Creep attenuation in glassy polymer nanocomposites with variable polymer–nanoparticle interactions

Buitrago, C. Francisco; Pressly, James; Yang, Anita S.; Gordon, Peter A.; Riggleman, Robert A.; Natarajan, Bharath; Winey, Karen I.

doi:10.1039/d0sm01247e

Cited by 17 publications

(26 citation statements)

References 30 publications

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“…This method for quantifying creep attenuation has been used previously and the exponential relation between critical time and NP loading are not qualitatively sensitive to the choice of critical compliance values. 10 We note that while t crit is small (< 100s) for this reference temperature, under ambient conditions (around 25 • C) t crit may be on the order of several 10s to 100s of years due to the timetemperature equivalence in polymer viscoelasticity. These results are in qualitative agreement with previous measurements of creep in P2VP-silica nanocomposites.…”

Section: Resultsmentioning

confidence: 73%

“…These results are in qualitative agreement with previous measurements of creep in P2VP-silica nanocomposites. 10 We also study the effects of polymer-NP interactions on creep suppression in simulation systems, by fixing the NP loading at 10 vol% and varying the interaction parameters between polymers and NPs. We find strongly interacting NPs better suppress creep, as evidenced by the shift of the upturn in compliance curves to a longer times and the increase in t crit with pn (Figure 2c and 2f).…”

Section: Resultsmentioning

confidence: 99%

“…5 Studies have shown that adding nanoparticles (NPs) with neutral or attractive polymer-NP interactions can significantly change the mechanical properties of polymer matrices, including increasing tensile strength and average shear and Young's moduli, altering polymers' nonaffine displacement field during deformation, and rendering the material less fragile. [6][7][8][9][10] While some studies show that polymer nanocomposites (PNCs) have a better resistance to creep, [10][11][12][13][14] the mechanism of creep suppression, including the role of NP size, loading, and polymer-NP interactions, remains unclear.…”

Section: Introductionmentioning

confidence: 99%

“…10 55.Riande, E.; Markovitz, H. Approximate relations among compliance functions of linear viscoelasticity for amorphous polymers. Journal of Polymer Science: Polymer Physics Edition 1975, 13, 947-951.…”

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confidence: 99%

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Understanding Creep Suppression Mechanism in Polymer Nanocomposites through Machine Learning

Yang¹,

Pressly²,

Natarajan³

et al. 2022

Preprint

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While recent efforts have shown how local structure plays an essential role in the dynamic heterogeneity of homogeneous glass-forming materials, systems containing interfaces such as thin films or composite materials remain poorly understood. It is known that interfaces perturb the molecular packing nearby, however, numerous studies show the dynamics are modified over a much larger range. Here, we examine the dynamics in polymer nanocomposites (PNCs) using a combination of simulations and experiments and quantitatively separate the role of polymer packing from other effects on the dynamics, as a function of distance from the nanoparticle surfaces. After showing good qualitative agreement between the simulations and experiments in glassy structure and creep compliance, we use a recently developed machine learning technique to decompose polymer dynamics in our simulated PNCs into structure-dependent and structureindependent processes. With this decomposition, the free energy barrier for polymer rearrangement can be described as a combination of packing-dependent and packing-independent barriers. We find both barriers are higher near nanoparticles and decrease with applied stress, quantitatively demonstrating that the slow interfacial dynamics is not solely due to polymer packing differences, but also the change of structure-dynamics relationships. Finally, we present how this decomposition can be used to accurately predict strain-time creep curves for PNCs from their static configuration, providing additional insights into the effects of polymernanoparticle interfaces on creep suppression in PNCs.

