Ernst Ruska Centre

Plant functional traits are the features (morphological, physiological, phenological) that represent ecological strategies and determine how plants respond to environmental factors, affect other trophic levels and influence ecosystem properties. Variation in plant functional traits, and trait syndromes, has proven useful for tackling many important ecological questions at a range of scales, giving rise to a demand for standardised ways to measure ecologically meaningful plant traits. This line of research has been among the most fruitful avenues for understanding ecological and evolutionary patterns and processes. It also has the potential both to build a predictive set of local, regional and global relationships between plants and environment and to quantify a wide range of natural and human-driven processes, including changes in biodiversity, the impacts of species invasions, alterations in biogeochemical processes and vegetation–atmosphere interactions. The importance of these topics dictates the urgent need for more and better data, and increases the value of standardised protocols for quantifying trait variation of different species, in particular for traits with power to predict plant- and ecosystem-level processes, and for traits that can be measured relatively easily. Updated and expanded from the widely used previous version, this handbook retains the focus on clearly presented, widely applicable, step-by-step recipes, with a minimum of text on theory, and not only includes updated methods for the traits previously covered, but also introduces many new protocols for further traits. This new handbook has a better balance between whole-plant traits, leaf traits, root and stem traits and regenerative traits, and puts particular emphasis on traits important for predicting species’ effects on key ecosystem properties. We hope this new handbook becomes a standard companion in local and global efforts to learn about the responses and impacts of different plant species with respect to environmental changes in the present, past and future.

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.

This work reports a study into the origin of the high efficiency in solution-processable bilayer solar cells based on methylammonium lead iodide (CH3NH3PbI3) and [6,6]-phenyl-C61-butyric acid methyl ester (PC61BM). Our cell has a power conversion efficiency (PCE) of 5.2% under simulated AM 1.5G irradiation (100 mW cm−2) and an internal quantum efficiency of close to 100%, which means that nearly all the absorbed photons are converted to electrons and are efficiently collected at the electrodes. This implies that the exciton diffusion, charge transfer and charge collection are highly efficient. The high exciton diffusion efficiency is enabled by the long diffusion length of CH3NH3PbI3 relative to its thickness. Furthermore, the low exciton binding energy of CH3NH3PbI3 implies that exciton splitting at the CH3NH3PbI3/PC61BM interface is very efficient. With further increase in CH3NH3PbI3 thickness, a higher PCE of 7.4% could be obtained. This is the highest efficiency attained for low temperature solution-processable bilayer solar cells to date.

Reference brains are indispensable tools in human brain mapping, enabling integration of multimodal data into an anatomically realistic standard space. Available reference brains, however, are restricted to the macroscopic scale and do not provide information on the functionally important microscopic dimension. We created an ultrahigh-resolution three-dimensional (3D) model of a human brain at nearly cellular resolution of 20 micrometers, based on the reconstruction of 7404 histological sections. "BigBrain" is a free, publicly available tool that provides considerable neuroanatomical insight into the human brain, thereby allowing the extraction of microscopic data for modeling and simulation. BigBrain enables testing of hypotheses on optimal path lengths between interconnected cortical regions or on spatial organization of genetic patterning, redefining the traditional neuroanatomy maps such as those of Brodmann and von Economo.

The Indian Ocean Experiment (INDOEX) was an international, multiplatform field campaign to measure long-range transport of air pollution from South and Southeast Asia toward the Indian Ocean during the dry monsoon season in January to March 1999. Surprisingly high pollution levels were observed over the entire northern Indian Ocean toward the Intertropical Convergence Zone at about 6 degrees S. We show that agricultural burning and especially biofuel use enhance carbon monoxide concentrations. Fossil fuel combustion and biomass burning cause a high aerosol loading. The growing pollution in this region gives rise to extensive air quality degradation with local, regional, and global implications, including a reduction of the oxidizing power of the atmosphere.

