Spatially selective catalysis of OSA starch for preparation of Pickering emulsions with high emulsification properties.

The traditional strategies of chemical catalysis and biocatalysis for producing octenyl succinic anhydride modified starch can only randomly graft hydrophobic groups on the surface of starch, resulting in unsatisfactory emulsification performance. In this work, a lipase-inorganic hybrid catalytic system with multi-scale flower like structure is designed and applied to spatially selective catalytic preparation of ocenyl succinic anhydride modified starch. With the appropriate floral morphology and petal density, lipases distributed in the "flower center" can selectively catalyze the grafting of hydrophobic groups in a spatial manner, the hydrophobic groups are concentrated on one side of starch particles. The obtaining OSA starch exhibits excellent emulsifying property, and the pickering emulsion has good protective effect on the embedded curcumin. This work provides a direction for the development of high-performance starch-based emulsifiers for the food and pharmaceutical industries, which is of great significance for improving the preparation and emulsification theory research of modified starch.

Biomass-derived multifunctional nanoscale carbon fibers toward fire warning sensors, supercapacitors and moist-electric generators.

Nowadays, great effort has been devoted to designing biomass-derived nanoscale carbon fibers with controllable fibrous morphology, high conductivity, big specific surface area and multifunctional characteristics. Herein, a green and renewable strategy is performed to prepare the biomass-based nanoscale carbon fibers for fire warning sensor, supercapacitor and moist-electric generator. This preparation strategy thoroughly gets over the dependence of petroleum-based polymeride, and effectually improves the energy storage capacity, sensing sensitivity, humidity power generation efficiency of the obtaining biomass-based carbon nanofibers. Without the introduction of any active components or pseudocapacitive materials, the specific capacitance and energy density for biomass-based nanoscale carbon fibers achieve 143.58 F/g and 19.9 Wh/kg, severally. The biomass-based fire sensor displays excellent fire resistance, stability, and flame sensitivity with a response time of 2 s. Furthermore, the biomass-based moist-electric generator shows high power generation efficiency. The output voltage and current of five series connected and parallel-connected biomass-based moist-electric generators reaches 4.30 V and 43 µA, respectively. Notably, as the number of biomass-based moist-electric generators in series or parallel increases, the overall output voltage and current of the device system have a linear relationship. This work proposes a self-powered fire prediction system based on nanoscale carbon fibers that integrates sensing, power generation, and energy storage functions.