Water in Alkali Aluminosilicate Glasses

To understand the influence of water and alkalis on aluminosilicate glasses, three polymerized glasses with varying ratios of Na/K were synthesized [(22. 5-x)Na2O-xK2O-22.5 Al2O3-55 SiO2 with x = 0, 7.5, and 11.25]. Subsequently, these glasses were hydrated (up to 8 wt% H2O) in an internally heated gas pressure vessel. The density of hydrous glasses linearly decreased with water content above 1 wt%, consistent with the partial molar volume of H2O of 12 cm3/mol. Near-infrared spectroscopy revealed that hydroxyl groups are the dominant species at water content of <4 wt%, and molecular water becomes dominating at water content of >5 wt%. The fraction of OH is particularly high in the pure Na-bearing glass compared to the mixed alkali glasses. 27Al magic angle spinning-NMR spectroscopy shows that aluminum is exclusively fourfold coordinated with some variations in the local geometry. It appears that the local structure around Al becomes more ordered with increasing K/Na ratio. The incorporation of H2O reinforces this effect. The differential thermal analysis of hydrous glasses shows a significant mass loss in the range of glass transition already during the first upscan, implying the high mobility of water in the glasses. This observation can be explained by the open structure of the aluminosilicate network and by the low dissociation enthalpy of H2O in the glasses (≈ 8 kJ/mol). The effect of the dissolved H2O on the glass transition temperature is less pronounced than for other aluminosilicate glasses, probably because of the large fraction of Al in the glasses. © Copyright © 2020 Balzer, Behrens, Waurischk, Reinsch, Müller, Kiefer, Deubener and Fechtelkord

Automated Analysis of Slow Crack Growth in Hydrous Soda-Lime Silicate Glasses

To explore the impact of ambient and structural water on static fatigue, the initiation and growth of 3279 Vickers induced median radial cracks were automatically recorded and analyzed. We find that humidity is more efficient in initiating cracks and promoting their growth than water, which is dissolved in the glass structure. In particular for slow crack growth (< 3 × 10–6 m s–1), tests in dry nitrogen showed a considerable decrease in the crack growth exponent with increasing water content of the glasses. On the other hand, if tests were performed in humid air, the crack growth exponent was independent of the water content of the hydrous glasses, while stress intensity decreased slightly. These observations indicate that water promotes the processes at the crack-tip regardless of its origin. However, ambient water is more efficient

Automated analysis of slow crack growth in hydrous soda-lime silicate glasses

To explore the impact of ambient and structural water on static fatigue, the initiation and growth of 3279 Vickers induced median radial cracks were automatically recorded and analyzed. We find that humidity is more efficient in initiating cracks and promoting their growth than water, which is dissolved in the glass structure. In particular for slow crack growth (< 3 × 10−6 m s−1), tests in dry nitrogen showed a considerable decrease in the crack growth exponent with increasing water content of the glasses. On the other hand, if tests were performed in humid air, the crack growth exponent was independent of the water content of the hydrous glasses, while stress intensity decreased slightly. These observations indicate that water promotes the processes at the crack-tip regardless of its origin. However, ambient water is more efficient

Mobilisation of critically ill patients receiving norepinephrine: a retrospective cohort study

Background: Mobilisation and exercise intervention in general are safe and feasible in critically ill patients. For patients requiring catecholamines, however, doses of norepinephrine safe for mobilisation in the intensive care unit (ICU) are not defined. This study aimed to describe mobilisation practice in our hospital and identify doses of norepinephrine that allowed a safe mobilisation. Methods: We conducted a retrospective single-centre cohort study of 16 ICUs at a university hospital in Germany with patients admitted between March 2018 and November 2021. Data were collected from our patient data management system. We analysed the effect of norepinephrine on level (ICU Mobility Scale) and frequency (units per day) of mobilisation, early mobilisation (within 72 h of ICU admission), mortality, and rate of adverse events. Data were extracted from free-text mobilisation entries using supervised machine learning (support vector machine). Statistical analyses were done using (generalised) linear (mixed-effect) models, as well as chi-square tests and ANOVAs. Results: A total of 12,462 patients were analysed in this study. They received a total of 59,415 mobilisation units. Of these patients, 842 (6.8%) received mobilisation under continuous norepinephrine administration. Norepinephrine administration was negatively associated with the frequency of mobilisation (adjusted difference -0.07 mobilisations per day; 95% CI - 0.09, - 0.05; p 0.1). Higher compared to lower doses of norepinephrine did not lead to a significant increase in adverse events in our practice (p > 0.1). We identified that mobilisation was safe with up to 0.20 mu g/kg/min norepinephrine for out-of-bed (IMS >= 2) and 0.33 mu g/kg/min for in-bed (IMS 0-1) mobilisation. Conclusions: Mobilisation with norepinephrine can be done safely when considering the status of the patient and safety guidelines. We demonstrated that safe mobilisation was possible with norepinephrine doses up to 0.20 mu g/kg/min for out-of-bed (IMS >= 2) and 0.33 mu g/kg/min for in-bed (IMS 0-1) mobilisation

