The aims of this study are the following two: (1) To show that in Langmuir monolayers (LM) at low supersaturation, domains grow forming fractal structures without an apparent orientational order trough tip splitting dynamics, where doublons are the building blocks producing domains with a seaweed shape. When supersaturation is larger, there is a morphology transition from tip splitting to side branching. Here, structures grow with a pronounced orientational order forming dendrites, which are also fractal. We observed this behavior in different Langmuir monolayers formed by nervonic acid, dioctadecylamine, ethyl stearate, and ethyl palmitate, using Brewster angle microscopy. (2) To present experimental evidence showing an important Marangoni flow during domain growth, where the hydrodynamic transport of amphipiles overwhelms diffusion. We were able to show that the equation that governs the pattern formation in LM is a Laplacian equation in the chemical potential with the appropriate boundary conditions. However, the underlying physics involved in Langmuir monolayers is different from the underlying physics in the Mullins-Sekerka instability; diffusional processes are not involved. We found a new kind of instability that leads to pattern formation, where Marangoni flow is the key factor. We also found that the equations governing pattern formation in LM can be reduced to those used in the theory of morphology diagrams for two-dimensional diffusional growth. Our experiments agree with this diagram.

Path sampling approaches have become invaluable tools to explore the mechanisms and dynamics of so-called rare events that are characterized by transitions between metastable states separated by sizeable free energy barriers. Their practical application, in particular to ever more complex molecular systems, is, however, not entirely trivial. Focusing on replica exchange transition interface sampling (RETIS) and forward flux sampling (FFS), we discuss a range of analysis tools that can be used to assess the quality and convergence of such simulations which is crucial to obtain reliable results. The basic ideas of a step-wise evaluation are exemplified for the study of nucleation in several systems with different complexity, providing a general guide for the critical assessment of RETIS and FFS simulations.

The archiving and dissemination of protein and nucleic acid structures as well as their structural, functional and biophysical annotations is an essential task that enables the broader scientific community to conduct impactful research in multiple fields of the life sciences. The Protein Data Bank in Europe (PDBe; pdbe.org) team develops and maintains several databases and web services to address this fundamental need. From data archiving as a member of the Worldwide PDB consortium (wwPDB; wwpdb.org), to the PDBe Knowledge Base (PDBe-KB; pdbekb. org), we provide data, data-access mechanisms, and visualizations that facilitate basic and applied research and education across the life sciences. Here, we provide an overview of the structural data and annotations that we integrate and make freely available. We describe the web services and data visualization tools we offer, and provide information on how to effectively use or even further develop them. Finally, we discuss the direction of our data services, and how we aim to tackle new challenges that arise from the recent, unprecedented advances in the field of structure determination and protein structure modeling.

The time evolution of many physical, chemical, and biological systems can be modelled by stochastic transitions between the minima of the potential energy surface describing the system of interest. We show that in cases where there are two (or more) possible pathways that the system can take, the time available for the transition to occur is crucially important. The well-known results of reaction rate theory for determining the rates of the transitions apply in the long-time limit. However, at short times, the system can instead choose to pass over higher energy barriers with much higher probability, as long as the distance to travel in phase space is shorter. We construct two simple models to illustrate this general phenomenon. We also apply a version of the geometric minimum action method algorithm of Vanden-Eijnden and Heymann [J. Chem. Phys. {\bf 128}, 061103 (2008)] to determine the most likely path at both short and long times.