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The application of electrochemical potentials to surfaces is an easy and direct way to alter surface charge density, the structure of the electrochemical double layer, and the presence of electrochemically activated species. On such electrified interfaces the formation of biofilms is reduced. Here we investigate how applied potentials alter the colonization of surfaces by the marine bacterium Cobetia marina and the marine diatom Navicula perminuta. Different constant potentials between -0.8 and 0.6 V as well as regular switching between two potentials were investigated, and their influence on the attachment of the two biofilm-forming microorganisms on gold-coated working electrodes was quantified. Reduced bacteria and diatom attachment were found when negative potentials and alternating potentials were applied. The results are discussed on the basis of the electrochemical processes occurring at the working electrode in artificial seawater as revealed by cyclic voltammetry.The present study complements our previous studies of the reactions of hydrogen atoms with C5 alkene species including 1- and 2-pentene and the branched isomers (2-methyl-1-butene, 2-methyl-2-butene, and 3-methyl-1-butene), by studying the reactions of hydrogen atoms with C2-C4 alkenes (ethylene, propene, 1- and 2-butene, and isobutene). The aim of the current work is to develop a hierarchical set of rate constants for Ḣ atom addition reactions to C2-C5 alkenes, both linear and branched, which can be used in the development of chemical kinetic models. High-pressure limiting and pressure-dependent rate constants are calculated using the Rice-Ramsperger-Kassel-Marcus (RRKM) theory and a one-dimensional master equation (ME). check details Rate constant recommendations for Ḣ atom addition and abstraction reactions in addition to alkyl radical decomposition reactions are also proposed and provide a useful tool for use in mechanisms of larger alkenes for which calculations do not exist. Additionally, validation of our theoretical results with single-pulse shock-tube pyrolysis experiments is carried out. An improvement in species mole fraction predictions for alkene pyrolysis is observed, showing the relevance of the present study.Using a three-dimensional (3D) Li-ion conducting ceramic network, such as Li7La3Zr2O12 (LLZO) garnet-type oxide conductor, has proved to be a promising strategy to form continuous Li ion transfer paths in a polymer-based composite. However, the 3D network produced by brittle ceramic conductor nanofibers fails to provide sufficient mechanical adaptability. In this manuscript, we reported a new 3D ion-conducting network, which is synthesized from highly loaded LLZO nanoparticles reinforced conducting polymer nanofibers, by creating a lightweight continuous and interconnected LLZO-enhanced 3D network to outperform conducting heavy and brittle ceramic nanofibers to offer a new design principle of composite electrolyte membrane featuring all-round properties in mechanical robustness, structural flexibility, high ionic conductivity, lightweight, and high surface area. This composite-nanofiber design overcomes the issues of using ceramic-only nanoparticles, nanowires, or nanofibers in polymer composite electrolyte, and our work can be considered as a new generation of composite electrolyte membrane in composite electrolyte development.The electronic angular momentum projected onto the diatomic axis couples with the angular momentum of the nuclei, significantly affecting the rotational motion of the system under electronic excitations by intense lasers. In this letter, we propose a pump-probe photodissociation scheme for an accurate determination of electron-rotation coupling effects induced by the strong fields. As a showcase we study the CH+ molecule excited by a short intense ultraviolet pump pulse to the A1Π state, which triggers coupled rovibrational dynamics. The dynamics is observed by measuring the kinetic energy release and angular resolved photofragmentation upon photodissociation induced by the time-delayed probe pulse populating the C1Σ+ state. Simulations of the rovibrational dynamics unravel clear fingerprints of the electron-rotation coupling effects that can be observed experimentally. The proposed pump-probe scheme opens new possibilities for the study of ultrafast dynamics following valence electronic transitions with current laser technology, and possible applications are also discussed.Macromolecular crowding influences protein mobility and stability in vivo. A precise description of the crowding effect on protein thermal stability requires the estimate of the combined effects of excluded volume, specific protein-environment interactions, as well as the thermal response of the crowders. Here, we explore an ideal model system, the lysozyme protein in powder state, to dissect the factors controlling the melting of the protein under extreme crowding. By deploying state-of-the art molecular simulations, supported by calorimetric experiments, we assess the role of the environment flexibility and of intermolecular electrostatic interactions. In particular, we show that the temperature-dependent flexibility of the macromolecular crowders, along with specific interactions, significantly alleviates the stabilizing contributions of the static volume effect.A metal-free Cs2CO3-promoted hydrothiolation of alkynes with aryl thioureas for stereoselective synthesis of (Z)-vinyl sulfides has been reported. Vinyl thioethers were obtained without a metal catalyst in good yields via anti-Markovnikov and cis addition. The protocol features a broad substrate scope of the starting materials, high atom economy, good yields, and exclusive stereoselectivity, showing potential synthetic value for the synthesis of a diversity of (Z)-vinyl thioethers.Machine learning classifiers trained on class imbalanced data are prone to overpredict the majority class. This leads to a larger misclassification rate for the minority class, which in many real-world applications is the class of interest. For binary data, the classification threshold is set by default to 0.5 which, however, is often not ideal for imbalanced data. Adjusting the decision threshold is a good strategy to deal with the class imbalance problem. In this work, we present two different automated procedures for the selection of the optimal decision threshold for imbalanced classification. A major advantage of our procedures is that they do not require retraining of the machine learning models or resampling of the training data. The first approach is specific for random forest (RF), while the second approach, named GHOST, can be potentially applied to any machine learning classifier. We tested these procedures on 138 public drug discovery data sets containing structure-activity data for a variety of pharmaceutical targets.