Porous crystalsincluding zeolites, metal–organic frameworks, and clathratesare widely used as catalysts and molecular sieves and in energy applications. These materials are synthesized from solution through an intermediate amorphous phase. However, the structural gap between the amorphous and porous crystal phases can lead to large nucleation barriers and difficulties in the control of crystal polymorphs. Previous reports indicate that porous mesophases can facilitate the amorphous to porous crystal transformation, directing the crystallization toward specific crystal structures. To date, it is not known how mesophase stability and synthesis temperature impact the facilitation. Here, we use molecular simulations and nucleation theory to investigate the crystallization of a zeolite in a family of models with tunable mesophase stability. We find that the nucleation mechanism evolves from non-classical to classical as the mesophase stability approaches that of the crystal. The simulations reveal that even an unstable mesophase can facilitate porous crystal nucleation through the formation of a transient fluctuation within which the crystal is originated. We conclude that tapping into the medium-range order of mesophases that have ordered pores without crystalline tiling is promising to increase the crystallization rates of porous crystals while directing the synthesis toward specific polymorphs.

We apply the adaptive multilevel splitting (AMS) method to the C eq ! C ax transition of alanine dipeptide in vacuum. Some properties of the algorithm are numerically illustrated, such as the unbiasedness of the probability estimator and the robustness of the method with respect to the reaction coordinate. We also calculate the transition time obtained via the probability estimator, using an appropriate ensemble of initial conditions. Finally, we show how the AMS method can be used to compute an approximation of the committor function.

The Collective Variables Dashboard is a software tool for real-time, seamless exploration of molecular structures and trajectories in a customizable space of collective variables. The Dashboard arises from the integration of the Collective Variables Module (also known as Colvars) with the visualization software VMD, augmented with a fully discoverable graphical interface offering interactive workflows for the design and analysis of collective variables. Typical use cases include a priori design of collective variables for enhanced sampling and free energy simulations as well as analysis of any type of simulation or collection of structures in a collective variable space. A combination of those cases commonly occurs when preliminary simulations, biased or unbiased, reveal that an optimized set of collective variables is necessary to improve sampling in further simulations. Then the Dashboard provides an efficient way to intuitively explore the space of likely collective variables, validate them on existing data, and use the resulting collective variable definitions directly in further biased simulations using the Collective Variables Module. Visualization of biasing energies and forces is proposed to help analyze or plan biased simulations. We illustrate the use of the Dashboard on two applications: discovering coordinates to describe ligand unbinding from a protein binding site and designing volume-based variables to bias the hydration of a transmembrane pore.

The S 1s X-ray absorption near edge structure (XANES) and X-ray photoelectron spectra (XPS) of the neutral complexes [SbL(dmit)] (L = Br or I; dmit =1,3-dithiole-2-thione-4,5-dithiolate) have been measured using tunable synchrotron radiation. The valence shell electronic excitation by ultraviolet-visible (UV-vis) spectroscopy and the infrared vibrational spectra are presented and analyzed. The UV-vis results lead to an assignment of bands at 400 nm as π(Sm) → π*(C═S), where S(m) is the thiolate sulfur. The corresponding S 1s → π*(C═S) transition was identified at 2468.3 eV. Ab initio calculations, within the improved virtual orbital (IVO) method, carried out with the GSCF3 program, were applied to establish a complete and accurate spectral assignment. It has been the first attempt to apply such methodology for dmit coordination compounds, and very consistent results were obtained.