Simultaneous optimization of the vulcanization characteristics and mechanical properties of chloroprene and natural rubber blend by response surface methodology


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Aktar Demirtaş E., Goksuzoglu M., Karadeniz Y.

Polymer Bulletin, cilt.81, sa.14, ss.12691-12714, 2024 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 81 Sayı: 14
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1007/s00289-024-05309-7
  • Dergi Adı: Polymer Bulletin
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Chemical Abstracts Core, Chimica, Compendex, INSPEC
  • Sayfa Sayıları: ss.12691-12714
  • Anahtar Kelimeler: Curing, Response surface methodology, Rheology, Rubber blend, Vulcanization
  • Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

Chloroprene rubber (CR) is an expensive and frequently used material in many industries. Thus, a blend of natural rubber (NR) and CR can be used to balance cost and product performance. In this research, the primary objective is to achieve the ideal blend of CR/NR rubber for automotive industry by simultaneously optimizing various response variables, including hardness, tensile strength (TS), vulcanization index (CRI), torque difference and Tan δ. This optimization process is carried out using response surface methodology (RSM) and desirability functions. The study delves into examining the influence of accelerators, retarders, curatives, and the ratio of NR in the final batch on both curing characteristics and mechanical properties. The investigation is conducted through the application of analysis of variance (ANOVA) and linear/nonlinear regression models with the assistance of Design Expert 11. When the quantities of the fillers, TMTM80, DP80, S80, and CTPI80, are at their optimum levels of 1.08, 1.78, 3.5, and 0.96 PHR, respectively, and the NR ratio in the final masterbatch is around 27%, the estimated values for Tan δ, hardness, and TS are approximately 0.144, 55.183 Shore A, and 21.085 MPa, respectively. The observations from the validation experiments align with the predicted outcomes, as all response variables fall within the 95% prediction interval. It is noteworthy to mention that prior research has not attempted simultaneous optimization for CR/NR blend, incorporating these fillers.