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Section: Resultsmentioning

confidence: 73%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Understanding Creep Suppression Mechanism in Polymer Nanocomposites through Machine Learning

Yang¹,

Pressly²,

Natarajan³

et al. 2022

Preprint

Self Cite

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show abstract

“…In addition to the interactions in the system, many preparation conditions, such as the volume fraction of nanoparticles and the surfactants, will also affect the structure of PNCs 101 . Winey et al 102 added 5%–20% silica nanoparticles to the PS and P2VP solutions, respectively. And the results showed that the particles formed aggregations even adding the lowest number of nanoparticles.…”

Section: Nanoparticles Dispersion In Polymer Solutionmentioning

confidence: 99%

Research progress on the correlation between properties of nanoparticles and their dispersion states in polymer matrix

Yang

Cui

Meng

et al. 2021

J of Applied Polymer Sci

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When fabricating polymer nanocomposites (PNCs), it is difficult for nanoparticles to disperse stably in polymer matrix since their high-surface energy can cause them to attract each other. In this paper, we review the effects of nanoparticle size, surface chemical properties, and thermodynamic parameters on the dispersion state of nanoparticles (including inorganic and organic particles) in PNCs and describe some key measures to promote the nanoparticles dispersion. The ideal nanoparticles dispersion in polymer melt is available when the particle size is smaller than the rotation radius of polymer chains and the particle surface is highly compatible or has interactions with the matrix. In polymer solution, establishing proper thermodynamic parameters is necessary to ensure the balance interactions among particles, solvents, and polymers, leading to the successful preparation of PNCs with ideal structure. These results could supply theoretical suggestions for the design of PNCs. Moreover, the equilibrium dispersion may be unavailable without reasonable kinetic parameters, even if the dispersion process is thermodynamically favorable. Therefore, more studies are required on both thermodynamics and kinetics of the dispersion process.

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The polytannic acid‐Fe(III) functionalized graphene oxide in poly (propylene carbonate) nanocomposite enabling enhanced shape memory, UV‐resistance, and self‐healing performance

Ren,

Yang,

Xie

et al. 2024

Polymers for Advanced Techs

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Polypropylene carbonate (PPC) is a promising candidate of substrate materials used for human wearable devices due to its excellent ductility and biocompatibility. However, PPC is prone to be deformed, thus resulting in poor shape recovery property. One effective solution is to construct composites. In this work, poly (tannic acid) with Fe3+ (FPTA) @ graphene oxide (GO) was added to fabricate FPTA@GO/PPC composites. The results show that FPTA@GO can construct a tight network of hydrogen bonds into PPC to improve shape memory and self‐healing properties. By varying the FPTA@GO content, the composites exhibit tunable shape memory property. Dynamic mechanical analysis confirms that FPTA@GO/PPC composites show better shape memory properties compared with pure PPC. 5 wt% FPTA@GO/PPC composite demonstrates superior shape fixation ratio (Rf = 99%) as well as superior shape recovery ratio (Rr = 94%) in 37°C. Moreover, 5 wt% FPTA@GO/PPC composite possesses great self‐healing efficiency of 81% and tensile strength (17.2 MPa). The UV absorption capacity of 5 wt% FPTA@GO/PPC is increased by 150% (far and mid‐UV regions) and 400% (near‐UV region) compared with pure PPC. Thus, FPTA@GO/PPC composites have potential applications in developing shape memory, self‐healing, and UV‐resistant materials for human wearable devices.

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Creep attenuation in glassy polymer nanocomposites with variable polymer–nanoparticle interactions

Abstract: The addition of nanoparticles attenuates creep deformation in polymer nanocomposites; networked nanoparticle morphologies are more effective.

Cited by 17 publications

References 30 publications

Understanding Creep Suppression Mechanism in Polymer Nanocomposites through Machine Learning

Understanding Creep Suppression Mechanism in Polymer Nanocomposites through Machine Learning

Research progress on the correlation between properties of nanoparticles and their dispersion states in polymer matrix

The polytannic acid‐Fe(III) functionalized graphene oxide in poly (propylene carbonate) nanocomposite enabling enhanced shape memory, UV‐resistance, and self‐healing performance

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