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Multijunction solar cells can overcome the fundamental efficiency limits of single-junction devices. The bandgap tunability of metal halide perovskite solar cells renders them attractive for multijunction architectures(1). Combinations with silicon and copper indium gallium selenide (CIGS), as well as all-perovskite tandem cells, have been reported(2-5). Meanwhile, narrow-gap non-fullerene acceptors have unlocked skyrocketing efficiencies for organic solar cells(6,7). Organic and perovskite semiconductors are an attractive combination, sharing similar processing technologies. Currently, perovskite-organic tandems show subpar efficiencies and are limited by the low open-circuit voltage (V-oc) of wide-gap perovskite cells(8) and losses introduced by the interconnect between the subcells(9,10). Here we demonstrate perovskite-organic tandem cells with an efficiency of 24.0 per cent (certified 23.1 per cent) and a high V-oc of 2.15 volts. Optimized charge extraction layers afford perovskite subcells with an outstanding combination of high V-oc and fill factor. The organic subcells provide a high external quantum efficiency in the near-infrared and, in contrast to paradigmatic concerns about limited photostability of non-fullerene cells(11), show an outstanding operational stability if excitons are predominantly generated on the non-fullerene acceptor, which is the case in our tandems. The subcells are connected by an ultrathin (approximately 1.5 nanometres) metal-like indium oxide layer with unprecedented low optical/electrical losses. This work sets a milestone for perovskite-organic tandems, which outperform the best p-i-n perovskite single junctions(12) and are on a par with perovskite-CIGS and all-perovskite multijunctions(13).
Perovskite photovoltaic (PV) cells have demonstrated power conversion efficiencies (PCE) that are close to those of monocrystalline silicon cells; however, in contrast to silicon PV, perovskites are not limited by Auger recombination under 1-sun illumination. Nevertheless, compared to GaAs and monocrystalline silicon PV, perovskite cells have significantly lower fill factors due to a combination of resistive and non-radiative recombination losses. This necessitates a deeper understanding of the underlying loss mechanisms and in particular the ideality factor of the cell. By measuring the intensity dependence of the external open-circuit voltage and the internal quasi-Fermi level splitting (QFLS), the transport resistance-free efficiency of the complete cell as well as the efficiency potential of any neat perovskite film with or without attached transport layers are quantified. Moreover, intensity-dependent QFLS measurements on different perovskite compositions allows for disentangling of the impact of the interfaces and the perovskite surface on the non-radiative fill factor and open-circuit voltage loss. It is found that potassium-passivated triple cation perovskite films stand out by their exceptionally high implied PCEs > 28%, which could be achieved with ideal transport layers. Finally, strategies are presented to reduce both the ideality factor and transport losses to push the efficiency to the thermodynamic limit.
In crystalline and amorphous semiconductors, the temperature-dependent Urbach energy can be determined from the inverse slope of the logarithm of the absorption spectrum and reflects the static and dynamic energetic disorder. Using recent advances in the sensitivity of photocurrent spectroscopy methods, we elucidate the temperature-dependent Urbach energy in lead halide perovskites containing different numbers of cation components. We find Urbach energies at room temperature to be 13.0 +/- 1.0, 13.2 +/- 1.0, and 13.5 +/- 1.0 meV for single, double, and triple cation perovskite. Static, temperature-independent contributions to the Urbach energy are found to be as low as 5.1 ?+/- 0.5, 4.7 +/- 0.3, and 3.3 +/- 0.9 meV for the same systems. Our results suggest that, at a low temperature, the dominant static disorder in perovskites is derived from zero-point phonon energy rather than structural disorder. This is unusual for solution-processed semiconductors but broadens the potential application of perovskites further to quantum electronics and devices.
