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- ItemEvaluating arbitrary strain configurations and doping in graphene with Raman spectroscopy(Bristol : IOP Publ., 2017-11-6) Mueller, Niclas S.; Heeg, Sebastian; Peña Alvarez, Miriam; Kusch, Patryk; Wasserroth, Sören; Clark, Nick; Schedin, Fredrik; Parthenios, John; Papagelis, Konstantinos; Galiotis, Costas; Kalbáč, Martin; Vijayaraghavan, Aravind; Huebner, Uwe; Gorbachev, Roman; Frank, Otakar; Reich, StephanieThe properties of graphene depend sensitively on strain and doping affecting its behavior in devices and allowing an advanced tailoring of this material. A knowledge of the strain configuration, i.e. the relative magnitude of the components of the strain tensor, is particularly crucial, because it governs effects like band-gap opening, pseudo-magnetic fields, and induced superconductivity. It also enters critically in the analysis of the doping level. We propose a method for evaluating unknown strain configurations and simultaneous doping in graphene using Raman spectroscopy. In our analysis we first extract the bare peak shift of the G and 2D modes by eliminating their splitting due to shear strain. The shifts from hydrostatic strain and doping are separated by a correlation analysis of the 2D and G frequencies, where we find Delta omega(2D)/Delta omega(G) = 2.21 +/- 0.05 for pure hydrostatic strain. We obtain the local hydrostatic strain, shear strain and doping without any assumption on the strain configuration prior to the analysis, as we demonstrate for two model cases: Graphene under uniaxial stress and graphene suspended on nanostructures that induce strain. Raman scattering with circular corotating polarization is ideal for analyzing frequency shifts, especially for weak strain when the peak splitting by shear strain cannot be resolved.
- Itemcorr2D: Implementation of Two-Dimensional Correlation Analysis in R(Los Angeles : UCLA, 2019) Geitner, Robert; Fritzsch, Robby; Bocklitz, Thomas W.; Popp, JürgenIn the package corr2D two-dimensional correlation analysis is implemented in R. This paper describes how two-dimensional correlation analysis is done in the package and how the mathematical equations are translated into R code. The paper features a simple tutorial with executable code for beginners, insight into the calculations done before the correlation analysis, a detailed look at the parallelization of the fast Fourier transformation based correlation analysis and a speed test of the calculation. The package corr2D offers the possibility to preprocess, correlate and postprocess spectroscopic data using exclusively the R language. Thus, corr2D is a welcome addition to the toolbox of spectroscopists and makes two-dimensional correlation analysis more accessible and transparent.
- ItemProximal Soil Sensing - A Contribution for Species Habitat Distribution Modelling of Earthworms in Agricultural Soils?(San Francisco, California, US : PLOS, 2016) Schirrmann, Michael; Joschko, Monika; Gebbers, Robin; Kramer, Eckart; Zörner, Mirjam; Barkusky, Dietmar; Timmer, JensBackground: Earthworms are important for maintaining soil ecosystem functioning and serve as indicators of soil fertility. However, detection of earthworms is time-consuming, which hinders the assessment of earthworm abundances with high sampling density over entire fields. Recent developments of mobile terrestrial sensor platforms for proximal soil sensing (PSS) provided new tools for collecting dense spatial information of soils using various sensing principles. Yet, the potential of PSS for assessing earthworm habitats is largely unexplored. This study investigates whether PSS data contribute to the spatial prediction of earthworm abundances in species distribution models of agricultural soils. Methodology/Principal Findings: Proximal soil sensing data, e.g., soil electrical conductivity (EC), pH, and near infrared absorbance (NIR), were collected in real-time in a field with two management strategies (reduced tillage / conventional tillage) and sandy to loam soils. PSS was related to observations from a long-term (11 years) earthworm observation study conducted at 42 plots. Earthworms were sampled from 0.5 x 0.5 x 0.2 m³ soil blocks and identified to species level. Sensor data were highly correlated with earthworm abundances observed in reduced tillage but less correlated with earthworm abundances observed in conventional tillage. This may indicate that management influences the sensor-earthworm relationship. Generalized additive models and state-space models showed that modelling based on data fusion from EC, pH, and NIR sensors produced better results than modelling without sensor data or data from just a single sensor. Regarding the individual earthworm species, particular sensor combinations were more appropriate than others due to the different habitat requirements of the earthworms. Earthworm species with soil-specific habitat preferences were spatially predicted with higher accuracy by PSS than more ubiquitous species. Conclusions/Significance: Our findings suggest that PSS contributes to the spatial modelling of earthworm abundances at field scale and that it will support species distribution modelling in the attempt to understand the soil-earthworm relationships in agroecosystems.
- ItemA meta-analysis of catalytic literature data reveals property-performance correlations for the OCM reaction([London] : Nature Publishing Group UK, 2019) Schmack, Roman; Friedrich, Alexandra; Kondratenko, Evgenii V.; Polte, Jörg; Werwatz, Axel; Kraehnert, RalphDecades of catalysis research have created vast amounts of experimental data. Within these data, new insights into property-performance correlations are hidden. However, the incomplete nature and undefined structure of the data has so far prevented comprehensive knowledge extraction. We propose a meta-analysis method that identifies correlations between a catalyst’s physico-chemical properties and its performance in a particular reaction. The method unites literature data with textbook knowledge and statistical tools. Starting from a researcher’s chemical intuition, a hypothesis is formulated and tested against the data for statistical significance. Iterative hypothesis refinement yields simple, robust and interpretable chemical models. The derived insights can guide new fundamental research and the discovery of improved catalysts. We demonstrate and validate the method for the oxidative coupling of methane (OCM). The final model indicates that only well-performing catalysts provide under reaction conditions two independent functionalities, i.e. a thermodynamically stable carbonate and a thermally stable oxide support.
