• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.358-358
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• 2010

Ion beam bombardment at low energy forms nanosize patterns such as ripples, dots or wrinkles on the surface of polymers in ambient temperature and pressure. It has been known that the ion beam can alter the polymer surface that induces skins stiffer or the density higher by higher compressive stress or strain energies associated with chain scissions and crosslinks of the polymer. Atomic scale structure evolution in polymers is essential to understand a stress generation mechanism during the ion beam bombardment, which governs the nanoscale surface structure evolution. In this work, Molecular Dynamics (MD) simulations are employed to characterize the phenomenon occurred in bombardment between the ion beam and polymers that forms nanosize patterns. We investigate the structure evolution of Low Density Polyethylene (LDPE) at 300 K as the polymer is bombarded with Argon ions having various kinetic energies ranging from 100 eV to 1 KeV with 50 eV intervals having the fluence of $1.45\;{\times}\;1014 #/cm2$. These simulations use the Reactive Force Field (ReaxFF), which can mimic chemical covalent bonds and includes van der Waals potentials for describing the intermolecular interactions. The results show the details of the structural evolution of LDPE by the low energy Ar ion bombardment. Analyses through kinetic and potential energy, number of crosslinks and chain scissions, level of local densification and motions of atoms support that the residual strain energies on the surface is strongly associated with the number of crosslinks or scissored chains. Also, we could find an optimal Ar ion beam energy to make crosslinks well.

• Bulletin of the Korean Chemical Society
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• v.31 no.2
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• pp.453-456
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• 2010

The structural and energetic preferences of thiacalix[4]biscrown-5 with and without alkali metal ions ($Na^+$, $K^+$, $Rb^+$, and $Cs^+$) have been theoretically investigated for the first time using molecular dynamic (MD) simulations and density functional theory (MPWB1K/6-31G(d)//B3LYP/6-31G(d)) methods. The formation of the metal ion complex by the host is mainly driven by the electrostatic attraction between crown-5 oxygens and a cation together with the minor contribution of the cation-$\pi$ interaction between two facing phenyl rings around the cation. The computed binding energies and the atomic charge distribution analysis for the metal binding complexes indicate the selectivity toward a potassium ion. The theoretical results herein explain the experimentally observed extractability order by this host towards various alkali metal ions. The physical nature and the driving forces for cation recognition by this host are discussed in detail.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.4
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• pp.343-348
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• 2009

In this study, an efficient sequential bridging method to characterize both the particle size effect and concentration effect on the mechanical properties of nanocomposites at high volume fraction is suggested through a molecular dynamics(MD) simulations and micromechanics of composites materials. The Young's modulus and the shear modulus of the nanocomposites at various particle radius and at 12% volume fraction were obtained from MD simulations and multi-inclusion model was adopted to describe both modulus in continuum model. In order to describe the particle size effect, an additional phase, effective interface, was adopted as characteristic phase and the non-dilute concentration effect which appears at 12% volume fraction was describe via the variation of the elastic modulus of the infinite medium. Both the elastic modulus of the interface and infinite medium were fitted into functions of particle radius for the applicability of the present bridging method at various particle radii. Using the present bridging method the elastic modulus of the nanocomposites was efficiently obtained with accuracy. In addition, the effect of the interface thickness and modulus on the elastic modulus of the nanocomposite was investigated.

• Bulletin of the Korean Chemical Society
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• v.35 no.8
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• pp.2494-2504
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• 2014

P38 mitogen activated protein (MAP) kinase is an important anti-inflammatory drug target, which can be activated by responding to various stimuli such as stress and immune response. Based on the conformation of the conserved DFG loop (in or out), binding inhibitors are termed as type-I and II. Type-I inhibitors are ATP competitive, whereas type-II inhibitors bind in DFG-out conformation of allosteric pocket. It remains unclear that how these allosteric inhibitors stabilize the DFG-out conformation and interact. Organosilicon compounds provide unusual opportunity to enhance potency and diversity of drug molecules due to their low toxicity. However, very few examples have been reported to utilize this property. In this regard, we performed docking of an inhibitor (BIRB) and its silicon analog (Si-BIRB) in an allosteric binding pocket of p38. Further, molecular dynamics (MD) simulations were performed to study the dynamic behavior of the simulated complexes. The difference in the biological activity and mechanism of action of the simulated inhibitors could be explained based on the molecular mechanics/generalized Born surface area (MM/GBSA) binding free energy per residue decomposition. MM/GBSA showed that biological activities were related with calculated binding free energy of inhibitors. Analyses of the per-residue decomposed energy indicated that van der Waals and non-polar interactions were predominant in the ligand-protein interactions. Further, crucial residues identified for hydrogen bond, salt bridge and hydrophobic interactions were Tyr35, Lys53, Glu71, Leu74, Leu75, Ile84, Met109, Leu167, Asp168 and Phe169. Our results indicate that stronger hydrophobic interaction of Si-BIRB with the binding site residues could be responsible for its greater binding affinity compared with BIRB.

