The surface science of quasicrystals

The surfaces of quasicrystals have been extensively studied since about 1990. In this paper we review work on the structure and morphology of clean surfaces, and their electronic and phonon structure. We also describe progress in adsorption and epitaxy studies. The paper is illustrated throughout with examples from the literature. We offer some reflections on the wider impact of this body of work and anticipate areas for future development. (Some figures in this article are in colour only in the electronic version

Ortholog identification in the presence of domain architecture rearrangement

Ortholog identification is used in gene functional annotation, species phylogeny estimation, phylogenetic profile construction and many other analyses. Bioinformatics methods for ortholog identification are commonly based on pairwise protein sequence comparisons between whole genomes. Phylogenetic methods of ortholog identification have also been developed; these methods can be applied to protein data sets sharing a common domain architecture or which share a single functional domain but differ outside this region of homology. While promiscuous domains represent a challenge to all orthology prediction methods, overall structural similarity is highly correlated with proximity in a phylogenetic tree, conferring a degree of robustness to phylogenetic methods. In this article, we review the issues involved in orthology prediction when data sets include sequences with structurally heterogeneous domain architectures, with particular attention to automated methods designed for high-throughput application, and present a case study to illustrate the challenges in this area

CVD-Enabled Graphene Manufacture and Technology.

Integrated manufacturing is arguably the most challenging task in the development of technology based on graphene and other 2D materials, particularly with regard to the industrial demand for “electronic-grade” large-area films. In order to control the structure and properties of these materials at the monolayer level, their nucleation, growth and interfacing needs to be understood to a level of unprecedented detail compared to existing thin film or bulk materials. Chemical vapor deposition (CVD) has emerged as the most versatile and promising technique to develop graphene and 2D material films into industrial device materials and this Perspective outlines recent progress, trends, and emerging CVD processing pathways. A key focus is the emerging understanding of the underlying growth mechanisms, in particular on the role of the required catalytic growth substrate, which brings together the latest progress in the fields of heterogeneous catalysis and classic crystal/thin-film growth.Funding from the ERC (Grant No. 279342, InSituNANO) and EPSRC (Grant No. EP/K016636/1, GRAPHTED) is acknowledged. R.S.W. acknowledges a research fellowship from St. John’s College, Cambridge.This is the final version of the article. It first appeared from ACS via http://dx.doi.org/10.1021/acs.jpclett.5b0105

Objective sequence-based subfamily classifications of mouse homeodomains reflect their in vitro DNA-binding preferences

Classifying proteins into subgroups with similar molecular function on the basis of sequence is an important step in deriving reliable functional annotations computationally. So far, however, available classification procedures have been evaluated against protein subgroups that are defined by experts using mainly qualitative descriptions of molecular function. Recently, in vitro DNA-binding preferences to all possible 8-nt DNA sequences have been measured for 178 mouse homeodomains using protein-binding microarrays, offering the unprecedented opportunity of evaluating the classification methods against quantitative measures of molecular function. To this end, we automatically derive homeodomain subtypes from the DNA-binding data and independently group the same domains using sequence information alone. We test five sequence-based methods, which use different sequence-similarity measures and algorithms to group sequences. Results show that methods that optimize the classification robustness reflect well the detailed functional specificity revealed by the experimental data. In some of these classifications, 73–83% of the subfamilies exactly correspond to, or are completely contained in, the function-based subtypes. Our findings demonstrate that certain sequence-based classifications are capable of yielding very specific molecular function annotations. The availability of quantitative descriptions of molecular function, such as DNA-binding data, will be a key factor in exploiting this potential in the future.Canadian Institutes of Health Research (MOP#82940)Sickkids FoundationOntario Research FundNational Science Foundation (U.S.)National Human Genome Research Institute (U.S.) (R01 HG003985

In situ observations of the atomistic mechanisms of Ni catalyzed low temperature graphene growth.

