Employing a Narrow-Band-Gap Mediator in Ternary Solar Cells for Enhanced Photovoltaic Performance.

Ternary organic solar cells (OSCs) provide a convenient and effective means to further improve the power conversion efficiency (PCE) of binary ones via composition control. However, the role of the third component remains to be explored in specific binary systems. Herein, we report ternary blend solar cells by adding the narrow-band-gap donor PCE10 as the mediator into the PBDB-T:IDTT-T binary blend system. The extended absorption, efficient fluorescence resonance energy transfer, enhanced charge dissociation, and induced tighter molecular packing of the ternary blend films enhance the photovoltaic properties of devices and deliver a champion PCE of 10.73% with an impressively high open-circuit voltage (VOC) of 1.03 V. Good miscibility and similar molecular packing behavior of the components guarantee the desired morphology in the ternary blend films, leading to solar cell devices with over 10% PCEs at a range of compositions. Our results suggest that ternary systems with properly aligned energy levels and overlapping absorption among the components hold great promises to further enhance the performance of corresponding binary ones

Immunization for complex network based on the effective degree of vertex

The basic idea of many effective immunization strategies is first to rank the importance of vertices according to the degrees of vertices and then remove the vertices from highest importance to lowest until the network becomes disconnected. Here we define the effective degrees of vertex, i.e., the number of its connections linking to un-immunized nodes in current network during the immunization procedure, to rank the importance of vertex, and modify these strategies by using the effective degrees of vertices. Simulations on both the scale-free network models with various degree correlations and two real networks have revealed that the immunization strategies based on the effective degrees are often more effective than those based on the degrees in the initial network.Comment: 16 pages, 5 figure

Reduced dynamics with renormalization in solid-state charge qubit measurement

Quantum measurement will inevitably cause backaction on the measured system, resulting in the well known dephasing and relaxation. In this report, in the context of solid--state qubit measurement by a mesoscopic detector, we show that an alternative backaction known as renormalization is important under some circumstances. This effect is largely overlooked in the theory of quantum measurement.Comment: 12 pages, 4 figure

Complex Discretization approximation for the full dynamics of system-environment quantum models

The method of discretization approximation for the environment in continuum suffers from the recurrence, that makes the simulation of the open dynamics inefficient. In order to tackle this problem, the discretization approximation is generalized into the complex plane by introducing complex Gauss quadratures in this paper. The resulting effective Hamiltonian is thus non-Hermitian due to the dissipative dynamics of system. As illustrations, the open dynamics in two exactly solvable models, dephasing model and the single-excitation open dynamics in the generalized Aubry-Andr\'{e}-Harper model, is checked respectively by the method. It is found that the recurrence can be compressed greatly due to the occurrence of complex discrete modes in environment. Thus, the open dynamics in the two models can be simulated in high efficiency and precision.Comment: 13 pages. the statement has been improved and the references are updated. Comments are welcom

Genome-wide linkage analysis for alcohol dependence: a comparison between single-nucleotide polymorphism and microsatellite marker assays

Both theoretical and applied studies have proven that the utility of single nucleotide polymorphism (SNP) markers in linkage analysis is more powerful and cost-effective than current microsatellite marker assays. Here we performed a whole-genome scan on 115 White, non-Hispanic families segregating for alcohol dependence, using one 10.3-cM microsatellite marker set and two SNP data sets (0.33-cM, 0.78-cM spacing). Two definitions of alcohol dependence (ALDX1 and ALDX2) were used. Our multipoint nonparametric linkage analysis found alcoholism was nominal linked to 12 genomic regions. The linkage peaks obtained by using the microsatellite marker set and the two SNP sets had a high degree of correspondence in general, but the microsatellite marker set was insufficient to detect some nominal linkage peaks. The presence of linkage disequilibrium between markers did not significantly affect the results. Across the entire genome, SNP datasets had a much higher average linkage information content (0.33 cM: 0.93, 0.78 cM: 0.91) than did microsatellite marker set (0.57). The linkage peaks obtained through two SNP datasets were very similar with some minor differences. We conclude that genome-wide linkage analysis by using approximately 5,000 SNP markers evenly distributed across the human genome is sufficient and might be more powerful than current 10-cM microsatellite marker assays

Multifactor-dimensionality reduction versus family-based association tests in detecting susceptibility loci in discordant sib-pair studies

Complex diseases are generally thought to be under the influence of multiple, and possibly interacting, genes. Many association methods have been developed to identify susceptibility genes assuming a single-gene disease model, referred to as single-locus methods. Multilocus methods consider joint effects of multiple genes and environmental factors. One commonly used method for family-based association analysis is implemented in FBAT. The multifactor-dimensionality reduction method (MDR) is a multilocus method, which identifies multiple genetic loci associated with the occurrence of complex disease. Many studies of late onset complex diseases employ a discordant sib pairs design. We compared the FBAT and MDR in their ability to detect susceptibility loci using a discordant sib-pair dataset generated from the simulated data made available to participants in the Genetic Analysis Workshop 14. Using FBAT, we were able to identify the effect of one susceptibility locus. However, the finding was not statistically significant. We were not able to detect any of the interactions using this method. This is probably because the FBAT test is designed to find loci with major effects, not interactions. Using MDR, the best result we obtained identified two interactions. However, neither of these reached a level of statistical significance. This is mainly due to the heterogeneity of the disease trait and noise in the data