Rational Design of Mesoporous Silica (SBA-15)/PF (Phenolic Resin) Nanocomposites by Tuning the Pore Sizes of Mesoporous Silica.

The development of composite materials with functional additives proved to be an effective way to improve or supplement the required properties of polymers. Herein, mesoporous silica (SBA-15) with different pore sizes were used as functional additives to prepare SBA-15/PF (phenolic resin) nanocomposites, which were prepared by in situ polymerization and then, compression molding. The physical properties and structural parameters of SBA-15 with different pore sizes were characterized by N2 adsorption-desorption, X-ray diffraction (XRD), and scanning electron microscopy (SEM). The thermal properties of the SBA-15/PF hybrid were investigated by differential scanning calorimetry (DSC) and thermal gravimetric analysis (TGA). The mechanical, friction, and dynamic mechanical properties of SBA-15/PF nanocomposites were also studied. The results revealed that the pore sizes of SBA-15 have a significant effect on the resulting SBA-15/PF hybrid and SBA-15/PF nanocomposites. The thermal stability of the SBA-15/PF hybrid was dramatically improved in comparison with pure PF. The friction and dynamic mechanical properties of the SBA-15/PF nanocomposites were enhanced significantly. Specifically, the glass transition temperature (Tg) of the nanocomposite increased by 19.0 °C for the SBA-15/PF nanocomposites modified with SBA-15-3. In addition, the nanocomposite exhibited a more stable friction coefficient and a lower wear rate at a high temperature. The enhancement in thermal and frictional properties for the nanocomposites is ascribed to the confinement of the PF chains or chain segments in the mesopores channels.

Freshness monitoring of raw fish by detecting biogenic amines using a gold nanoparticle-based colorimetric sensor array.

We herein report the quantitative detection of biogenic amines using a gold nanoparticle-based colorimetric chemosensor array for food analysis. The gold nanoparticles are functionalized with carboxylate derivatives, which capture target amines through hydrogen bonds and electrostatic interactions. The simultaneous discrimination of 10 amine derivatives was achieved by a linear discriminant analysis with a 100% correct classification based on the multi-colorimetric response pattern of structural differences. Furthermore, a real sample analysis for raw fish (i.e., tuna) demonstrated highly accurate determination of histamine concentrations by a support vector machine, the result of which was matched with high-performance liquid chromatography. Most importantly, the chemosensor array succeeded in detecting the time-dependent concentration change of histamine in the raw fish, meaning that the decomposition of the fish could be monitored by the colorimetric changes. Hence, the proposed chemosensor array combined with pattern recognition techniques can be a user-friendly analytical method for food freshness monitoring.