Cluster Superlattices on Hexagonal Boron Nitride and Graphene/Ir(111) and Their Embedding with Carbon

Cluster and nanoparticle research is at the forefront of nanotechnology owing to the exceptional physicochemical properties of individual nanoparticles which greatly differ from their bulk counterparts. The preparation of similar sized and well ordered clusters is a challenging task. A remarkable method to fabricate dense, two-dimensional arrays of clusters with a narrow size distribution is ultra-high vacuum growth on surface templates. Such templated cluster superlattices have been successful as model systems for heterogeneous catalysis, magnetism, optics, and electronics, as they allow the study of cluster properties with conventional surface science techniques. Their periodic arrangement allows the application of both local probes and integrating methods. Wide-spread application of supported cluster superlattices is inherently hampered by their tendency to degrade under reaction conditions, i.e. atmospheric pressure and/or temperatures of a few hundred degrees Celsius. Under these circumstances, they lose their advantageous periodic arrangement, narrow size distribution and homogeneous environment, and in some cases even the cluster structure may be altered or destroyed. One way of approaching this issue is to curb the decay of cluster superlattices, another is the exploration of new substrates for templated cluster growth that provide enhanced stability. Single-layer hexagonal boron nitride on Ir(111) is a new template for the growth of highly stable cluster superlattices. We demonstrate, that it enables the synthesis of highly ordered Ir, Pt, Au, and C cluster superlattices. Characterization with scanning tunneling microscopy reveals high superlattice densities and an unparalleled thermal stability. The results are corroborated by x-ray photoemission spectroscopy and density functional theory calculations, which unravel the binding mechanism of the clusters to the substrate. Furthermore, we explore carbon embedding of cluster superlattices in ultra-high vacuum as a method to suppress sintering of cluster superlattices. Carbon embedding is also an integral step in the formation of a novel free-standing material containing a cluster superlattice sandwiched between a two-dimensional material and a thin matrix of amorphous carbon. The thesis comprises three manuscripts in their entirety, a comprehensive overview of the relevant scientific background, and a detailed discussion of each chapter together with an outlook. In the first manuscript, we introduce a monolayer of hexagonal boron nitride on Ir(111) as a template for the growth of periodic arrays of clusters. We demonstrate the templating capabilities for Ir, Au and C clusters. In an exemplary case study on Ir clusters, we examine the cluster binding site and epitaxial growth, and compare scanning tunneling microscopy results to ab initio density functional theory calculations. Ir clusters grow epitaxially in the valley regions of the moiré. By varying the Ir deposition, the average cluster size of the arrays can be tuned. Moreover, we find that the thermal stability of the cluster superlattices on h-BN/Ir(111) is exceptional and exceeds all other known substrates for templated growth. The excellent stability is explained by selective rehybridization of the h-BN underneath the clusters with bond formation between B and Ir cluster atoms. In the second experimental chapter, we expand the range of cluster materials forming superlattices on hexagonal boron nitride on Ir(111) to Pt. We elucidate the growth and structure of the Pt clusters by means of x-ray photoemission spectroscopy and scanning tunneling microscopy. The XPS results provide direct evidence of the binding mechanism by rehybridization and confirms the calculated results obtained for Ir clusters on hexagonal boron nitride on Ir(111). We analyze the thermal stability of Pt clusters and observe cluster superlattice degradation via Smoluchowski ripening and intercalation below the h-BN above 650 K. Notably, one- and three-layer clusters are favored during growth of Pt clusters on hexagonal boron nitride on Ir(111). Moreover, mild heating to 730 K induces a shape transformation from one- to three-layer clusters for the case of an average cluster size of 63 atoms, indicating two-layer Pt clusters to be metastable. Scanning tunneling spectroscopy reveals the electronic decoupling of the Pt clusters from the substrate, which gives rise to Coulomb blockade effects. Third, we demonstrate the embedding of Ir cluster superlattices on graphene on Ir(111) with elemental carbon. Embedded clusters have a dramatically increased thermal stability against coalescence compared to bare clusters, as evidenced by scanning tunneling microscopy. Moreover, in controlled cluster pick-up experiments with the tip of the scanning tunneling microscope, we show the improved mechanical stability of embedded clusters. We demonstrate that the deposited carbon adheres first to the clusters, leading to conformal embedding without impeding the structural perfectness of the cluster superlattice. Scanning tunneling spectroscopy reveals that the only path left for cluster degradation is via intercalation below the Gr layer at temperatures above 850 K. This embedding method constitutes a crucial step in the fabrication of a novel material, consisting of a cluster superlattice sandwiched between a 2D material and an embedding matrix of carbon. The scientific appendix provides additional data on the interaction of further materials with graphene and hexagonal boron nitride on Ir(111). We explore low temperature deposition as a method to create perfect arrays of Au and Fe clusters on hexagonal boron nitride on Ir(111). Furthermore, we investigate Mo, Ta, Nb, Dy, and Tm deposition on graphene and hexagonal boron nitride on Ir(111) in view of cluster superlattice formation. The interaction of CO with Pt clusters on hexagonal boron nitride on Ir(111) is studied in operando by scanning tunneling microscopy. Shape transformations and sintering of Pt clusters are found to occur upon CO adsorption

