Substrate-mediated interactions and intermolecular forces between molecules adsorbed on surfaces

Adsorbate interactions and reactions on metal surfaces have been investigated using scanning tunneling microscopy. The manners in which adsorbates perturb the surface electronic structure in their vicinity are discussed. The effects these perturbations have on other molecules are shown to be important in overlayer growth. Interactions of molecules with surface steps are addressed, and each molecule's electron affinity is shown to dictate its adsorption sites at step edges. Standing waves emanating from steps are demonstrated to effect transient molecular adsorption up to 40 A away from the step edge. Halobenzene derivatives are used to demonstrate how the surface is important in aligning reactive intermediates.     

Adsorption and desorption kinetics of hydrocarbons in FCC catalysts studied using a tapered element oscillating microbalance (TEOM). Part 2: numerical simulations

The factors affecting the adsorption and desorption kinetics in a TEOM are reviewed in detail with particular attention given to the assumptions required to obtain physical transport parameters from the data. Two models are presented to simulate TEOM adsorption data in the case that concentration differences down the catalyst bed can be neglected, as is appropriate when the amount of catalyst used is small, the carrier gas flowrate is large, and/or the adsorbate partial pressure is low. In the first model, the effective diffusion coefficient, D_e, is taken to be constant. In the second model, the effective diffusion coefficient is assumed to obey the Darken equation, D_e=D₀/(1−θ). The TEOM results obtained on n-hexane, n heptane, n-octane, toluene and p-xylene on a commercial FCC catalyst and on pure rare-earth exchanged zeolite Y under non-reacting conditions (373-) are analysed in detail. It is found that intracrystalline diffusion is not the limiting factor affecting the overall rates of adsorption and desorption for the systems studied. Instead, it is the transport of molecules between the adsorbed and vapour phases at the edge of zeolite crystallites that is the limiting transport step affecting the overall kinetics. For the FCC catalyst, the limiting step is the transport of molecules at the zeolite-matrix interface rather than, say, the matrix-vapour interface. Local rate constants for the desorption of the hydrocarbons at the rate-controlling interface have been obtained.     

Development of optical anisotropy in vitrains during carbonization

The purpose of this work was to examine the possible significance in the formation of metallurgical coke of the anisotropic spherical mesophase exemplified by that found during the carbonization of pitch-like materials, and to ascertain if the various types of optical anisotropy found in coke could form a basis for the characterization of cokes produced from different coals. Vitrains from a wide range of coals were carbonized at temperatures from 370 to 1000 °C and the types and amounts of optical anisotropy in the resulting semi-cokes and cokes were determined from microscopic examination, the anisotropic components being classified according to grain size of the granular mosaics and appearance. The anisotropy developed directly from the isotropic phase, appearing initially as a fine-grained mosaic. With increasing carbonization temperature, this fine-grained mosaic was transformed into progressively coarser-grained anisotropy, the extent of this transformation depending on the rank of the vitrain. It is therefore concluded that the formation, growth and coalescence of anisotropic spherical bodies, such as occurs during the carbonization of pitch, is not a necessary precursor of the mosaic anisotropy in coke. The type and amount of anisotropy developed provide a quantitative means of characterising different cokes.     

A rapid computational filter for predicting the rate of human renal clearance

In silico models that predict the rate of human renal clearance for a diverse set of drugs, that exhibit both active secretion and net re-absorption, have been produced using three statistical approaches. Partial Least Squares (PLS) and Random Forests (RF) have been used to produce continuous models whereas Classification And Regression Trees (CART) has only been used for a classification model. The best models generated from either PLS or RF produce significant models that can predict acids/zwitterions, bases and neutrals with approximate average fold errors of 3, 3 and 4, respectively, for an independent test set that covers oral drug-like property space. These models contain additional information on top of any influence arising from plasma protein binding on the rate of renal clearance. Classification And Regression Trees (CART) has been used to generate a classification tree leading to a simple set of Renal Clearance Rules (RCR) that can be applied to man. The rules are influenced by lipophilicity and ion class and can correctly predict 60% of an independent test set. These percentages increase to 71% and 79% for drugs with renal clearances of < 0.1 ml/min/kg and > 1 ml/min/kg, respectively. As far as the authors are aware these are the first set of models to appear in the literature that predict the rate of human renal clearance and can be used to manipulate molecular properties leading to new drugs that are less likely to fail due to renal clearance.     

Towards automated traceability maintenance

Traceability relations support stakeholders in understanding the dependencies between artifacts created during the development of a software system and thus enable many development-related tasks. To ensure that the anticipated benefits of these tasks can be realized, it is necessary to have an up-to-date set of traceability relations between the established artifacts. This goal requires the creation of traceability relations during the initial development process. Furthermore, the goal also requires the maintenance of traceability relations over time as the software system evolves in order to prevent their decay. In this paper, an approach is discussed that supports the (semi-) automated update of traceability relations between requirements, analysis and design models of software systems expressed in the UML. This is made possible by analyzing change events that have been captured while working within a third-party UML modeling tool. Within the captured flow of events, development activities comprised of several events are recognized. These are matched with predefined rules that direct the update of impacted traceability relations. The overall approach is supported by a prototype tool and empirical results on the effectiveness of tool-supported traceability maintenance are provided.     

A Neuro-fuzzy Coding for Processing Incomplete Data: Application to the Classification of Seismic Events

This letter presents a method for modelling and processing incomplete data in connectionist systems. The approach consists in applying a neuro-fuzzy coding to the input data of a neural network. After an introduction to the different kinds of imperfections, we propose a neuro-fuzzy coding in order to take incomplete data into account. We show the efficiency of this coding on the problem of the classification of seismic events. The results show that a neuro-fuzzy coding of the inputs of a neural network increases the performance and classifies incomplete data with little affect on the results.