ETH Zurich

About: ETH Zurich is a education organization based out in Zurich, Switzerland. It is known for research contribution in the topics: Population & Computer science. The organization has 48393 authors who have published 122408 publications receiving 5111383 citations. The organization is also known as: Swiss Federal Institute of Technology in Zurich & Eidgenössische Technische Hochschule Zürich.

Atomically precise bottom-up fabrication of graphene nanoribbons

Abstract: Graphene nanoribbons, narrow straight-edged strips of the single-atom-thick sheet form of carbon, are predicted to exhibit remarkable properties, making them suitable for future electronic applications. Before this potential can be realized, more chemically precise methods of production will be required. Cai et al. report a step towards that goal with the development of a bottom-up fabrication method that produces atomically precise graphene nanoribbons of different topologies and widths. The process involves the deposition of precursor monomers with structures that 'encode' the topology and width of the desired ribbon end-product onto a metal surface. Surface-assisted coupling of the precursors into linear polyphenylenes is then followed by cyclodehydrogenation. Given the method's versatility and precision, it could even provide a route to more unusual graphene nanoribbon structures with tuned chemical and electronic properties. Graphene nanoribbons (GNRs) have structure-dependent electronic properties that make them attractive for the fabrication of nanoscale electronic devices, but exploiting this potential has been hindered by the lack of precise production methods. Here the authors demonstrate how to reliably produce different GNRs, using precursor monomers that encode the structure of the targeted nanoribbon and are converted into GNRs by means of surface-assisted coupling. Graphene nanoribbons—narrow and straight-edged stripes of graphene, or single-layer graphite—are predicted to exhibit electronic properties that make them attractive for the fabrication of nanoscale electronic devices1,2,3. In particular, although the two-dimensional parent material graphene4,5 exhibits semimetallic behaviour, quantum confinement and edge effects2,6 should render all graphene nanoribbons with widths smaller than 10 nm semiconducting. But exploring the potential of graphene nanoribbons is hampered by their limited availability: although they have been made using chemical7,8,9, sonochemical10 and lithographic11,12 methods as well as through the unzipping of carbon nanotubes13,14,15,16, the reliable production of graphene nanoribbons smaller than 10 nm with chemical precision remains a significant challenge. Here we report a simple method for the production of atomically precise graphene nanoribbons of different topologies and widths, which uses surface-assisted coupling17,18 of molecular precursors into linear polyphenylenes and their subsequent cyclodehydrogenation19,20. The topology, width and edge periphery of the graphene nanoribbon products are defined by the structure of the precursor monomers, which can be designed to give access to a wide range of different graphene nanoribbons. We expect that our bottom-up approach to the atomically precise fabrication of graphene nanoribbons will finally enable detailed experimental investigations of the properties of this exciting class of materials. It should even provide a route to graphene nanoribbon structures with engineered chemical and electronic properties, including the theoretically predicted intraribbon quantum dots21, superlattice structures22 and magnetic devices based on specific graphene nanoribbon edge states3.

On the Separation of Net Ecosystem Exchange into Assimilation and Ecosystem Respiration: Review and Improved Algorithm

Abstract: This paper discusses the advantages and disadvantages of the different methods that separate net ecosystem exchange (NEE) into its major components, gross ecosystem carbon uptake (GEP) and ecosystem respiration (Reco). In particular, we analyse the effect of the extrapolation of night-time values of ecosystem respiration into the daytime; this is usually done with a temperature response function that is derived from long-term data sets. For this analysis, we used 16 one-year-long data sets of carbon dioxide exchange measurements from European and US-American eddy covariance networks. These sites span from the boreal to Mediterranean climates, and include deciduous and evergreen forest, scrubland and crop ecosystems. We show that the temperature sensitivity of Reco, derived from long-term (annual) data sets, does not reflect the short-term temperature sensitivity that is effective when extrapolating from night- to daytime. Specifically, in summer active ecosystems the long

The IntCal20 Northern Hemisphere Radiocarbon Age Calibration Curve (0-55 cal kBP)

Abstract: Radiocarbon (14C) ages cannot provide absolutely dated chronologies for archaeological or paleoenvironmental studies directly but must be converted to calendar age equivalents using a calibration curve compensating for fluctuations in atmospheric 14C concentration. Although calibration curves are constructed from independently dated archives, they invariably require revision as new data become available and our understanding of the Earth system improves. In this volume the international 14C calibration curves for both the Northern and Southern Hemispheres, as well as for the ocean surface layer, have been updated to include a wealth of new data and extended to 55,000 cal BP. Based on tree rings, IntCal20 now extends as a fully atmospheric record to ca. 13,900 cal BP. For the older part of the timescale, IntCal20 comprises statistically integrated evidence from floating tree-ring chronologies, lacustrine and marine sediments, speleothems, and corals. We utilized improved evaluation of the timescales and location variable 14C offsets from the atmosphere (reservoir age, dead carbon fraction) for each dataset. New statistical methods have refined the structure of the calibration curves while maintaining a robust treatment of uncertainties in the 14C ages, the calendar ages and other corrections. The inclusion of modeled marine reservoir ages derived from a three-dimensional ocean circulation model has allowed us to apply more appropriate reservoir corrections to the marine 14C data rather than the previous use of constant regional offsets from the atmosphere. Here we provide an overview of the new and revised datasets and the associated methods used for the construction of the IntCal20 curve and explore potential regional offsets for tree-ring data. We discuss the main differences with respect to the previous calibration curve, IntCal13, and some of the implications for archaeology and geosciences ranging from the recent past to the time of the extinction of the Neanderthals.

Review of Particle Physics

Abstract: This biennial Review summarizes much of particle physics. Using data from previous editions, plus 2158 new measurements from 551 papers, we list, evaluate, and average measured properties of gauge bosons, leptons, quarks, mesons, and baryons. We also summarize searches for hypothetical particles such as Higgs bosons, heavy neutrinos, and supersymmetric particles. All the particle properties and search limits are listed in Summary Tables. We also give numerous tables, figures, formulae, and reviews of topics such as the Standard Model, particle detectors, probability, and statistics. Among the 108 reviews are many that are new or heavily revised including those on neutrino mass, mixing, and oscillations, QCD, top quark, CKM quark-mixing matrix, V-ud & V-us, V-cb & V-ub, fragmentation functions, particle detectors for accelerator and non-accelerator physics, magnetic monopoles, cosmological parameters, and big bang cosmology.

Generalized neural-network representation of high-dimensional potential-energy surfaces.

Abstract: The accurate description of chemical processes often requires the use of computationally demanding methods like density-functional theory (DFT), making long simulations of large systems unfeasible. In this Letter we introduce a new kind of neural-network representation of DFT potential-energy surfaces, which provides the energy and forces as a function of all atomic positions in systems of arbitrary size and is several orders of magnitude faster than DFT. The high accuracy of the method is demonstrated for bulk silicon and compared with empirical potentials and DFT. The method is general and can be applied to all types of periodic and nonperiodic systems.