• Membrane Journal
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• v.25 no.2
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• pp.162-170
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• 2015

In this study, gas permeability of polyimide materials having a various amine group was measured and molecular dynamics was used to analyze the dynamic characteristics of the gas molecules in the polyimide by calculating the position and velocity of the gas molecules with change of the time. The gas permeability of polyimide membrane having substitution site which increase free volume in the polymer was increased. However, polyimide with rigid structure showed decreased gas permeability. As a result of analyzing the change in the gas permeation behavior using molecular dynamics simulations, we confirmed that the results show the same tendency with actual measurements of the gas permeability.

• Membrane Journal
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• v.30 no.4
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• pp.242-251
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• 2020

Computer simulation tools mainly used for polymer materials and polymeric membranes are divided into various fields depending on the size of the object to be simulated and the time to be simulated. The computer simulations introduced in this review are classified into three categories: Quantum mechanics (QM), molecular dynamics (MD), and mesoscale modeling, which are mainly used in computational material chemistry. The computer simulation used in polymer research has different research target for each kind of computational simulation. Quantum mechanics deals with microscopic phenomena such as molecules, atoms, and electrons to study small-sized phenomena, molecular dynamics calculates the movement of atoms and molecules calculated by Newton's equation of motion when a potential or force of is given, and mesoscale simulation is a study to determine macroscopically by reducing the computation time with large molecules by forming beads by grouping atoms together. In this review, various computer simulation programs mainly used for polymers and polymeric membranes divided into the three types classified above will be introduced according to each feature and field of use.

• Composites Research
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• v.31 no.6
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• pp.371-378
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• 2018

In this study, the thermoelastic properties of poly lactic acid (PLA) based nanocomposites are predicted by molecular dynamics (MD) simulation and a micromechanics model. The stereocomplex mixed with L-lactic acid (PLLA) and D-lactic acid (PDLA) is modeled as matrix phase and a single walled carbon nanotube is embedded as reinforcement. The glass transition temperature, elastic moduli and thermal expansion coefficients of pure matrix and nanocomposites unit cells are predicted though ensemble simulations according to the hydrolysis. In micromechanics model, the double inclusion (D-I) model with a perfect interface condition is adopted to predict the properties of nanocomposites at the same composition. It is found that the stereocomplex nanocomposites show prominent improvement in thermal stability and interfacial adsorption regardless of the hydrolysis. Moreover, it is confirmed from the comparison of MD simulation results with those from the D-I model that the interface between CNT and the stereocomplex matrix is slightly weak in nature.

• Journal of Ocean Engineering and Technology
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• v.36 no.5
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• pp.340-352
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• 2022

This article presents a modeling method for the uncorrelated measurement error of the ultra-short baseline (USBL) acoustic positioning system for aiding navigation of underwater vehicles. The Mahalanobis distance (MD) and principal component analysis are applied to decorrelate the errors of USBL measurements, which are correlated in the x- and y-directions and vary according to the relative direction and distance between a reference station and the underwater vehicles. The proposed method can decouple the radial-direction error and angular direction error from each USBL measurement, where the former and latter are independent and dependent, respectively, of the distance between the reference station and the vehicle. With the decorrelation of the USBL errors along the trajectory of the vehicles in every time step, the proposed method can reduce the threshold of the outlier decision level. To demonstrate the effectiveness of the proposed method, simulation studies were performed with motion data obtained from a field experiment involving an autonomous underwater vehicle and USBL signals generated numerically by matching the specifications of a specific USBL with the data of a global positioning system. The simulations indicated that the navigation system is more robust in rejecting outliers of the USBL measurements than conventional ones. In addition, it was shown that the erroneous estimation of the navigation system after a long USBL blackout can converge to the true states using the MD of the USBL measurements. The navigation systems using the uncorrelated error model of the USBL, therefore, can effectively eliminate USBL outliers without loss of uncontaminated signals.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4A
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• pp.529-536
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• 2008

The failure behavior of structures is changed under different loading rates, which might arise from the rate dependency of materials. This phenomenon has been focused in the engineering fields. However, the failure mechanism is not fully understood yet, so that it is hard to be implemented in numerical simulations. In this study, the numerical experiments to a brittle material are simulated by the Molecular Dynamics (MD) for understanding the rate dependent failure behavior. The material specimen with a notch is modeled for the compact tension test simulation. Lennard-Jones potential is used to describe the properties of a brittle material. Several dynamic failure features under 6 different loading rates are achieved from the numerical experiments, where remarkable characteristics such as crack roughness, crack recession/arrest, and crack branching are observed during the crack propagation. These observations are interpreted by the energy inflow-consumption rates. This study will provides insight about the dynamic failure mechanism under different loading rates. In addition, the applicability of the MD to the macroscopic mechanics is estimated by simulating the previous experimental research.