The fate of allochthonous dissolved organic carbon (DOC) in aquatic systems is primarily controlled by the turnover of heterotrophic bacteria. However, the roles that abiotic and biotic factors such as light and DOC release by aquatic primary producers play in the microbial decomposition of allochthonous DOC is not well understood. We therefore tested if light and autochthonous DOC additions would increase allochthonous DOC decomposition rates and change bacterial growth efficiencies and community composition (BCC). We established continuous growth cultures with different inocula of natural bacterial communities and alder leaf leachates (DOCleaf) with and without light exposure before amendment. Furthermore, we incubated DOCleaf together with autochthonous DOC from lysed phytoplankton cultures (DOCphyto). Our results revealed that pretreatments of DOCleaf with light resulted in a doubling of bacterial growth efficiency (BGE), whereas additions of DOCphyto or combined additions of DOCphyto and light had no effect on BGE. The change in BGE was not accompanied by shifts in the phylogenetic structure of the BCC, but BCC was influenced by the DOC source. Our results highlight that a doubling of BGE is not necessarily accompanied by a shift in BCC and that BCC is more strongly affected by resource properties.
Freshwater fungi are a poorly studied ecological group that includes a high taxonomic diversity. Most studies on aquatic fungal diversity have focused on single habitats, thus the linkage between habitat heterogeneity and fungal diversity remains largely unexplored. We took 216 samples from 54 locations representing eight different habitats in the meso-oligotrophic, temperate Lake Stechlin in North-East Germany. These included the pelagic and littoral water column, sediments, and biotic substrates. We performed high throughput sequencing using the Roche 454 platform, employing a universal eukaryotic marker region within the large ribosomal subunit (LSU) to compare fungal diversity, community structure, and species turnover among habitats. Our analysis recovered 1027 fungal OTUs (97% sequence similarity). Richness estimates were highest in the sediment, biofilms, and benthic samples (189-231 OTUs), intermediate in water samples (42-85 OTUs), and lowest in plankton samples (8 OTUs). NMDS grouped the eight studied habitats into six clusters, indicating that community composition was strongly influenced by turnover among habitats. Fungal communities exhibited changes at the phylum and order levels along three different substrate categories from littoral to pelagic habitats. The large majority of OTUs (> 75%) could not be classified below the order level due to the lack of aquatic fungal entries in public sequence databases. Our study provides a first estimate of lake-wide fungal diversity and highlights the important contribution of habitat heterogeneity to overall diversity and community composition. Habitat diversity should be considered in any sampling strategy aiming to assess the fungal diversity of a water body.
Crop model intercomparison studies have mostly focused on the assessment of predictive capabilities for crop development using weather and basic soil data from the same location. Still challenging is the model performance when considering complex interrelations between soil and crop dynamics under a changing climate. The objective of this study was to test the agronomic crop and environmental flux-related performance of a set of crop models. The aim was to predict weighing lysimeter-based crop (i.e., agronomic) and water-related flux or state data (i.e., environmental) obtained for the same soil monoliths that were taken from their original environment and translocated to regions with different climatic conditions, after model calibration at the original site. Eleven models were deployed in the study. The lysimeter data (2014-2018) were from the Dedelow (Dd), Bad Lauchstadt (BL), and Selhausen (Se) sites of the TERENO (TERrestrial ENvironmental Observatories) SOILCan network. Soil monoliths from Dd were transferred to the drier and warmer BL site and the wetter and warmer Se site, which allowed a comparison of similar soil and crop under varying climatic conditions. The model parameters were calibrated using an identical set of crop- and soil-related data from Dd. Environmental fluxes and crop growth of Dd soil were predicted for conditions at BL and Se sites using the calibrated models. The comparison of predicted and measured data of Dd lysimeters at BL and Se revealed differences among models. At site BL, the crop models predicted agronomic and environmental components similarly well. Model performance values indicate that the environmental components at site Se were better predicted than agronomic ones. The multi-model mean was for most observations the better predictor compared with those of individual models. For Se site conditions, crop models failed to predict site-specific crop development indicating that climatic conditions (i.e., heat stress) were outside the range of variation in the data sets considered for model calibration. For improving predictive ability of crop models (i.e., productivity and fluxes), more attention should be paid to soil-related data (i.e., water fluxes and system states) when simulating soil-crop-climate interrelations in changing climatic conditions.
