Superconducting topological Dirac semimetals: P6/mP6/m-Si6_6 and P6/mP6/m-NaSi6_6

We theoretically propose that hexagonal silicon-based crystals, $P6/m$-Si$_6$ and $P6/m$-NaSi$_6$, are topological Dirac semimetals with superconducting critical temperatures of 12 K and 13 K, respectively, at ambient pressure. Band inversion occurs with the Fu-Kane topological invariant $\mathbb{Z}_2=1$, even in the absence of spin-orbit coupling. The Dirac nodes protected by $C_6$ crystal rotational symmetry remain gapless with spin-orbit coupling. Using first-principles calculations, we find pressure-induced topological phase transitions for $P6/m$-Si$_6$ and $P6/m$-NaSi$_6$ with critical external pressures of 11.5 GPa and 14.9 GPa, respectively. Above the critical pressures, the Dirac bands are gapped with $\mathbb{Z}_2=0$, while the superconducting states and the crystal symmetries are retained.Our results may shed light into a search for silicon-based topological materials with superconductivity.Comment: 12 pages, 11 figure

Viable stretchable plasmonics based on unidirectional nanoprisms

Well-defined ordered arrays of plasmonic nanostructures were fabricated on stretchable substrates and tunable plasmon-coupling-based sensing properties were comprehensively demonstrated upon extension and contraction. Regular nanoprism patterns consisting of Ag, Au and Ag/Au bilayers were constructed on the stretchable polydimethylsiloxane substrate. The nanoprisms had the same orientation over the entire substrate (3 x 3 cm(2)) via metal deposition on a single-crystal microparticle monolayer assembly. The plasmonic sensor based on the Ag/Au bilayer showed a 6-fold enhanced surface enhanced Raman scattering signal under 20% uniaxial extension, whereas a 3-fold increase was observed upon 6% contraction, compared with the Au nanoprism arrays. The sensory behaviors were corroborated by finite-difference time-domain simulation, demonstrating the tunable electromagnetic field enhancement effect via the localized surface plasmon resonance coupling. The advanced flexible plasmonic-coupling-based devices with tunable and quantifiable performance herein suggested are expected to unlock promising potential in practical bio-sensing, biotechnological applications and optical devices.11Ysciescopu

Quantum Interference in Superconducting Wire Networks and Josephson Junction Arrays: Analytical Approach based on Multiple-Loop Aharonov-Bohm Feynman Path-Integrals

We investigate analytically and numerically the mean-field superconducting-normal phase boundaries of two-dimensional superconducting wire networks and Josephson junction arrays immersed in a transverse magnetic field. The geometries we consider include square, honeycomb, triangular, and kagome' lattices. Our approach is based on an analytical study of multiple-loop Aharonov-Bohm effects: the quantum interference between different electron closed paths where each one of them encloses a net magnetic flux. Specifically, we compute exactly the sums of magnetic phase factors, i.e., the lattice path integrals, on all closed lattice paths of different lengths. A very large number, e.g., up to $10^{81}$ for the square lattice, exact lattice path integrals are obtained. Analytic results of these lattice path integrals then enable us to obtain the resistive transition temperature as a continuous function of the field. In particular, we can analyze measurable effects on the superconducting transition temperature, $T_c(B)$, as a function of the magnetic filed $B$, originating from electron trajectories over loops of various lengths. In addition to systematically deriving previously observed features, and understanding the physical origin of the dips in $T_c(B)$ as a result of multiple-loop quantum interference effects, we also find novel results. In particular, we explicitly derive the self-similarity in the phase diagram of square networks. Our approach allows us to analyze the complex structure present in the phase boundaries from the viewpoint of quantum interference effects due to the electron motion on the underlying lattices.Comment: 18 PRB-type pages, plus 8 large figure

KOREAN DIALECT IDENTIFICATION BASED ON INTONATION MODELING

Korean dialect identification (K-DID) is a challenging task due to its relatively unexplored field of study, mutual comprehensibility between the dialects, and lack of sufficient Korean dialect datasets available in the past. With large-scaled dialect datasets now available, this paper proposes intonational modeling of the Korean dialects by feeding frame-wise acoustic features on sequential modeling of a neural network. Compared to previous prosodic labeling with syllable-based pitch marking, our approach of intonation modeling is realized with the combination of a set of spectral features, including fundamental frequency, trained on a bidirectional LSTM network with attention mechanism. We believe the attention mechanism enables the detection of dialect-rich segments hidden among the dominant non-dialect segments within the same utterance. We test the networks on different combinations of speaker ages and speech styles. The best performance of the K-DID is achieved with 68.51% in utterance-level accuracy, which surpasses our previous work.N

Optical Contribution of Graphene in Enhanced sensitivity of graphene-gold coupled surface plasmon resonance sensing

