Materials and interfaces for electrocatalytic hydrogen production and utilization.

Mass industrialization over the last few centuries has created a global economy which is dependent upon fossil fuels to satisfy an exponentially increasing demand for energy. Aside from the possible depletion of this finite resource, the combustion of fossil fuels releases greenhouse gases into the atmosphere which cause the global temperature to rise – a phenomenon which has already begun to create geologic and geopolitical instability and shows no signs of abatement. One proposed method to rid humanity of its dependence on fossil fuels is to use green hydrogen as an energy carrier. In this scheme, excess electricity from a robust renewable energy generation infrastructure is diverted to grid-scale electrolyzers which split water into hydrogen and oxygen. The hydrogen is in turn distributed via supply chain to end users who employ fuel cells to locally convert the energy stored in the chemical bond of hydrogen into electricity on-demand. This vision for an alternative global energy economy has been inhibited by several factors including the low utilization of renewable energy generating technologies, the considerable cost of precious metals required for electrolyzer electrodes, and the relatively low efficiency of the cathodic fuel cell reaction. This vi dissertation is a compilation of experimental work related to the development of materials and interfaces for enhanced electrocatalytic hydrogen evolution using non-precious materials and hydrogen utilization in highly-efficient proton exchange membrane fuel cells. Chapter 1 begins with an overview of the global energy diet and the problem of climate change followed by a discussion of renewable energy technologies, ending with a proposal of how the large-scale implementation of green hydrogen technologies may fit into the futuristic energy landscape. Chapter 2 presents a brief review of the mechanism of hydrogen evolution electrocatalysis including its thermodynamic, kinetic, and mass transport limitations. In Chapter 3, we demonstrate a simple and scalable fabrication process for highly-active non-precious molybdenum sulfide electrolyzer cathodes. Molybdenum sulfide and other transition metal dichalcogenides have received considerable attention in recent years as electrolyzer catalysts due to their environmental benignity, high stability, good catalytic activity, and low cost. Aside from the issue of low efficiency, industrial implementation of most reported molybdenum sulfide fabrication procedures is complicated by extreme and/or lengthy processing conditions. Our process is roll-to-roll amenable and produces a catalyst film in milliseconds without the use of harsh processing conditions or excessive chemicals. Ex-situ characterization of the resulting electrode confirms transformation of the precursor to molybdenum sulfide and reveals a hydrogen evolution reaction overpotential of 200 mV at 10 mA cm-2 which is comparable to that of other reported highly-active molybdenum sulfide catalysts. Chapter 4 deals with the development and ex-situ characterization of a novel non-precious electrocatalyst platform for hydrogen evolution based upon a nickel-centered thiosemicarbazone molecular framework. The enzyme hydrogenase, found in most forms of life, has served as a source of inspiration for researchers due to its ability to reversibly catalyze hydrogen evolution efficiently. However, efforts to translate the activity of the hydrogenase active site to an electrode have been limited in their success. We report a class of molecular catalysts inspired by previous work on hydrogenase active site analogues. Successful translation and retention of the catalyst to the electrode surface is confirmed, and ex-situ testing reveals a hydrogen evolution reaction overpotential of 450 mV at 10 mA cm-2 with remarkable stability – a promising milestone which lays the foundation for further development of this class of materials. Beginning in Chapter 5, the focus of the dissertation is shifted away from materials for hydrogen evolution and toward the development of highly-efficient proton exchange membrane fuel cell devices. Chapter 5 details the interplay between chemical transport, catalytic kinetics, thermodynamic considerations, and Ohmic losses which influence fuel cell efficiency. In Chapter 6, we introduce a structured proton exchange membrane fuel cell cathode which utilizes an array of bulk-like ionomer channels to improve the interface between the catalyst layer and membrane. The channels serve as conduits for rapid proton transport, dramatically decreasing the cathode sheet resistance and enabling a reduction in electrode ionomer content which attenuates active site inhibition from sulfonate adsorption. Using this approach, the mass activity of Vulcan carbon-based Pt viii catalyst is improved by up to 80 %, and the power density is improved by up to hundreds of mW cm-2 at benchmark cell potentials – particularly under arid conditions. Further performance gains may be realized by tuning the electrode geometry and/or applying this technology to other catalyst types including those based upon high-surface-area carbon. The results described in this dissertation 1) advance the understanding of materials and fabrication processes for hydrogen evolution electrodes and 2) provide a simple tool for mitigating chemical transport and catalyst poisoning limitations in the proton exchange membrane fuel cell cathode

