Bonsung Koo

An optimized cross-linked network model to simulate the linear elastic material response of a smart polymer

This article presents a novel approach to model the mechanical response of smart polymeric materials. A cyclobutane-based mechanophore, named “smart particle” in this article, is embedded in an epoxy polymer matrix to form the self-sensing smart material. A spring–bead model is developed based on the results from molecular dynamics simulation at the nanoscale to represent bond clusters of a smart polymer. The spring–bead network model is developed through parametric studies and mechanical equivalence optimization to represent the microstructure of the material. A statistical network model is introduced, which is capable of bridging the high-accuracy molecular dynamics model at the nanoscale and the computationally efficient finite element model at the macroscale. A comparison between experimental and simulation results shows that the multiscale model can capture global mechanical response and local material properties.

Study of glass transition temperature (Tg) of novel stress-sensitive composites using molecular dynamic simulation

This study investigates the glass transition temperature (Tg) of novel stress-sensitive composites capable of detecting a damage precursor using molecular dynamics (MD) simulations. The molecular structures of a cross-linked epoxy network (which consist of epoxy resin, hardener and stress-sensitive material) have been simulated and experimentally validated. The chemical constituents of the molecular structures are di-glycidyl ether of bisphenol F (DGEBF: epoxy resin), di-ethylene tri-amine (DETA: hardener) and tris-(cinnamoyloxymethyl)-ethane (TCE: stress-sensitive material). The cross-linking degree is varied by manipulating the number of covalent bonds through tuning a cutoff distance between activated DGEBF and DETA during the non-equilibrium MD simulation. A relationship between the cross-linking degree and Tgs has been studied numerically. In order to validate a proposed MD simulation framework, MD-predicted Tgs of materials used in this study have been compared to the experimental results obtained by the differential scanning calorimetry (DSC). Two molecular models have been constructed for comparative study: (i) neat epoxy (epoxy resin with hardener) and (ii) smart polymer (neat epoxy with stress-sensitive material). The predicted Tgs show close agreement with the DSC results.

A novel statistical spring-bead based network model for self-sensing smart polymer materials

This paper presents a multiscale modeling approach to simulating the self-sensing behavior of a load sensitive smart polymer material. A statistical spring-bead based network model is developed to bridge the molecular dynamics simulations at the nanoscale and the finite element model at the macroscale. Parametric studies are conducted on the developed network model to investigate the effects of the thermoset crosslinking degree on the mechanical response of the self-sensing material. A comparison between experimental and simulation results shows that the multiscale framework is able to capture the global mechanical response with adequate accuracy and the network model is also capable of simulating the self-sensing phenomenon of the smart polymer. Finally, the molecular dynamics simulation and network model based simulation are implemented to evaluate damage initiation in the self-sensing material under monotonic loading.

Dimeric anthracene-based mechanophore particles for damage precursor detection in reinforced epoxy matrix composites

The problem of catastrophic damage purveys in any material application, and minimizing its occurrence is paramount for general health and safety. We have successfully synthesized, characterized, and applied dimeric 9-anthracene carboxylic acid (Di-AC)-based mechanophore particles to form stress sensing epoxy matrix composites. As Di-AC had never been previously applied as a mechanophore and thermosets are rarely studied in mechanochemistry, this created an alternative avenue for study in the field. Under an applied stress, the cyclooctane-rings in the Di-AC particles reverted back to their fluorescent anthracene form, which linearly enhanced the overall fluorescence of the composite in response to the applied strain. The fluorescent signal further allowed for stress sensing in the elastic region of the stress–strain curve, which is considered to be a form of damage precursor detection. Overall, the incorporation of Di-AC to the epoxy matrix added much desired stress sensing and damage precursor detection capabilities with good retention of the material properties.

Multiscale damage analysis of carbon nanotube nanocomposite using a continuum damage mechanics approach

A multiscale-modeling framework is presented to understand damage and failure response in carbon nanotube reinforced nanocomposites. A damage model is developed using the framework of continuum damage mechanics with a physical damage evolution equation inspired by molecular dynamics simulations. This damage formulation is applied to randomly dispersed carbon nanotube reinforced nanocomposite unit cells with periodic boundary conditions to investigate preferred sites and the tendency towards damage. The continuum model is seen as successfully capturing much of the unique nonlinear trends observed in the molecular dynamics simulations in a volume 1000 times greater than the molecular dynamics unit cell. Additionally, application of the damage model to the continuum unit cell revealed insights into the failure of carbon nanotube reinforced nanocomposites at the sub-microscale.

Molecular dynamics-based multiscale damage initiation model for CNT/epoxy nanopolymers

Abstract A methodology that accurately simulates the brittle behavior of epoxy polymers initiating at the molecular level due to bond elongation and subsequent bond dissociation is presented in this paper. The system investigated in this study comprises a combination of crystalline carbon nanotubes (CNTs) dispersed in epoxy polymer molecules. Molecular dynamics (MD) simulations are performed with an appropriate bond order-based force field to capture deformation-induced bond dissociation between atoms within the simulation volume. During deformation, the thermal vibration of molecules causes the elongated bonds to re-equilibrate; thus, the effect of mechanical deformation on bond elongation and scission cannot be captured effectively. This issue is overcome by deforming the simulation volume at zero temperature—a technique adopted from the concept of quasi-continuum and demonstrated successfully in the authors’ previous work. Results showed that a combination of MD deformation tests with ultra-high strain rates at near-zero temperatures provides a computationally efficient alternative for the study of bond dissociation phenomenon in amorphous epoxy polymer. In this paper, the ultra-high strain rate deformation approach is extended to the CNT-epoxy system at various CNT weight fractions and the corresponding bond disassociation energy extracted from the simulation volume is used as input to a low-fidelity continuum damage mechanics (CDM) model to demonstrate the bridging of length scales and to study matrix failure at the microscale. The material parameters for the classical CDM model are directly obtained from physics-based atomistic simulations, thus improving the accuracy of the multiscale approach.

