Poly(vinylpyrrolidone)-iodine (PVPI)-based materials have attracted significant attention, owing to their effective inhibition of COVID-19. However, the complexation and release manner of iodine in PVPI are not fully understood. This article reveals the role of halogen bonding in PVPI chemistry through a combination of experimental and computational approaches, including ultraviolet−visible spectroscopy, Fourier-transform infrared spectroscopy, Raman spectroscopy, electronic structure calculations, electronically excited-state analysis, electrostatic potential mapping on molecular van der Waals surfaces, halogen bond energy calculations, and thermodynamic equilibrium analysis. Our research shows that, in both the solid state and solution, PVPI contains iodine molecules bonded with carbonyl groups as well as polyiodides derived from the ionization and assembling of iodine molecules. The iodophors (i.e., PVP, iodide, and polyiodides) interact with iodine molecules through halogen bonds. The halogen bond energy is as low as 2−8 kcal/mol, enabling the easy release of iodine by the iodophors. In PVPI solutions, the complexation and release of iodine reach a chemical equilibrium that is susceptible to temperature and other iodophors. Raising the temperature favors the release of iodine. Some synthetic polymers, biological proteins, and phospholipids can extract iodine molecules from solutions of PVPI, demonstrating good iodophor abilities.

The flammability of polypropylene and its intumescent flame retardant composites consisting of ammonium polyphosphate (APP), pentaerythritol (PER) and SiO2 were studied and the synergistic effect of SiO2, as well as the synergistic mechanism was discussed in detail. For the composites, the content of SiO2 varied from 0 to 12 wt.% where the total addition of APP/PER/SiO2 was constant at 30 wt.%. The flammability properties were characterized by Limiting Oxygen Index (LOI) and UL-94 tests, while the synergistic mechanism of SiO2 was investigated by a combination of thermogravimetric analysis (TGA), Fourier transform infrared (FTIR) spectrometry and scanning electron microscopy (SEM). The results showed that SiO2 had a synergistic effect on the PP/APP/PER system, with an optimum addition at 3.5 wt.%. The introduction of SiO2 improved the flame retardant properties of the PP/APP/PER system and the strength of the char layer.

No abstract

The selection of material parameters relates to the excavation stability of the underground caverns. However, back analysis is an efficient method to evaluate mechanical parameters. Given the defects of BP neural network, such as low capability of generalization and long training time, by using GA, which have global optimization ability to optimize the BP neural network weights. The parameter of surrounding rock was designed by uniform and orthogonal method, not only reduced the iterative time also improved the accuracy of the prediction. The proposed method is further illustrated with its application to the underground cavern of Lvchunba railway tunnel. Based on the surrounding rock’s parameters obtained by back analysis, the displacement of the surrounding rock was predicted. The results showed that the error between numerical calculation value and actual monitoring value was 13.2%,-8.3%,-8.9%,9.4% respectively.

No abstract