Scaling Law for Thermal Evolution in Concentrated Aqueous Systems Based on Logistic Kinetics: Experimental Modelling, Bibliometric Mapping, and Implications for Chemistry Education and Sustainable Development Goals (SDGs)

This study establishes a scaling law for the thermal evolution of concentrated aqueous systems using a logistic kinetics framework. Temperature–time profiles of aqueous glucose solutions with concentrations ranging from 2.5% to 45.0% were obtained under constant heating conditions and analyzed through a logistic differential model. The results reveal a universal sigmoidal heating behavior characterized by an initial rapid temperature rise followed by saturation toward a concentration-dependent boiling equilibrium. The intrinsic thermal rate constant exhibits a linear dependence on solute concentration, forming the basis of a predictive scaling relationship. Experimental validation demonstrates excellent model performance, with mean squared error values between 0.008 and 0.051, root mean squared error values between 0.087 and 0.227, and coefficients of determination consistently approaching 0.999. Nonparametric statistical tests confirm heat-source consistency and the absence of significant differences between predicted and experimental temperatures. Bibliometric mapping highlights increasing research interest in logistic-based thermal modelling across chemistry, materials science, and soft-matter systems. Beyond its predictive capability, the proposed framework provides a conceptually accessible platform for teaching nonlinear kinetics, data-driven modelling, and thermally activated processes in chemistry education.