• Multiscale and Multiphysics Mechanics
• /
• v.1 no.1
• /
• pp.65-76
• /
• 2016

In this study, an influence of local variation of nanoparticulate volume fraction on the homogenized elastic properties is investigated. It is well known that interface effect is dependent on the radius and volume fraction of reinforced nanofillers. However, there is no study on the multiscale modeling and analysis of polymer nanocomposites including polydispersed nanoparticles with consideration of interphase zone, which is dependent on the volume fraction of corresponding nanoparticles. As results of numerical examples, it is confirmed that an influence of local variation of nanoparticulate volume fraction should be considered for non-dilute system such as cluster of nanoparticles. Therefore representative volume element analysis is conducted by considering local variation of nanoparticle volume fraction in order to analyze the practical size of cell including hundreds of nanoparticles. It is expected that this study could be extended to the multiparticulate nanocomposite systems including polydispersed nanoparticles.

• ETRI Journal
• /
• v.42 no.6
• /
• pp.912-921
• /
• 2020

Quantum-dot cellular automata (QCA) is an alternative complementary metal-oxide-semiconductor (CMOS) technology that is used to implement high-speed logical circuits at the atomic or molecular scale. In this study, an optimal 2-to-4 decoder in QCA is presented. The proposed QCA decoder is designed using a new formulation based on the MV32 gate. Notably, the MV32 gate has three inputs and two outputs, which is equivalent two 3-input majority gates, and operates based on cellular interactions. A multilayer design is suggested for the proposed decoder. Subsequently, a new and efficient 3-to-8 QCA decoder architecture is presented using the proposed 2-to-4 QCA decoder. The simulation results of the QCADesigner 2.0.3 software show that the proposed decoders perform well. Comparisons show that the proposed 2-to-4 QCA decoder is superior to the previously proposed ones in terms of cell count, occupied area, and delay.

• Applied Microscopy
• /
• v.50
• /
• pp.19.1-19.9
• /
• 2020

Deformation twinning, one of the major deformation modes in a crystalline material, has typically been analyzed using generalized planar fault energy (GPFE) curves. Despite the significance of these curves in understanding the twin nucleation and its effect on the mechanical properties of crystals, their experimental validity is lacking. In this comparative study based on the first-principles calculation, molecular dynamics simulation, and quantitative in-situ tensile testing of Al nanowires inside a transmission electron microscopy system, we present both a theoretical and an experimental approach that enable the measurement of a part of the twin formation energy of the perfect Al crystal. The proposed experimental method is also regarded as an indirect but quantitative means for validating the GPFE theory.

• BMB Reports
• /
• v.55 no.3
• /
• pp.111-112
• /
• 2022

We visualized the distribution of heterochromatin in a single nucleus using plasmonic nanoparticle-conjugated H3K9me3 and H3K27me3 antibodies. Due to distance-dependent plasmonic coupling effects between nanoprobes, their scattering spectra shift to longer wavelengths as the distance between heterochromatin histone markers reduced during oncogene-induced senescence (OIS). These observations were supported by simulating scattering profiles based on considerations of particle numbers, interparticle distances, and the spatial arrangements of plasmonic nanoprobes. Using this plasmon-based colourimetric imaging, we estimated changes in distances between H3K9me3 and H3K27me3 during the formation of senescence-associated heterochromatin foci in OIS cells. We anticipate that the devised analytical technique combined with high-spatial imaging and spectral simulation will eventually lead to a new means of diagnosing and monitoring disease progression and cellular senescence.

• Interdisciplinary Bio Central
• /
• v.1 no.1
• /
• pp.3.1-3.6
• /
• 2009

Introduction: GTPases known as translation factor play a vital role as ribosomal subunit assembly chaperone. The bacterial Obg proteins ($Spo{\underline{0B}}$-associated ${\underline{G}}TP$-binding protein) belong to the subfamily of P-loop GTPase proteins and now it is considered as one of the new target for antibacterial drug. The majority of bacterial Obgs have been commonly found to be associated with ribosome, implying that these proteins may play a fundamental role in ribosome assembly or maturation. In addition, one of the experimental evidences suggested that Bacillus subtilis Obg (BsObg) protein binds to the L13 ribosomal protein (BsL13) which is known to be one of the early assembly proteins of the 50S ribosomal subunit in Escherichia coli. In order to investigate binding mode between the BsObg and the BsL13, protein-protein docking simulation was carried out after generating 3D structure of the BsL13 structure using homology modeling method. Materials and Methods: Homology model structure of BsL13 was generated using the EcL13 crystal structure as a template. Protein-protein docking of BsObg protein with ribosomal protein BsL13 was performed by DOT, a macro-molecular docking software, in order to predict a reasonable binding mode. The solvated energy minimization calculation of the docked conformation was carried out to refine the structure. Results and Discussion: The possible binding conformation of BsL13 along with activated Obg fold in BsObg was predicted by computational docking study. The final structure is obtained from the solvated energy minimization. From the analysis, three important H-bond interactions between the Obg fold and the L13 were detected: Obg:Tyr27-L13:Glu32, Obg:Asn76-L13:Glu139, and Obg:Ala136-L13:Glu142. The interaction between the BsObg and BsL13 structures were also analyzed by electrostatic potential calculations to examine the interface surfaces. From the results, the key residues for hydrogen bonding and hydrophobic interaction between the two proteins were predicted. Conclusion and Prospects: In this study, we have focused on the binding mode of the BsObg protein with the ribosomal BsL13 protein. The interaction between the activated Obg and target protein was investigated with protein-protein docking calculations. The binding pattern can be further used as a base for structure-based drug design to find a novel antibacterial drug.