The key atomistic mechanisms of graphene formation on Ni for technologically relevant hydrocarbon exposures below 600 °C are directly revealed via complementary in situ scanning tunneling microscopy and X-ray photoelectron spectroscopy. For clean Ni(111) below 500 °C, two different surface carbide (Ni2C) conversion mechanisms are dominant which both yield epitaxial graphene, whereas above 500 °C, graphene predominantly grows directly on Ni(111) via replacement mechanisms leading to embedded epitaxial and/or rotated graphene domains. Upon cooling, additional carbon structures form exclusively underneath rotated graphene domains. The dominant graphene growth mechanism also critically depends on the near-surface carbon concentration and hence is intimately linked to the full history of the catalyst and all possible sources of contamination. The detailed XPS fingerprinting of these processes allows a direct link to high pressure XPS measurements of a wide range of growth conditions, including polycrystalline Ni catalysts and recipes commonly used in industrial reactors for graphene and carbon nanotube CVD. This enables an unambiguous and consistent interpretation of prior literature and an assessment of how the quality/structure of as-grown carbon nanostructures relates to the growth modes.L.L.P. acknowledges funding from Area di Ricerca Scientifica e Tecnologica of Trieste and from MIUR through Progetto Strategico NFFA. C.A. acknowledges support from CNR through the ESF FANAS project NOMCIS. C.A. and C.C. acknowledge financial support from MIUR (PRIN 2010-2011 nº 2010N3T9M4). S.B. acknowledges funding from ICTP TRIL program. S.H. acknowledges funding from ERC grant InsituNANO (n°279342). R.S.W. acknowledges funding from EPSRC (Doctoral training award), and the Nano Science & Technology Doctoral Training Centre Cambridge (NanoDTC). The help of C. Dri and F. Esch (design) and P. Bertoch and F. Salvador (manufacturing) in the realization of the high temperature STM sample holder is gratefully acknowledged. We acknowledge the Helmholtz-Zentrum-Berlin Electron storage ring BESSY II for provision of synchrotron radiation at the ISISS beamline and we thank the BESSY staff for continuous support of our experiments.This is the accepted manuscript. The final version is available from ACS at http://pubs.acs.org/doi/abs/10.1021/nn402927q

Interdependency of subsurface carbon distribution and graphene-catalyst interaction.

The dynamics of the graphene-catalyst interaction during chemical vapor deposition are investigated using in situ, time- and depth-resolved X-ray photoelectron spectroscopy, and complementary grand canonical Monte Carlo simulations coupled to a tight-binding model. We thereby reveal the interdependency of the distribution of carbon close to the catalyst surface and the strength of the graphene-catalyst interaction. The strong interaction of epitaxial graphene with Ni(111) causes a depletion of dissolved carbon close to the catalyst surface, which prevents additional layer formation leading to a self-limiting graphene growth behavior for low exposure pressures (10(-6)-10(-3) mbar). A further hydrocarbon pressure increase (to ∼10(-1) mbar) leads to weakening of the graphene-Ni(111) interaction accompanied by additional graphene layer formation, mediated by an increased concentration of near-surface dissolved carbon. We show that growth of more weakly adhered, rotated graphene on Ni(111) is linked to an initially higher level of near-surface carbon compared to the case of epitaxial graphene growth. The key implications of these results for graphene growth control and their relevance to carbon nanotube growth are highlighted in the context of existing literature.R.S.W. acknowledges a Research Fellowship from St. John’s College, Cambridge. S.H. acknowledges funding from ERC grant InsituNANO (No. 279342) and EPSRC under grant GRAPHTED (Ref. EP/K016636/1). We acknowledge the Helmholtz-Zentrum-Berlin Electron storage ring BESSY II for provision of synchrotron radiation at the ISISS beamline and we thank the BESSY staff for continuous support of our experiments. This research was partially supported by the EU FP7 Work Programme under grant Graphene Flagship (No. 604391). PRK acknowledges funding the Cambridge Commonwealth Trust. H.A. and C.B. acknowledge J.-Y. Raty and B. Legrand for fruitful discussions.This is the final published version. It's also available from ACS at http://pubs.acs.org/doi/abs/10.1021/ja505454v

Adaptive tuning functions arise from visual observation of past movement

Visual observation of movement plays a key role in action. For example, tennis players have little time to react to the ball, but still need to prepare the appropriate stroke. Therefore, it might be useful to use visual information about the ball trajectory to recall a specific motor memory. Past visual observation of movement (as well as passive and active arm movement) affects the learning and recall of motor memories. Moreover, when passive or active, these past contextual movements exhibit generalization (or tuning) across movement directions. Here we extend this work, examining whether visual motion also exhibits similar generalization across movement directions and whether such generalization functions can explain patterns of interference. Both the adaptation movement and contextual movement exhibited generalization beyond the training direction, with the visual contextual motion exhibiting much broader tuning. A second experiment demonstrated that this pattern was consistent with the results of an interference experiment where opposing force fields were associated with two separate visual movements. Overall, our study shows that visual contextual motion exhibits much broader (and shallower) tuning functions than previously seen for either passive or active movements, demonstrating that the tuning characteristics of past motion are highly dependent on their sensory modality

