Multi-scale coarse-grained molecular dynamics simulation to investigate the thermo-mechanical behavior of shape-memory polyurethane copolymers

Park, Sung Woo; Moon, Jin San; Kim, Byungjo; Cho, Maenghyo

doi:10.1016/j.polymer.2020.123228

Cited by 42 publications

(40 citation statements)

References 42 publications

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“…RHPU grouting materials are porous mediums consisting of a large number of closed micro‐foams and the mechanical properties are mainly affected by the mechanical behavior of the micro‐foam walls 16,18 . It has been known that as the density increases, the average diameter of the micro‐foams declines, and the walls of the micro‐foams become thicker, 16,18 which indicates the stronger adsorption between the molecular chains 57,58 as well as the enhanced stiffness of the micro‐foam walls, 34 and thus the strength of the micro‐foams is enhanced. With the same amount of deformation, the strain energy accumulated in the RHPU grouting materials of the relatively higher density will increase, resulting in enhanced mechanical properties 59,60 .…”

Section: Resultsmentioning

confidence: 99%

“…59,60 When the axial stress reaches the yield strength, the accumulated strain energy begins to dissipate. 61,62 For the high-density RHPU grouting materials, the amount of strain energy dissipated by the friction between polymer chains will decrease due to the enhanced adsorption of polymer chains, 57,58 while the amount converted to the surface energy of new cracks will correspondingly increase, and thus the micro-foam walls in the high-density RHPU are more prone to fracture. The formation of the new cracks is the main cause of the stress declining after yield.…”

Section: The Influences Of Densitymentioning

confidence: 99%

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Study of the mechanical properties and constitutive model of the roadbed rehabilitation polyurethane grouting materials under uniaxial compression

Fang

Zheng

et al. 2022

J of Applied Polymer Sci

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Polyurethane grouting materials are increasingly used in the non-excavation rehabilitation of roadbeds. The compressive strength of roadbed rehabilitation polyurethane (RHPU) grouting materials is the key to achieving the desirable repair effect, whereas the constitutive model of RHPU grouting materials is not yet understood. Here, the mechanical properties of RHPU grouting materials under compression were experimentally investigated, followed by establishing the hyperfoam constitutive model. The variation laws of the critical parameters in the model with density were function fitted, and then the constitutive model was simplified as an equation of density as the single independent variable. The comparisons between the theoretical and experimental mechanical behavior of RHPU grouting materials were discussed to illustrate the applicability of the hyperfoam constitutive model. Results show that with the increasing density, both the yield strength (σ 1 ), elastic modulus (E 1 ), and secant modulus (E s ) increases exponentially, and the Poisson's ratio (v) increases logarithmically. The maximum increase in σ 1 , E 1 , E s , and v are about 750%, 720%, 940%, and 50%, respectively. Compared to the effects of density on the mechanical properties, the effect of loading rate is much smaller, and the side length has no effect. For RHPU samples with a density not exceeding 0.35 g/cm 3 , the hyperfoam model can well describe the uniaxial compression mechanical behavior, but for those whose density exceeds 0.35 g/cm 3 , the model can only describe the mechanical behavior before yielding. The theoretical yield strength of the RHPU samples obtained from the model is close to the experimental value (with differences of about 0.1%-14.4%). This study provides a base to evaluate the compressive strength of the practically used RHPU grouting materials based on the density.

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Section: Resultsmentioning

confidence: 99%

Section: The Influences Of Densitymentioning

confidence: 99%

Study of the mechanical properties and constitutive model of the roadbed rehabilitation polyurethane grouting materials under uniaxial compression

Fang

Zheng

et al. 2022

J of Applied Polymer Sci

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“…This calculational tool has already been successfully used for studies of polymerization of quite different macromolecular systems, such as star-branched macromolecules and polymer brushes [37][38][39]. The DLL model was described and discussed in detail elsewhere [35,36] and, therefore, we are going to give only a short description here. The model objects occupy all lattice sites in the system and they are not able to move at larger distances due to the crowding caused by the presence of other objects.…”

