Machine Learning and Structural Design to Optimize the Flame Retardancy of Polymer Nanocomposites with Graphene Oxide Hydrogen Bonded Zinc Hydroxystannate

Study on properties and simulation application scenarios of flame retarded modified konjac glucomannan organic and inorganic composite aerogel

In this paper, a new organic-inorganic biomass composite aerogel was prepared by freeze-drying method with glucomannan, hydrophilic isocyanate, water-soluble flame retardant, and water glass as raw materials. Biomass Konjac glucose mannan (KGM) was used as the main network framework, KGM was chemically cross-linked and alkali-cross-linked with hydrophilic isocyanate and Na2SiO3 solution, and flame retardant modified with water-soluble flame retardant and water glass. The microstructure showed an obvious organic-inorganic interpenetrating network structure. The compressive strength of sample K2S4P2 was 4.751 ± 0.089 MPa, and the compression modulus of sample K2S4P1B modified by boric acid hydrolysis of Na2SiO3 was 63.76 ± 1.81 × 103 m2/s2. The introduction of boron ions contributes to the thermal stability of organic components. The peak and total heat release rates of sample K2S4P1A4 decreased by 80.3 % and 50.8 %, respectively. In addition, the thermal simulation calculation of the external wall in winter and summer using ANSYS software showed that the thickness of the insulation layer with the best insulation effect is 40-60 mm. The organic-inorganic composite aerogel provides a simple and environmentally friendly method for the application of external wall insulation systems in low-energy buildings with both mechanical properties and flame retardant properties.

Machine-Learning-Based Predictions of Polymer and Postconsumer Recycled Polymer Properties: A Comprehensive Review

There has been a tremendous increase in demand for virgin and postconsumer recycled (PCR) polymers due to their wide range of chemical and physical characteristics. Despite the numerous potential benefits of using a data-driven approach to polymer design, major hurdles exist in the development of polymer informatics due to the complicated hierarchical polymer structures. In this review, a brief introduction on virgin polymer structure, PCR polymers, compatibilization of polymers to be recycled, and their characterization using sensor array technologies as well as factors affecting the polymer properties are provided. Machine-learning (ML) algorithms are gaining attention as cost-effective scalable solutions to exploit the physical and chemical structures of polymers. The basic steps for applying ML in polymer science such as fingerprinting, algorithms, open-source databases, representations, and polymer design are detailed in this review. Further, a state-of-the-art review of the prediction of various polymer material properties using ML is reviewed. Finally, we discuss open-ended research questions on ML application to PCR polymers as well as potential challenges in the prediction of their properties using artificial intelligence for more efficient and targeted PCR polymer discovery and development.

Recent Advances in Zinc Hydroxystannate-Based Flame Retardant Polymer Blends

During the combustion of polymeric materials, plenty of heat, smoke, and toxic gases are produced that may cause serious harm to human health. Although the flame retardants such as halogen- and phosphorus-containing compounds can inhibit combustion, they cannot effectively reduce the release of toxic fumes. Zinc hydroxystannate (ZHS, ZnSn(OH)6) is an environmentally friendly flame retardant that has attracted extensive interest because of its high efficiency, safety, and smoke suppression properties. However, using ZHS itself may not contribute to the optimal flame retardant effect, which is commonly combined with other flame retardants to achieve more significant efficiency. Few articles systematically review the recent development of ZHS in the fire safety field. This review aims to deliver an insight towards further direction and advancement of ZHS in flame retardant and smoke suppression for multiple polymer blends. In addition, the fire retarded and smoke suppression mechanism of ZHS will be demonstrated and discussed in depth.