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Prediction of curing kinetics of resorcinol‐added resole phenolic resins using differential scanning calorimetry for the fabrication of carbon/carbon composites

Cordeiro, Jose C. ; Davis, Rachel E. ; Ramsurn, Hema ; Crunkleton, Daniel W. ; Otanicar, Todd P. ; Keller, Michael W.

Journal of applied polymer science, 2022-10, Vol.139 (39), p.n/a [Periódico revisado por pares]

Hoboken, USA: John Wiley & Sons, Inc

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  • Título:
    Prediction of curing kinetics of resorcinol‐added resole phenolic resins using differential scanning calorimetry for the fabrication of carbon/carbon composites
  • Autor: Cordeiro, Jose C. ; Davis, Rachel E. ; Ramsurn, Hema ; Crunkleton, Daniel W. ; Otanicar, Todd P. ; Keller, Michael W.
  • Assuntos: Activation energy ; Carbon ; Carbon-carbon composites ; Curing ; Differential scanning calorimetry ; Heat measurement ; Kinetics ; Mathematical analysis ; Noise sensitivity ; Phenolic resins ; Polymer matrix composites ; Resins ; theory and modeling ; Thermogravimetric analysis
  • É parte de: Journal of applied polymer science, 2022-10, Vol.139 (39), p.n/a
  • Notas: Funding information
    Francis Manning Undergraduate Research Grant, The University of Tulsa; U.S. Department of Energy, Grant/Award Number: DE‐EE0008736
    USDOE
    DE‐EE0008736
  • Descrição: Phenolic resins are commonly used as carbon precursors for the fabrication of carbon/carbon composites due to their high carbon yield and aromatic nature. To decrease curing times, acid catalysts are generally used, but the addition of resorcinol was found to have a similar effect while being incorporated into the resin matrix with no contamination or corrosion issues. In this work, the curing kinetics of pure, 10, 20, and 30 wt% resorcinol‐added phenolic resins were investigated through differential scanning calorimetry. Heating rates of 0.5, 1, 2.5, and 5°C min−1 were used with several curing models to predict isothermal curing. Averaged mean absolute error (MAE) for the isoconversional mathematical approaches namely Kissinger–Akahira–Sunose (MAE = 12.9 min), Flynn–Wall–Ozawa (15.8 min), and Vyazovkin (14 min) show that these methods provide the best predictions, attributed to their adoption of an activation energy that depends on the extent of cure (Ea (α)). The Kissinger method (MAE = 36 min), which depends only on peak temperature with a constant activation energy assumption, and the data noise sensitive Friedman model (MAE = 1144.7 min) provide the least accurate results. Thermogravimetric analysis revealed that resorcinol decreases the curing times by up to 71% without lowering carbon yield. Resorcinol‐added phenolic resins show a complex curing reaction behavior, where resorcinol and phenol play competing roles. Differential scanning calorimetry is used with pure, 10, 20, and 30 wt% resorcinol added phenolic resins to fit different curing methods. Isoconversional model‐free models are able to best predict isothermal curing times for these systems.
  • Editor: Hoboken, USA: John Wiley & Sons, Inc
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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