This study introduces a novel methodology for the kinetic analysis of the polymer melting process, which is based on the exponential model of Toda–Hikosaka–Yamada (https://doi.org/10.1016/S0032-3861(01)00733-9) and originates from nucleation theory. The proposed approach utilizes melting peak temperatures from nonisothermal experiments conducted at constant heating rates and employs linear regression to simultaneously determine the nonequilibrium melting temperature \({T}_{m}\) and the kinetic parameters of the exponential model. While a similar linear regression technique has been widely applied to the power-law model of the Toda–Hikosaka–Yamada model, its use in nonpower-law melting processes yields inaccurate \({T}_{m}\) estimates. The accuracies of both the power-law and exponential models were validated using simulated melting data, and the methods were subsequently applied to experimental polyethylene melting kinetics. The results revealed differences in the estimated \({T}_{m}\) values between the models. A comparison with the fast scanning calorimetry curves indicates that the \({T}_{m}\) estimated by the exponential model is more physically realistic, and is consistently lower than the observed melting onset temperatures. The validity levels of the proposed methods were tested by applying them to the melting peak temperatures of several polymers, including isotactic polypropylene, low-density polyethylene, poly(ϵ-caprolactone), poly(ethylene terephthalate), poly(butylene terephthalate), poly(vinylidene fluoride), and ultrahigh-molecular-weight polyethylene. The corresponding kinetic parameters for both the power-law and exponential models were subsequently estimated for these polymers. To facilitate implementation, GNU Octave/MATLAB scripts are provided for researchers to apply the methodologies to their kinetic datasets.
