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Reactivity studies of the GeII→B complex L(Cl)Ge⋅BH3 ( 1 ; L=2-Et2NCH2-4,6-tBu2-C6H2) were performed to determine the effect on the GeII→B donation. N-coordinated compounds L(OtBu)Ge⋅BH3 ( 2 ) and [LGe⋅BH3]2 ( 3 ) were prepared. The possible tuning of the GeII→B interaction was proved experimentally, yielding compounds 1-PPh2-8-(LGe)-C10H6 ( 4 ) and L(Cl)Ge⋅GaCl3 ( 5 ) without a GeII→B interaction. In 5 , an unprecedented GeII→Ga coordination was revealed. The experimental results were complemented by a theoretical study focusing on the bonding in 1 − 5 . The different strength of the GeII→E (E=B, Ga) donation was evaluated by using energy decomposition analysis. The basicity of different L(X)Ge groups through proton affinity is also assessed.  相似文献   
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Riociguat is novel antihypertensive drug for treatment of pulmonary hypertension. As such, it is still being tested in many clinical and pharmacokinetic trials. Existing methods that determine serum riociguat and desmethylriociguat (DMR) are based solely on liquid chromatography with mass spectrometry. Therefore, we present a novel capillary electrophoresis with mass spectrometry method (CE-MS) for their determination in human serum as alternative method for ongoing trials. Complete resolution of both analytes was achieved by means of pH optimization of ammonium formate background electrolytes that are fully compatible with ESI/MS detection. Simple liquid-liquid extraction was used as sample pretreatment. The calibration dependence of the method was linear (in the range of 10–1000 ng/mL), with adequate accuracy (90.1–114.9%) and precision (13.4%). LOD and LOQ were arbitrarily set at 10 ng/mL for both analytes. Clinical applicability was validated using serum samples from patients treated with riociguat in pharmacokinetic study and the results corresponded with reference HPLC-MS/MS values. Capillary electrophoresis proved to be sensitive and selective tool for the analysis of riociguat and DMR.  相似文献   
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There are thousands of papers published every year investigating the properties and possible applications of ionic liquids. Industrial use of these exceptional fluids requires adequate understanding of their physical properties, in order to create the ionic liquid that will optimally suit the application. Computational property prediction arose from the urgent need to minimise the time and cost that would be required to experimentally test different combinations of ions. This review discusses the use of machine learning algorithms as property prediction tools for ionic liquids (either as standalone methods or in conjunction with molecular dynamics simulations), presents common problems of training datasets and proposes ways that could lead to more accurate and efficient models.

In this review article, the authors discuss the use of machine learning algorithms as tools for the prediction of physical and chemical properties of ionic liquids.  相似文献   
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Monatshefte für Chemie - Chemical Monthly - The voltammetric behavior of 5-nitroindazole was investigated at polished (p-AgSAE) and at mercury meniscus-modified (m-AgSAE) silver solid amalgam...  相似文献   
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The nonlinear frequency response analysis (NFRA) can be seen as an extension of electrochemical impedance spectroscopy. NFRA gives a full and detailed representation of the system response and can establish a connection between model parameters and the experimentally observed phenomena. In this article, different theoretical NFRA approaches and the most recent application examples are discussed. A simple electrochemical example is used to showcase the benefits and disadvantages of analyzing the system response by using different approaches. In addition, it was shown how to extract experimental harmonic values and analyze them.  相似文献   
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