• Journal of Ginseng Research
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• v.46 no.1
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• pp.156-166
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• 2022

Background: Panax ginseng Meyer (P. ginseng), a herb distributed in Korea, China and Japan, exerts benefits on diverse inflammatory conditions. However, the underlying mechanism and active ingredients remains largely unclear. Herein, we aimed to explore the active ingredients of P. ginseng against inflammation and elucidate underlying mechanisms. Methods: Inflammation model was constructed by lipopolysaccharide (LPS) in C57BL/6 mice and RAW264.7 macrophages. Molecular docking, molecular dynamics, surface plasmon resonance imaging (SPRi) and immunofluorescence were utilized to predict active component. Results: P. ginseng significantly inhibited LPS-induced lung injury and the expression of proinflammatory factors, including TNF-α, IL-6 and IL-1β. Additionally, P. ginseng blocked fluorescencelabeled LPS (LPS488) binding to the membranes of RAW264.7 macrophages, the phosphorylation of nuclear factor-κB (NF-κB) and mitogen-activated protein kinases (MAPKs). Furthermore, molecular docking demonstrated that ginsenoside Ro (GRo) docked into the LPS binding site of toll like receptor 4 (TLR4)/myeloid differentiation factor 2 (MD2) complex. Molecular dynamic simulations showed that the MD2-GRo binding conformation was stable. SPRi demonstrated an excellent interaction between TLR4/ MD2 complex and GRo (K_D value of 1.16 × 10^-9 M). GRo significantly inhibited LPS488 binding to cell membranes. Further studies showed that GRo markedly suppressed LPS-triggered lung injury, the transcription and secretion levels of TNF-α, IL-6 and IL-1β. Moreover, the phosphorylation of NF-κB and MAPKs as well as the p65 subunit nuclear translocation were inhibited by GRo dose-dependently. Conclusion: Our results suggest that GRo exerts anti-inflammation actions by direct inhibition of TLR4 signaling pathway.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.3
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• pp.137-145
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• 2014

We present a design sensitivity analysis(DSA) method for multiscale problems based on bridging scale decomposition. In this paper, we utilize a bridging scale method for the coupled system analysis. Since the analysis of full MD systems requires huge amount of computational costs, a coupled system of MD-level and continuum-level simulation is usually preferred. The information exchange between the MD and continuum levels is taken place at the MD-continuum boundary. In the bridging scale method, a generalized Langevin equation(GLE) is introduced for the reduced MD system and the GLE force using a time history kernel is applied at the boundary atoms in the MD system. Therefore, we can separately analyze the MD and continuum level simulations, which can accelerate the computing process. Once the simulation of coupled problems is successful, the need for the DSA is naturally arising for the optimization of macro-scale design, where the macro scale performance of the system is maximized considering the micro scale effects. The finite difference sensitivity is impractical for the gradient based optimization of large scale problems due to the restriction of computing costs but the analytical sensitivity for the coupled system is always accurate. In this study, we derive the analytical design sensitivity to verify the accuracy and applicability to the design optimization of the coupled system.

