The crystal structures of the charge-transfer (CT) cocrystals formed by the π-electron acceptor 1,3,4,5,7,8-hexafluoro-11,11,12,12-tetracyanonaphtho-2,6-quinodimethane (F 6 TNAP) with the planar π-electron-donor molecules triphenylene (TP), benzo[b]benzo[4,5]thieno[2,3-d]thiophene (BTBT), benzo[1,2-b:4,5-b′]dithiophene (BDT), pyrene (PY), anthracene (ANT), and carbazole (CBZ) have been determined using single-crystal X-ray diffraction (SCXRD), along with those of two polymorphs of F 6 TNAP. All six cocrystals exhibit 1:1 donor/acceptor stoichiometry and adopt mixed-stacking motifs. Cocrystals based on BTBT and CBZ π-electron donor molecules exhibit brickwork packing, while the other four CT cocrystals show herringbone-type crystal packing. Infrared spectroscopy, molecular geometries determined by SCXRD, and electronic structure calculations indicate that the extent of ground-state CT in each cocrystal is small. Density functional theory calculations predict large conduction bandwidths and, consequently, low effective masses for electrons for all six CT cocrystals, while the TP-, BDT-, and PYbased cocrystals are also predicted to have large valence bandwidths and low effective masses for holes. Charge-carrier mobility values are obtained from space-charge limited current (SCLC) measurements and field-effect transistor measurements, with values exceeding 1 cm 2 V −1 s −1 being estimated from SCLC measurements for BTBT:F 6 TNAP and CBZ:F 6 TNAP cocrystals. exhibit properties distinct from those of their individual components. In chargetransfer (CT) cocrystals, one component acts as an π-electron donor (D) and another component acts as a π-electron acceptor (A), and both are typically planar molecules in order to facilitate CT interactions in the solid state. Two major types of molecular stacking motifs are found in CT crystals with 1:1 stoichiometry: mixed stacks, in which D and A molecules alternate along the stacking direction, -D-A-D-A, and segregated stacks, in which donor and acceptor molecules form separate stacks, -D-D-D-and -A-A-A. [1][2][3] When free of disorder, metallic conductivities can be obtained along the stacking direction of CT cocrystals that form segregated stacks and that exhibit extents of CT approximately midway (ρ = ca. 0.5) between the completely neutral (ρ = 0) and fully ionic (ρ = 1) limits. [1][2][3][4] On the other hand, CT cocrystals that consist of mixed stacks generally behave as semiconductors or insulators. [3,5] Recently there has been increasing interest in the semiconducting [6][7][8][9][10][11][12][13][14][15][16][17][18] and photoconductive [19][20][21] properties of mixed-stack cocrystals. Large charge-carrier mobility values, µ, have been reported for several examples using space-charge limited current (SCLC) or field-effect transistor (FET) measurements, includingThe ORCID identification number(s) for the author(s) of this article can be found under https://doi.
Aiming at three potential area for aerodynamic resistance reduction including the head type streamlined area, bogie region baffle and windshield area end wall, this paper put forward different shape, size and arrangement of microstructures. Through simulation and test, the feasible application for resistance reduction by using microstructure surface is obtained. Simulation and test results show that the area of bogie region baffle and windshield area end wall with microstructure surface has good resistance reduction effect, but the microstructure is not suitable for head type streamlined area. The microstructure surface provides a new way and technical support for deeply aerodynamic resistance reduction and design of higher level of high-speed EMU.
SummaryIn view of the entrusted transportation management model of High‐Speed Railways (HSR) in China, some questions have been exposed during its operation (eg, the supervision and inspection power of HSR company is not fully implemented, the poor management of safety investments, and no incentive and restraint mechanism). Through the analysis of the current situation of the HSR safety supervision system, a system dynamics (SD) model that is composed of an HSR company, the State Railway Administration (SRA) and the commissioned Railways Bureau (RB) have been established based on evolutionary game theory. The behavioral characteristics and the steady state of the decision‐making of all parties involved in the system are proved by the combination of evolutionary game theory and a system dynamics simulation. The results show that, under the clear incentive and restraint mechanism assumptions, the safety supervision and inspection rate of the system has been effectively improved and the supervision power of HSR company has been implemented.
In view of the entrusted transportation management model (ETMM) of China’s high–speed railway (HSR), the supervision strategy of an HSR company for its multiple agents plays a very important role in ensuring the safety and sustainable development of HSR. Due to the existence of multiple agents in ETMM, the supervision strategy for these agents is usually difficult to formulate. In this study, a quadruplicate HSR safety supervision system evolutionary game model composed of an HSR company and three agents was established through the analysis of the complex game relationship existing in the system. The behavioral characteristics and the steady state of decision–making of all stakeholders involved in the system are proved by evolutionary game theory and system dynamics simulation. The results show that there will be long–term fluctuations in the strategies selected by the four stakeholders in the static reward–penalty control scenario (RPCS), which indicates that an evolutionary stable strategy does not exist. With increases in the reward–penalty coefficient, the fluctuations are intensified. Therefore, the dynamic RPCS was proposed to control the fluctuations, and the simulation was repeated. The results show that the fluctuations can be effectively restrained by adopting the dynamic RPCS, but if the coefficients are the same, the static RPCS is better than the dynamic RPCS for increasing the safety investment rate of the three agents. This demonstrates that the HSR company should apply these two control scenarios flexibly according to the actual situation when formulating a supervision strategy in order to effectively control and enhance the safety level of HSR operations when multiple agents are involved.
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