Plasmonic nanoparticle enhanced light absorption in GaAs solar cells

We demonstrate an improvement in efficiency of optically thin GaAs solar cells decorated with size-controlled Ag nanoparticles fabricated by masked deposition through anodic aluminum oxide templates. The strong scattering by the interacting surface plasmons in densely formed high aspect-ratio nanoparticles effectively increases the optical path of the incident light in the absorber layers resulting in an 8% increase in the short circuit current density of the cell. The nanoparticle array sheet conductivity also reduces the cell surface sheet resistance evidenced by an improved fill factor. This dual function of plasmonic nanoparticles has potential to enable thinner photovoltaic layers in solar cells

Surface plasmon enhanced photocurrent in thin GaAs solar cells

We report fabrication of size-controlled plasmonic nanoparticle arrays by which optically thin GaAs single junction solar cells are decorated. Ordered Ag and Al nanoparticles with average diameters of 60-150 nm and interparticle spacings of 100-300 nm were templated onto the window layers of the GaAs solar cells using nanoporous anodic aluminum oxide membrane templates. Near the surface plasmon resonances, 60nm-diameter Ag and Al nanoparticles serve as light-absorbers so that non-radiative surface plasmon resonances reduce the photocurrent of the cells, which is improved by increasing the nanoparticle size. Photocurrent enhancements are seen at wavelengths longer than surface plasmon resonance which is maximized near the band gap edge of GaAs. These enhancements can be attributed to the increased optical path in the photovoltaic layers resulting from multi-angle scattering by the nanoparticles, while high scattering efficiency nanoparticles in turn increase the back scattering light out of the cell reducing the photocurrent

Plasmon-enhanced absorption and photocurrent in ultrathin GaAs solar cells with metallic nanostructures

Metallic nanostructures can excite surface plasmons and can dramatically increase the optical path length in thin active photovoltaic layers to enhance overall photoabsorption. This effect has potential for cost and weight reduction with thinned layers and also for efficiency enhancement associated with increased carrier excitation level in the absorber layer

Patterns of Drug Prescription for Japanese Cedar Pollinosis Using a Clinical Vignette Questionnaire

ABSTRACTBackgroundAlthough prescribed drugs directly affect patient outcome, the variation in physicians' attitudes towards drug therapy for cedar pollinosis has not been quantitatively assessed. This research investigated the prescription patterns of drugs for cedar pollinosis by ear, nose, and throat specialists (ENTs), general physicians (GPs) and internal medicine doctors (IMs) in Yamanashi Prefecture, Japan.MethodsA cross-sectional study was conducted by mailing questionnaires to 532 physicians in autumn 2006. The main part of the questionnaire constituted clinical vignettes of pollinosis cases with nasal and ocular symptoms ranging from mild to severe. We requested that the physicians fill out prescription medications they considered appropriate for each vignette.ResultsResponses from 172 physicians (32%) for six clinical vignettes were analyzed. The number of drugs prescribed by ENTs was significantly higher than that by GPs and IMs for vignettes representing moderate to severe cases (p < 0.004). The percentage of physicians who said they would prescribe nasal corticosteroid and eye drops was higher in the ENT group compared to the other two groups in these vignettes. In terms of second-generation antihistamines, no differences were observed between the three groups for all vignettes.ConclusionsOur investigation suggested that, compared to ENTs, GPs and IMs have a lower tendency to concomitantly prescribe drugs for localized treatment such as nasal corticosteroids and eye drops with oral medication. There may be differences in prescription patterns of drugs for pollinosis between ENTs and non-specialist physicians

VQE-generated Quantum Circuit Dataset for Machine Learning

Quantum machine learning has the potential to computationally outperform classical machine learning, but it is not yet clear whether it will actually be valuable for practical problems. While some artificial scenarios have shown that certain quantum machine learning techniques may be advantageous compared to their classical counterpart, it is unlikely that quantum machine learning will outclass traditional methods on popular classical datasets such as MNIST. In contrast, dealing with quantum data, such as quantum states or circuits, may be the task where we can benefit from quantum methods. Therefore, it is important to develop practically meaningful quantum datasets for which we expect quantum methods to be superior. In this paper, we propose a machine learning task that is likely to soon arise in the real world: clustering and classification of quantum circuits. We provide a dataset of quantum circuits optimized by the variational quantum eigensolver. We utilized six common types of Hamiltonians in condensed matter physics, with a range of 4 to 16 qubits, and applied ten different ans\"{a}tze with varying depths (ranging from 3 to 32) to generate a quantum circuit dataset of six distinct classes, each containing 300 samples. We show that this dataset can be easily learned using quantum methods. In particular, we demonstrate a successful classification of our dataset using real 4-qubit devices available through IBMQ. By providing a setting and an elementary dataset where quantum machine learning is expected to be beneficial, we hope to encourage and ease the advancement of the field.Comment: 9 pages, 6figure

Suppressive Effect of Wild Saccharomyces cerevisiae and Saccharomyces paradoxus Strains on Ige Production by Mouse Spleen Cells

The genus Saccharomyces includes industrial yeasts that are used for bread and alcoholic beverage production. Saccharomyces strains isolated from natural resources, referred to as “wild” yeasts, are used for making products with strain-specific flavors that are different from those of the “domesticated” industrial yeasts. The physiological effects of wild yeast are poorly understood. In this study, we isolated 2 Saccharomyces cerevisiae strains (S02 − 03) and 5 Saccharomyces paradoxus strains (P01 − 02, S01, S04 − 05) from natural resources in the Kiso area and investigated the effect of these fungal strains on IgE production by mouse spleen cells. Culturing spleen cells with heat-killed yeasts resulted in elevated IFN-γ and IL-12 levels followed by significant reduction in IgE levels. The S03 and P01 strains induced IL-12 p40 and IL-10 expression in RAW264 cells. Thus, wild strains of S. cerevisiae and S. paradoxus regulate macrophage cytokine production to improve the Th1/Th2 immune balance and suppress IgE production.ArticleFOOD SCIENCE AND TECHNOLOGY RESEARCH. 19(6):1019-1027 (2013)journal articl

Improved electrical properties of wafer-bonded p-GaAs/n-InP interfaces with sulfide passivation

Sulfide-passivated GaAs and InP wafers were directly bonded to explore the efficiency of sulfide passivation on the bonded interfacial properties. We find that the bonded GaAs/InP interfaces after sulfide passivation contain sulfur atoms and a decreased amount of oxide species relative to the pairs bonded after conventional acid treatment; however, the residual sulfur atoms have no effect on the bonding strength. The electrical properties of the bonded p-GaAs/n-InP heterojunctions were studied for different acceptor concentrations in p-GaAs. A reduced interfacial trap state density enhances the tunnel current flow across the depletion layer in the sulfide-passivated case. A directly bonded tunnel diode with a heavily doped p-GaAs/n-InP heterojunction was achieved when the wafers were sulfide passivated and then bonded at temperatures as low as 300 °C. This sulfide-passivated tunnel diode can be used for fabrication of lattice-mismatched multijunction solar cells in which subcells are integrated via direct bonding