Efficient Conversion of Light to Chemical Energy: Directional,Chiral Photoswitches with Very High Quantum Yields

Photochromic systems have been used to achieve a number of engineering functions such as light energy conversion, molecular motors, pumps, actuators, and sensors. Key to practical applications is a high efficiency in the conversion of light to chemical energy, a rigid structure for the transmission of force to the environment, and directed motion during isomerization. We present a novel type of photochromic system (diindane diazocines) that converts visible light with an efficiency of 18 % to chemical energy. Quantum yields are exceptionally high with >70 % for the cis–trans isomerization and 90 % for the back‐reaction and thus higher than the biochemical system rhodopsin (64 %). Two diastereomers (meso and racemate) were obtained in only two steps in high yields. Both isomers are directional switches with high conversion rates (76–99 %). No fatigue was observed after several thousands of switching cycles in both systems.     

Synthesis of Tris‐ and Tetrakis(pentafluoroethyl)silanes

The synthesis and complete characterization of functional, highly Lewis acidic tris(pentafluoroethyl)silanes as well as tetrakis(perfluoroalkyl)silanes Si(C₂F₅)₄ and Si(C₂F₅)₃CF₃ by direct fluorination is described. The reaction of SiCl₄ with LiC₂F₅ invariably affords (pentafluoroethyl)fluorosilicates. To avoid silicate formation by fluoride transfer from LiC₂F₅ the Lewis acidity of the silane has to be decreased by electron‐donating substituents, such as dialkylamino groups. The easily accessible Si(C₂F₅)₃NEt₂ is a valuable precursor for a series of tris(pentafluoroethyl)silanes.     

Species selective preconcentration and quantification of gold nanoparticles using cloud point extraction and electrothermal atomic absorption spectrometry

The determination of metallic nanoparticles in environmental samples requires sample pretreatment that ideally combines pre-concentration and species selectivity. With cloud point extraction (CPE) using the surfactant Triton X-114 we present a simple and cost effective separation technique that meets both criteria. Effective separation of ionic gold species and Au nanoparticles (Au-NPs) is achieved by using sodium thiosulphate as a complexing agent. The extraction efficiency for Au-NP ranged from 1.01 ± 0.06 (particle size 2 nm) to 0.52 ± 0.16 (particle size 150 nm). An enrichment factor of 80 and a low limit of detection of 5 ng L⁻¹ is achieved using electrothermal atomic absorption spectrometry (ET-AAS) for quantification. TEM measurements showed that the particle size is not affected by the CPE process. Natural organic matter (NOM) is tolerated up to a concentration of 10 mg L⁻¹. The precision of the method expressed as the standard deviation of 12 replicates at an Au-NP concentration of 100 ng L⁻¹ is 9.5%. A relation between particle concentration and the extraction efficiency was not observed. Spiking experiments showed a recovery higher than 91% for environmental water samples.     

Using Background Knowledge from Preceding Studies for Building a Random Forest Prediction Model: A Plasmode Simulation Study

There is an increasing interest in machine learning (ML) algorithms for predicting patient outcomes, as these methods are designed to automatically discover complex data patterns. For example, the random forest (RF) algorithm is designed to identify relevant predictor variables out of a large set of candidates. In addition, researchers may also use external information for variable selection to improve model interpretability and variable selection accuracy, thereby prediction quality. However, it is unclear to which extent, if at all, RF and ML methods may benefit from external information. In this paper, we examine the usefulness of external information from prior variable selection studies that used traditional statistical modeling approaches such as the Lasso, or suboptimal methods such as univariate selection. We conducted a plasmode simulation study based on subsampling a data set from a pharmacoepidemiologic study with nearly 200,000 individuals, two binary outcomes and 1152 candidate predictor (mainly sparse binary) variables. When the scope of candidate predictors was reduced based on external knowledge RF models achieved better calibration, that is, better agreement of predictions and observed outcome rates. However, prediction quality measured by cross-entropy, AUROC or the Brier score did not improve. We recommend appraising the methodological quality of studies that serve as an external information source for future prediction model development.     

Kjeldahlkolben und andere Glasger?te aus arsenfreiem Glas

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Das Hamiltonsche Prinzip bei nichtholonomen Systemen

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Zum Gedächtnis von Walther v. Dyck

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Aufbau von Mittelwerten mehrerer Argumente. II. (Analytische Mittelwerte.)

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Beiträge zur Topologie geschlossener Kurven mit Knotenpunkten und zur Kroneckerschen Charakteristikentheorie

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