A multiscale model for the synthesis of thermosetting resins: From the addition reaction to cross-linked network formation

Li, Jing; Jumpei, Sakamoto; Waizumi, Hiroki; Oya, Yutaka; Huang, Yue; Kishimoto, Naoki; Okabe, Tomonaga

doi:10.1016/j.cplett.2019.02.012

Cited by 20 publications

(14 citation statements)

References 19 publications

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“…Manfredi et al reported T g values of 506 K and 530 K for 1.2:1 and 1.5:1 F:P ratios, respectively [31]. In comparison to other simulated literature, the simulation in this work shows a clear improvement, e.g., the comparable simulation produced by Li et al, which resulted in a T g of 412 K for a 1.5:1 F:P ratio model [30]. Simulated values of Tg were derived for the 1.2:1 and 1.5:1 F:P ratio cured models, and achieved values of 515 K and 526 K, respectively.…”

Section: Simulation Outcomessupporting

confidence: 52%

“…This is a simple method for generating crosslinked structures, although it limits the potential variability in the models, leaving the simulation prone to bias. Work by Li et al utilises a novel mixed modelling technique for generating resole phenolic resin structures using quantum calculations, Monte Carlo and MD simulation originating from monomers [30]. Although they report model densities supported by empirical literature, their T g results fall significantly below those produced empirically by Manfredi et al, with an F:P ratio of 2.0 simulating a T g of 403 K, compared to 543 K from empirical resin derived by dynamic mechanical analysis [31].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Approach to Atomistic Molecular Dynamics Simulation of Phenolic Resins Using Symthons

et al. 2020

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Materials science is beginning to adopt computational simulation to eliminate laboratory trial and error campaigns—much like the pharmaceutical industry of 40 years ago. To further computational materials discovery, new methodology must be developed that enables rapid and accurate testing on accessible computational hardware. To this end, the authors utilise a novel methodology concept of intermediate molecules as a starting point, for which they propose the term ‘symthon’ (The term ‘Symthon’ is being used as a simulation equivalent of the synthon, popularised by Dr Stuart Warren in ‘Organic Synthesis: The Disconnection Approach’, OUP: Oxford, 1983.) rather than conventional monomers. The use of symthons eliminates the initial monomer bonding phase, reducing the number of iterations required in the simulation, thereby reducing the runtime. A novel approach to molecular dynamics, with an NVT (Canonical) ensemble and variable unit cell geometry, was used to generate structures with differing physical and thermal properties. Additional script methods were designed and tested, which enabled a high degree of cure in all sampled structures. This simulation has been trialled on large-scale atomistic models of phenolic resins, based on a range of stoichiometric ratios of formaldehyde and phenol. Density and glass transition temperature values were produced, and found to be in good agreement with empirical data and other simulated values in the literature. The runtime of the simulation was a key consideration in script design; cured models can be produced in under 24 h on modest hardware. The use of symthons has been shown as a viable methodology to reduce simulation runtime whilst generating accurate models.

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Section: Simulation Outcomessupporting

confidence: 52%

Section: Introductionmentioning

confidence: 99%

A Novel Approach to Atomistic Molecular Dynamics Simulation of Phenolic Resins Using Symthons

et al. 2020

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“…This probability was determined from the activation energy and local temperature, where the activation energy and H f were calculated by a semiempirical molecular orbital (MO) method. More recently, Li et al 28 employed an ab‐initio MO method (Gaussian) to calculate the activation energy and H f and further combined it with the MC/MD simulations. These studies revealed that the exothermic chemical reactivity ( E a and H f ) impacted the curing structure in thermosetting epoxy resins 17,18,28 …”

Section: Curing Simulationmentioning

confidence: 99%

“…These studies revealed that the exothermic chemical reactivity (E a and H f ) impacted the curing structure in thermosetting epoxy resins. 17,18,28 3.2 | Model systems and curing procedure…”

Section: Molecular Dynamics Simulations For Exothermic Reaction Systemmentioning

confidence: 99%

Amine/epoxy stoichiometric ratio dependence of crosslinked structure and ductility inamine‐curedepoxy thermosetting resins

Odagiri

Shirasu

Kawagoe

et al. 2021

J of Applied Polymer Sci

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Epoxy‐amine thermosetting resins undergo different reactions depending on the amine/epoxy stoichiometric ratio (r). Although many desirable properties can be achieved by varying the stoichiometric ratio, the effects of the variation on the crosslinked structure and mechanical properties and the contribution of these factors to the ductility of materials have not been fully elucidated. This study investigates the brittle‐ductile behavior of epoxies with various stoichiometric ratios and performs curing simulations using molecular dynamics (MD) to evaluate the crosslinked structures. The molecular structure is predominantly branched in low‐stoichiometric ratio samples, whereas the chain extension type structure dominates the high‐stoichiometric ratio samples. As a result, the higher‐stoichiometric ratio samples enhances the ductility of materials and the elongation at break increases form 1.4% (r = 0.6) to 11.4% (r = 1.4). Additionally, the tensile strength (105.4 MPa) and strain energy (7.96 J/cm3) are maximum at r = 0.8 and 1.2, respectively. On the other hand, the Young's modulus is negatively impacted and it decreased from 4.2 to 2.7 GPa with increasing stoichiometric ratio.

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“…Although the curing behavior was simulated in this study, it focused more on the resulting mechanical properties caused by different functional groups. In the study from Li et al [ 16 ], the model was extended to a hybrid molecular dynamics/Monte Carlo ( MD / MC ) approach with reaction probabilities based on reaction path energies. Reactions of phenol resin with formaldehyde are investigated, and several thermal-mechanical properties agree with the experimental values.…”

Section: Introductionmentioning

confidence: 99%

Characterization of Cure Behavior in Epoxy Using Molecular Dynamics Simulation Compared with Dielectric Analysis and DSC

2021

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The curing behavior of a thermosetting material that influences the properties of the material is a key issue for predicting the changes in material properties during processing. An empirical equation can describe the reaction kinetics of the curing behavior of an investigated material, which is usually estimated using experimental methods. In this study, the curing process of an epoxy resin, the polymer matrix in an epoxy molding compound, is computed concerning thermal influence using molecular dynamics. Furthermore, the accelerated reaction kinetics, which are influenced by an increased reaction cutoff distance, are investigated. As a result, the simulated crosslink density with various cutoff distances increases to plateau at a crosslink density of approx. 90% for the investigated temperatures during curing time. The reaction kinetics are derived according to the numerical results and compared with the results using experimental methods (dielectric analysis and differential scanning calorimetry), whereby the comparison shows a good agreement between experiment and simulation.

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A multiscale model for the synthesis of thermosetting resins: From the addition reaction to cross-linked network formation

Cited by 20 publications

References 19 publications

A Novel Approach to Atomistic Molecular Dynamics Simulation of Phenolic Resins Using Symthons

A Novel Approach to Atomistic Molecular Dynamics Simulation of Phenolic Resins Using Symthons

Amine/epoxy stoichiometric ratio dependence of crosslinked structure and ductility inamine‐curedepoxy thermosetting resins

Characterization of Cure Behavior in Epoxy Using Molecular Dynamics Simulation Compared with Dielectric Analysis and DSC

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