Phenology has emerged as key indicator of the biological impacts of climate change, yet the role of functional traits constraining variation in herbaceous species' phenology has received little attention. Botanical gardens are ideal places in which to investigate large numbers of species growing under common climate conditions. We ask whether interspecific variation in plant phenology is influenced by differences in functional traits. We recorded onset, end, duration and intensity of initial growth, leafing out, leaf senescence, flowering and fruiting for 212 species across five botanical gardens in Germany. We measured functional traits, including plant height, absolute and specific leaf area, leaf dry matter content, leaf carbon and nitrogen content and seed mass and accounted for species' relatedness. Closely related species showed greater similarities in timing of phenological events than expected by chance, but species' traits had a high degree of explanatory power, pointing to paramount importance of species' life-history strategies. Taller plants showed later timing of initial growth, and flowered, fruited and underwent leaf senescence later. Large-leaved species had shorter flowering and fruiting durations. Taller, large-leaved species differ in their phenology and are more competitive than smaller, small-leaved species. We assume climate warming will change plant communities' competitive hierarchies with consequences for biodiversity.
Aim Biotic interactions within guilds or across trophic levels have widely been ignored in species distribution models (SDMs). This synthesis outlines the development of species interaction distribution models (SIDMs), which aim to incorporate multispecies interactions at large spatial extents using interaction matrices. Location Local to global. Methods We review recent approaches for extending classical SDMs to incorporate biotic interactions, and identify some methodological and conceptual limitations. To illustrate possible directions for conceptual advancement we explore three principal ways of modelling multispecies interactions using interaction matrices: simple qualitative linkages between species, quantitative interaction coefficients reflecting interaction strengths, and interactions mediated by interaction currencies. We explain methodological advancements for static interaction data and multispecies time series, and outline methods to reduce complexity when modelling multispecies interactions. Results Classical SDMs ignore biotic interactions and recent SDM extensions only include the unidirectional influence of one or a few species. However, novel methods using error matrices in multivariate regression models allow interactions between multiple species to be modelled explicitly with spatial co-occurrence data. If time series are available, multivariate versions of population dynamic models can be applied that account for the effects and relative importance of species interactions and environmental drivers. These methods need to be extended by incorporating the non-stationarity in interaction coefficients across space and time, and are challenged by the limited empirical knowledge on spatio-temporal variation in the existence and strength of species interactions. Model complexity may be reduced by: (1) using prior ecological knowledge to set a subset of interaction coefficients to zero, (2) modelling guilds and functional groups rather than individual species, and (3) modelling interaction currencies and species effect and response traits. Main conclusions There is great potential for developing novel approaches that incorporate multispecies interactions into the projection of species distributions and community structure at large spatial extents. Progress can be made by: (1) developing statistical models with interaction matrices for multispecies co-occurrence datasets across large-scale environmental gradients, (2) testing the potential and limitations of methods for complexity reduction, and (3) sampling and monitoring comprehensive spatio-temporal data on biotic interactions in multispecies communities.
Maltose frequently occurs as intermediate of the central carbon metabolism of prokaryotic and eukaryotic cells. Various mutants possess elevated maltose levels. Maltose exists as two anomers, (alpha- and beta-form) which are rapidly interconverted without requiring enzyme-mediated catalysis. As maltose is often abundant together with other oligoglucans, selective quantification is essential. In this communication, we present a photometric maltose assay using 4-alpha-glucanotransferase (AtDPE2) from Arabidopsis thaliana. Under in vitro conditions, AtDPE2 utilizes maltose as glucosyl donor and glycogen as acceptor releasing the other hexosyl unit as free glucose which is photometrically quantified following enzymatic phosphorylation and oxidation. Under the conditions used, DPE2 does not noticeably react with other di- or oligosaccharides. Selectivity compares favorably with that of maltase frequently used in maltose assays. Reducing end interconversion of the two maltose anomers is in rapid equilibrium and, therefore, the novel assay measures total maltose contents. Furthermore, an AtDPE2-based continuous photometric assay is presented which allows to quantify beta-amylase activity and was found to be superior to a conventional test. Finally, the AtDPE2-based maltose assay was used to quantify leaf maltose contents of both Arabidopsis wild type and AtDPE2-deficient plants throughout the light-dark cycle. These data are presented together with assimilatory starch levels. (C) 2017 Published by Elsevier Inc.