Redox-based nanoionic resistive memory cells are one of the most promising emerging nanodevices for future information technology with applications for memory, logic and neuromorphic computing. Recently, the serendipitous discovery of the link between redox-based nanoionic-resistive memory cells and memristors and memristive devices has further intensified the research in this field. Here we show on both a theoretical and an experimental level that nanoionic-type memristive elements are inherently controlled by non-equilibrium states resulting in a nanobattery. As a result, the memristor theory must be extended to fit the observed non-zero-crossing I–V characteristics. The initial electromotive force of the nanobattery depends on the chemistry and the transport properties of the materials system but can also be introduced during redox-based nanoionic-resistive memory cell operations. The emf has a strong impact on the dynamic behaviour of nanoscale memories, and thus, its control is one of the key factors for future device development and accurate modelling. The original definition of a memristor envisions a two-terminal memory device with a pinched, zero-crossing hysteresis loop. As the authors show here, an electromotive force leads to non-zero-crossing characteristics in nanoionic-type memristors, implying that the memristor definition must be amended.

We demonstrate how shape selectivity and optimized surface composition result in exceptional oxygen reduction activity of octahedral PtNi nanoparticles (NPs). The alloy octahedra were obtained by utilizing a facile, completely surfactant-free solvothermal synthesis. We show that the choice of precursor ligands controls the shape, while the reaction time tunes the surface Pt:Ni composition. The 9.5 nm sized PtNi octahedra reached a 10-fold surface area-specific (~3.14 mA/cm(Pt)(2)) as well as an unprecedented 10-fold Pt mass based (~1.45 A/mg(Pt)) activity gain over the state-of-art Pt electrocatalyst, approaching the theoretically predicted limits.

A precision measurement by AMS of the positron fraction in primary cosmic rays in the energy range from 0.5 to 500 GeV based on 10.9 million positron and electron events is presented. This measurement extends the energy range of our previous observation and increases its precision. The new results show, for the first time, that above ∼200 GeV the positron fraction no longer exhibits an increase with energy.

The phenomenon of a partial 2H→1T phase transition within multiwalled WS2 nanotubes under substitutional rhenium doping is discovered by means of high-resolution transmission electron microscopy. Using density-functional tight-binding calculations for the related MoS2 compound, we consider a possible origin of this phase transition, which was known formerly only for WS2 and MoS2 intercalated by alkali metals. An interplay between the stability of layered or nanotubular forms of 2H and 1T allotropes is found to be intimately related with their electronic structures and electro-donating ability of an impurity.

This book examines the physical phenomena which occur when light from short-pulse lasers interacts with material in gaseous, liquid or solid forms.

Abstract Bimetallic nanoparticles of noble metals are of high interest in imaging, biomedical devices, including nanomedicine, and heterogeneous catalysis. Synthesis, properties, characterization, biological properties, and practical applicability of nanoparticles on the basis of platinum group metals and the coin metals Ag and Au are discussed, also in comparison with the corresponding monometallic nanoparticles. In addition to the parameters that are required to characterize monometallic nanoparticles (mainly size, size distribution, shape, crystallographic nature, surface functionalization, charge), further information is required for a full characterization of bimetallic nanoparticles. This concerns the overall elemental composition of a bimetallic nanoparticle population (ratio of the two metals) and the internal distribution of the elements in individual nanoparticles (e.g., the presence of homogeneous alloys, core–shell systems, and possible intermediate stages). It is also important to ensure that all particles are identical in terms of elemental composition, that is, that the homogeneity of the particle population is given. Macroscopic properties like light absorption, antibacterial effects, and catalytic activity depend on these properties. The currently available methods for a full characterization of bimetallic nanoparticles are discussed, and future developments in this field are outlined.