- ItemFluorosolvatochromism of furanyl- and thiophenyl-substituted acetophenones(London : RSC, 2015) Friebe, Nadine; Schreiter, Katja; Kübel, Joachim; Dietzek, Benjamin; Moszner, Norbert; Burtscher, Peter; Oehlke, Alexander; Spange, StefanA series of para-substituted acetophenones bearing a furanyl or a thiophenyl moiety show a large Stokes-shift, which is a function of various solvent properties. Photophysical properties such as emission lifetime of the compounds have been determined using time-correlated-single photon counting to secure the intrinsic fluorescence behaviour. The solvent dependent position of the UV/Vis emission band [small nu, Greek, tilde]max,em of the compounds has been measured in 26 various solvents. The influence of the solvent on [small nu, Greek, tilde]max,em is of very complex nature and mathematically analysed by multiple square linear solvation energy (LSE)-correlation analysis using Catalán's four-solvent parameter set. Solvent acidity has a strong influence on the bathochromic shift of 2,5-disubstituted furan derivatives compared to the non-5-substituted furan and thiophene derivatives, which show a contrary behaviour. Therefore, the 5-cyanofuranyl-substituted acetophenone derivative is useful as a probe for measuring environmental properties by fluorescence spectroscopy.
- ItemA human development framework for CO 2 reductions(San Francisco, CA : Public Library of Science (PLoS), 2011) Costa, L.; Rybski, D.; Kropp, J.P.Although developing countries are called to participate in CO 2 emission reduction efforts to avoid dangerous climate change, the implications of proposed reduction schemes in human development standards of developing countries remain a matter of debate. We show the existence of a positive and time-dependent correlation between the Human Development Index (HDI) and per capita CO 2 emissions from fossil fuel combustion. Employing this empirical relation, extrapolating the HDI, and using three population scenarios, the cumulative CO 2 emissions necessary for developing countries to achieve particular HDI thresholds are assessed following a Development As Usual approach (DAU). If current demographic and development trends are maintained, we estimate that by 2050 around 85% of the world's population will live in countries with high HDI (above 0.8). In particular, 300 Gt of cumulative CO 2 emissions between 2000 and 2050 are estimated to be necessary for the development of 104 developing countries in the year 2000. This value represents between 20 % to 30 % of previously calculated CO 2 budgets limiting global warming to 2°C. These constraints and results are incorporated into a CO 2 reduction framework involving four domains of climate action for individual countries. The framework reserves a fair emission path for developing countries to proceed with their development by indexing country-dependent reduction rates proportional to the HDI in order to preserve the 2°C target after a particular development threshold is reached. For example, in each time step of five years, countries with an HDI of 0.85 would need to reduce their per capita emissions by approx. 17% and countries with an HDI of 0.9 by 33 %. Under this approach, global cumulative emissions by 2050 are estimated to range from 850 up to 1100 Gt of CO 2. These values are within the uncertainty range of emissions to limit global temperatures to 2°C.
- ItemCorrecting systematic errors by hybrid 2D correlation loss functions in nonlinear inverse modelling(San Francisco, California, US : PLOS, 2023) Mayerhöfer, Thomas G.; Noda, Isao; Pahlow, Susanne; Heintzmann, Rainer; Popp, JürgenRecently a new family of loss functions called smart error sums has been suggested. These loss functions account for correlations within experimental data and force modeled data to obey these correlations. As a result, multiplicative systematic errors of experimental data can be revealed and corrected. The smart error sums are based on 2D correlation analysis which is a comparably recent methodology for analyzing spectroscopic data that has found broad application. In this contribution we mathematically generalize and break down this methodology and the smart error sums to uncover the mathematic roots and simplify it to craft a general tool beyond spectroscopic modelling. This reduction also allows a simplified discussion about limits and prospects of this new method including one of its potential future uses as a sophisticated loss function in deep learning. To support its deployment, the work includes computer code to allow reproduction of the basic results.
- ItemNetwork-based identification and characterization of teleconnections on different scales([London] : Macmillan Publishers Limited, part of Springer Nature, 2019) Agarwal, Ankit; Caesar, Levke; Marwan, Norbert; Maheswaran, Rathinasamy; Merz, Bruno; Kurths, JürgenSea surface temperature (SST) patterns can – as surface climate forcing – affect weather and climate at large distances. One example is El Niño-Southern Oscillation (ENSO) that causes climate anomalies around the globe via teleconnections. Although several studies identified and characterized these teleconnections, our understanding of climate processes remains incomplete, since interactions and feedbacks are typically exhibited at unique or multiple temporal and spatial scales. This study characterizes the interactions between the cells of a global SST data set at different temporal and spatial scales using climate networks. These networks are constructed using wavelet multi-scale correlation that investigate the correlation between the SST time series at a range of scales allowing instantaneously deeper insights into the correlation patterns compared to traditional methods like empirical orthogonal functions or classical correlation analysis. This allows us to identify and visualise regions of – at a certain timescale – similarly evolving SSTs and distinguish them from those with long-range teleconnections to other ocean regions. Our findings re-confirm accepted knowledge about known highly linked SST patterns like ENSO and the Pacific Decadal Oscillation, but also suggest new insights into the characteristics and origins of long-range teleconnections like the connection between ENSO and Indian Ocean Dipole.