Correlating Antiagglomerant Performance with Gas Hydrate Cohesion.

Although inhibiting hydrate formation in hydrocarbon-water systems is paramount in preventing pipe blockage in hydrocarbon transport systems, the molecular mechanisms responsible for antiagglomerant (AA) performance are not completely understood. To better understand why macroscopic performance is affected by apparently small changes in the AA molecular structure, we perform molecular dynamics simulations. We quantify the cohesion energy between two gas hydrate nanoparticles dispersed in liquid hydrocarbons in the presence of different AAs, and we achieve excellent agreement against experimental data obtained at high pressure using the micromechanical force apparatus. This suggests that the proposed simulation approach could provide a screening method for predicting, in silico, the performance of new molecules designed to manage hydrates in flow assurance. Our results suggest that entropy and free energy of solvation of AAs, combined in some cases with the molecular orientation at hydrate-oil interfaces, are descriptors that could be used to predict performance, should the results presented here be reproduced for other systems as well. These insights could help speed up the design of new AAs and guide future experiments.

A DFT and KMC based study on the mechanism of the water gas shift reaction on the Pd(100) surface.

We present a combined density functional theory (DFT) and Kinetic Monte Carlo (KMC) study of the water gas shift (WGS) reaction on the Pd(100) surface. We propose a mechanism comprising both the redox and the associative pathways for the WGS within a single framework, which consists of seven core elementary steps, which in turn involve splitting of a water molecule followed by the production of an H-atom and an OH-species on the Pd(100) surface. In the following steps, these intermediates then recombine with each other and with CO leading to the evolution of CO2, and H2. Seven other elementary steps, involving the diffusion and adsorption of the surface intermediate species are also considered for a complete description of the mechanism. The geometrical and electronic properties of each of the reactants, products, and the transition states of the core elementary steps are presented. We also discuss the analysis of Bader charges and spin densities for the reactants, transition states and the products of these elementary steps. Our study indicates that the WGS reaction progresses simultaneously via the direct oxidation and the carboxyl paths on the Pd(100) surface.

Efficient and selective carbon-carbon coupling on coke-resistant PdAu single-atom alloys.

We demonstrate that PdAu single-atom alloy model catalysts offer a heterogeneous route to selective Würtz-type C-C coupling. Specifically, when methyl iodide is exposed to an otherwise unreactive Au(111) surface, single Pd atoms in the surface layer promote C-I dissociation and C-C coupling, leading to the selective formation of ethane.

Pt/Cu single-atom alloys as coke-resistant catalysts for efficient C-H activation.

The recent availability of shale gas has led to a renewed interest in C-H bond activation as the first step towards the synthesis of fuels and fine chemicals. Heterogeneous catalysts based on Ni and Pt can perform this chemistry, but deactivate easily due to coke formation. Cu-based catalysts are not practical due to high C-H activation barriers, but their weaker binding to adsorbates offers resilience to coking. Using Pt/Cu single-atom alloys (SAAs), we examine C-H activation in a number of systems including methyl groups, methane and butane using a combination of simulations, surface science and catalysis studies. We find that Pt/Cu SAAs activate C-H bonds more efficiently than Cu, are stable for days under realistic operating conditions, and avoid the problem of coking typically encountered with Pt. Pt/Cu SAAs therefore offer a new approach to coke-resistant C-H activation chemistry, with the added economic benefit that the precious metal is diluted at the atomic limit.

Adaptive coarse-grained Monte Carlo simulation of reaction and diffusion dynamics in heterogeneous plasma membranes.

