Nonisothermal crystallization of polymers: Getting more out of kinetic analysis of differential scanning calorimetry data. Issue 2 (10th April 2018)

• Record Type: Journal Article
• Authors: Vyazovkin, Sergey
• Is Part Of: Polymer crystallization. Volume 1:Issue 2(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-04-10
• Subjects: crystallization -- differential scanning calorimetry -- kinetics; Crystalline polymers -- Periodicals; Crystallization -- Periodicals; Polymers -- Periodicals; 668.9
• DOI: 10.1002/pcr2.10003
• Languages: English
• ISSNs: 2573-7619

Abstract

Abstract: Differential scanning calorimetry data on nonisothermal crystallization kinetics of polymers are routinely parameterized in terms of the Avrami model. The parameterization is most commonly accomplished by the techniques proposed by Ozawa, Jeziorny, and Mo that are discussed briefly. The Ozawa technique frequently gives rise to nonlinear plots that do not enable determining the Avrami exponent. The Jeziorny technique appears inadequate for correctly evaluating the Avrami exponent. The Mo technique yields parameters whose numerical values cannot be directly interpreted in terms of the Avrami model. The emerging technique based on combining the Hoffman‐Lauritzen model with an isoconversional method is considered as a more rewarding alternative. This technique produces physically meaningful parameters capable of providing insights into the kinetics and mechanisms of nonisothermal crystallization. It is cautioned that the Kissinger method as well as some popular integral isoconversional methods (eg, Kissinger‐Akahira‐Sunose and Ozawa‐Flynn‐Wall) should not be used for evaluating the activation energy of the melt crystallization. Abstract : Application of an isoconversional method to differential scanning calorimetry data on nonisothermal crystallization allows one to experimentally determine a temperature dependence of isoconversional activation energy. Parameterization of this dependence in terms of the Hoffman‐Lauritzen model affords estimating physically meaningful parameters of the process as well as obtaining insights into the process kinetics and mechanism.