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Two composition series of Zr‐deficient NaSICON materials are investigated with respect to their ionic and thermal transport properties. The bulk conductivity varies between 1.4 and 6.6 mS cm⁻¹. The total conductivity showdecreasing values with increasing Zr deficiency due to the impact of the increasing fraction of glass phase. The calculated grain boundary conductivity is about two orders of magnitude lower than the total conductivity but does not correspond to the conductivity of any known glass composition of sodium silicates/phosphates. Nuclear magnetic resonance reveals three ²³Na relaxation rates, the fastest of which is attributed to the NaSICON phase and the two slower relaxation rates to sodium orthophosphates and the glass phase. Thermal conductivity varies between 0.9 and 1.0 W m⁻¹ K⁻¹ at 25 °C. At elevated temperatures, a clear trend is observed toward lower thermal conductivity with a higher glass fraction. In addition, atom probe tomography is applied to precisely quantify the composition of specific microstructural regions found within the glassy phase. A scanning electron microscopy study of the surfaces of sintered pellets shows an increasing amount of glass phase between the NaSICON particles with increasing Zr deficiency. Furthermore, a time‐dependent phase separation is observed in relation to the dynamic formation and dissolution of Na3PO4 domains.
Zusammenfassung Mit der Veröffentlichung von ChatGPT Ende November 2022 begann ein Hype um das Thema Generative KI, der bis heute anhält. Die Art und Weise, wie sich diese neue Technologie auf vielfältige Weise nutzen lässt, führt dazu, dass inzwischen insbesondere Große Sprachmodelle (Large Language Models, kurz: LLM) auf vielfältige Art und Weise in andere Prozesse und größere Systeme integriert werden. Dadurch ergeben sich bis dato unbekannte Sicherheitsrisiken, deren Mitigation aufgrund der stetigen Weiterentwicklungen in diesem Bereich eine Herausforderung darstellt, die aktuell noch nicht adäquat bewältigt wird. In diesem Artikel beschreiben wir ausgewählte Risiken, Testmöglichkeiten und Gegenmaßnahmen und skizzieren, wie die weitere Entwicklung im Bereich der Absicherung von LLMs aus unserer Sicht verlaufen sollte.
Most current Data Center Interconnects (DCI) use intensity modulation direct detection (IMDD) configurations due to their low complexity and cost. However, significant scaling challenges allow coherent solutions to become contenders in these short reach applications. We present an O-band coherent optical fiber transmission system based on Quantum Dot—Mode Locked Lasers (QD-MLLs) using two independent free-running comb lasers, one each for the carrier and the Local Oscillator (LO). Using a comb-to-comb configuration, we demonstrate a 10 km single mode fiber, O-band, coherent, heterodyne, 12.1 Tbps system operating at 0.47 Tbps/λ using 26 λs. We used fewer comb lines (26 λs), faster symbol rate (56 GBaud) and higher constellation cardinality (32 QAM) relative to the highest capacity C-band systems reported to date. Through design, analysis, and experimentation, we quantify the optimum comb line spacing for this use case. We compare potential configurations for increasing data center interconnect capacities whilst reducing power consumption, complexity, and cost.
The copper slate deposit of the Mansfeld copper mining area was mined in the 19th and 20th century. Mineral collectors can still find traces of copper smelting activities on the slag heaps of the various copper smelters. A piece from the Krug smelter slag heap mainly consists of Cu and Fe sulfides. The piece in question might be the intermediate product copper matte. The pieces from Hettstedt and the August Bebel smelter contain clearly visible metallic copper. The Hettstedt specimen might be a piece of furnace lining with adhering slag. Cr and Mg could be found, suggesting that chromium magnesia was used as refractory material. The piece from the August Bebel smelter contains up to 18 wt. % Cu. It does, however, not contain any sulfur. It is most likely Fe2SiO4 slag (fayalite) with a high proportion of FeO. The presence of Sn and Zn suggests that this slag was formed during the processing of bronze or brass.
Recently, the feasibility of differential-mode power detection for built-in self-test (BIST) in millimeter-wave SiGe transceiver front ends has been demonstrated. In this work, a system analysis of typical BIST scenarios is performed. Specifications for the input power levels as well as the accuracy of power detectors are derived from this analysis. A need for at least two different differential detector architectures is identified. Two detectors are derived from the differential power measurement concept, analyzed, and implemented in the 76–81-GHz automotive radar frequency band. They feature a low power consumption of 500 μ\mu W and, to the authors’ best knowledge, the lowest published circuit areas of approximately 0.005 mm 2^2 while still being input matched to the differential 100 Ω\Omega system impedance. Both these characteristics are essential to keep the overhead of the BIST minimal. With dynamic ranges of 30 dB and up to 46 dB for the two different architectures, the differential power detector concept can achieve sufficient performance for BIST applications. The robustness against process and temperature effects as well as noise is analyzed and reported for both detectors.
In this study, we explore the potential of generative pre-trained transformer (GPT), as a coding assistant for MRI sequence programming using the Pulseq framework. The programming of MRI sequences is traditionally a complex and time-consuming task, and the Pulseq standard has recently simplified this process. It allows researchers to define and generate complex pulse sequences used in MRI experiments. Leveraging GPT-4’s capabilities in natural language generation, we adapted it for MRI sequence programming, creating a specialized assistant named GPT4MR. Our tests involved generating various MRI sequences, revealing that GPT-4, guided by a tailored prompt, outperformed GPT-3.5, producing fewer errors and demonstrating improved reasoning. Despite limitations in handling complex sequences, GPT4MR corrected its own errors and successfully generated code with step-by-step instructions. The study showcases GPT4MR’s ability to accelerate MRI sequence development, even for novel ideas absent in its training set. While further research and improvement are needed to address complexity limitations, a well-designed prompt enhances performance. The findings propose GPT4MR as a valuable MRI sequence programming assistant, streamlining prototyping and development. The future prospect involves integrating a PyPulseq plugin into lightweight, open-source LLMs, potentially revolutionizing MRI sequence development and prototyping.
Anode changes cause strong recurring disturbances of the Hall-Héroult process during smelter operations. Depending on its position, each anode change triggers a specific redistribution of anode currents. This pushes the cell into a different magnetohydrodynamic regime with a changed metal/melt flow behavior and metal pad deformation. We have combined a magnetohydrodynamic model based on computational fluid dynamics (MHD-CFD) with an equivalent electric circuit cell model (EECCM) to account for the dynamic coupling between magnetic field, metal/melt flow, metal pad shape, and anode current distribution. The model integrates all dominant resistance contributions and allows cell voltage drop or anode–cathode distance (ACD) to be calibrated through simulated anode beam movements. Based on numerical results, cell responses from individual anode current changes and their effect on cell stability are evaluated. Predicted individual anode currents shortly before and after anode replacements are compared with measurement data and found to be in good agreement.
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