Stress-sensing thermoset polymer networks via grafted cinnamoyl/cyclobutane mechanophore units in epoxy

The incorporation of mechanophores into networked thermoset polymers, such as epoxy, is notably missing from the mechanochemistry literature, which focuses more on traditional thermoplastic and elastomeric polymers. In this work, we develop novel approaches for direct covalent grafting of photoactive mechanophore units into an epoxy matrix (a two-part network polymer), to create a self-sensing thermoset network nanocomposite, linked by both epoxide and mechanophore bonds. Two routes of grafting mechanophore units into an epoxy system to form a self-sensing nanocomposite were explored, including grafting of the mechanophore precursor molecule cinnamamide to the epoxy resin, with subsequent hardener addition and ultraviolet curing to form the mechanically sensitive cyclobutane rings, and the separate grafting of the solution-made mechanophore di-cinnamamide to the epoxy resin to allow for maximum cyclobutane concentration in the formed nanocomposites. Under a compressive force, the cyclobutane rings in the mechanophore units break, increasing the overall fluorescence, which can then be correlated with the applied stress. The goals of this work included detecting early damage by fluorescence spectroscopy, environmental robustness, and retention of the mechanical and thermal properties of the composite. Overall, there was successful formation of self-sensing nanocomposites and achievement of the early damage detection functionality. This systematic work additionally aims to provide further fundamental understanding of mechanochemistry as a whole.

Multiscale Modeling and Characterization of Stress-sensitive Mechanophore-embedded Nanocomposites

This paper presents the characterization and multiscale modeling of novel stresssensitive mechanophore-embedded nanocomposites. Stress-sensitive mechanophores that emit fluorescence under mechanical loading have been developed recently. In this study, a cyclobutane-based mechanophore is incorporated into thermoset polymer matrix for early damage detection. Tris-Cinnamoyloxymethyl-Ethane monomer is used to make the cyclobutane-based mechanophore using ultra violet (UV) light by a process called UV-dimerization. Test results indicate that the cyclobutane-based mechanophore embedded thermoset polymer matrix is capable of capturing crack nucleation by exhibiting a color change under mechanical loading. A multiscale modeling framework connecting sub-nanoscale phenomena to a bulk polymer system is also developed by implementing a hybrid MD simulation approach. The multiscale modeling framework simulates cyclobutane-based mechanophore synthesis and mechanophore activation successfully. Local force analysis implemented by the multiscale modeling framework enables quantitative analysis of the mechanophore activation process and shows good correlation with experimental results. doi: 10.12783/SHM2015/277

Multiscale Modeling of a Mechanophore-embedded Nanocomposite for Damage Initiation Detection

This paper presents multiscale modeling of a mechanophore-embedded nanocomposite material for detection of damage initiation. Mechanophores are force-responsive functional units which allow for molecular-scale understanding of the local mechanical environment and can transform the material properties in response. Recently, a cyclobutane-based mechanophore embedded in a thermoset polymer matrix has been investigated for detecting damage precursors and tracking propagation in a thermoset polymeric matrix. Tris-(Cinnamoyloxymethyl)-Ethane (TCE) was used as fluorescent crack sensing additives in epoxy network polymer blends. The cyclobutane sensing units were produced by photodimerization of the C=C double bond in the cinnamoyl functional group of TCE. When the blended system undergoes crack formation and propagation, the cyclobutane units are mechanochemically cleaved to afford the monomeric structure. This structure is capable of strong fluorescence emission, indicating the location of the crack in the epoxy. This study aims at developing a mechanochemical reaction-based multiscale modeling framework to simulate the self-sensing phenomenon of TCE-embedded thermoset polymers. The methodology initiates at the atomistic level and connects the relevant length scales; ranging from mechanophore activation at the sub-molecular level to fluorescence intensity at the nano/microscale. A quantum theory-based method is incorporated to quantify the interatomic potential of the mechanophore under external force. Intermolecular force is estimated using molecular dynamics (MD) simulation by analyzing energy distribution in the epoxy/smart material network structure. A bond ordered potential-based MD simulation has been incorporated to simulate mechanophore activation, which is correlated to the fluorescence intensity of the mechanophore. The experimentally observed color change phenomena associated with damage initiation have also been interpreted using this quantum theory-based modeling framework.

A multiscale model coupling molecular dynamics simulations and micromechanics to study the behavior of CNT-enhanced nanocomposites

A comprehensive, point-information-to-continuum-level analysis framework is presented in this paper to accurately characterize the behavior of CNT-enhanced composite materials. Molecular dynamics (MD) simulations are performed to study atomistic interactions of the CNT with the polymeric phase. The effect of crosslinking between the epoxy resin and the hardener on the mechanical properties of the polymer is investigated; furthermore, the effect of CNT weight fraction on the most likely polymer cross-linking degree is also studied through stochastic models. The stochastic distributions obtained from MD simulations provide a basis to simulate local variations in the matrix properties at the fiber-centered continuum model at the microscale. The interfaces at nanoscale (CNT and matrix) and microscale (fiber and CNT-dispersed matrix) are characterized by performing CNT pullout simulations, and a single fiber pullout simulation, respectively.