• Bulletin of the Korean Chemical Society
• /
• v.33 no.3
• /
• pp.975-979
• /
• 2012

Structure and Dynamics of dilute two-dimensional (2D) ring polymer solutions are investigated by using discontinuous molecular dynamics simulations. A ring polymer and solvent molecules are modeled as a tangent-hard disc chain and hard discs, respectively. Some of solvent molecules are confined inside the 2D ring polymer unlike in 2D linear polymer solutions or three-dimensional polymer solutions. The structure and the dynamics of the 2D ring polymers change significantly with the number ($N_{in}$) of such solvent molecules inside the 2D ring polymers. The mean-squared radius of gyration ($R^2$) increases with $N_{in}$ and scales as $R{\sim}N^{\nu}$ with the scaling exponent $\nu$ that depends on $N_{in}$. When $N_{in}$ is large enough, ${\nu}{\approx}1$, which is consistent with experiments. Meanwhile, for a small $N_{in}{\approx}0.66$ and the 2D ring polymers show unexpected structure. The diffusion coefficient (D) and the rotational relaxation time ($\tau_{rot}$) are also sensitive to $N_{in}$: D decreases and $\tau$ increases sharply with $N_{in}$. D of 2D ring polymers shows a strong size-dependency, i.e., D ~ ln(L), where L is the simulation cell dimension. But the rotational diffusion and its relaxation time ($\tau_{rot}$) are not-size dependent. More interestingly, the scaling behavior of $\tau_{rot}$ also changes with $N_{in}$; for a large $N_{in}$ $\tau_{rot}{\sim}N^{2.46}$ but for a small $N_{in}$ $\tau_{rot}{\sim}N^{1.43}$.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2016.02a
• /
• pp.190.1-190.1
• /
• 2016

One of the most serious problems faced by billions of people today is the availability of fresh water. According to statistics, 15% of the world's total output of dye products is discharged into the environment as dye wastewater, which seriously pollutes groundwater resources. For the treatment of chemically and biologically contaminated water the advanced oxidation processes (AOPs) shows the promising action. The main advantage with AOPs is the ability to degrade the organic pollutants to $CO_2$ and $H_2O$. For this degradation process the AOPs generation of powerful and non-selective radicals that may oxidize majority of the organic pollutants present in the water body. To generate the various reactive chemical species such as radicals (${\bullet}OH$, ${\bullet}H$, ${\bullet}O$, ${\bullet}HO_2$) and molecular species ($H_2O_2$, $H_2$, $O_2$) in large amount in water, we have used the atmospheric pressure plasma. Among the reactive and non-reactive species, the hydroxyl radical (${\bullet}OH$) plays important role due to its higher oxidation potential (E0: 2.8 V). Therefore, in this work we have checked the degradation of various dyes such as methyl orange, methylene blue and congo red using different type of atmospheric pressure plasma sources (Indirect jet and direct jet). To check the degradation we have used the UV-visible spectroscopy, HPLC and LC-MS spectroscopy. Further, to estimate role of ${\bullet}OH$ on the degradation of dyes we have studied the molecular dynamic simulation.

• Smart Structures and Systems
• /
• v.22 no.5
• /
• pp.561-574
• /
• 2018

In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three wellknown optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.12
• /
• pp.7473-7482
• /
• 2013

The G-protein coupled receptor 87 (GPR87) is a recently discovered orphan GPCR which means that the search of their endogenous ligands has been a novel challenge. GPR87 has been shown to be overexpressed in squamous cell carcinomas (SCCs) or adenocarcinomas in lungs and bladder. The 3D structure of GPR87 was here modeled using two templates (2VT4 and 2ZIY) by a threading method. Functional assignment of GPR87 by SVM revealed that along with transporter activity, various novel functions were predicted. The 3D structure was further validated by comparison with structural features of the templates through Verify-3D, ProSA and ERRAT for determining correct stereochemical parameters. The resulting model was evaluated by Ramachandran plot and good 3D structure compatibility was evidenced by DOPE score. Molecular dynamics simulation and solvation of protein were studied through explicit spherical boundaries with a harmonic restraint membrane water system. A DRY-motif (Asp-Arg-Tyr sequence) was found at the end of transmembrane helix3, where GPCR binds and thus activation of signals is transduced. In a search for better inhibitors of GPR87, in silico modification of some substrate ligands was carried out to form polar interactions with Arg115 and Lys296. Thus, this study provides early insights into the structure of a major drug target for SCCs.

• Weed & Turfgrass Science
• /
• v.6 no.1
• /
• pp.28-31
• /
• 2017

The mutation rate of proline in the position 197 (Pro197) in acetohydroxy acid synthase (AHAS) is highest among sulfonylurea (SU) herbicide-resistance mutants. Therefore, it is significant to investigate the resistance mechanism for the mutation and to develop the herbicides specific to the mutants. SU herbicide resistance mechanism of the mutants, 197Ser, 197Thr and 197Ala, in AHAS were targeted for designing new SU-herbicide. We did molecular dynamics (MD) simulation for understanding SU herbicide-resistance mechanisms of AHAS mutants and designed new herbicides with docking and MD evaluations. We have found that mutation to 197Ala and 197Ser enlarged the entrance of the active site, while 197Thr contracted. Map of the root mean square derivation (RMSD) and radius gyrations (Rg) revealed the domain indicating the conformations for herbicide resistant. Based on the enlarging-contracting mechanism of active site entrance, we designed new herbicides with substitution at the heterocyclic moiety of a SU herbicide for the complementary binding to the changed active site entrances of mutants, and designed new herbicides. We confirmed that our screened new herbicides bonded to both AHAS wild type and mutants with higher affinity, showing more stable binding conformation than the existing herbicides.