We characterized bulk-heterojunction (BHJ) solar cells using a new phenylene-thiophene oligomer, 3,7-bis[5-(4-n-hexylphenyl)-2-thienyl]dibenzothiophene-5,5-dioxide (37HPTDBTSO), and phenyl-C61-butyric-acid methyl ester (PCBM). Their photovoltaic properties including current-voltage characteristics and spectrum response were investigated. It was found that 37HPTDBTSO is appraised to be valuable electron donor. The characteristics of BHJ solar cells using mixed two donors of 37HPTDBTSO and a polymer of poly(3-hexylthiophene) (P3HT) were further investigated. OSC using the blend film of mixed donars and PCBM achieved a power conversion efficiency of 0.89%.

Model-based sensorless control of permanent magnet synchronous motor (PMSM) is promising for high-speed operation to estimate motor state, which is the speed and the position of the rotor, via electric signals of the stator, beside the inevitable fact that estimation accuracy is degraded by electromagnet interference (EMI) from switching devices of the converter. In this paper, the simulation system based on Luenberger observer and phase-locked loop (PLL) has been established, analyzing impacts of EMI on motor state estimations theoretically, exploring influences of EMI with different cutoff frequency, rated speeds, frequencies and amplitudes. The results show that Luenberger observer and PLL have strong immunity, which enable PMSM can still operate stably even under certain degrees of interference. EMI produces sideband harmonics that enlarge pulsation errors of speed and position estimations. Additionally, estimation errors are positively correlated with cutoff frequency of low-pass filter and the amplitude of EMI, and negatively correlated with rated speed of the motor and the frequency of EMI.  When the frequency is too high, its effects on motor state estimations are negligible. This work contributes to the comprehensive understanding of how EMI affects motor state estimations, which further enhances practical application of sensorless PMSM.

The Boolean network (BN) can be used to create discrete mathematical models of gene regulatory networks. In this paper, we consider three problems on BNs that are known to be NP-hard: detection of a singleton attractor, finding a control strategy that shifts a BN from a given initial state to the desired state, and control of attractors. We propose integer programming-based methods which solve these problems in a unified manner. Then, we present results of computational experiments which suggest that the proposed methods are useful for solving moderate size instances of these problems. We also show that control of attractors is -hard, which suggests that control of attractors is harder than the other two problems.