• Advances in nano research
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• v.12 no.5
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• pp.529-547
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• 2022

Graphene is one of the strongest, stiffest, and lightest nanoscale materials known to date, making it a potentially viable and attractive candidate for developing lightweight structural composites to prevent high-velocity ballistic impact, as commonly encountered in defense and space sectors. In-plane twist in bilayer graphene has recently revealed unprecedented electronic properties like superconductivity, which has now started attracting the attention for other multi-physical properties of such twisted structures. For example, the latest studies show that twisting can enhance the strength and stiffness of graphene by many folds, which in turn creates a strong rationale for their prospective exploitation in high-velocity impact. The present article investigates the ballistic performance of twisted bilayer graphene (tBLG) nanostructures. We have employed molecular dynamics (MD) simulations, augmented further by coupling gaussian process-based machine learning, for the nanoscale characterization of various tBLG structures with varying relative rotation angle (RRA). Spherical diamond impactors (with a diameter of 25Å) are enforced with high initial velocity (V_i) in the range of 1 km/s to 6.5 km/s to observe the ballistic performance of tBLG nanostructures. The specific penetration energy (E_p^*) of the impacted nanostructures and residual velocity (V_r) of the impactor are considered as the quantities of interest, wherein the effect of stochastic system parameters is computationally captured based on an efficient Gaussian process regression (GPR) based Monte Carlo simulation approach. A data-driven sensitivity analysis is carried out to quantify the relative importance of different critical system parameters. As an integral part of this study, we have deterministically investigated the resonant behaviour of graphene nanostructures, wherein the high-velocity impact is used as the initial actuation mechanism. The comprehensive dynamic investigation of bilayer graphene under the ballistic impact, as presented in this paper including the effect of twisting and random disorder for their prospective exploitation, would lead to the development of improved impact-resistant lightweight materials.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.11a
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• pp.241-242
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• 2008

The Velocity Autocorrelation Function (VAF) of the sodium ions is calculated for a range of temperature from 250K to 1000K and converted into the linear ac-conductivity and ac-susceptibility response via Fourier transformation. A peak is found in the conductivity around $6\times10^{12}$ Hz that has some of the character of a Poley absorption. Here it is shown to be due to an harmonically coupled site vibrations of the sodium atoms, which extend only over a limited range. At frequencies below the peak the conductivity tends towards a constant i.e. dc value corresponding to a constant flow of ions through the simulation cell. At high temperatures the conductivity due to this ion transport process behaves like a metal with an insulator to metal transition occurring around a specific temperature.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.6
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• pp.423-430
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• 2013

In this research, a paramteric study to account for the effect of interfacial strength and nanotube agglomeration on the elastoplastic behavior of carbon nanotube reinforced polypropylene composites is performed. At first, the elastoplastic behavior of nanocomposites is predicted from molecular dynamics(MD) simulations. By combining the MD simulation results with the nonlinear micromechanics model based on the Mori-Tanaka model, a two-step domain decomposition method is applied to inversely identify the elastoplastic behavior of adsorption interphase zone inside nanocomposites. In nonlinear micromechanics model, the secant moduli method combined with field fluctuation method is used to predict the elastoplastic behavior of nanocomposites. To account for the imperfect material interface between nanotube and matrix polymer, displacement discontinuity condition is applied to the micromechanics model. Using the elastoplastic behavior of the adsorption interphase zone obtained from the present study, stress-strain relation of nanocomposites at various interfacial bonding condition and local nanotube agglomeration is predicted from nonlinear micromechanics model with and without the adsorption interphase zone. As a result, it has been found that local nanotube agglomeration is the most important design factor to maximize reinforcing effect of nanotube in elastic and plastic behavior.

• Journal of the Korean GEO-environmental Society
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• v.25 no.4
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• pp.13-20
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• 2024

In this paper, a parallel analysis algorithm for Smoothed Particle Hydrodynamics (SPH), one of the numerical methods for fluidic materials, is introduced. SPH, which is a meshless method, can represent the behavior of a continuum using a particle-based approach, but it demands substantial computational resources. Therefore, parallel analysis algorithms are essential for SPH simulations. The domain decomposition algorithm, which divides the computational domain into partitions to be independently analyzed, is the most representative method among parallel analysis algorithms. In Discrete Element Method (DEM) and Molecular Dynamics (MD), the Cartesian coordinate-based domain decomposition method is popularly used because it offers advantages in quickly and conveniently accessing particle positions. However, in SPH, it is important to share particle information among partitioned domains because SPH particles are defined based on information from nearby particles within the smoothing length. Additionally, maintaining CPU load balance is crucial. In this study, a highly parallel efficient algorithm is proposed to dynamically minimize the size of orthogonal domain partitions to prevent excess CPU utilization. The efficiency of the proposed method was validated through numerical analysis models. The parallel efficiency of the proposed method is evaluated for up to 30 CPUs for fluidic models, achieving 90% parallel efficiency for up to 28 physical cores.