Section: Computer Simulations: the Model And The Methodsmentioning

confidence: 99%

“…Recently, a thermo-mechanical behavior of shape-memory PUR copolymers was reported in the literature. Park et al simulated the SMP using a coarse-grained molecular dynamics simulation [35]. However, to our knowledge, no research concerning computer simulations of complex two-step OCD synthesis, followed by the synthesis of urethane prepolymers and curing process of PCUUs has been carried out before.…”

Section: Introductionmentioning

confidence: 99%

Synthesis of Shape-Memory Polyurethanes: Combined Experimental and Simulation Studies

Rolińska

Mazurek-Budzyńska

Parzuchowski

et al. 2022

IJMS

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The presented research focuses on the synthesis and structure–properties relationship of poly(carbonate-urea-urethane) (PCUU) systems including investigations on shape memory effect capability. Furthermore, we approached the topic from a broader perspective by conducting extensive analysis of the relationship between the synthesized compounds and the results of computer simulations by means of the Monte Carlo method. For the first time, by using a unique simulation tool, the dynamic lattice liquid model (DLL), all steps of multi-step synthesis of these materials were covered by the simulations. Furthermore, broad thermal, mechanical, and thermomechanical characterization of synthesized PCUUs was performed, as well as determining the shape memory properties. PCUUs exhibited good mechanical properties with a tensile strength above 20 MPa, elongation at break around 800%, and an exhibited shape memory effect with shape fixity and shape recovery ratios above 94% and 99%, respectively. The dynamic lattice liquid model was employed to show the products and their molar mass distribution, as well as monomer conversion or the dispersity index for individual reaction steps. The results obtained in the following manuscript allow the planning of syntheses for the PCUUs of various structures, including crosslinked and soluble systems, which can provide a broad variety of applications of these materials, as well as a better understanding of the composition–properties relationship.

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“…317,318 Recently, Park et al used IBI to develop CG models to describe and analyze the behavior of shape-memory polyurethanes upon thermomechanical deformation. 319 Interestingly, their parameterization was performed at a single temperature of 300 K but nonetheless exhibited reasonable temperature and composition transferability. Although not necessarily used for SMPs, the energy renormalization method 38,257,320 can achieve molecular mobility differences based on the temperature-dependent non-bonded interaction parameters.…”

Section: Stimuli Responsementioning

confidence: 99%

Chemically specific coarse‐graining of polymers: Methods and prospects

Dhamankar

Webb

2021

Journal of Polymer Science

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Coarse-grained (CG) modeling is an invaluable tool for the study of polymers and other soft matter systems due to the span of spatiotemporal scales that typify their physics and behavior. Given continuing advancements in experimental synthesis and characterization of such systems, there is ever greater need to leverage and expand CG capabilities to simulate diverse soft matter systems with chemical specificity. In this review, we discuss essential modeling techniques, bottom-up coarse-graining methodologies, and outstanding challenges for the chemically specific CG modeling of polymer-based systems. This methodologically oriented discussion is complemented by representative literature examples for polymer simulation; we also offer some advisory practical considerations that should be useful for new researchers. Given its growing importance in the modeling and polymer science community, we further highlight some recent applications of machine learning that enhance CG modeling strategies. Overall, this review provides comprehensive discussion of methods and prospects for the chemically specific coarse-graining of polymers.

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Multi-scale coarse-grained molecular dynamics simulation to investigate the thermo-mechanical behavior of shape-memory polyurethane copolymers

Cited by 42 publications

References 42 publications

Study of the mechanical properties and constitutive model of the roadbed rehabilitation polyurethane grouting materials under uniaxial compression

Study of the mechanical properties and constitutive model of the roadbed rehabilitation polyurethane grouting materials under uniaxial compression

Synthesis of Shape-Memory Polyurethanes: Combined Experimental and Simulation Studies

Chemically specific coarse‐graining of polymers: Methods and prospects

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