112 research outputs found

    Reactive Interactions between the Ionic Liquid BMP‐TFSI and a Na Surface

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    In order to obtain atomistic insights into the initial stages of the formation of the solid electrolyte interphase (SEI) in Na ion or Na metal batteries, we employ surface chemistry experiments and DFT calculations to study the interactions and reactions between a Na surface and the ionic liquid (IL) 1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide (BMP-TFSI), a candidate to be used as electrolyte in batteries. Oxygen-free Na thin films, which were grown on Ru(0001) and characterized by X-ray and ultraviolet photoelectron spectroscopy (XPS, UPS), can be understood as model of a Na-rich electrode. After deposition of submonolayer to multilayer BMP-TFSI films on the Na thin films at room temperature, XPS measurements revealed partial decomposition and the formation of a ‘contact layer’ at the Na surface, consisting of mainly TFSI-based decomposition products

    Model Studies on the Formation of the Solid Electrolyte Interphase: Reaction of Li with Ultrathin Adsorbed Ionic-Liquid Films and Co3_{3}O4_{4}(111) Thin Films

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    In this work we aim towards the molecular understanding of the solid electrolyte interphase (SEI) formation at the electrode electrolyte interface (EEI). Herein, we investigated the interaction between the battery‐relevant ionic liquid (IL) 1‐butyl‐1‐methylpyrrolidinium bis(trifluoromethylsulfonyl)imide (BMP‐TFSI), Li and a Co3_{3}O4_{4}(111) thin film model anode grown on Ir(100) as a model study of the SEI formation in Li‐ion batteries (LIBs). We employed mostly X‐ray photoelectron spectroscopy (XPS) in combination with dispersion‐corrected density functional theory calculations (DFT‐D3). If the surface is pre‐covered by BMP‐TFSI species (model electrolyte), post‐deposition of Li (Li+^{+} ion shuttle) reveals thermodynamically favorable TFSI decomposition products such as LiCN, Li2_{2}NSO2_{2}CF3_{3}, LiF, Li2_{2}S, Li2_{2}O2_{2}, Li2_{2}O, but also kinetic products like Li2_{2}NCH3_{3}C4_{4}H9_{9} or LiNCH3_{3}C4_{4}H9_{9} of BMP. Simultaneously, Li adsorption and/or lithiation of Co3_{3}O4_{4}(111) to LinCo3_{3}O4_{4} takes place due to insertion via step edges or defects; a partial transformation to CoO cannot be excluded. Formation of Co0^{0} could not be observed in the experiment indicating that surface reaction products and inserted/adsorbed Li at the step edges may inhibit or slow down further Li diffusion into the bulk. This study provides detailed insights of the SEI formation at the EEI, which might be crucial for the improvement of future batteries

    Targeted PI3K/AKT-hyperactivation induces cell death in chronic lymphocytic leukemia.

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    Current therapeutic approaches for chronic lymphocytic leukemia (CLL) focus on the suppression of oncogenic kinase signaling. Here, we test the hypothesis that targeted hyperactivation of the phosphatidylinositol-3-phosphate/AKT (PI3K/AKT)-signaling pathway may be leveraged to trigger CLL cell death. Though counterintuitive, our data show that genetic hyperactivation of PI3K/AKT-signaling or blocking the activity of the inhibitory phosphatase SH2-containing-inositol-5'-phosphatase-1 (SHIP1) induces acute cell death in CLL cells. Our mechanistic studies reveal that increased AKT activity upon inhibition of SHIP1 leads to increased mitochondrial respiration and causes excessive accumulation of reactive oxygen species (ROS), resulting in cell death in CLL with immunogenic features. Our results demonstrate that CLL cells critically depend on mechanisms to fine-tune PI3K/AKT activity, allowing sustained proliferation and survival but avoid ROS-induced cell death and suggest transient SHIP1-inhibition as an unexpectedly promising concept for CLL therapy

    Identifying core MRI sequences for reliable automatic brain metastasis segmentation

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    BACKGROUND Many automatic approaches to brain tumor segmentation employ multiple magnetic resonance imaging (MRI) sequences. The goal of this project was to compare different combinations of input sequences to determine which MRI sequences are needed for effective automated brain metastasis (BM) segmentation. METHODS We analyzed preoperative imaging (T1-weighted sequence ± contrast-enhancement (T1/T1-CE), T2-weighted sequence (T2), and T2 fluid-attenuated inversion recovery (T2-FLAIR) sequence) from 339 patients with BMs from seven centers. A baseline 3D U-Net with all four sequences and six U-Nets with plausible sequence combinations (T1-CE, T1, T2-FLAIR, T1-CE + T2-FLAIR, T1-CE + T1 + T2-FLAIR, T1-CE + T1) were trained on 239 patients from two centers and subsequently tested on an external cohort of 100 patients from five centers. RESULTS The model based on T1-CE alone achieved the best segmentation performance for BM segmentation with a median Dice similarity coefficient (DSC) of 0.96. Models trained without T1-CE performed worse (T1-only: DSC = 0.70 and T2-FLAIR-only: DSC = 0.73). For edema segmentation, models that included both T1-CE and T2-FLAIR performed best (DSC = 0.93), while the remaining four models without simultaneous inclusion of these both sequences reached a median DSC of 0.81-0.89. CONCLUSIONS A T1-CE-only protocol suffices for the segmentation of BMs. The combination of T1-CE and T2-FLAIR is important for edema segmentation. Missing either T1-CE or T2-FLAIR decreases performance. These findings may improve imaging routines by omitting unnecessary sequences, thus allowing for faster procedures in daily clinical practice while enabling optimal neural network-based target definitions

    Does Endogenous Technical Change Make a Difference in Climate Policy Analysis? A Robustness Exercise with the FEEM-RICE Model

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    Emissions Trading, CDM, JI, and More - The Climate Strategy of the EU

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