Doping dependence of the superconducting gap in Bi2Sr2CaCu2O{8 + delta}

Bi2Sr2CaCu2O{8 + \delta} crystals with varying hole concentrations (0.12 < p < 0.23) were studied to investigate the effects of doping on the symmetry and magnitude of the superconducting gap. Electronic Raman scattering experiments that sample regions of the Fermi surface near the diagonal (B_{2g}) and principal axes (B_{1g}) of the Brillouin Zone have been utilized. The frequency dependence of the Raman response function at low energies is found to be linear for B_{2g} and cubic for B_{1g} (T< T_c). The latter observations have led us to conclude that the doping dependence of the superconducting gap is consistent with d_{x^2-y^2} symmetry, for slightly underdoped and overdoped crystals. Studies of the pair-breaking peak found in the B_{1g} spectra demonstrate that the magnitude of the maximum gap decreases monotonically with increasing hole doping, for p > 0.12. Based on the magnitude of the B_{1g} renormalization, it is found that the number of quasiparticles participating in pairing increases monotonically with increased doping. On the other hand, the B_{2g} spectra show a weak "pair-breaking peak" that follows a parabolic-like dependence on hole concentration, for 0.12 < p < 0.23.Comment: 9 pages REvTex document including 8 eps figures; new table II; changes to Fig. 5 and tex

Quantifying atmospheric nitrogen deposition through a nationwide monitoring network across China

A Nationwide Nitrogen Deposition Monitoring Network (NNDMN) containing 43 monitoring sites was established in China to measure gaseous NH3, NO2, and HNO3 and particulate NH4+ and NO3− in air and/or precipitation from 2010 to 2014. Wet/bulk deposition fluxes of Nr species were collected by precipitation gauge method and measured by continuous-flow analyzer; dry deposition fluxes were estimated using airborne concentration measurements and inferential models. Our observations reveal large spatial variations of atmospheric Nr concentrations and dry and wet/bulk Nr deposition. On a national basis, the annual average concentrations (1.3–47.0 μg N m−3) and dry plus wet/bulk deposition fluxes (2.9–83.3 kg N ha−1 yr−1) of inorganic Nr species are ranked by land use as urban > rural > background sites and by regions as north China > southeast China > southwest China > northeast China > northwest China > Tibetan Plateau, reflecting the impact of anthropogenic Nr emission. Average dry and wet/bulk N deposition fluxes were 20.6 ± 11.2 (mean ± standard deviation) and 19.3 ± 9.2 kg N ha−1 yr−1 across China, with reduced N deposition dominating both dry and wet/bulk deposition. Our results suggest atmospheric dry N deposition is equally important to wet/bulk N deposition at the national scale. Therefore, both deposition forms should be included when considering the impacts of N deposition on environment and ecosystem health

A lanthanide-based magnetic nanosensor as an erasable and visible platform for multi-color point-of-care detection of multiple targets and the potential application by smartphone

The sensitive, selective and point-of-care detection of dipicolinic acid (DPA) is of great significance for the prevention of the anthrax virus and the containment of bioterrorism. In this work, a multi-color fluorescent nanoprobe composed of lanthanides and magnetic nanoparticles (Fe3O4@CePO4:Tb-EDTA-Eu) has been designed, in which the portion of Fe3O4@CePO4:Tb can be used as the internal stable signal of green fluorescence, while the EDTA-Eu part can be used as the sensitive reaction signal for monitoring DPA. Upon the addition of DPA, the red fluorescence of Eu3+ ions is significantly enhanced, while the fluorescent color of the nanoprobes can change from green to red (such as yellow-green, orange-yellow and orange-red), achieving visual multi-color fluorescent detection even by the naked eye. By using the magnetic separation method, the composites can be easily purified for point-of-care testing. More importantly, the nanoprobe fixed test pieces enable real-time analysis of DPA by using an easy-to-access color-scanning application on a smartphone. Furthermore, the fluorescence intensity can be quenched by the addition of Cu2+, which leads to a rewritable nanosensor and can be used in the detection of cysteine (Cys) with high sensitivity. With the addition of Cys, this erasable nano detection platform can also display the original multi-color visual point-of-care detection. With further optimization, this new type of multi-color fluorescent assay is promising in point-of-care clinics for multi-target diagnostics.Jun Xu, Xiao-Ke Shen, Lei Jia, Jian-Liang Cao, Yan Wang, Xiao-Lei Zhao, Ning Bi, Sheng-Li Guoa and Tian-Yi M

Visible photoluminescence of co-sputtered Ge–Si duplex nanocrystals

The photoluminescence (PL) characteristics of co-sputtered Ge-Si duplex nanocrystal films were examined under excitation by a 325-nm HeCd laser, combined with Raman and Fourier-transform infrared reflection spectra analysis. A broad visible PL spectrum from the as-deposited Ge-Si nanocrystal films was observed in the wavelength range 350-700 nm. Basically, the PL spectrum can be considered to consist of two distinct parts originating from different emission mechanisms: (i) the spectrum in the range 350-520 nm, consisting of characteristic double peaks at 410 and 440 nm with PL intensities decreasing after vacuum annealing, probably due to vacancy defects in Si nanocrystals; and (ii) the spectrum in the range 520-700 nm, consisting of a characteristic peak at 550 nm with a PL intensity not affected by vacuum annealing, probably due to Ge-related interfacial defects. No size dependence of PL peak energy expected from quantum confinement effects was observed in the wavelength range investigated. However, with an increase of crystal size, the PL peak intensity in the blue zone decreased. The PL intensity is found to be strongly affected by silicon concentration. A film heated in air has a different PL mechanism from the as-deposited and vacuum-annealed films. © Springer-Verlag 2005.link_to_subscribed_fulltex

Tokamak plasma disruption precursor onset time study based on semi-supervised anomaly detection

Plasma disruption in tokamak experiments is a challenging issue that causes damage to the device. Reliable prediction methods are needed, but the lack of full understanding of plasma disruption limits the effectiveness of physics-driven methods. Data-driven methods based on supervised learning are commonly used, and they rely on labelled training data. However, manual labelling of disruption precursors is a time-consuming and challenging task, as some precursors are difficult to accurately identify. The mainstream labelling methods assume that the precursor onset occurs at a fixed time before disruption, which leads to mislabeled samples and suboptimal prediction performance. In this paper, we present disruption prediction methods based on anomaly detection to address these issues, demonstrating good prediction performance on J-TEXT and EAST. By evaluating precursor onset times using different anomaly detection algorithms, it is found that labelling methods can be improved since the onset times of different shots are not necessarily the same. The study optimizes precursor labelling using the onset times inferred by the anomaly detection predictor and test the optimized labels on supervised learning disruption predictors. The results on J-TEXT and EAST show that the models trained on the optimized labels outperform those trained on fixed onset time labels