Teaching Machines to Read and Comprehend

Teaching machines to read natural language documents remains an elusive challenge. Machine reading systems can be tested on their ability to answer questions posed on the contents of documents that they have seen, but until now large scale training and test datasets have been missing for this type of evaluation. In this work we define a new methodology that resolves this bottleneck and provides large scale supervised reading comprehension data. This allows us to develop a class of attention based deep neural networks that learn to read real documents and answer complex questions with minimal prior knowledge of language structure.Comment: Appears in: Advances in Neural Information Processing Systems 28 (NIPS 2015). 14 pages, 13 figure

Dead or Alive: Continuous Data Profiling for Interactive Data Science

Profiling data by plotting distributions and analyzing summary statistics is a critical step throughout data analysis. Currently, this process is manual and tedious since analysts must write extra code to examine their data after every transformation. This inefficiency may lead to data scientists profiling their data infrequently, rather than after each transformation, making it easy for them to miss important errors or insights. We propose continuous data profiling as a process that allows analysts to immediately see interactive visual summaries of their data throughout their data analysis to facilitate fast and thorough analysis. Our system, AutoProfiler, presents three ways to support continuous data profiling: it automatically displays data distributions and summary statistics to facilitate data comprehension; it is live, so visualizations are always accessible and update automatically as the data updates; it supports follow up analysis and documentation by authoring code for the user in the notebook. In a user study with 16 participants, we evaluate two versions of our system that integrate different levels of automation: both automatically show data profiles and facilitate code authoring, however, one version updates reactively and the other updates only on demand. We find that both tools facilitate insight discovery with 91% of user-generated insights originating from the tools rather than manual profiling code written by users. Participants found live updates intuitive and felt it helped them verify their transformations while those with on-demand profiles liked the ability to look at past visualizations. We also present a longitudinal case study on how AutoProfiler helped domain scientists find serendipitous insights about their data through automatic, live data profiles. Our results have implications for the design of future tools that offer automated data analysis support.Comment: To appear at IEEE VIS conference 202

The effects of peripheral and central high insulin on brain insulin signaling and amyloid-β in young and old APP/PS1 mice

Hyperinsulinemia is a risk factor for late-onset Alzheimer's disease (AD). In vitro experiments describe potential connections between insulin, insulin signaling, and amyloid-β (Aβ), but in vivo experiments are needed to validate these relationships under physiological conditions. First, we performed hyperinsulinemic-euglycemic clamps with concurrent hippocampal microdialysis in young, awake, behaving APP(swe)/PS1(dE9) transgenic mice. Both a postprandial and supraphysiological insulin clamp significantly increased interstitial fluid (ISF) and plasma Aβ compared with controls. We could detect no increase in brain, ISF, or CSF insulin or brain insulin signaling in response to peripheral hyperinsulinemia, despite detecting increased signaling in the muscle. Next, we delivered insulin directly into the hippocampus of young APP/PS1 mice via reverse microdialysis. Brain tissue insulin and insulin signaling was dose-dependently increased, but ISF Aβ was unchanged by central insulin administration. Finally, to determine whether peripheral and central high insulin has differential effects in the presence of significant amyloid pathology, we repeated these experiments in older APP/PS1 mice with significant amyloid plaque burden. Postprandial insulin clamps increased ISF and plasma Aβ, whereas direct delivery of insulin to the hippocampus significantly increased tissue insulin and insulin signaling, with no effect on Aβ in old mice. These results suggest that the brain is still responsive to insulin in the presence of amyloid pathology but increased insulin signaling does not acutely modulate Aβ in vivo before or after the onset of amyloid pathology. Peripheral hyperinsulinemia modestly increases ISF and plasma Aβ in young and old mice, independent of neuronal insulin signaling. SIGNIFICANCE STATEMENT The transportation of insulin from blood to brain is a saturable process relevant to understanding the link between hyperinsulinemia and AD. In vitro experiments have found direct connections between high insulin and extracellular Aβ, but these mechanisms presume that peripheral high insulin elevates brain insulin significantly. We found that physiological hyperinsulinemia in awake, behaving mice does not increase CNS insulin to an appreciable level yet modestly increases extracellular Aβ. We also found that the brain of aged APP/PS1 mice was not insulin resistant, contrary to the current state of the literature. These results further elucidate the relationship between insulin, the brain, and AD and its conflicting roles as both a risk factor and potential treatment

