Scientists have long been fascinated by the lower critical solution temperature (LCST), which is the temperature below which the components of a mixture are completely mixed, and above which partial mixing occurs. dissolution phenomenon. This phenomenon widely exists in many small molecules and polymer systems, which is closely related to their molecular structure, interactions and other factors.
"Below the LCST, the system is completely miscible in all proportions, while above it exhibits partial liquid miscibility."
To understand the concept of LCST in depth, we need to look at how it differs from other phase behaviors. For many mixtures, the mixing phenomenon is affected by both entropy and enthalpy. However, in the case of LCST, the separation phenomenon is often caused by unfavorable entropy. This means that below the LCST, interactions between components promote spontaneous mixing, while above the LCST, phase separation occurs, which is directly related to the positive and negative variations of the Gibbs free energy change.
In polymer solutions, factors that affect LCST include the molecular weight of the polymer, the degree of polymerization of the polymer, and the degree of branching. The most well-known is poly(N-isopropylacrylamide) aqueous solution, whose LCST is generally considered to be around 32 °C, but may actually vary depending on factors such as polymer concentration and molecular weight. Such changes make LCST predictions closely related to polymer properties.
“The screening and design needs of polymers have led us to conduct a lot of research on LCST in order to find solutions that can be applied in the manufacturing process.”
The key to the emergence of LCST lies in physical factors. For systems containing large molecules, compressibility effects can lead to LCST phenomena. Taking the example of polystyrene in cyclohexane, the solvent and polymer under high pressure show different expansion behaviors, so that the solvent must shrink at high temperatures, thereby losing entropy to achieve mixing conditions.
In statistical mechanics, LCST is modeled by the lattice fluid model theory, which takes into account the effects of variable density and compressibility. Through these theories, we can better understand and predict the LCST of different mixtures. At the same time, a variety of methods are currently used to predict LCST, including models based on experimental data and empirical equations based on physical and chemical properties. Recently, there have also been attempts to introduce molecular connectivity indices into models, a method that has shown its potential in QSPR/QSAR studies of polymers and polymer solutions, enabling efficient prediction of LCST before experiments.
“QSPR/QSAR research not only reduces trial and error costs, but also accelerates the design of new materials.”
Research on LCST is still ongoing, and more polymer systems and different combinations of their hybrid behaviors may be explored in the future. As materials science advances and new technologies emerge, new polymers or small molecule systems that link LCST behavior will continue to emerge. This not only has a profound impact on basic scientific research, but also opens up more possibilities for applied science.
Do the chemical and physical laws hidden behind these studies inspire us to rethink the behavior of mixtures in changing environments?