BACKGROUND: An adaptive coarse-grained (kinetic) Monte Carlo (ACGMC) simulation framework is applied to reaction and diffusion dynamics in inhomogeneous domains. The presented model is relevant to the diffusion and dimerization dynamics of epidermal growth factor receptor (EGFR) in the presence of plasma membrane heterogeneity and specifically receptor clustering. We perform simulations representing EGFR cluster dissipation in heterogeneous plasma membranes consisting of higher density clusters of receptors surrounded by low population areas using the ACGMC method. We further investigate the effect of key parameters on the cluster lifetime. RESULTS: Coarse-graining of dimerization, rather than of diffusion, may lead to computational error. It is shown that the ACGMC method is an effective technique to minimize error in diffusion-reaction processes and is superior to the microscopic kinetic Monte Carlo simulation in terms of computational cost while retaining accuracy. The low computational cost enables sensitivity analysis calculations. Sensitivity analysis indicates that it may be possible to retain clusters of receptors over the time scale of minutes under suitable conditions and the cluster lifetime may depend on both receptor density and cluster size. CONCLUSIONS: The ACGMC method is an ideal platform to resolve large length and time scales in heterogeneous biological systems well beyond the plasma membrane and the EGFR system studied here. Our results demonstrate that cluster size must be considered in conjunction with receptor density, as they synergistically affect EGFR cluster lifetime. Further, the cluster lifetime being of the order of several seconds suggests that any mechanisms responsible for EGFR aggregation must operate on shorter timescales (at most a fraction of a second), to overcome dissipation and produce stable clusters observed experimentally.

Astrocyte signaling in the presence of spatial inhomogeneities.

Astrocytes, a special type of glial cells, were considered to have just a supporting role in information processing in the brain. However, several recent studies have shown that they can be chemically stimulated by various neurotransmitters, such as ATP, and can generate Ca2+ and ATP waves, which can propagate over many cell lengths before being blocked. Although pathological conditions, such as spreading depression and epilepsy, have been linked to abnormal wave propagation in astrocytic cellular networks, a quantitative understanding of the underlying characteristics is still lacking. Astrocytic cellular networks are inhomogeneous, in the sense that the domain they occupy contains passive regions or gaps, which are unable to support wave propagation. Thus, this work focuses on understanding the complex interplay between single-cell signal transduction, domain inhomogeneity, and the characteristics of wave propagation and blocking in astrocytic cellular networks. The single-cell signal transduction model that was employed accounts for ATP-mediated IP3 production, the subsequent Ca2+ release from the ER, and ATP release into the extracellular space. The model is excitable and thus an infinite range of wave propagation is observed if the domain of propagation is homogeneous. This is not always the case for inhomogeneous domains. To model wave propagation in inhomogeneous astrocytic networks, a reaction-diffusion framework was developed and one-gap as well as multiple-gap cases were simulated using an efficient finite-element algorithm. The minimum gap length that blocks the wave was computed as a function of excitability levels and geometric characteristics of the inhomogeneous network, such as the length of the active regions (cells). Complex transient patterns, such as wave reflection, wave trapping, and generation of echo waves, were also predicted by the model, and their relationship to the geometric characteristics of the network was evaluated. Therefore, the proposed model can help in the formulation of testable hypotheses to explain the observed abnormal wave propagation in pathological situations.

Modeling of ATP-mediated signal transduction and wave propagation in astrocytic cellular networks.

Astrocytes, a special type of glial cells, were considered to have supporting role in information processing in the brain. However, several recent studies have shown that they can be chemically stimulated by neurotransmitters and use a form of signaling, in which ATP acts as an extracellular messenger. Pathological conditions, such as spreading depression, have been linked to abnormal range of wave propagation in astrocytic cellular networks. Nevertheless, the underlying intra- and inter-cellular signaling mechanisms remain unclear. Motivated by the above, we constructed a model to understand the relationship between single-cell signal transduction mechanisms and wave propagation and blocking in astrocytic networks. The model incorporates ATP-mediated IP3 production, the subsequent Ca2+ release from the ER through IP3R channels and ATP release into the extracellular space. For the latter, two hypotheses were tested: Ca2+- or IP3-dependent ATP release. In the first case, single astrocytes can exhibit excitable behavior and frequency-encoded oscillations. Homogeneous, one-dimensional astrocytic networks can propagate waves with infinite range, while in two dimensions, spiral waves can be generated. However, in the IP3-dependent ATP release case, the specific coupling of the driver ATP-IP3 system with the driven Ca2+ subsystem leads to one- and two-dimensional wave patterns with finite range of propagation.