A common behavior of thermoelectric layered cobaltites: incommensurate spin density wave states in [Ca2_2Co4/3_{4/3}Cu2/3_{2/3}O4_4]0.62_{0.62}[CoO2_2] and [Ca2_2CoO3_3]0.62_{0.62}[CoO2_2]

Magnetism of a misfit layered cobaltite [Ca$_2$Co$_{4/3}$Cu$_{2/3}$O$_4$]$_x^{\rm RS}$[CoO$_2$] ($x \sim$ 0.62, RS denotes a rocksalt-type block) was investigated by a positive muon spin rotation and relaxation ($\mu^+$SR) experiment. A transition to an incommensurate ({\sf IC}) spin density wave ({\sf SDW}) state was found below 180 K (= $T_{\rm C}^{\rm on}$); and a clear oscillation due to a static internal magnetic field was observed below 140 K (= $T_{\rm C}$). Furthermore, an anisotropic behavior of the zero-field $\mu^+$SR experiment indicated that the {\sf IC-SDW} propagates in the $a$-$b$ plane, with oscillating moments directed along the c axis. These results were quite similar to those for the related compound [Ca$_2$CoO$_3$]$_{0.62}^{\rm RS}$[CoO$_2$], {\sl i.e.}, Ca$_3$Co$_4$O$_9$. Since the {\sf IC-SDW} field in [Ca$_2$Co$_{4/3}$Cu$_{2/3}$O$_4$]$_{0.62}^{\rm RS}$[CoO$_2$] was approximately same to those in pure and doped [Ca$_2$CoO$_3$]$_{0.62}^{\rm RS}$[CoO$_2$], it was concluded that the {\sf IC-SDW} exist in the [CoO$_2$] planes.Comment: 15 pages, 6 figures. accepted for publication in J. Phys.: Condens. Matte

Hidden magnetic transitions in thermoelectric layered cobaltite, [Ca2_2CoO3_3]0.62_{0.62}[CoO2_2]

A positive muon spin rotation and relaxation ($\mu^+$SR) experiment on [Ca$_2$CoO$_3$]$_{0.62}$[CoO$_2$], ({\sl i.e.}, Ca$_3$Co$_4$O$_9$, a layered thermoelectric cobaltite) indicates the existence of two magnetic transitions at $\sim$ 100 K and 400 - 600 K; the former is a transition from a paramagnetic state to an incommensurate ({\sf IC}) spin density wave ({\sf SDW}) state. The anisotropic behavior of zero-field $\mu^+$SR spectra at 5 K suggests that the {\sf IC-SDW} propagates in the $a$-$b$ plane, with oscillating moments directed along the c-axis; also the {\sf IC-SDW} is found to exist not in the [Ca$_2$CoO$_3$] subsystem but in the [CoO$_2$] subsystem. In addition, it is found that the long-range {\sf IC-SDW} order completes below $\sim$ 30 K, whereas the short-range order appears below 100 K. The latter transition is interpreted as a gradual change in the spin state of Co ions %% at temperatures above 400 K. These two magnetic transitions detected by $\mu^+$SR are found to correlate closely with the transport properties of [Ca$_2$CoO$_3$]$_{0.62}$[CoO$_2$].Comment: 7 pages, 8 figures. to be appeared in Phys. Rev.

Static magnetic order in Na0.75_{0.75}CoO2_2 detected by muon spin rotation and relaxation

The nature of the magnetic transition of the Na-rich thermoelectric Na$_{0.75}$CoO$_2$ at 22K was studied by positive muon-spin-rotation and relaxation ($\mu^+$SR) spectroscopy, using a polycrystalline sample in the temperature range between 300 and 2.5 K. Zero field $\mu$SR measurements indicated the existence of a static internal magnetic field at temperatures below 22 K (= $T_{\rm m}$). The observed muon spin precession signal below $T_{\rm m}$ consisted of three components with different precession frequencies, corresponding to three inequivalent muon$^+$ sites in the Na$_{0.75}$CoO$_2$ lattice. The total volume fraction of the three components was estimated as $\sim$21% at 2.5 K; thus, this magnetic transition was not induced by impurities but is an intrinsic change in the magnetism of the sample, although the sample was magnetically inhomogeneous otherwise. On the other hand, a similar experiment on a Na$_{0.65}$CoO$_2$ sample exhibited no magnetic transition down to 2.5 K; which indicates that the average valence of the Co ions is responsible for inducing the magnetic transition at 22 K.Comment: 5 pages, 4 figures, Phys. Rev. B 68 (2003) in pres

Cross-Dehydrogenative Couplings between Indoles and β-Keto Esters : Ligand-Assisted Ligand Tautomerization and Dehydrogenation via a Proton-Assisted Electron Transfer to Pd(II)

Cross-dehydrogenative coupling reactions between -ketoesters and electron-rich arenes, such as indoles, proceed with high regiochemical fidelity with a range of -ketoesters and indoles. The mechanism of the reaction between a prototypical -ketoester, ethyl 2-oxocyclopentanonecarboxylate and N-methylindole, has been studied experimentally by monitoring the temporal course of the reaction by 1H NMR, kinetic isotope effect studies, and control experiments. DFT calculations have been carried out using a dispersion-corrected range-separated hybrid functional (B97X-D) to explore the basic elementary steps of the catalytic cycle. The experimental results indicate that the reaction proceeds via two catalytic cycles. Cycle A, the dehydrogenation cycle, produces an enone intermediate. The dehydrogenation is assisted by N-methylindole, which acts as a ligand for Pd(II). The compu-tational studies agree with this conclusion, and identify the turnover-limiting step of the dehydrogenation step, which involves a change in the coordination mode of the -keto ester ligand from an O,O’-chelate to an C-bound Pd enolate. This ligand tautom-erization event is assisted by the -bound indole ligand. Subsequent scission of the ’-C–H bond takes place via a proton-assisted electron transfer mechanism, where Pd(II) acts as an electron sink and the trifluoroacetate ligand acts as a proton acceptor, to pro-duce the Pd(0) complex of the enone intermediate. The coupling is completed in cycle B, where the enone is coupled with indole. Pd(TFA)2 and TFA-catalyzed pathways were examined experimentally and computationally for this cycle, and both were found to be viable routes for the coupling step

Communication-oriented model fine-tuning for packet-loss resilient distributed inference under highly lossy IoT networks

Abstract The distributed inference (DI) framework has gained traction as a technique for real-time applications empowered by cutting-edge deep machine learning (ML) on resource-constrained Internet of things (IoT) devices. In DI, computational tasks are offloaded from the IoT device to the edge server via lossy IoT networks. However, generally, there is a communication system-level trade-off between communication latency and reliability; thus, to provide accurate DI results, a reliable and high-latency communication system is required to be adapted, which results in non-negligible end-to-end latency of the DI. This motivated us to improve the trade-off between the communication latency and accuracy by efforts on ML techniques. Specifically, we have proposed a communication-oriented model tuning (COMtune), which aims to achieve highly accurate DI with low-latency but unreliable communication links. In COMtune, the key idea is to fine-tune the ML model by emulating the effect of unreliable communication links through the application of the dropout technique. This enables the DI system to obtain robustness against unreliable communication links. Our ML experiments revealed that COMtune enables accurate predictions with low latency and under lossy networks