Multiscale investigation on molecular structure and mechanical properties of thermal‐treated rigid polyurethane foam under high temperature

Investigation of the relation between free volume and physico-mechanical performance in rigid polyurethane foam containing turkey feather fibers: Part 2

Rigid polyurethane foams (RPUFs) were modified with 0–15 wt.% turkey feather fibers (TFFs) produced from waste turkey feathers. One-shut free rising method was used for the production of TFFs-filled-RPUFs in a closed mold. The dependence of mechanical performance and water vapor permeability (WVP) feature of the final foams on TFFs loading was evaluated with free volume change. The free volume analysis was performed via Positron Annihilation Lifetime Spectroscopy (PALS), while the mechanical and WVP characteristics were determined with the use of the universal tester machines. PALS findings showed that the incorporation of TFFs with RPUF matrix caused the considerable diminishment in the free volume due to TFFs serving as a filling material and formation of strong secondary bonds between components. Moreover, tensile strength and extension of the foams decreased with the increasing of TFFs, which caused by the occurrence of noteworthy restriction on the spatial alignment and orientation capability of polyurethane chains due to the lack of sufficient free volume allowing the chains to move freely. As for the compression tests, all the TFFs-loaded RPUFs depicted substantially lower performance due to TFFs interfering with the ordered organization of isocyanate domains. Moreover, impact test results showed that the addition of TFFs into RPUF matrix brought about the insufficient impact energy delocalization throughout the matrix due to the restriction on the mobility of polymer chains. Additionally, the remarkable diminishment in WVP was recorded due to the reduction in the number of vacancies and constitution of keratin composed of roundly 60% of hydrophilic protein (especially cystine). All in all, this study established a strong links between free volume and characteristics of TFFs-loaded RPUFs.

A Review of Research on the Effect of Temperature on the Properties of Polyurethane Foams

Temperature is one of the main factors affecting the properties of polyurethane foams, and there are large differences in the mechanical properties of polyurethane foams at different temperatures. To understand the effect of temperature on the mechanical properties of polyurethane foams and to provide a theoretical basis for the application of polyurethane foams in extreme environments, this paper systematically describes the research on the effect of mold temperature, raw material temperature, and environmental temperature on the microstructure and mechanical properties of polyurethane foams in the formation and service stages of rigid polyurethane foams by domestic and foreign scholars, and summarizes the effect of temperature on the mechanical properties of polyurethane foams and the mechanism of action. A review of the literature shows that the effect of different temperatures on the mechanical properties of polyurethane foams can be summarized. The literature review shows that there are certain changes in the foaming process, pore structure, and mechanical properties of polyurethane foams at different temperatures, and the increase in temperature generally leads to the increase in pore size, decrease in density, and decrease in mechanical properties of polyurethane foams.

Predicting Young's Modulus of Linear Polyurethane and Polyurethane-Polyurea Elastomers: Bridging Length Scales with Physicochemical Modeling and Machine Learning

Predicting the properties of complex polymeric materials based on monomer chemistry requires modeling physical interactions that bridge molecular, interchain, microstructure, and bulk length scales. For polyurethanes, a polymer class with global commercial and industrial significance, these multiscale challenges are intrinsic due to the thermodynamic incompatibility of the urethane and polyol-rich domains, resulting in heterogeneities from molecular to microstructural length scales. Machine learning can model patterns in data to establish a relationship between the monomer chemistry and bulk material properties, but this is made difficult by small data sets and a diverse set of monomers. Using a data set of 63 industrially relevant and complex elastomers, we demonstrate that accurate machine learning predictions are possible when monomer chemistry is used to estimate interactions at interchain length scales. Here, these features were used to accurately (r² = 0.91) predict the Young's modulus of polyurethane and polyurethane-urea elastomers. Furthermore, by a query of the trained model for compositions that yield a target modulus within the range of accessible values, the capabilities of using this methodology as a design tool are demonstrated. The presented methodology could become increasingly useful in building models for materials with small data sets and may guide the interpretation of the underlying physicochemical forces.