The strong interchain packing and polarity of polyimide (PI) compromise its outstanding thermal and mechanical properties. Crown ethers are theoretically expected to form host–guest inclusion complex with PI and improve its disadvantages. On the basis of this hypothesis, we synthesized a series of PI/crown ether composite films and investigated their synthesis mechanism, structures and properties. Our results suggest that the introduction of crown ethers increased the free volume of PI matrix and generated a special necklace-like supramolecular structure, which simultaneously and greatly improved PI’s mechanical, dielectric and hydrophobic properties. The Young modulus, elongation and tensile energy at break of PI composite films were maximally increased by 73.0%, 135.5%, and 190.0%, respectively. Meanwhile their dielectric constant and water absorption were minimized by 16.6% and 66.8%, respectively. Crown ethers with different molecular sizes demonstrated different improvement effects on PI’s properties. Their inclusion rates stabilized at ∼50%, which are related to the equal reaction probability between anhydride and amino groups.

In this work, the effects of solvent additives on the trapping and recombination of carriers in polymer solar cells based on the blend of poly(3-hexylthiophene) (P3HT) and indene-C 60bisadduct (ICBA) are investigated by measuring the ideality factor and transient photocurrent. The addition of a few percent of 4-bromoanisole (BrAni) and 1-chloronaphthalene (CN) can give rise to the preferable morphology with well-ordered interpenetrating networks, which is beneficial for charge transport. Efficiency enhancement of polymer solar cells with solvent additives originates from the decreased defects and suppressed trap-assisted recombination at the interface between the donor and acceptor materials.

: The article reviews the research progress in the preparation of polycaprolactone through the ring-opening polymerization of -caprolactone initiated by biopolymers in recent years. The structure characteristics of starch, cellulose, chitosan, polyhydroxyalkanoates, polylactic acid, the reaction mechanism, the preparation method and the application of - caprolactone were introduced. Finally, the future development of new polycaprolactone copolymers is prospected.

Bulk-heterojunction polymer solar cells (BHJ-PSCs) have attracted considerable attention because of their unique advantages of lightweight, low cost, mechanical flexibility and suitable for large-area fabrication [1–3]. In the last decades, much attention has been paid to the donor and acceptor system P3HT:PCBM, However, because of the relatively large bandgap of P3HT (∼1.9 eV) and the relatively small energy difference between the lowest unoccupied molecular orbital (LUMO) of PCBM and the highest occupied molecular orbital (HOMO) of P3HT, the photovoltaic performance of the PSCs based on P3HT:PCBM is still significantly lower than the inorganic solar cells. Recently more work has been done on the novel donor materials which have a reduced energy gap with an ability of harvesting more of the sun’s spectral emission and a high charge carriers mobility for charge transport. One of the most promising new donor polymer is poly [N-9"-hepta-decanyl-2,7-carbazole-alt-5,5-(4',7'-di-2-thienyl-2',1',3' -benzothiadiazole)] (PCDTBT) with a HOMO level of 5.5eV which is 0.4 eV down-shifted than that of P3HT. When PCDTBT is blended with the fullerene acceptor PC70BM, it showed excellent photovoltaic performance with a power conversion efficiency of ∼ 6%. [6]

Since the turn of the twenty-first century, the issue of aging has gained international attention. Both developed and developing nations are currently dealing with this issue. To ensure the sustained and healthy growth of the economy and society in the face of an aging society, it is especially important to establish a scientific old-age insurance system and a reasonable retirement system. We are all aware that the key indicators for the state to control the old-age insurance system in the old-age insurance system are the income and expenditure balance of the old-age insurance pooling account and the analysis of the ideal retirement age. In this paper, a better machine algorithm is used. By independently learning the rules present in a large amount of data and gaining new experience and knowledge, machine learning (ML) can increase computer intelligence and give computers decision-making abilities comparable to those of humans. In general, a machine learning algorithm uses the laws it derives from data to predict unknown data after automatically analysing the data. This study’s findings suggest that the ideal retirement age and life expectancy are positively correlated, with the ideal retirement age’s growth rate 12.57 percent higher than that of life expectancy.