Abstract: The ability of some nanostructured materials to perform as effective heterogeneous catalysts is potentially hindered by the failure of the liquid reactant to effectively wet the solid catalyst surface. In this work, two different chemical reactions, each involving a change of phase from liquid to gas on a solid catalyst surface, are investigated. The first reaction is the catalyzed decomposition of a H2O2 monopropellant within a micro-chemical reactor chamber, decorated with RuO2 nanorods (NRs). The second reaction involves the electrolysis of dilute aqueous solutions of H2SO4 performed with the cathode electrode coated with different densities and sizes of RuO2 NRs. In the catalyzed H2O2 decomposition, the reaction rate is observed to decrease with increasing catalyst surface density because of a failure of the liquid to wet on the catalyst surface. In the electrolysis experiment, however, the reaction rate increased in proportion to the surface density of RuO2 NRs. In this case, the electrical bias applied to drive the electrolysis reaction also causes an electrostatic force of attraction between the fluid and the NR coated surface, and thus assures effective wetting.
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.
Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.
Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.
Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).