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Abstract Quasi-periodic pulsations (QPPs) are frequently detected in solar and stellar flares, but the underlying physical mechanisms are still to be ascertained. Here, we show microwave QPPs during a solar flare originating from quasi-periodic magnetic reconnection at the flare current sheet. They appear as two vertically detached but closely related sources with the brighter ones located at flare loops and the weaker ones along the stretched current sheet. Although the brightness temperatures of the two microwave sources differ greatly, they vary in phase with periods of about 10–20 s and 30–60 s. The gyrosynchrotron-dominated microwave spectra also present a quasi-periodic soft-hard-soft evolution. These results suggest that relevant high-energy electrons are accelerated by quasi-periodic reconnection, likely arising from the modulation of magnetic islands within the current sheet as validated by a 2.5-dimensional magnetohydrodynamic simulation. 

Sr(Ti 0.3 Fe 0.7 )O 3−δ (STF) and the associated exsolution electrodes Sr 0.95 (Ti 0.3 Fe 0.63 Ru 0.07 )O 3−δ (STFR), or Sr 0.95 (Ti 0.3 Fe 0.63 Ni 0.07 )O 3−δ (STFN) are alternatives to Ni-based cermet fuel electrodes for solid oxide electrochemical cells (SOCs). They can provide improved tolerance to redox cycling and fuel impurities, and may allow direct operation with hydrocarbon fuels. However, such perovskite-oxide-based electrodes present processing challenges for co-sintering with thin electrolytes to make fuel electrode supported SOCs. Thus, they have been mostly limited to electrolyte-supported SOCs. Here, we report the first example of the application of perovskite oxide fuel electrodes in novel oxygen electrode supported SOCs (OESCs) with thin YSZ electrolytes, and demonstrate their excellent performance. The OESCs have La 0.8 Sr 0.2 MnO 3−δ –Zr 0.92 Y 0.16 O 2−δ (LSM–YSZ) oxygen electrode-supports that are enhanced via infiltration of SrTi 0.3 Fe 0.6 Co 0.1 O 3−δ , while the fuel electrodes are either Ni-YSZ, STF, STFN, or STFR. Fuel cell power density as high as 1.12 W cm −2 is obtained at 0.7 V and 800 °C in humidified hydrogen and air with the STFR electrode, 60% higher than the same cell made with a Ni-YSZ electrode. Electrolysis current density as high as −1.72 A cm −2 is obtained at 1.3 V and 800 °C in 50% H 2 O to 50% H 2 mode; the STFR cell yields a value 72% higher than the same cell made with a Ni-YSZ electrode, and competitive with the widely used conventional Ni-YSZ-supported cells. The high performance is due in part to the low resistance of the thin YSZ electrolyte, and also to the low fuel electrode polarization resistance, which decreases with fuel electrode in the order: Ni-YSZ > STF > STFN > STFR. The high performance of the latter two electrodes is due to exsolution of catalytic metal nanoparticles; the results are discussed in terms of the microstructure and properties of each electrode material, and surface oxygen exchange resistance values are obtained over a range of conditions for STF, STFN, and STFN. The STF fuel electrodes also provide good stability during redox cycling. 

We consider how to generate graphs of arbitrary size whose chromatic numbers can be chosen (or are well-bounded) for testing graph coloring algorithms on parallel computers. For the distance-1 graph coloring problem, we identify three classes of graphs with this property. The first is the Erdős-Rényi random graph with prescribed expected degree, where the chromatic number is known with high probability. It is also known that the Greedy algorithm colors this graph using at most twice the number of colors as the chromatic number. The second is a random geometric graph embedded in hyperbolic space where the size of the maximum clique provides a tight lower bound on the chromatic number. The third is a deterministic graph described by Mycielski, where the graph is recursively constructed such that its chromatic number is known and increases with graph size, although the size of the maximum clique remains two. For Jacobian estimation, we bound the distance-2 chromatic number of random bipartite graphs by considering its equivalence to distance-1 coloring of an intersection graph. We use a “balls and bins” probabilistic analysis to establish a lower bound and an upper bound on the distance-2 chromatic number. The regimes of graph sizes and probabilities that we consider are chosen to suit the Jacobian estimation problem, where the number of columns and rows are asymptotically nearly equal, and have number of nonzeros linearly related to the number of columns. Computationally we verify the theoretical predictions and show that the graphs are often be colored optimally by the serial and parallel Greedy algorithms. 

Sr(Ti 1−x Fe x )O 3−δ (STF) has recently been explored as an oxygen electrode for solid oxide electrochemical cells (SOCs). Model thin film electrode studies show oxygen surface exchange rates that generally improve with increasing Fe content when x < 0.5, and are comparable to the best Co-containing perovskite electrode materials. Recent results on porous electrodes with the specific composition Sr(Ti 0.3 Fe 0.7 )O 3−δ show excellent electrode performance and stability, but other compositions have not been tested. Here we report results for porous electrodes with a range of compositions from x = 0.5 to 0.9. The polarization resistance decreases with increasing Fe content up to x = 0.7, but increases for further increases in x . This results from the interaction of two effects – the oxygen solid state diffusion coefficient increases with increasing x , but the electrode surface area and surface oxygen exchange rate decrease due to increased sinterability and Sr surface segregation for the Fe-rich compositions. Symmetric cells showed no degradation during 1000 h life tests at 700 °C even at a current density of 1.5 A cm −2 , showing that all the STF electrode compositions worked stably in both fuel cell mode and electrolysis modes. The excellent stability may be explained by X-ray Photoelectron Spectroscopy (XPS) results showing that the amount of surface segregated Sr did not change during the long-term testing, and by relatively low polarization resistances that help avoid electrode delamination. 

This white paper is on the HMCS Firefly mission concept study. Firefly focuses on the global structure and dynamics of the Sun's interior, the generation of solar magnetic fields, the deciphering of the solar cycle, the conditions leading to the explosive activity, and the structure and dynamics of the corona as it drives the heliosphere. 

In‐memory computing is a computing scheme that integrates data storage and arithmetic computation functions. Resistive random access memory (RRAM) arrays with innovative peripheral circuitry provide the capability of performing vector‐matrix multiplication beyond the basic Boolean logic. With such a memory–computation duality, RRAM‐based in‐memory computing enables an efficient hardware solution for matrix‐multiplication‐dependent neural networks and related applications. Herein, the recent development of RRAM nanoscale devices and the parallel progress on circuit and microarchitecture layers are discussed. Well suited for analog synapse and neuron implementation, RRAM device properties and characteristics are emphasized herein. 3D‐stackable RRAM and on‐chip training are introduced in large‐scale integration. The circuit design and system organization of RRAM‐based in‐memory computing are essential to breaking the von Neumann bottleneck. These outcomes illuminate the way for the large‐scale implementation of ultra‐low‐power and dense neural network accelerators.