Elucidating the mechanism and active site of the cyclohexanol dehydrogenation on copper-based catalysts: A density functional theory study

Abstract The dehydrogenation of cyclohexanol to cyclohexanone is very important in the manufacture of nylon. Copper-based catalysts are the most popular catalysts for this reaction, and on these catalysts the reaction mechanism and active site are in debate. In order to elucidate the mechanism and active site of the cyclohexanol dehydrogenation on copper-based catalysts, density functional theory with dispersion corrections were performed on up to six facets of copper in two different oxidation states: monovalent copper and metallic copper. By calculating the surface energies of these facets, Cu(111) and Cu2O(111) were found to be the most stable facets for metallic copper and for monovalent copper, respectively. On these two facets, all the possible elementary steps in the dehydrogenation pathway of cyclohexanol were calculated, including the adsorption, dehydrogenation, hydrogen coupling and desorption. Two different reaction pathways for dehydrogenation were considered on both surfaces. It was revealed that the dehydrogenation mechanisms are different on these two surfaces: on Cu(111) the hydrogen belonging to the hydroxyl is removed first, then the hydrogen belonging to the carbon is subtracted, while on Cu2O(111) the hydrogen belonging to the carbon is removed followed by the subtraction of the hydrogen in the hydroxyl group. Furthermore, by comparing the energy profiles of these two surfaces, Cu2O(111) was found to be more active for cyclohexanol dehydrogenation than Cu(111). In addition, we found that the coordinatively unsaturated copper sites on Cu2O(111) are the reaction sites for all the steps. Therefore, the coordinatively unsaturated copper site on Cu2O(111) is likely to be the active site for cyclohexanol dehydrogenation on the copper-based catalysts.

Finite domination and Novikov rings. Laurent polynomial rings in several variables

We present a homological characterisation of those chain complexes of modules over a Laurent polynomial ring in several indeterminates which are finitely dominated over the ground ring (that is, are a retract up to homotopy of a bounded complex of finitely generated free modules). The main tools, which we develop in the paper, are a non-standard totalisation construction for multi-complexes based on truncated products, and a high-dimensional mapping torus construction employing a theory of cubical diagrams that commute up to specified coherent homotopies.

Context-dependent Combination of Sensor Information in Dempster-Shafer Theory for BDI

There has been much interest in the belief–desire–intention (BDI) agent-based model for developing scalable intelligent systems, e.g. using the AgentSpeak framework. However, reasoning from sensor information in these large-scale systems remains a significant challenge. For example, agents may be faced with information from heterogeneous sources which is uncertain and incomplete, while the sources themselves may be unreliable or conflicting. In order to derive meaningful conclusions, it is important that such information be correctly modelled and combined. In this paper, we choose to model uncertain sensor information in Dempster–Shafer (DS) theory. Unfortunately, as in other uncertainty theories, simple combination strategies in DS theory are often too restrictive (losing valuable information) or too permissive (resulting in ignorance). For this reason, we investigate how a context-dependent strategy originally defined for possibility theory can be adapted to DS theory. In particular, we use the notion of largely partially maximal consistent subsets (LPMCSes) to characterise the context for when to use Dempster’s original rule of combination and for when to resort to an alternative. To guide this process, we identify existing measures of similarity and conflict for finding LPMCSes along with quality of information heuristics to ensure that LPMCSes are formed around high-quality information. We then propose an intelligent sensor model for integrating this information into the AgentSpeak framework which is responsible for applying evidence propagation to construct compatible information, for performing context-dependent combination and for deriving beliefs for revising an agent’s belief base. Finally, we present a power grid scenario inspired by a real-world case study to demonstrate our work.