribution of microstates. Efficient reweighting to recover the unbiased distribution can be nontrivial when employing adaptive sampling techniques such as metadynamics, variationally enhanced sampling, or parallel bias metadynamics, in which the system evolves in a quasi-equilibrium manner under a time-dependent bias. We introduce an iterative unbiasing scheme that makes efficient use of all the trajectory data and that does not require the distribution to be evaluated on a grid. The method can thus be used even when the bias has a high dimensionality. We benchmark this approach against some of the existing schemes on model systems with different complexity and dimensionality.

Comment on "Water-water correlations in electrolyte solutions probed by hyper-Rayleigh scattering" [J. Chem. Phys. 147, 214505 (2017)].

The work by Shelton [J. Chem. Phys. 147, 214505 (2017)] discussed and interpreted differences with a previous study by Chen et al. [Sci. Adv. 2, e1501891 (2016)] regarding the influence of electrolytes on the structure of water. It is argued by Shelton [J. Chem. Phys. 147, 214505 (2017)] that impurities and hyper-Raman scattering contributions are the reasons for differences in the measured second harmonic intensity between the above two studies. Here, we show that these proposed effects are not relevant and discuss the influence of pulse parameters, focusing on pulse duration, since these two sets of experiments are performed with substantially different pulse durations, 100 ns and 190 fs, respectively. We show that inelastic higher-order effects play a role in the experiment with 100 ns laser pulses (the probed structure is that of the electrolyte solution that is modified by a laser pulse), while in the experiment with 190 fs laser pulses, only the elastic second-order response is measured (probing the unperturbed water structure).

Accurate molecular dynamics and nuclear quantum effects at low cost by multiple steps in real and imaginary time: Using density functional theory to accelerate wavefunction methods.

The development and implementation of increasingly accurate methods for electronic structure calculations mean that, for many atomistic simulation problems, treating light nuclei as classical particles is now one of the most serious approximations. Even though recent developments have significantly reduced the overhead for modeling the quantum nature of the nuclei, the cost is still prohibitive when combined with advanced electronic structure methods. Here we present how multiple time step integrators can be combined with ring-polymer contraction techniques (effectively, multiple time stepping in imaginary time) to reduce virtually to zero the overhead of modelling nuclear quantum effects, while describing inter-atomic forces at high levels of electronic structure theory. This is demonstrated for a combination of MP2 and semi-local DFT applied to the Zundel cation. The approach can be seamlessly combined with other methods to reduce the computational cost of path integral calculations, such as high-order factorizations of the Boltzmann operator or generalized Langevin equation thermostats.

Simultaneous measurement of lithium and fluorine momentum in 7LiF.

We present momentum widths and mean kinetic energies of lithium and fluorine in (7)LiF, as determined simultaneously from deep inelastic neutron scattering (DINS) measurements. Experimental data across a temperature range from 4 to 300 K are presented, and these results compared to those calculated using a quasi-harmonic density-functional approach. In all cases, measured momentum widths are seen to be within approximately 5% of those calculated, despite the very low scattering cross sections of both (7)Li and (19)F. This is the first determination and comparison with theory of such simultaneous measurements for nuclei of mass > 4 amu, and demonstrates the implementation of the DINS method in its current form as a mass-selective neutron spectroscopy.

Density functional study of the decomposition pathways of SiH3 and GeH3 at the Si(100) and Ge(100) surfaces.

By means of first-principles calculations we studied the decomposition pathways of SiH3 on Ge(100) and of GeH3 on Si(100), of interest for the growth of crystalline SiGe alloys and Si/Ge heterostructures by plasma-enhanced chemical vapor deposition. We also investigated H desorption via reaction of two adsorbed SiH2/GeH2 species (ß2 reaction) or via Eley-Rideal abstraction of surface H atoms from the impinging SiH3 and GeH3 species. The calculated activation energies for the different processes suggest that the rate-limiting step for the growth of Si/Ge systems is still the ß2 reaction of two SiH2 as in the growth of crystalline Si.

Impact-driven effects in thin-film growth: steering and transient mobility at the Ag(110) surface.

Low-energy atomic impacts on the Ag(110) surface are investigated by molecular dynamics simulations based on reliable many-body semiempirical potentials. Trajectory deflections (steering) caused by the atom-surface interaction are observed, together with impact-following, transient-mobility effects. Such processes are quantitatively analysed and their dependence on the initial kinetic energy and on the impinging direction is discussed. A clear influence of the surface anisotropy on both steering and transient mobility effects is revealed by our simulations for the simple isolated-atom case and in the submonolayer-growth regime. For the latter case, we illustrate how steering and transient mobility affect the film morphology at the nanoscale.