Denitrification of Coal Tar Diesel Fraction by Phosphate Imidazolium Based Polymeric Ionic Liquids

A series of highly cross-linked polymeric ionic liquids P[Ci(Vim)_2][Cl]_2(i = 2,3,4,5,6) were synthesized by quaternization reaction and polymerization,and used to remove nitrogen compounds from oils.The polymeric ionic liquids P[Ci(Vim)_2][H_2PO_4]_2(i = 2,3,4,5,6) were then obtained via ion exchange.The structures of P[C_4(Vim)_2][Cl]_2 and P[C_4(Vim)_2][H_2PO_4]_2 were characterized by Fourier transform infrared(FT-IR) spectroscopy,energy dispersive spectrometry(EDS),N2 adsorption-desorption isotherm measurements,scanning electron microscopy(SEM),thermogravimetric analysis and differential scanning calorimetry(TG/DSC).The removal of nitrogen compounds was characterized by pyridineFTIR spectrometry.The results indicated that P[C_4(Vim)_2][H_2PO_4]_2 with an average pore size of 19.23 nm and a specific surface area of 11.78 m~2/g was efficient for the removal of nitrogen compounds,and exhibited good thermal stability.The adsorption rate in the simulated oil reached 93.8% when using a polymeric ionic liquid P[C_4(Vim)_2][H_2PO_4]_2 to oil ratio of 0.04 and a temperature of 313 K.The nitrogen removal rate from the coal-tar diesel fraction achieved by P[C_4(Vim)_2][H_2PO_4]_2 was 90.3%.     

基于SLM-PTS算法融合的NC-OFDM峰均比优化

基于非连续正交频分复用（non-continuous orthogonal frequency division multiplexing，NC-OFDM）模型，提出和研究了选择映射（selected mapping，SLM）算法和部分传输序列（partial transmit sequence，PTS）算法，及其SLM-PTS融合优化技术，设计了融合模型和改进流程。仿真结果与其他文献方法进行了对比，验证了SLM-PTS的融合具有优秀的峰值平均功率比（peak to average power ratio，PAPR）降低能力，但缺点是算法实现复杂度过高。因此，又进一步提出了互补型映射和限幅的联合算法（SLM-Clipping）融合解决方案，并利用深度学习方法建立PAPRnet模型。仿真结果验证了此算法对NC-OFDM系统具有PAPR良好的抑制效果，而且能够提高仿真运算效率。