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Pt-supported catalysts are widely used industrially for hydrogenation reactions. However, the kinetics of hydrogen activation, a critical step for any hydrogenation reaction, is still not well understood on supported Pt surfaces. Recent studies had shown that activity and selectivity vary with Pt nuclearity for the acetylene semihydrogenation reaction, increasing in activity and decreasing in selectivity while increasing the particle size from single atoms (SA) to sub-nanoclusters to nanoparticles (NP), attributing the cause of these differences on activities to the activity of H2 activation in the H/D isotopic exchange reaction. In this work, the kinetics of H2 is studied by performing the H2-D2 isotopic exchange reaction on Pt-supported catalysts with different nuclearity to extract the activation barriers and pre-exponential factors for dissociating adsorption and associative desorption (Eads, Edes, and vads, vdes respectively) from the microkinetic model derived from the Bonhoeffer Farkas mechanism, this to perform a more in-depth analysis regarding the differences in activity when comparing the H2 adsorption energy (Eads+ = Eads-Edes) and frequency factors as a function of nuclearity. Experiments were carried out in a quartz tubular fixed bed reactor coupled with a Mass Spectrometer to analyze the product gas by carrying out both, an integral analysis (from 0 to equilibrium conversion) by performing light-off experiments and differential analysis (low conversions) by performing Arrhenius experiments in the low and high coverage regions.

Most Statistical Process Control (SPC) research has focused on the development of charting techniques for process monitoring. Unfortunately, little attention has been paid to the importance of bringing the process in control automatically via these charting techniques. This thesis shows that by drawing upon concepts from Automatic Process Control (APC), it is possible to devise schemes whereby the process is monitored and automatically controlled via SPC procedures. It is shown that Partial Correlation Analysis (PCorrA) or Principal Component Analysis (PCA) can be used to determine the variables that have to be monitored and manipulated as well as the corresponding control laws. We call this proposed procedure Active SPC and the capabilities of various strategies that arise are demonstrated by application to a simulated reaction process. Reactor product concentration was controlled using different manipulated input configurations e.g. manipulating all input variables, manipulating only two input variables, and manipulating only a single input variable. The last two manipulating schemes consider the cases when all input variables can be measured on-line but not all can be manipulated on-line. Different types of control charts are also tested with the new Active SPC method e.g. Shewhart chart with action limits; Shewhart chart with action and warning limits for individual observations, and lastly the Exponentially Weighted Moving Average control chart. The effects of calculating control limits on-line to accommodate possible changes in process characteristics were also studied. The results indicate that the use of the Exponentially Weighted Moving Average control chart, with limits calculated using Partial Correlations, showed the best promise for further development. It is also shown that this particular combination could provide better performance than the common Proportional Integral (PI) controller when manipulations incur costs.

Actors have become widespread in programming languages and programming frameworks focused on parallel and distributed computing. While actors provide a more disciplined model for concurrency than threads, their interactions, if not constrained, admit nondeterminism. As a consequence, actor programs may exhibit unintended behaviors and are less amenable to rigorous testing. The same problem exists in other dominant concurrency models, such as threads, shared-memory models, publish-subscribe systems, and service-oriented architectures.We propose “reactors,” a new model of computation that combines synchronous-reactive principles with a sophisticated model of time to enable determinism while preserving much of the style and performance of actors. Reactors promote modularity and allow for distributed execution. The relationship that reactors establish between events across timelines allows for: 1. the construction of programs that react predictably to unpredictable external events; 2. the formulation of deadlines that grant control over timing; and 3. the preservation of a deterministic distributed execution semantics under quantifiable assumptions. We bring the deterministic concurrency and time-based semantics of reactors to the world of mainstream programming languages through Lingua Franca (LF), a polyglot coordination language with support (so far) for C, C++, Python, and TypeScript. In LF, program logic is given in one or more of those target languages, enabling developers to use familiar languages and integrate extensive libraries and legacy code. The main contributions of this work consist of a formalization of reactors, the implementation of an efficient runtime system for the execution of reactors, and the design and implementation of LF.