AbstractThe AV3Sb5 prototype kagome materials have been demonstrated as a versatile platform for exploring exotic properties in condensed matter physics, including charge density waves, superconductivity, non-trivial electron topology, as well as topological superconductivity. Here we identify that ANb3Bi5 (A = K, Rb, Cs) exhibit non-trivial coexisting superconductivity and topological properties via first-principles calculations. The negative formation energy and the absence of imaginary phonon dispersion demonstrate both thermodynamics and dynamics stabilities of ANb3Bi5 (A = K, Rb, Cs) under ambient conditions. By analytically solving the Allen-Dynes-modified McMillan formula, the superconducting transition temperatures are predicted to be 2.11, 2.15 and 2.21 K for KNb3Bi5, RbNb3Bi5, and CsNb3Bi5, respectively. More importantly, the kagome materials proposed here can be classified into $${{\mathbb{Z}}}_{2}$$ Z 2 topological metals due to the non-trivial topological index and the obvious surface states around the Fermi level. Such coexistence of superconductivity and non-trivial band characters in ANb3Bi5 (A = K, Rb, Cs) offer us more insights to study the relationship between superconductivity and topological properties, and to design innate topological superconductors.
Epilepsy is a common neurological disease that affects a wide range of the world population and is not limited by age. Moreover, seizures can occur anytime and anywhere because of the sudden abnormal discharge of brain neurons, leading to malfunction. The seizures of approximately 30% of epilepsy patients cannot be treated with medicines or surgery; hence these patients would benefit from a seizure prediction system to live normal lives. Thus, a system that can predict a seizure before its onset could improve not only these patients’ social lives but also their safety. Numerous seizure prediction methods have already been proposed, but the performance measures of these methods are still inadequate for a complete prediction system. Here, a seizure prediction system is proposed by exploring the advantages of multivariate entropy, which can reflect the complexity of multivariate time series over multiple scales (frequencies), called multivariate multiscale modified-distribution entropy (MM-mDistEn), with an artificial neural network (ANN). The phase-space reconstruction and estimation of the probability density between vectors provide hidden complex information. The multivariate time series property of MM-mDistEn provides more understandable information within the multichannel data and makes it possible to predict of epilepsy. Moreover, the proposed method was tested with two different analyses: simulation data analysis proves that the proposed method has strong consistency over the different parameter selections, and the results from experimental data analysis showed that the proposed entropy combined with an ANN obtains performance measures of 98.66% accuracy, 91.82% sensitivity, 99.11% specificity, and 0.84 area under the curve (AUC) value. In addition, the seizure alarm system was applied as a postprocessing step for prediction purposes, and a false alarm rate of 0.014 per hour and an average prediction time of 26.73 min before seizure onset were achieved by the proposed method. Thus, the proposed entropy as a feature extraction method combined with an ANN can predict the ictal state of epilepsy, and the results show great potential for all epilepsy patients.
AbstractThe clathrate Cs8–xGa8–ySi38+y was obtained from a stoichiometric reaction of the elements in an alkali metal halide flux, whereas K8Zn3.5Si42.5 and Rb7.9Zn3.6Si42.4 were synthesized using a combined alkali metal halide/zinc flux. These methods allow to get virtually single‐phase materials with good crystallinity. The compounds were analyzed and characterized by means of powder and single‐crystal X‐ray diffraction methods. Rather unexpectedly, the substitution of Si by Zn in K8Zn3.5Si42.5 and Rb7.9Zn3.6Si42.4 also occurs at the atomic site 24k beside the usually observed 6c site, which has not been found before for intermetallic clathrates with alkali metal guest atoms and substitution of the host atom by group 12 elements. The size effect of the guest atoms Rb and Cs on the alkali metal content of Ga‐Si and Zn‐Si clathrates is established. Furthermore, magnetic and transport measurements (electrical resistivity, Seebeck coefficient and thermal conductivity) are reported.
Single crystals of clathrate-II A8Na16Si136 (A = K, Rb, Cs) were synthesized by spark plasma sintering by simultaneous electrochemical redox and ion-exchange reactions.
By implanting Co and Fe in sequence into Si (111), metastable ternary Co1−xFexSi2 phases were formed. Mössbauer effect measurements showed three resonance line components in the spectrum. Comparison of the central shift (CS) values of the components with those appearing in the stable ternary phases indicated that iron atoms are positioned in the substitutional Co site, in the empty cube of the fluorite-type lattice and in CsCl-like B2 structures. It was found that the CS values of two components are in the velocity range of the values obtained for the metastable γ-FeSi2 synthesized using various methods. This result suggests the existence of a similar structure.
Silicon surfaces having native oxides were implanted with 3 keV Cs+ ions and annealed. Implanted doses of 1, 1.7, and 3×1016 Cs/cm2 led to room-temperature work functions with stable, reproducible values of 2.3±0.15 eV after vacuum annealing at 100–560 °C. The resulting surfaces have been characterized with regard to the amount of Cs retained, the thermal and environmental stability of the work function, and the composition and chemistry of the implanted layer. The surface layers consisted of a compound of Si–Cs–O, which is compositionally stable to temperatures of ∼400 °C in vacuum. In addition, we found that these surfaces are stable with regard to exposures to background gases and ambient air.