Low-dimensional ferroelectric structures are a promising basis for the next generation of ultrahigh-density nonvolatile memory devices. Depolarization fields, created by incompletely compensated charges at the surfaces and interfaces, depress the polarization of such structures. Theory suggests that under conditions of uncompensated surface charges, local dipoles can organize in flux-closure structures in thin films and vortex structures in nano-sized ferroelectrics, reducing depolarization fields. However, the continuous rotation of the dipoles required in vortex structures and the behavior of unit cell dipoles in flux-closure structures have never been experimentally established. By aberration-corrected transmission electron microscopy, we obtained experimental evidence for continuous rotation of the dipoles closing the flux of 180° domains in a ferroelectric perovskite thin film.

The ability and motivation to share attention is a unique aspect of human cognition. Despite its significance, the neural basis remains elusive. To investigate the neural correlates of joint attention, we developed a novel, interactive research paradigm in which participants' gaze behavior--as measured by an eye tracking device--was used to contingently control the gaze of a computer-animated character. Instructed that the character on screen was controlled by a real person outside the scanner, 21 participants interacted with the virtual other while undergoing fMRI. Experimental variations focused on leading versus following the gaze of the character when fixating one of three objects also shown on the screen. In concordance with our hypotheses, results demonstrate, firstly, that following someone else's gaze to engage in joint attention resulted in activation of anterior portion of medial prefrontal cortex (MPFC) known to be involved in the supramodal coordination of perceptual and cognitive processes. Secondly, directing someone else's gaze toward an object activated the ventral striatum which--in light of ratings obtained from participants--appears to underlie the hedonic aspects of sharing attention. The data, therefore, support the idea that other-initiated joint attention relies upon recruitment of MPFC previously related to the "meeting of minds." In contrast, self-initiated joint attention leads to a differential increase of neural activity in reward-related brain areas, which might contribute to the uniquely human motivation to engage in the sharing of experiences.

Graphitic carbon nitride (g-C3N4), a metal-free semiconductor with a band gap of 2.7 eV, has received considerable attention owing to its fascinating photocatalytic performances under visible-light. g-C3N4 exhibits high thermal and chemical stability and non-toxicity such that it has been considered as the most promising photocatalyst for environmental improvement and energy conservation. Hence, it is of great importance to obtain high-quality g-C3N4 and gain a clear understanding of its optical properties. Herein, we report a high-yield synthesis of g-C3N4 products via heating of high vacuum-sealed melamine powder in an ampoule at temperatures between 450 and 650 °C. Using transmission electron microscopy (TEM), scanning transmission electron microscopy (STEM), electron energy loss spectroscopy (EELS), thermogravimetric analysis (TGA), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS), the chemical composition and crystallization of the as-produced g-C3N4 are demonstrated. A systematic optical study of g-C3N4 is carried out with several approaches. The optical phonon behavior of g-C3N4 is revealed by infrared and Raman spectroscopy, and the emission properties of g-C3N4 are investigated using photoluminescence (PL) spectroscopy, while the photocatalytic properties are explored by the photodegradation experiment.

Artificial intelligence and other data-intensive applications have escalated the demand for data storage and processing. New computing devices, such as phase-change random access memory (PCRAM)-based neuro-inspired devices, are promising options for breaking the von Neumann barrier by unifying storage with computing in memory cells. However, current PCRAM devices have considerable noise and drift in electrical resistance that erodes the precision and consistency of these devices. We designed a phase-change heterostructure (PCH) that consists of alternately stacked phase-change and confinement nanolayers to suppress the noise and drift, allowing reliable iterative RESET and cumulative SET operations for high-performance neuro-inspired computing. Our PCH architecture is amenable to industrial production as an intrinsic materials solution, without complex manufacturing procedure or much increased fabrication cost.

