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Full-Text Articles in Chemistry
Applying Bayesian Machine Learning Methods To Theoretical Surface Science, Shane Carr
Applying Bayesian Machine Learning Methods To Theoretical Surface Science, Shane Carr
McKelvey School of Engineering Theses & Dissertations
Machine learning is a rapidly evolving field in computer science with increasingly many applications to other domains. In this thesis, I present a Bayesian machine learning approach to solving a problem in theoretical surface science: calculating the preferred active site on a catalyst surface for a given adsorbate molecule. I formulate the problem as a low-dimensional objective function. I show how the objective function can be approximated into a certain confidence interval using just one iteration of the self-consistent field (SCF) loop in density functional theory (DFT). I then use Bayesian optimization to perform a global search for the solution. …
Simulation In Algorithmic Self-Assembly, Jacob Hendricks
Simulation In Algorithmic Self-Assembly, Jacob Hendricks
Graduate Theses and Dissertations
Winfree introduced a model of self-assembling systems called the abstract Tile Assembly Model (aTAM) where square tiles with glues on their edges attach spontaneously via matching glues to form complex structures. A generalization of the aTAM called the 2HAM (two-handed aTAM) not only allows for single tiles to bind, but also for "supertile" assemblies consisting of any number of tiles to attach. We consider a variety of models based on either the aTAM or the 2HAM. The underlying commonality of the work presented here is simulation. We introduce the polyTAM, where a tile system consists of a collection of polyomino …