Predicting lethal courses in critically ill COVID-19 patients using a machine learning model trained on patients with non-COVID-19 viral pneumonia

In a pandemic with a novel disease, disease-specific prognosis models are available only with a delay. To bridge the critical early phase, models built for similar diseases might be applied. To test the accuracy of such a knowledge transfer, we investigated how precise lethal courses in critically ill COVID-19 patients can be predicted by a model trained on critically ill non-COVID-19 viral pneumonia patients. We trained gradient boosted decision tree models on 718 (245 deceased) non-COVID-19 viral pneumonia patients to predict individual ICU mortality and applied it to 1054 (369 deceased) COVID-19 patients. Our model showed a significantly better predictive performance (AUROC 0.86 [95% CI 0.86-0.87]) than the clinical scores APACHE2 (0.63 [95% CI 0.61-0.65]), SAPS2 (0.72 [95% CI 0.71-0.74]) and SOFA (0.76 [95% CI 0.75-0.77]), the COVID-19-specific mortality prediction models of Zhou (0.76 [95% CI 0.73-0.78]) and Wang (laboratory: 0.62 [95% CI 0.59-0.65]; clinical: 0.56 [95% CI 0.55-0.58]) and the 4C COVID-19 Mortality score (0.71 [95% CI 0.70-0.72]). We conclude that lethal courses in critically ill COVID-19 patients can be predicted by a machine learning model trained on non-COVID-19 patients. Our results suggest that in a pandemic with a novel disease, prognosis models built for similar diseases can be applied, even when the diseases differ in time courses and in rates of critical and lethal courses

Ultra-fast detector for wide range spectral measurements

KALYPSO is a novel detector operating at line rates above 10 Mfps. The detector board holds a silicon or InGaAs linear array sensor with spectral sensitivity ranging from 400 nm to 2600 nm. The sensor is connected to a cutting-edge, custom designed, ASIC readout chip which is responsible for the remarkable frame rate. The FPGA readout architecture enables continuous data acquisition and processing in real time. This detector is currently employed in many synchrotron facilities for beam diagnostics and for the characterization of self-built Ytterbium-doped fiber laser emitting around 1050 nm with a bandwidth of 40 nm

Ultrafast linear array detector for real-time imaging

KALYPSO is a novel detector operating at line rates above 10 Mfps. It consists of a detector board connected to FPGA based readout card for real time data processing. The detector board holds a Si or InGaAs linear array sensor, with spectral sensitivity ranging from 400 nm to 2600 nm, which is connected to a custom made front-end ASIC. A FPGA readout framework performs the real time data processing. In this contribution, we present the detector system, the readout electronics and the heterogeneous infrastructure for machine learning processing. The detector is currently in use at several synchrotron facilities for beam diagnostics as well as for single-pulse laser characterizations. Thanks to the shot-to-shot capability over long time scale, new attractive applications are open up for imaging in biological and medical research

A trapped single ion inside a Bose-Einstein condensate

Improved control of the motional and internal quantum states of ultracold neutral atoms and ions has opened intriguing possibilities for quantum simulation and quantum computation. Many-body effects have been explored with hundreds of thousands of quantum-degenerate neutral atoms and coherent light-matter interfaces have been built. Systems of single or a few trapped ions have been used to demonstrate universal quantum computing algorithms and to detect variations of fundamental constants in precision atomic clocks. Until now, atomic quantum gases and single trapped ions have been treated separately in experiments. Here we investigate whether they can be advantageously combined into one hybrid system, by exploring the immersion of a single trapped ion into a Bose-Einstein condensate of neutral atoms. We demonstrate independent control over the two components within the hybrid system, study the fundamental interaction processes and observe sympathetic cooling of the single ion by the condensate. Our experiment calls for further research into the possibility of using this technique for the continuous cooling of quantum computers. We also anticipate that it will lead to explorations of entanglement in hybrid quantum systems and to fundamental studies of the decoherence of a single, locally controlled impurity particle coupled to a quantum environment