Generation of subnanometric platinum with high stability during transformation of a 2D zeolite into 3D

[EN] Single metal atoms and metal clusters have attracted much attention thanks to their advantageous capabilities as heterogeneous catalysts. However, the generation of stable single atoms and clusters on a solid support is still challenging. Herein, we report a new strategy for the generation of single Pt atoms and Pt clusters with exceptionally high thermal stability, formed within purely siliceous MCM-22 during the growth of a two-dimensional zeolite into three dimensions. These subnanometric Pt species are stabilized by MCM-22, even after treatment in air up to 540 degrees C. Furthermore, these stable Pt species confined within internal framework cavities show size-selective catalysis for the hydrogenation of alkenes. High-temperature oxidation-reduction treatments result in the growth of encapsulated Pt species to small nanoparticles in the approximate size range of 1 to 2 nm. The stability and catalytic activity of encapsulated Pt species is also reflected in the dehydrogenation of propane to propylene.This work was funded by the Spanish Government (Consolider Ingenio 2010-MULTICAT (CSD2009-00050) and MAT2014-52085-C2-1-P) and by the Generalitat Valenciana (Prometeo). The Severo Ochoa Program (SEV-2012-0267) is gratefully acknowledged. L.L. thanks ITQ for a contract. The authors also thank the Microscopy Service of UPV for the TEM and STEM measurements. The HAADF-HRSTEM works were conducted in the Laboratorio de Microscopias Avanzadas (LMA) at the Instituto de Nanociencia de Aragon (INA)-Universidad de Zaragoza (Spain), a Spanish ICTS National Facility. Some of the research leading to these results has received funding from the European Union Seventh Framework Program under Grant Agreement 312483-ESTEEM2 (Integrated Infrastructure Initiative-I3). R.A. also acknowledges funding from the Spanish Ministerio de Economia y Competitividad (FIS2013-46159-C3-3-P) and the European Union Horizon 2020 research and innovation programme under the Marie Sldodowska-Curie grant agreement No. 642742.Liu, L.; Díaz Morales, UM.; Arenal, R.; Agostini, G.; Concepción Heydorn, P.; Corma Canós, A. (2017). Generation of subnanometric platinum with high stability during transformation of a 2D zeolite into 3D. Nature Materials. 16(1):132-138. https://doi.org/10.1038/NMAT4757S132138161Boronat, M., Leyva-Perez, A. & Corma, A. Theoretical and experimental insights into the origin of the catalytic activity of subnanometric gold clusters: attempts to predict reactivity with clusters and nanoparticles of gold. Acc. Chem. Res. 47, 834–844 (2014).Flytzani-Stephanopoulos, M. & Gates, B. C. Atomically dispersed supported metal catalysts. Ann. Rev. Chem. Bio. Eng. 3, 545–574 (2012).Gates, B. C. Supported metal clusters: synthesis, structure, and catalysis. Chem. 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Testing the Ortholog Conjecture with Comparative Functional Genomic Data from Mammals

A common assumption in comparative genomics is that orthologous genes share greater functional similarity than do paralogous genes (the “ortholog conjecture”). Many methods used to computationally predict protein function are based on this assumption, even though it is largely untested. Here we present the first large-scale test of the ortholog conjecture using comparative functional genomic data from human and mouse. We use the experimentally derived functions of more than 8,900 genes, as well as an independent microarray dataset, to directly assess our ability to predict function using both orthologs and paralogs. Both datasets show that paralogs are often a much better predictor of function than are orthologs, even at lower sequence identities. Among paralogs, those found within the same species are consistently more functionally similar than those found in a different species. We also find that paralogous pairs residing on the same chromosome are more functionally similar than those on different chromosomes, perhaps due to higher levels of interlocus gene conversion between these pairs. In addition to offering implications for the computational prediction of protein function, our results shed light on the relationship between sequence divergence and functional divergence. We conclude that the most important factor in the evolution of function is not amino acid sequence, but rather the cellular context in which proteins act