• Biomolecules & Therapeutics
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• v.32 no.3
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• pp.390-398
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• 2024

FoxO1, a member of the Forkhead transcription factor family subgroup O (FoxO), is expressed in a range of cell types and is crucial for various pathophysiological processes, such as apoptosis and inflammation. While FoxO1's roles in multiple diseases have been recognized, the target has remained largely unexplored due to the absence of cost-effective and efficient inhibitors. Therefore, there is a need for natural FoxO1 inhibitors with minimal adverse effects. In this study, docking, MMGBSA, and ADMET analyses were performed to identify natural compounds that exhibit strong binding affinity to FoxO1. The top candidates were then subjected to molecular dynamics (MD) simulations. A natural product library was screened for interaction with FoxO1 (PDB ID-3CO6) using the Glide module of the Schrödinger suite. In silico ADMET profiling was conducted using SwissADME and pkCSM web servers. Binding free energies of the selected compounds were assessed with the Prime-MMGBSA module, while the dynamics of the top hits were analyzed using the Desmond module of the Schrödinger suite. Several natural products demonstrated high docking scores with FoxO1, indicating their potential as FoxO1 inhibitors. Specifically, the docking scores of neochlorogenic acid and fraxin were both below -6.0. These compounds also exhibit favorable drug-like properties, and a 25 ns MD study revealed a stable interaction between fraxin and FoxO1. Our findings highlight the potential of various natural products, particularly fraxin, as effective FoxO1 inhibitors with strong binding affinity, dynamic stability, and suitable ADMET profiles.

• 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.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.4
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• pp.315-321
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• 2012

In this study, a sequential multiscale homogenization method to characterize the effective thermal conductivity of nano particulate polymer nanocomposites is proposed through a molecular dynamics(MD) simulations and a finite element-based homogenization method. The thermal conductivity of the nanocomposites embedding different-sized nanoparticles at a fixed volume fraction of 5.8% are obtained from MD simulations. Due to the Kapitza thermal resistance, the thermal conductivity of the nanocomposites decreases as the size of the embedded nanoparticle decreases. In order to describe the nanoparticle size effect using the homogenization method with accuracy, the Kapitza interface in which the temperature discontinuity condition appears and the effective interphase zone formed by highly densified matrix polymer are modeled as independent phases that constitutes the nanocomposites microstructure, thus, the overall nanocomposites domain is modeled as a four-phase structure consists of the nanoparticle, Kapitza interface, effective interphase, and polymer matrix. The thermal conductivity of the effective interphase is inversely predicted from the thermal conductivity of the nanocomposites through the multiscale homogenization method, then, exponentially fitted to a function of the particle radius. Using the multiscale homogenization method, the thermal conductivities of the nanocomposites at various particle radii and volume fractions are obtained, and parametric studies are conducted to examine the effect of the effective interphase on the overall thermal conductivity of the nanocomposites.

• 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.

• Composites Research
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• v.31 no.5
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• pp.282-287
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• 2018

In this paper, we explore interfacial properties of the mineralized CNTs when they are employed as reinforcing fillers in a polymer nanocomposite using molecular dynamics (MD) simulations. Recently, several studies on mineralizing carbon nanotubes (CNTs) with an aid of nitrogen doping to CNTs have been reported. However, there is a lack of studies on the reinforcing effects of the mineralized CNTs when it is employed as a filler of nanocomposites. Silica ($SiO_2$) is used as a mineral material and poly (methyl metacrylate) (PMMA) is used as a polymer matrix. Pull-out simulations are conducted to obtain the interfacial energy and the interfacial shear stress. It was found that the silica mineralized CNTs have higher interfacial interaction with the polymer matrix. In the future, by examining various thermomechanical properties of the mineralized-CNT-filler/polymer nanocomposites, we will search for potential applications of the novel reinforcing filler.