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Induced polarization monitoring of in-situ chemical oxidation for quantification of contaminant consumption
No full textLong Functional Graft Polymer Induced Multiscale Morphological Inversion and Enhanced Anion Transport Efficiency in Radiation-Grafted Anion Exchange Membranes
No full textAssessing the Impact of Concentration and Stacking Faults in the Aliovalent-Substituted Ionic Conductor
No full textHalide electrolytes have gained interest due to their decent conductivities in the range and wide electrochemical stability windows. The ionic transport can be influenced by changing the concentration in the structure. Due to the high cost of the rare-earth elements in the halide electrolytes, the substitution of lower-cost elements is favored. Based on the idea of changing the concentration and substituting with low-cost elements, the two substitution series and (0 ≤ ≤ 0.3) are investigated in this work. Structural information was obtained by X-ray and neutron diffraction and combined with transport properties obtained by impedance spectroscopy. Two main transport influencing factors were found: The concentration and the c/a lattice parameter. The occupation of the -only layers seems to affect the lattice parameter in the c-direction. However, the structural refinement was not straightforward as stacking faults appear in layered halide materials that complicate the refinements, and the substitution with seems to influence the extent of stacking fault formation. Overall, this work highlights the need to consider several factors in halide materials to correlate the structure–transport processes
Positron emission intensity in the decay of 72As for use in PET studies
No full text72As is a β+-emitter (T1/2 = 26.0 h; Eβ+ = 1.17 MeV,Iβ+ = 87.8 %) that can be produced at a cyclotron and has significant potential for use in PET studies. Experiments have been undertaken to determine its positron emission intensity with greater precision. Thin enriched 72Ge targets were irradiated with protons of energies around 9 MeV at the cyclotron BC1710 of the Forschungszentrum Jülich. Three different counting methods were used: high-resolution γ-ray spectroscopy, beta counting and X-ray spectroscopy. The major γ-ray peaks of 72As formed via the 72Ge(p,n)72As reaction were analysed to calculate its absolute radioactivity, while the annihilation radiation was characterized by a careful analysis of the 511 keV peak. Beta counting of the same samples was undertaken over a long period of time to validate the results. X-ray counting was also carried out to obtain the integral decay of 72As via electron capture (EC).The measurements furnished a total positron decay (87.3 ± 3.7 %) and total EC decay (12.7 ± 0.6 %). These experimental values agree with those deduced from a detailed evaluation of the decay scheme of 72As
Alterations of neurofluid transport in patients with obstructive sleep apnea and insomnia disorder
No full textSleep appears to modulate brain-wide neurofluid transport, encompassing the movement and exchange of cerebrospinal and interstitial fluids via perivascular pathways. However, neurofluid transport in common sleep disorders, such as insomnia disorder and obstructive sleep apnea, requires further assessment. In this study, we recruited 159 participants: patients with moderate to severe obstructive sleep apnea (n = 36) or chronic insomnia disorder (n = 62), and healthy controls (n = 61). Participants underwent structural magnetic resonance imaging, polysomnography, the Pittsburgh Sleep Quality Index, and the STOP-Bang questionnaires. Here, neurofluid transport is indirectly assessed using two noninvasive MRI indices (i.e., the perivascular space volume fraction and diffusion tensor imaging along perivascular spaces). Patients with obstructive sleep apnea exhibited a significantly larger perivascular space volume fraction compared with patients with insomnia disorder (p = 0.042) and healthy controls (p = 0.032), whereas no group differences were observed for the diffusion-based index. Partial correlation analyses, adjusted for age, sex, and body mass index, revealed that in obstructive sleep apnea, a larger perivascular space volume fraction was associated with less sleep disturbance (r = −0.35, p = 0.04), and diffusion measures increased with snoring severity (r = 0.38, p = 0.03). In insomnia disorder, a larger perivascular space volume fraction was associated with a higher nocturnal wake index (r = 0.38, p = 0.006) and an elevated risk of blood pressure (r = 0.50, p < 0.001), while inversely relating to subjective sleep quality (r = −0.35, p = 0.01). Our results highlight different patterns of neurofluid transport alterations across obstructive sleep apnea and insomnia disorder
Optimizing Edge AI Models on HPC Systems with the Edge in the Loop
No full textArtificial Intelligence (AI) and Machine Learning (ML) models deployed on edge devices, e.g., for quality control in Additive Manufacturing (AM), are frequently small in size. Such models usually have to deliver highly accurate results within a short time frame. Methodsthat are commonly employed in literature start out with larger trained models and try to reduce their memory and latency footprint by structural pruning, knowledge distillation, or quantization. It is, however, also possible to leverage hardware-aware Neural Architecture Search (NAS), an approach that seeks to systematically explore the architecture space to find optimized configurations. In this study, a hardware-aware NAS workflow is introduced that couples an edge device located in Belgium with a powerful High-Performance Computing (HPC) system in Germany, to train possible architecture candidates as fast as possible while performing real-time latency measurements on the target hardware. The approach is verified on a use case in the AM domain, based on the open RAISE-LPBF dataset, achieving ≈ 8.8 times faster inference speed while simultaneously enhancing model quality by a factor of ≈ 1.35, compared to a human-designed baseline
Coarse-grained physics-based modelling for tape casting of fuel-electrode supports in Solid Oxide Cells
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