The dynamic modulus of polymer solutions and melts can be expressed as a universal function of reduced frequency when the modulus is scaled by a characteristic value according to the scaling theory of polymer physics. Although the plot of the scaled modulus as a function of the scaled frequency supports the theory, it suffers from considerable scattered distribution of data points around the hypothetical master curve. Compared with the master curve of the time–temperature superposition (TTS) of polymer melts, the master curve of polymer solutions has poor quality. Furthermore, the scale factors of polymer solutions may not show a clear dependency on molecular weight and concentrations. Experimental errors and molecular weight distribution appear to enhance the inaccuracy of the master curve. Therefore, we apply a global optimization for the superposition of the viscoelastic data of polymer solutions with various molecular weights and concentrations. The global optimization resulted in the superposition of data as accurate as that of TTS. Furthermore, the numerically determined shift factors, which were relative scale factors, showed clear dependences on molecular weight and concentrations. We compared our global optimization with previous scaling methodologies.

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