How Accurate Is the Mean-Field Approximation for Catalytic Kinetics?

Modelling catalytic kinetics is indispensable for the design of reactors and chemical processes. Currently, the majority of kinetic models employ mean-field approximations and are formulated as ordinary differential equations, which leads to an approximate description of catalytic kinetics by omitting spatial correlations. On the other hand, kinetic Monte Carlo (KMC) approaches provide a discrete-space continuous-time stochastic formulation that enables a detailed treatment of spatial correlations in the adlayer, but at a significant computation expense. Such spatial correlations arise from slow diffusion in tandem with 2-site reactions, or from adsorbate-adsorbate lateral interactions, and have been shown to markedly affect the observed kinetics. It is thus well known that mean-field models are limited, as they neglect such correlations; yet, due to their computational efficiency, such approaches are ideal in multiscale modelling frameworks (for instance as chemistry modules in computational fluid dynamics). However, it is possible to develop higher order approximations that systematically increase the accuracy of kinetic models by treating spatial correlations at a progressively higher level of detail but at the cost of higher computational effort. In this study, we assess the error and computational efficiency of mean-field and higher order approximations for kinetics in catalytic systems with strongly interacting adsorbates. We thus focus on a model for NO oxidation incorporating first nearest neighbor lateral interactions and construct a sequence of approximate models of progressively higher accuracy, starting from the mean-field treatment and continuing with a sequence of Bethe-Peierls models with increasing cluster sizes. By comparing the turnover frequencies of these models with those obtained from KMC simulation, we show that the mean-field predictions deviate by several orders of magnitude from the KMC simulation results. The Bethe-Peierls model, with a cluster incorporating sites up to 2nd nearest neighbors, performs well for predicting coverages; however, due to the exponential dependence of reaction rate on activation energy, the turnover frequency predictions are still inadequate. One requires Bethe-Peierls approximations with clusters of 4th or higher nearest neighbors, in order to faithfully reproduce the KMC predictions. We show that such approximations, while more computationally intense than the mean-field treatment, still enable significant computational savings compared to a KMC simulation, thereby paving the road for employing them in multiscale modelling frameworks

The merger-driven evolution of massive early-type galaxies

Galaxie

The contribution of in-situ and ex-situ star formation in early-type galaxies: MaNGA versus IllustrisTNG

Interstellar matter and star formationGalaxie

A MegaCam Survey of Outer Halo Satellites. III. Photometric and Structural Parameters

We present structural parameters from a wide-field homogeneous imaging survey of Milky Way satellites carried out with the MegaCam imagers on the 3.6 m Canada–France–Hawaii Telescope and 6.5 m Magellan-Clay telescope. Our survey targets an unbiased sample of "outer halo" satellites (i.e., substructures having galactocentric distances greater than 25 kpc) and includes classical dSph galaxies, ultra-faint dwarfs, and remote globular clusters. We combine deep, panoramic gr imaging for 44 satellites and archival gr imaging for 14 additional objects (primarily obtained with the DECam instrument as part of the Dark Energy Survey) to measure photometric and structural parameters for 58 outer halo satellites. This is the largest and most uniform analysis of Milky Way satellites undertaken to date and represents roughly three-quarters (58/81 ≃ 72%) of all known outer halo satellites. We use a maximum-likelihood method to fit four density laws to each object in our survey: exponential, Plummer, King, and Sérsic models. We systematically examine the isodensity contour maps and color–magnitude diagrams for each of our program objects, present a comparison with previous results, and tabulate our best-fit photometric and structural parameters, including ellipticities, position angles, effective radii, Sérsic indices, absolute magnitudes, and surface brightness measurements. We investigate the distribution of outer halo satellites in the size–magnitude diagram and show that the current sample of outer halo substructures spans a wide range in effective radius, luminosity, and surface brightness, with little evidence for a clean separation into star cluster and galaxy populations at the faintest luminosities and surface brightnesses

A MegaCam Survey of Outer Halo Satellites. I. Description of the Survey

We describe a deep, systematic imaging study of satellites in the outer halo of the Milky Way. Our sample consists of 58 stellar overdensities—i.e., substructures classified as either globular clusters, classical dwarf galaxies, or ultra-faint dwarf galaxies—that are located at Galactocentric distances of R_(GC) ≥ 25 kpc (outer halo) and out to ~400 kpc. This includes 44 objects for which we have acquired deep, wide-field, g- and r-band imaging with the MegaCam mosaic cameras on the 3.6 m Canada–France–Hawaii Telescope and the 6.5 m Magellan-Clay telescope. These data are supplemented by archival imaging, or published gr photometry, for an additional 14 objects, most of which were discovered recently in the Dark Energy Survey (DES). We describe the scientific motivation for our survey, including sample selection, observing strategy, data reduction pipeline, calibration procedures, and the depth and precision of the photometry. The typical 5σ point-source limiting magnitudes for our MegaCam imaging—which collectively covers an area of ≈52 deg^2—are g_(lim) ≃ 25.6 and r_(lim) ≃ 25.3 AB mag. These limits are comparable to those from the coadded DES images and are roughly a half-magnitude deeper than will be reached in a single visit with the Large Synoptic Survey Telescope. Our photometric catalog thus provides the deepest and most uniform photometric database of Milky Way satellites available for the foreseeable future. In other papers in this series, we have used these data to explore the blue straggler populations in these objects, their density distributions, star formation histories, scaling relations, and possible foreground structures

Predicting the F(ab)-mediated effect of monoclonal antibodies in vivo by combining cell-level kinetic and pharmacokinetic modelling

Cell-level kinetic models for therapeutically relevant processes increasingly benefit the early stages of drug development. Later stages of the drug development processes, however, rely on pharmacokinetic compartment models while cell-level dynamics are typically neglected. We here present a systematic approach to integrate cell-level kinetic models and pharmacokinetic compartment models. Incorporating target dynamics into pharmacokinetic models is especially useful for the development of therapeutic antibodies because their effect and pharmacokinetics are inherently interdependent. The approach is illustrated by analysing the F(ab)-mediated inhibitory effect of therapeutic antibodies targeting the epidermal growth factor receptor. We build a multi-level model for anti-EGFR antibodies by combining a systems biology model with in vitro determined parameters and a pharmacokinetic model based on in vivo pharmacokinetic data. Using this model, we investigated in silico the impact of biochemical properties of anti-EGFR antibodies on their F(ab)-mediated inhibitory effect. The multi-level model suggests that the F(ab)-mediated inhibitory effect saturates with increasing drug-receptor affinity, thereby limiting the impact of increasing antibody affinity on improving the effect. This indicates that observed differences in the therapeutic effects of high affinity antibodies in the market and in clinical development may result mainly from Fc-mediated indirect mechanisms such as antibody-dependent cell cytotoxicity