Surface plasmons at metal/dielectric interface can resonate with the incident light depending on the incident angle, wavelength of the light or the refractive index (RI) of the medium. These characteristics have been utilized as a basis of surface plasmon resonance (SPR) sensors, providing label-free and real-time sensing format. However, the sensitivity of SPR sensors still needs to be improved to meet the requirements for the small molecule sensing. In order to enhance the performance, plasmonic nanomaterials have been introduced on SPR sensor chip. Dirac fermions in graphene can behave like photons showing linear dispersion relation. In this regard, graphene can be utilized as an alternative plasmonic material to conventional metal nanostructure. Herein, we employed graphene from different preparation methods; graphene oxide (GO) using Hummer???s method, graphene from chemical vapor deposition (CVD) and N-doped reduced graphene oxide were incorporated on top of Au film of 50 nm thickness with the aim to increase electric field through coupling of graphene plasmons with propagating SPs from Au film which was located in Kretschmann configuration-based surface plasmon resonance spectroscopy. Thickness, reduction state and nitrogen doping state of graphene were systematically controlled and RI sensing was conducted. Au substrates with CVD graphene bilayers showed highest RI sensitivity (RIS) compared to bare Au film or Au film with other types of graphene and the figure of merit of Au/graphene substrates was not deteriorated due to the extremely thin graphene layer. Immuno-sensing was demonstrated with the mass sensitivity of 1430 pg/mm2, 3.3 times higher than that of bare Au film. Moreover, the optical contribution of graphene for the overall sensitivity enhancement mechanism could be confirmed by studying RIS. Therefore, graphene adlayers could amplify electric field and biomolecular adsorption which was experimentally proved by monitoring RIS and immunoassay

Plasmonic Hot Carriers Imaging: Promise and Outlook

Extraordinary light matter interaction on the surface of metallic nanostructures can excite surface plasmons (SPs), followed by generation of charge carriers with high energy, that is, "hot electrons and holes", via nonradiative decay. Such plasmonic hot carriers are potentially useful for photocatalysis, electrocatalysis, photovoltaics, optoelectronics, and theragnosis since hot carrier transfer to the desired substrate can accelerate specific redox reactions or facilitate electrical benefits on devices. In this regard, there is a growing interest in the detection and visualization of hot carriers at the location where plasmonic hot carriers are practically generated and transferred by means of conventional or newly developed procedures, as summarized in Table 1 of the main paper. Although direct imaging of plasmonic hot carriers or pathways are still challenging due to ultrafast dynamics of plasmonic hot carriers, state-of-the-art microscopic approaches have successfully demonstrated the mapping of the localized surface plasmons (LSPs) and plasmonic hot carriers. In addition, more accessible and facile approaches by mediation of chemical probes have also been emerged in recent years for the same purpose. The aim of this Perspective is to provide an idea of how spatial information on the generation and transfer of plasmonic hot carriers can be associated with the future design of plasmonic nanomaterials or nanocomposites to increase the output of hot carrier-driven processes. Along with a comprehensive overview of surface plasmon decay into plasmonic hot carriers and the necessity of plasmonic hot carrier imaging, we will highlight some recent advances in plasmonic hot carrier imaging techniques and provide remarks on future prospects of these technique

Enhancing Solar Light-Driven Photocatalytic Activity of Mesoporous Carbon–TiO2 Hybrid Films via Upconversion Coupling

Solar energy conversion has emerged as an attractive pathway in the decomposition of hazardous organic pollutants. Herein, tridoped β-NaYF4:Yb3+,Tm3+,Gd3+ upconversion (UC) nanorods were embedded in a carbon-doped mesostructured TiO2 hybrid film using triblock copolymer P123 acting as a mesoporous template and carbon source. The photoactivity of our novel material was reflected in the degradation of nitrobenzene, as a representative organic waste. The broad-band absorption of our rationally designed UC nanorod-embedded C-doped TiO2 in the UV to NIR range unveiled a remarkable increase in nitrobenzene degradation (83%) within 3 h compared with pristine TiO2 (50%) upon light irradiation. These results establish for the first time a synergetic bridge between the effects of a creative photon trapping TiO2 architecture, improved NIR light-harvesting efficiency upon UC nanorod incorporation, and a simultaneous decrease in the band gap energy and increased visible light absorption by C-doping of the oxide lattice. The resulting nanostructure was believed to favor efficient charge and energy transfer between the photocatalyst components and to reduce charge recombination. Our novel hybrid nanostructure and its underlined synthesis strategy reflect a promising route to improve solar energy utilization in environmental remediation and in a wide range of photocatalytic applications, e.g., water splitting, CO2 reutilization, and production of fuels

Artificial intelligence-based computer-assisted detection/diagnosis (AI-CAD) for screening mammography: Outcomes of AI-CAD in the mammographic interpretation workflow

Purpose: To evaluate the stand-alone diagnostic performances of AI-CAD and outcomes of AI-CAD detected abnormalities when applied to the mammographic interpretation workflow. Methods: From January 2016 to December 2017, 6499 screening mammograms of 5228 women were collected from a single screening facility. Historic reads of three radiologists were used as radiologist interpretation. A commercially-available AI-CAD was used for analysis. One radiologist not involved in interpretation had retrospectively reviewed the abnormality features and assessed the significance (negligible vs. need recall) of the AI-CAD marks. Ground truth in terms of cancer, benign or absence of abnormality was confirmed according to histopathologic diagnosis or negative results on the next-round screen. Results: Of the 6499 mammograms, 6282 (96.7%) were in the negative, 189 (2.9%) were in the benign, and 28 (0.4%) were in the cancer group. AI-CAD detected 5 (17.9%, 5 of 28) of the 9 cancers that were intially interpreted as negative. Of the 648 AI-CAD recalls, 89.0% (577 of 648) were marks seen on examinations in the negative group, and 267 (41.2%) of the AI-CAD marks were considered to be negligible. Stand-alone AI-CAD has significantly higher recall rates (10.0% vs. 3.4%, P < 0.001) with comparable sensitivity and cancer detection rates (P = 0.086 and 0.102, respectively) when compared to the radiologists’ interpretation. Conclusion: AI-CAD detected 17.9% additional cancers on screening mammography that were initially overlooked by the radiologists. In spite of the additional cancer detection, AI-CAD had significantly higher recall rates in the clinical workflow, in which 89.0% of AI-CAD marks are on negative mammograms