How do soft nanoparticles affect temperature-induced nonlinearity of a UCST copolymer blend?

Abstract

Temperature-induced nonlinearity of an upper critical solution temperature (UCST) copolymer blend and its nanocomposites containing 5 wt% mono-size soft nanoparticles (SNPs) were investigated. Mechanical and thermal energies contribution into the nonlinearity of UCST copolymer blend was 8.9×10 3 Jm −3 and 2.2×10 3 Jmol −1 , respectively. Addition of SNP did not change the system thermal-based nonlinearity, while altered its mechanical contribution at constant heating and solicitation conditions. It diminished to 0.4× 10 3 Jm −3 in the nanocomposite containing nano-size dispersion of aged SNPs. Micron-size agglomeration of the fresh SNPs in the nanocomposite; however, enhanced the required mechanical energy for nonlinearity to 4.1×10 3 Jm −3 . Shorttime annealing of the nanocomposite with micron-size agglomerates reduced its mechanical energy part to 2.8 × 10 3 Jm −3 , while annealing extension maximized it at 9.3× 10 3 Jm −3 . Heating rate increase amplified the thermal contribution into the nonlinearity at constant or reduced mechanical contribution. Finally, room-temperature annealing magnified the temperature-induced nonlinearity of the UCST copolymer blend at minimum mechanical contribution.

Active layer thickness across the crack plane and fracture energy consumption in polymer nanocomposites: adhesion against tear strength

“…Several transitions were also observed in the heat ow rst-derivative curve of the DSC thermogram at À26 (with a shoulder at À9), 54, and 97 C, with an obvious peak far from the components' glass transition temperatures, T g , at 155 C, assigned to the system's phase transition. 10 Based on the obtained results, the matrix presented roughly two kinds of random copolymers, one rich in BA and the other one rich in MMA. 10 In other words, each deconvoluted peak in the GPC curve and rst derivative of the DSC thermogram was indicative of individual random copolymers with a specic composition (average comonomer fraction in their chains).…”

“…10 Based on the obtained results, the matrix presented roughly two kinds of random copolymers, one rich in BA and the other one rich in MMA. 10 In other words, each deconvoluted peak in the GPC curve and rst derivative of the DSC thermogram was indicative of individual random copolymers with a specic composition (average comonomer fraction in their chains). 10 The heat ow rst-derivative curve of the DSC thermogram was deconvoluted into four Gaussian functions using MATLAB soware (R2010b).…”

“…The synthesized matrix, MBC30, was thoroughly characterized by gel permeation chromatography (GPC), differential scanning calorimetry (DSC), AFM, and rheometric mechanical spectroscopy (RMS) and the results were presented and discussed in our previous publication. 10 The GPC curve exhibited three overlapping peaks with weight-average molecular weight, M w , and dispersity of 92 kg mol À1 and 2.7, respectively. Several transitions were also observed in the heat ow rst-derivative curve of the DSC thermogram at À26 (with a shoulder at À9), 54, and 97 C, with an obvious peak far from the components' glass transition temperatures, T g , at 155 C, assigned to the system's phase transition.…”

“…9 In addition, colloidal polymer blends may also evolve into different morphologies, due to the components' size and/or stiffness disparity, through searching for structures with minimum free energies. [10][11][12][13] Interfacial healing among so polymer nanoparticles starts with capillary forces and continues up to molecular-scale homogeneity. 10,[14][15][16] Meanwhile, chain interdiffusion through the interfaces functions as the main mechanism of cohesion build-up.…”

“…[10][11][12][13] Interfacial healing among so polymer nanoparticles starts with capillary forces and continues up to molecular-scale homogeneity. 10,[14][15][16] Meanwhile, chain interdiffusion through the interfaces functions as the main mechanism of cohesion build-up. 2,3,17 The adhesive lm surface wettability and interfacial bond formation through nonlinear viscoelastic deformation are other key parameters determining joint formation and target performance.…”