Modeling Potential-Dependent Electrochemical Activation Barriers: Revisiting the Alkaline Hydrogen Evolution Reaction.

Accurate theoretical simulation of electrochemical activation barriers is key to understanding electrocatalysis and guides the design of more efficient catalysts. Providing a detailed picture of proton transfer processes encounters several challenges: the constant potential requirement during charge transfer, the different time scales involved in the processes, and the thermal fluctuation of the solvent. Hence, it is prohibitively expensive computationally to apply density functional theory (DFT) calculations in modeling the potential-dependent activation barrier at the electrode-solvent interface, and the results are dubious.

Combining artificial intelligence and physics-based modeling to directly assess atomic site stabilities: from sub-nanometer clusters to extended surfaces.

The performance of functional materials is dictated by chemical and structural properties of individual atomic sites. In catalysts, for example, the thermodynamic stability of constituting atomic sites is a key descriptor from which more complex properties, such as molecular adsorption energies and reaction rates, can be derived. In this study, we present a widely applicable machine learning (ML) approach to instantaneously compute the stability of individual atomic sites in structurally and electronically complex nano-materials.

Size and Shape Dependence of the Electronic Structure of Gold Nanoclusters on TiO.

Understanding the mechanism behind the superior catalytic power of single- or few-atom heterogeneous catalysts has become an important topic in surface chemistry. This is particularly the case for gold, with TiO being an efficient support. Here we use scanning tunneling microscopy/spectroscopy with theoretical calculations to investigate the adsorption geometry and local electronic structure of several-atom Au clusters on rutile TiO(110), with the clusters fabricated by controlled manipulation of single atoms.

Effectiveness and safety of nivolumab in the treatment of lung cancer patients in France: preliminary results from the real-world EVIDENS study.

EVIDENS is an ongoing, prospective, non-interventional study evaluating the effectiveness and safety of nivolumab in lung cancer patients in France (ClinicalTrials.gov NCT03382496). Adults with a pathologically confirmed diagnosis of lung cancer and initiating treatment with nivolumab were recruited from 146 sites in France.

Dynein-mediated microtubule translocation powering neurite outgrowth in chick and neurons requires microtubule assembly.

Previously, we have shown that bulk microtubule (MT) movement correlates with neurite elongation, and blocking either dynein activity or MT assembly inhibits both processes. However, whether the contributions of MT dynamics and dynein activity to neurite elongation are separate or interdependent is unclear. Here, we investigated the underlying mechanism by testing the roles of dynein and MT assembly in neurite elongation of and chick neurites using time-lapse imaging, fluorescent speckle microscopy, super-resolution imaging and biophysical analysis.