In monkeys, the somatosensory cortex on the parietal operculum can be differentiated into several distinct cortical fields. Potential human homologues for these areas have already been defined by cytoarchitectonic mapping and functional imaging experiments. Differences between the two most widely studied areas [operculum parietale (OP) 1 and OP 4] within this region particularly pertain to their connection with either the perceptive parietal network or the frontal motor areas. In the present study, we investigated differences in anatomical connection patterns probed by probabilistic tractography on diffusion tensor imaging data. Functional connectivity was then mapped by coordinate-based meta-analysis of imaging studies. Comparison between these two aspects of connectivity showed a good congruency and hence converging evidence for an involvement of these areas in matching brain networks. There were, however, also several instances in which anatomical and functional connectivity diverged, underlining the independence of these measures and the need for multimodal characterization of brain connectivity. The connectivity analyses performed showed that the two largest areas within the human parietal operculum region display considerable differences in their connectivity to frontoparietal brain regions. In particular, relative to OP 1, area OP 4 is more closely integrated with areas responsible for basic sensorimotor processing and action control, while OP 1 is more closely connected to the parietal networks for higher order somatosensory processing. These results are largely congruent with data on nonhuman primates. Differences between anatomical and functional connectivity as well as between species, however, highlight the need for an integrative view on connectivity, including comparison and cross-validation of results from different approaches.

Using aberration-corrected scanning transmission electron microscopy and electron energy loss spectroscopy line profiles with Ångstrom resolution, we uncover novel core-shell fine structures in a series of catalytically active dealloyed Pt(x)Ni(1-x) core-shell nanoparticles, showing the formation of unusual near-surface Ni-enriched inner shells. The radial location and the composition of the Ni-enriched inner shells were sensitively dependent on the initial alloy compositions. We further discuss how these self-organized Ni-enriched inner shells play a key role in maintaining surface lattice strain and thus control the surface catalytic activity for oxygen reduction.

Chemical dealloying of Pt binary alloy precursors has emerged as a novel and important preparation process for highly active fuel cell catalysts. Dealloying is a selective (electro)chemical leaching of a less noble metal M from a M rich Pt alloy precursor material and has been a familiar subject of macroscale corrosion technology for decades. The atomic processes occurring during the dealloying of nanoscale materials, however, are virtually unexplored and hence poorly understood. Here, we have investigated how the morphology and intraparticle composition depend on the particle size of dealloyed Pt-Co and Pt-Cu alloy nanoparticle precursor catalysts. To examine the size-morphology-composition relation, we used a combination of high-resolutionscanning transmission electron microscopy (STEM), transmission electron microscopy (TEM), electron energy loss (EEL) spectroscopy, energy-dispersive X-ray spectroscopy (EDS), and surface-sensitive cycling voltammetry. Our results indicate the existence of three distinctly different size-dependent morphology regimes in dealloyed Pt-Co and Pt-Cu particle ensembles: (i) The arrangement of Pt shell surrounding a single alloy core ("single core-shell nanoparticles") is exclusively formed by dealloying of particles below a characteristic diameter d(multiple cores) of 10-15 nm. (ii) Above d(multiple cores), nonporous bimetallic core-shell particles dominate and show structures with irregular shaped multiple Co/Cu rich cores ("multiple cores-shell nanoparticles"). (iii) Above the second characteristic diameter d(pores) of about 30 nm, the dealloyed Pt-Co and Pt-Cu particles start to show surface pits and nanoscale pores next to multiple Co/Cu rich cores. This structure prevails up to macroscopic bulklike dealloyed particles with diameter of more than 100 nm. The size-morphology-composition relationships link the nano to the macro scale and provide an insight into the existing material gap of dealloyed nanoparticles and highly porous bulklike bimetallic particles in corrosion science.

Seventy-five years after its invention, transmission electron microscopy has taken a great step forward with the introduction of aberration-corrected electron optics. An entirely new generation of instruments enables studies in condensed-matter physics and materials science to be performed at atomic-scale resolution. These new possibilities are meeting the growing demand of nanosciences and nanotechnology for the atomic-scale characterization of materials, nanosynthesized products and devices, and the validation of expected functions. Equipped with electron-energy filters and electron-energy-loss spectrometers, the new instruments allow studies not only of structure but also of elemental composition and chemical bonding. The energy resolution is about 100 milli-electron volts, and the accuracy of spatial measurements has reached a few picometers. However, understanding the results is generally not straightforward and only possible with extensive quantum-mechanical computer calculations.