Wallerian-like axonal degeneration in the optic nerve after excitotoxic retinal insult: an ultrastructural study

BACKGROUND: Excitotoxicity is involved in the pathogenesis of a number neurodegenerative diseases, and axonopathy is an early feature in several of these disorders. In models of excitotoxicity-associated neurological disease, an excitotoxin delivered to the central nervous system (CNS), could trigger neuronal death not only in the somatodendritic region, but also in the axonal region, via oligodendrocyte N-methyl-D-aspartate (NMDA) receptors. The retina and optic nerve, as approachable regions of the brain, provide a unique anatomical substrate to investigate the “downstream” effect of isolated excitotoxic perikaryal injury on central nervous system (CNS) axons, potentially providing information about the pathogenesis of the axonopathy in clinical neurological disorders. Herein, we provide ultrastructural information about the retinal ganglion cell (RGC) somata and their axons, both unmyelinated and myelinated, after NMDA-induced retinal injury. Male Sprague-Dawley rats were killed at 0 h, 24 h, 72 h and 7 days after injecting 20 nM NMDA into the vitreous chamber of the left eye (n = 8 in each group). Saline-injected right eyes served as controls. After perfusion fixation, dissection, resin-embedding and staining, ultrathin sections of eyes and proximal (intraorbital) and distal (intracranial) optic nerve segments were evaluated by transmission electron tomography (TEM). RESULTS: TEM demonstrated features of necrosis in RGCs: mitochondrial and endoplasmic reticulum swelling, disintegration of polyribosomes, rupture of membranous organelle and formation of myelin bodies. Ultrastructural damage in the optic nerve mimicked the changes of Wallerian degeneration; early nodal/paranodal disturbances were followed by the appearance of three major morphological variants: dark degeneration, watery degeneration and demyelination. CONCLUSION: NMDA-induced excitotoxic retinal injury causes mainly necrotic RGC somal death with Wallerian-like degeneration of the optic nerve. Since axonal degeneration associated with perikaryal excitotoxic injury is an active, regulated process, it may be amenable to therapeutic intervention.Sarabjit K. Saggu, Hiren P. Chotaliya, Peter C. Blumbergs and Robert J. Casso

Strategy Logic with Imperfect Information

We introduce an extension of Strategy Logic for the imperfect-information setting, called SLii, and study its model-checking problem. As this logic naturally captures multi-player games with imperfect information, the problem turns out to be undecidable. We introduce a syntactical class of "hierarchical instances" for which, intuitively, as one goes down the syntactic tree of the formula, strategy quantifications are concerned with finer observations of the model. We prove that model-checking SLii restricted to hierarchical instances is decidable. This result, because it allows for complex patterns of existential and universal quantification on strategies, greatly generalises previous ones, such as decidability of multi-player games with imperfect information and hierarchical observations, and decidability of distributed synthesis for hierarchical systems. To establish the decidability result, we introduce and study QCTL*ii, an extension of QCTL* (itself an extension of CTL* with second-order quantification over atomic propositions) by parameterising its quantifiers with observations. The simple syntax of QCTL* ii allows us to provide a conceptually neat reduction of SLii to QCTL*ii that separates concerns, allowing one to forget about strategies and players and focus solely on second-order quantification. While the model-checking problem of QCTL*ii is, in general, undecidable, we identify a syntactic fragment of hierarchical formulas and prove, using an automata-theoretic approach, that it is decidable. The decidability result for SLii follows since the reduction maps hierarchical instances of SLii to hierarchical formulas of QCTL*ii