Primary tumor–derived systemic nANGPTL4 inhibits metastasis

Primary tumors and distant site metastases form a bidirectionally communicating system. Yet, the molecular mechanisms of this crosstalk are poorly understood. Here, we identified the proteolytically cleaved fragments of angiopoietin-like 4 (ANGPTL4) as contextually active protumorigenic and antitumorigenic contributors in this communication ecosystem. Preclinical studies in multiple tumor models revealed that the C-terminal fragment (cANGPTL4) promoted tumor growth and metastasis. In contrast, the N-terminal fragment of ANGPTL4 (nANGPTL4) inhibited metastasis and enhanced overall survival in a postsurgical metastasis model by inhibiting WNT signaling and reducing vascularity at the metastatic site. Tracing ANGPTL4 and its fragments in tumor patients detected full-length ANGPTL4 primarily in tumor tissues, whereas nANGPTL4 predominated in systemic circulation and correlated inversely with disease progression. The study highlights the spatial context of the proteolytic cleavage-dependent pro- and antitumorigenic functions of ANGPTL4 and identifies and validates nANGPTL4 as a novel biomarker of tumor progression and antimetastatic therapeutic agent

Comprehensive DNA barcode coverage of North American birds

DNA barcoding seeks to assemble a standardized reference library for DNA-based identification of eukaryotic species. The utility and limitations of this approach need to be tested on well-characterized taxonomic assemblages. Here we provide a comprehensive DNA barcode analysis for North American birds including 643 species representing 93% of the breeding and pelagic avifauna of the USA and Canada. Most (94%) species possess distinct barcode clusters, with average neighbour-joining bootstrap support of 98%. In the remaining 6%, barcode clusters correspond to small sets of closely related species, most of which hybridize regularly. Fifteen (2%) currently recognized species are comprised of two distinct barcode clusters, many of which may represent cryptic species. Intraspecific variation is weakly related to census population size and species age. This study confirms that DNA barcoding can be effectively applied across the geographical and taxonomic expanse of North American birds. The consistent finding of constrained intraspecific mitochondrial variation in this large assemblage of species supports the emerging view that selective sweeps limit mitochondrial diversity

Gravitational Radiation from Post-Newtonian Sources and Inspiralling Compact Binaries

The article reviews the current status of a theoretical approach to the problem of the emission of gravitational waves by isolated systems in the context of general relativity. Part A of the article deals with general post-Newtonian sources. The exterior field of the source is investigated by means of a combination of analytic post-Minkowskian and multipolar approximations. The physical observables in the far-zone of the source are described by a specific set of radiative multipole moments. By matching the exterior solution to the metric of the post-Newtonian source in the near-zone we obtain the explicit expressions of the source multipole moments. The relationships between the radiative and source moments involve many non-linear multipole interactions, among them those associated with the tails (and tails-of-tails) of gravitational waves. Part B of the article is devoted to the application to compact binary systems. We present the equations of binary motion, and the associated Lagrangian and Hamiltonian, at the third post-Newtonian (3PN) order beyond the Newtonian acceleration. The gravitational-wave energy flux, taking consistently into account the relativistic corrections in the binary moments as well as the various tail effects, is derived through 3.5PN order with respect to the quadrupole formalism. The binary's orbital phase, whose prior knowledge is crucial for searching and analyzing the signals from inspiralling compact binaries, is deduced from an energy balance argument.Comment: 109 pages, 1 figure; this version is an update of the Living Review article originally published in 2002; available on-line at http://www.livingreviews.org

Indirect evaluation of Mars Gravity Model 2011 using a replication experiment on Earth

Curtin University’s Mars Gravity Model 2011 (MGM2011) is a high-resolution composite set of gravity field functionals that uses topography-implied gravity effects at medium- and short-scales (~125 km to ~3 km) to augment the space-collected MRO110B2 gravity model. Ground-truth gravity observations that could be used for direct validation of MGM2011 are not available on Mars’s surface. To indirectly evaluate MGM2011 and its modelling principles, an as-close-as-possible replication of the MGM2011 modelling approach was performed on Earth as the planetary body with most detailed gravity field knowledge available. Comparisons among six ground-truth data sets (gravity disturbances, quasigeoid undulations and vertical deflections) and the MGM2011-replication over Europe and North America show unanimously that topography-implied gravity information improves upon space-collected gravity models over areas with rugged terrain. The improvements are ~55% and ~67% for gravity disturbances, ~12% and ~47% for quasigeoid undulations, and ~30% to ~50% for vertical deflections. Given that the correlation between space-collected gravity and topography is higher for Mars than Earth at spatial scales of a few 100 km, topography-implied gravity effects are more dominant on Mars. It is therefore reasonable to infer that the MGM2011 modelling approach is suitable, offering an improvement over space-collected Martian gravity field models