Coordination mode of cyclohex-1-enylolonium cation and bridging pyridyl derivatives as gem-diol chelates to rhenium(I) and (VII)

Transition Metal Chemistry - Rhenium(I) and (VII) complexes with cyclohex-1-enylolonium cation and bridging pyridyl derivatives are reported. Additionally, the CO-bridged pyridyl and their related...     

Improving simulated annealing through derandomization

We propose and study a version of simulated annealing (SA) on continuous state spaces based on \((t,s)_R\)-sequences. The parameter \(R\in \bar{\mathbb {N}}\) regulates the degree of randomness of the input sequence, with the case \(R=0\) corresponding to IID uniform random numbers and the limiting case \(R=\infty \) to (t, s)-sequences. Our main result, obtained for rectangular domains, shows that the resulting optimization method, which we refer to as QMC-SA, converges almost surely to the global optimum of the objective function \(\varphi \) for any \(R\in \mathbb {N}\). When \(\varphi \) is univariate, we are in addition able to show that the completely deterministic version of QMC-SA is convergent. A key property of these results is that they do not require objective-dependent conditions on the cooling schedule. As a corollary of our theoretical analysis, we provide a new almost sure convergence result for SA which shares this property under minimal assumptions on \(\varphi \). We further explain how our results in fact apply to a broader class of optimization methods including for example threshold accepting, for which to our knowledge no convergence results currently exist. We finally illustrate the superiority of QMC-SA over SA algorithms in a numerical study.     

High-throughput characterization of sediment organic matter by pyrolysis–gas chromatography/mass spectrometry and multivariate curve resolution: A promising analytical tool in (paleo)limnology

Molecular-level chemical information about organic matter (OM) in sediments helps to establish the sources of OM and the prevalent degradation/diagenetic processes, both essential for understanding the cycling of carbon (C) and of the elements associated with OM (toxic trace metals and nutrients) in lake ecosystems. Ideally, analytical methods for characterizing OM should allow high sample throughput, consume small amounts of sample and yield relevant chemical information, which are essential for multidisciplinary, high-temporal resolution and/or large spatial scale investigations. We have developed a high-throughput analytical method based on pyrolysis–gas chromatography/mass spectrometry and automated data processing to characterize sedimentary OM in sediments. Our method consumes 200 μg of freeze-dried and ground sediment sample. Pyrolysis was performed at 450 °C, which was found to avoid degradation of specific biomarkers (e.g., lignin compounds, fresh carbohydrates/cellulose) compared to 650 °C, which is in the range of temperatures commonly applied for environmental samples. The optimization was conducted using the top ten sediment samples of an annually resolved sediment record (containing 16–18% and 1.3–1.9% of total carbon and nitrogen, respectively). Several hundred pyrolytic compound peaks were detected of which over 200 were identified, which represent different classes of organic compounds (i.e., n-alkanes, n-alkenes, 2-ketones, carboxylic acids, carbohydrates, proteins, other N compounds, (methoxy)phenols, (poly)aromatics, chlorophyll and steroids/hopanoids). Technical reproducibility measured as relative standard deviation of the identified peaks in triplicate analyses was 5.5 ± 4.3%, with 90% of the RSD values within 10% and 98% within 15%. Finally, a multivariate calibration model was calculated between the pyrolytic degradation compounds and the sediment depth (i.e., sediment age), which is a function of degradation processes and changes in OM source type. This allowed validation of the Py–GC/MS dataset against fundamental processes involved in OM cycling in aquatic ecosystems.     

Unraveling the electronic structure of transition metal dimers using resonant four‐wave mixing

The potential of two‐color resonant and degenerate four‐wave mixing spectroscopy for investigations of the complex spectra of transition metal dimers is explored. Two‐color resonant and degenerate four‐wave mixing spectroscopy scans of the well‐known A‐X and B‐X transitions in Cu₂ are reported and compared with previous experimental data obtained from standard single‐resonance techniques. The selectivity of the method is shown to enable the measurement of isotopologue pure spectra without the need for isotopically enriched metal targets. Specific subsets of the rovibronic structure are separated in a congested spectral region of overlapping transitions. The sensitivity of the method compares satisfactorily with linear spectroscopic methods such as laser‐induced fluorescence and cavity ring‐down. A new laser vaporization source for the production of transition metal dimers and clusters has been constructed. The new design aims for a high number density and maximum possible shot‐to‐shot stability. The possibilities of further applications of non‐linear four‐wave mixing spectroscopy to Cu₂ and other transition metal dimers are discussed. Copyright © 2015 John Wiley & Sons, Ltd.     

A Tandem In Situ Peptide Cyclization through Trifluoroacetic Acid Cleavage

We present a new approach for peptide cyclization during solid phase synthesis under highly acidic conditions. Our approach involves simultaneous in situ deprotection, cyclization and trifluoroacetic acid (TFA) cleavage of the peptide, which is achieved by forming an amide bond between a lysine side chain and a succinic acid linker at the peptide N‐terminus. The reaction proceeds via a highly active succinimide intermediate, which was isolated and characterized. The structure of a model cyclic peptide was solved by NMR spectroscopy. Theoretical calculations support the proposed mechanism of cyclization. Our new methodology is applicable for the formation of macrocycles in solid‐phase synthesis of peptides and organic molecules.     

Towards a modular,versatile and portable sensor system for measurements in gaseous environments based on microcantilevers

Microfabricated silicon cantilever sensor arrays represent a powerful platform for sensing applications in physics, chemistry, material science, biology and medicine. The sensor response is mechanical bending due to absorption of molecules. In gaseous environment, polymer-coated microcantilevers are used as electronic nose for characterization of vapors, resulting in cantilever bending due to polymer swelling upon exposure. Medical applications involve fast characterization of exhaled patient's breath samples for detection of diseases, based on the presence of certain chemicals in breath. We present a portable, compact, modular microcantilever setup, which uses a micropump for aspiration and a bluetooth interface for remote data acquisition.     

Obtaining the dividends-penalty identities by interpretation

The dividends-penalty identity is a relation between three functions: the discounted penalty function without dividends, the discounted penalty function if a barrier dividend strategy is applied, and the expected discounted dividends until ruin. The classical model of risk theory is modified in that the deterministic premiums are replaced by a compound Poisson process with exponential jumps. In this model, the dividends-penalty identity is new and can be derived by interpretation. Then the dividends-penalty identity in the classical model is obtained as a limit.