Type-specific dendritic integration in mouse retinal ganglion cells

Neural computation relies on the integration of synaptic inputs across a neuron’s dendritic arbour. However, it is far from understood how different cell types tune this process to establish cell-type specific computations. Here, using two-photon imaging of dendritic Ca2+ signals, electrical recordings of somatic voltage and biophysical modelling, we demonstrate that four morphologically distinct types of mouse retinal ganglion cells with overlapping excitatory synaptic input (transient Off alpha, transient Off mini, sustained Off, and F-mini Off) exhibit type-specific dendritic integration profiles: in contrast to the other types, dendrites of transient Off alpha cells were spatially independent, with little receptive field overlap. The temporal correlation of dendritic signals varied also extensively, with the highest and lowest correlation in transient Off mini and transient Off alpha cells, respectively. We show that differences between cell types can likely be explained by differences in backpropagation efficiency, arising from the specific combinations of dendritic morphology and ion channel densities

The influence of long-term exposure to dialect variation on representation specificity and word learning in toddlers.

Until very recently language development research classified the language learner as belonging to one of two discrete groups – monolingual or bilingual. This thesis explores the hypothesis that this is an insufficient description of language input and that there are sub-groups within the monolingual category based on the phonological variability of their exposure that could be considered akin to that of bilingual toddlers. For some monolingual toddlers, classified as monodialectal, their language exposure is generally consistent, because both of their parents speak the dialect of the local area. Yet for other toddlers, classified as multidialectal, the language environment is more variable, because at least one of their parents speaks with a dialect that differs from the local area. It is considered that by testing this group of multidialectal toddlers it will be possible to explore the effect of variability on language development and how increased variability in the bilingual linguistic environment might be influencing aspects of language development. This thesis approaches the influence of variability from three areas of interest: phonetic specificity of familiar words using a mispronunciation paradigm (Experiments 1 and 2), target recognition of naturally occurring pronunciation alternatives (Experiments 3 and 4) and use of the Mutual Exclusivity strategy in novel word learning (Experiment 5). Results show that there are differences between the two dialect groups (monodialectal and multidialectal) in a mispronunciation detection task but that toddlers perform similarly with naturally occurring pronunciation alternatives and in their application of the Mutual Exclusivity strategy. This programme of work highlights that there is an influence of linguistic variability on aspects of language development, justifying the parallel between bilingualism and multidialectalism

The Lagrangian-space Effective Field Theory of Large Scale Structures

We introduce a Lagrangian-space Effective Field Theory (LEFT) formalism for the study of cosmological large scale structures. Unlike the previous Eulerian-space construction, it is naturally formulated as an effective field theory of extended objects in Lagrangian space. In LEFT the resulting finite size effects are described using a multipole expansion parameterized by a set of time dependent coefficients and organized in powers of the ratio of the wavenumber of interest $k$ over the non-linear scale $k_{\rm NL}$. The multipoles encode the effects of the short distance modes on the long-wavelength universe and absorb UV divergences when present. There are no IR divergences in LEFT. Some of the parameters that control the perturbative approach are not assumed to be small and can be automatically resummed. We present an illustrative one-loop calculation for a power law universe. We describe the dynamics both at the level of the equations of motion and through an action formalism.Comment: 38+13 pages. 3 figures. Minor changes. Version to appear in JCA

Review of feature selection techniques in Parkinson's disease using OCT-imaging data

Several spectral-domain optical coherence tomography studies (OCT) reported a decrease on the macular region of the retina in Parkinson’s disease. Yet, the implication of retinal thinning with visual disability is still unclear. Macular scans acquired from patients with Parkinson’s disease (n = 100) and a control group (n = 248) were used to train several supervised classification models. The goal was to determine the most relevant retinal layers and regions for diagnosis, for which univari- ate and multivariate filter and wrapper feature selection methods were used. In addition, we evaluated the classification ability of the patient group to assess the applicability of OCT measurements as a biomarker of the disease