HPI Future SOC Lab
(2024)
The “HPI Future SOC Lab” is a cooperation of the Hasso Plattner Institute (HPI) and industry partners. Its mission is to enable and promote exchange and interaction between the research community and the industry partners.
The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores and 2 TB main memory. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies.
This technical report presents results of research projects executed in 2020. Selected projects have presented their results on April 21st and November 10th 2020 at the Future SOC Lab Day events.
The intensification of Northern Hemisphere glaciations at the end of the Pliocene epoch marks one of the most substantial climatic shifts of the Cenozoic. Despite global cooling, sea surface temperatures in the high latitude North Atlantic Ocean rose between 2.9–2.7 million years ago. Here we present sedimentary geochemical proxy data from the Gulf of Cadiz to reconstruct the variability of Mediterranean Outflow Water, an important heat source to the North Atlantic. We find evidence for enhanced production of Mediterranean Outflow from the mid-Pliocene to the late Pliocene which we infer could have driven a sub-surface heat channel into the high-latitude North Atlantic. We then use Earth System Models to constrain the impact of enhanced Mediterranean Outflow production on the northward heat transport in the North Atlantic. In accord with the proxy data, the numerical model results support the formation of a sub-surface channel that pumped heat from the subtropics into the high latitude North Atlantic. We further suggest that this mechanism could have delayed ice sheet growth at the end of the Pliocene.
Technical report
(2019)
Design and Implementation of service-oriented architectures imposes a huge number of research questions from the fields of software engineering, system analysis and modeling, adaptability, and application integration. Component orientation and web services are two approaches for design and realization of complex web-based system. Both approaches allow for dynamic application adaptation as well as integration of enterprise application.
Commonly used technologies, such as J2EE and .NET, form de facto standards for the realization of complex distributed systems. Evolution of component systems has lead to web services and service-based architectures. This has been manifested in a multitude of industry standards and initiatives such as XML, WSDL UDDI, SOAP, etc. All these achievements lead to a new and promising paradigm in IT systems engineering which proposes to design complex software solutions as collaboration of contractually defined software services.
Service-Oriented Systems Engineering represents a symbiosis of best practices in object-orientation, component-based development, distributed computing, and business process management. It provides integration of business and IT concerns.
The annual Ph.D. Retreat of the Research School provides each member the opportunity to present his/her current state of their research and to give an outline of a prospective Ph.D. thesis. Due to the interdisciplinary structure of the research school, this technical report covers a wide range of topics. These include but are not limited to: Human Computer Interaction and Computer Vision as Service; Service-oriented Geovisualization Systems; Algorithm Engineering for Service-oriented Systems; Modeling and Verification of Self-adaptive Service-oriented Systems; Tools and Methods for Software Engineering in Service-oriented Systems; Security Engineering of Service-based IT Systems; Service-oriented Information Systems; Evolutionary Transition of Enterprise Applications to Service Orientation; Operating System Abstractions for Service-oriented Computing; and Services Specification, Composition, and Enactment.
Convolutional neural networks (CNNs) have been used for a wide range of applications in astronomy, including for the restoration of degraded images using a spatially invariant point spread function (PSF) across the field of view. Most existing development techniques use a single PSF in the deconvolution process, which is unrealistic when spatially variable PSFs are present in real observation conditions. Such conditions are simulated in this work to yield more realistic data samples. We propose a method that uses a simulated spatially variable PSF for the T80-South (T80-S) telescope, an 80-cm survey imager at Cerro Tololo (Chile). The synthetic data use real parameters from the detector noise and atmospheric seeing to recreate the T80-S observational conditions for the CNN training. The method is tested on real astronomical data from the T80-S telescope. We present the simulation and training methods, the results from real T80-S image CNN prediction, and a comparison with space observatory Gaia. A CNN can fix optical aberrations, which include image distortion, PSF size and profile, and the field position variation while preserving the source's flux. The proposed restoration approach can be applied to other optical systems and to post-process adaptive optics static residual aberrations in large-diameter telescopes.