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Computational predictions of the polymorphic outcomes of a crystallization process, referred to as polymorph selection, can accelerate the process development for manufacturing solid products with targeted properties. Polymorph selection requires understanding the interplay between the thermodynamic and kinetic factors that drive nucleation. Moreover, post-nucleation events, such as crystal growth and polymorphic transformation, can affect the resulting crystal structures. Here, the nucleation kinetics of the Lennard-Jones (LJ) fluid from the melt is investigated with a focus on the competition between FCC and HCP crystal structures. Both molecular dynamics (MD) simulations and 2D free energy calculations reveal that polymorph selection occurs not during nucleation but when the cluster sizes exceed the critical cluster size. This result contrasts with the classical nucleation mechanism, where each polymorph is assumed to nucleate independently as an ideal bulk-like cluster, comprised only of its given structure. Using the 2D free energy surface and the MD simulation-derived diffusion coefficients, a structure-dependent nucleation rate is estimated, which agrees with the rate obtained from brute force MD simulations. Furthermore, a comprehensive population balance modeling (PBM) approach for polymorph selection is proposed. The PBM combines the calculated nucleation rate with post-nucleation kinetics while accounting for the structural changes of the clusters after nucleation. When applied to the LJ system, the PBM predicts with high accuracy the polymorphic distribution found in a population of crystals generated from MD simulations. Due to the non-classical nucleation mechanism of the LJ system, post-nucleation kinetic events are crucial in determining the structures of the grown crystals. [ABSTRACT FROM AUTHOR]

A Brownian bridge is a continuous random walk conditioned to end in a given region by adding an effective drift to guide paths toward the desired region of phase space. This idea has many applications in chemical science where one wants to control the endpoint of a stochastic process—e.g., polymer physics, chemical reaction pathways, heat/mass transfer, and Brownian dynamics simulations. Despite its broad applicability, the biggest limitation of the Brownian bridge technique is that it is often difficult to determine the effective drift as it comes from a solution of a Backward Fokker–Planck (BFP) equation that is infeasible to compute for complex or high-dimensional systems. This paper introduces a fast approximation method to generate a Brownian bridge process without solving the BFP equation explicitly. Specifically, this paper uses the asymptotic properties of the BFP equation to generate an approximate drift and determine ways to correct (i.e., re-weight) any errors incurred from this approximation. Because such a procedure avoids the solution of the BFP equation, we show that it drastically accelerates the generation of conditioned random walks. We also show that this approach offers reasonable improvement compared to other sampling approaches using simple bias potentials. [ABSTRACT FROM AUTHOR]

Before insulin can stimulate myocytes to take up glucose, it must first move from the circulation to the interstitial space. The continuous endothelium of skeletal muscle (SkM) capillaries restricts insulin's access to myocytes. The mechanism by which insulin crosses this continuous endothelium is critical to understand insulin action and insulin resistance; however, methodological obstacles have limited understanding of endothelial insulin transport in vivo. Here, we present an intravital microscopy technique to measure the rate of insulin efflux across the endothelium of SkM capillaries. This method involves development of a fully bioactive, fluorescent insulin probe, a gastrocnemius preparation for intravital microscopy, an automated vascular segmentation algorithm, and the use of mathematical models to estimate endothelial transport parameters. We combined direct visualization of insulin efflux from SkM capillaries with modeling of insulin efflux kinetics to identify fluid-phase transport as the major mode of transendothelial insulin efflux in mice. Model-independent experiments demonstrating that insulin movement is neither saturable nor affected by insulin receptor antagonism supported this result. Our finding that insulin enters the SkM interstitium by fluid-phase transport may have implications in the pathophysiology of SkM insulin resistance as well as in the treatment of diabetes with various insulin analogs., Introduction Interorgan communication is essential for maintaining physiological homeostasis. One way organs communicate with each other is by sending molecular signals through the circulation. Before these signals can stimulate biological [...]

The equilibrium conformation of a polymer molecule in an external field is often used in field theories to calculate macroscopic polymer properties of melts and solutions. We use a mathematical method called a Brownian bridge to exactly sample continuous polymer chains to end in a given state. We show that one can systematically develop such processes to sample specific polymer topologies, to confine polymers in a given geometry for its entire path, to efficiently generate high-probability conformations by excluding small Boltzmann weights, or to simulate rare events in a rugged energy landscape. This formalism can improve the polymer sampling efficiency significantly compared to traditional methods (e.g., Monte Carlo or Rosenbluth). [ABSTRACT FROM AUTHOR]