2019
DOI: 10.1021/acs.macromol.8b02136
|View full text |Cite
|
Sign up to set email alerts
|

Effect of Copolymer Sequence on Local Viscoelastic Properties near a Nanoparticle

Abstract: We simulate a simple nanocomposite consisting of a single spherical nanoparticle surrounded by coarse-grained polymer chains that are composed of two monomer types differing only in their interactions with the nanoparticle. We measure the atomic stress fluctuations and use them to estimate the local stress autocorrelation as a function of distance from the nanoparticle. This local stress autocorrelation is substituted into the well-known relationship between the bulk stress autocorrelation and the bulk (freque… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

2
8
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
7
1
1

Relationship

0
9

Authors

Journals

citations
Cited by 13 publications
(10 citation statements)
references
References 97 publications
2
8
0
Order By: Relevance
“… 55 In addition, the results of computer simulations using the Kremer–Grest bead–spring model show higher dynamic modulus values as a function of distance from the nanoparticle surface for the block copolymer than for the alternating copolymer, indicating a higher interaction energy of the block copolymer with the nanoparticle surface. 56 The results of the theoretical studies were consistent with the results of experimental studies by Brun 57 and Peltier, 58 who studied the elution behavior of random and block copolymers with comparable chemical composition and molar mass, where the late elution of the block copolymer compared to the random copolymer was explained by the different microstructures. In contrast, Augenstein and Müller 59 attributed the late elution of block copolymers compared to random copolymers to the formation of supramolecular micelles.…”
Section: Introductionsupporting
confidence: 87%
“… 55 In addition, the results of computer simulations using the Kremer–Grest bead–spring model show higher dynamic modulus values as a function of distance from the nanoparticle surface for the block copolymer than for the alternating copolymer, indicating a higher interaction energy of the block copolymer with the nanoparticle surface. 56 The results of the theoretical studies were consistent with the results of experimental studies by Brun 57 and Peltier, 58 who studied the elution behavior of random and block copolymers with comparable chemical composition and molar mass, where the late elution of the block copolymer compared to the random copolymer was explained by the different microstructures. In contrast, Augenstein and Müller 59 attributed the late elution of block copolymers compared to random copolymers to the formation of supramolecular micelles.…”
Section: Introductionsupporting
confidence: 87%
“…Predicting the T g of nanocomposites remains challenging due to the complexity introduced by polymer/filler interfaces not captured by current models . In polymer nanocomposites, attractive nanoparticle surfaces significantly slow down the segmental dynamics of neighboring polymer chains, leading to a position-dependent increase in T g . The relationships between nanocomposite composition and T g become even more complicated when the convoluted effects of nanofiller size, ,, polymer chain length, ,,, and chemical structure ,, are considered.…”
mentioning
confidence: 99%
“…The force-field defining the interactions between the different components of our systems is a combination of the models proposed by Kremer and Grest for polymer chains [ 76 ] and Smith et al for NPs [ 77 ]. These models have been applied in the past to investigate structural and dynamical properties across several length and time scales [ 72 , 73 , 78 , 79 ]. In particular, non-bonded interactions are described by a shifted Weeks–Chandler–Andersen (WCA) potential [ 80 ] that reads: where is the intensity of the force between beads and , with ; is a shifting parameter, is the Heaviside step distribution; and is the cutoff distance.…”
Section: Model and Simulation Methodologymentioning
confidence: 99%