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

Polymers ◽  
2021 ◽  
Vol 13 (18) ◽  
pp. 3085
Author(s):  
Shuang Yan ◽  
Wolfgang Verestek ◽  
Harald Zeizinger ◽  
Siegfried Schmauder
Keyword(s):  
Molecular Dynamics ◽  
Reaction Kinetics ◽  
Crosslink Density ◽  
Experimental Methods ◽  
Dynamics Simulation ◽  
Dielectric Analysis ◽  
Scanning Calorimetry ◽  
Curing Behavior ◽  
Molding Compound ◽  
Thermal Influence

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.

scholarly journals Interactive Mechanism of Potential Inhibitors with Glycosyl for SARS-CoV-2 by Molecular Dynamics Simulation

Processes ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1749
Author(s):  
Yuqi Zhang ◽  
Li Chen ◽  
Xiaoyu Wang ◽  
Yanyan Zhu ◽  
Yongsheng Liu ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Small Molecules ◽  
Binding Sites ◽  
Md Simulations ◽  
Experimental Methods ◽  
Dynamics Simulation ◽  
Theoretical Research ◽  
Stacking Interactions ◽  
Receptor Binding Domain ◽  
Potential Inhibitors

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a type of Ribonucleic Acid (RNA) coronavirus and it has infected and killed many people around the world. It is reported that the receptor binding domain of the spike protein (S_RBD) of the SARS-CoV-2 virus is responsible for attachment to human angiotensin converting enzyme II (ACE2). Many researchers are attempting to search potential inhibitors for fighting SARS-CoV-2 infection using theoretical or experimental methods. In terms of experimental and theoretical research, Cefuroxime, Erythromycin, Lincomycin and Ofloxacin are the potential inhibitors of SARS-CoV-2. However, the interactive mechanism of the protein SARS-CoV-2 and the inhibitors are still elusive. Here, we investigated the interactions between S_RBD and the inhibitors using molecular dynamics (MD) simulations. Interestingly, we found that there are two binding sites of S_RBD for the four small molecules. In addition, our analysis also illustrated that hydrophobic and π-π stacking interactions play crucial roles in the interactions between S_RBD and the small molecules. In our work, we also found that small molecules with glycosyl group have more effect on the conformation of S_RBD than other inhibitors, and they are also potential inhibitors for the genetic variants of SARS-CoV-2. This study provides in silico-derived mechanistic insights into the interactions of S_RBD and inhibitors, which may provide new clues for fighting SARS-CoV-2 infection.

scholarly journals Molecular Dynamics Simulation of Polysulfone and Polystyrene-co-maleic Anhydride Blends Compatibility: A mesoscopic, Ewald Approach and Experimental Comparison

2021 ◽  
Author(s):  
John Michael Tesha
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Maleic Anhydride ◽  
Cell Model ◽  
Dynamics Simulation ◽  
Solubility Parameters ◽  
Experimental Comparison ◽  
Scanning Calorimetry ◽  
Binary Blend ◽  
Time Step

Abstract This work aims to use molecular modeling to envisage the compatibility of Polysulfone (PSF) and Poly (styrene-co-maleic anhydride) (PSMA) polymers blend. A blend-module was developed based on the molecular dynamics (MD) technique compared to an experimental study. Molecular dynamics simulations were achieved using the condensed phase-optimized molecular-potentials for atomistic simulation studies (COMPASS) force field with atomic-based electrostatic. The PSF/PSMA blend compatibility facets and thermodynamic Gibb’s free energy across ranges of PSF/PSMA blend compositions were calculated. In doing so, the Flory Huggins chi interaction parameter of mixing (χ) and solubility parameters (δ) were computed from 298K and on increasing temperature to predict the miscibility of the polymers blend in the amorphous cell model by atomistic simulations. It was found that the blend-system is miscible using the interaction chi parameter of Florry Huggins at a temperature above 400K. At higher time-step, mesoscopic simulations for PSF/PSMA reached equilibrium and computed free energy. Mixing energy indicated the stability of the PSF/PSMA polymer blend. The results of this work narrate to the Flory Huggins theory enthalpy of mixing for binary blend polymers at 40 and 60 % PSMA.Additionally, the kinetic phase of the miscibility/immiscibility of the PSF/PSMA blend system's miscibility/immiscibility was examined using Differential Scanning Calorimetry (DSC). The result confirms the good interaction between the two polymers through the shift of glass transition temperature (Tg) values within individual polymers Tg. It is crucial to investigate the miscibility of two different polymers for a variety of polymer applications. The MD simulation provides a powerful, accurate computational tool in the estimation of polymer compatibilities.

scholarly journals INVESTIGATING THE ROLE OF MOLECULAR INTERACTIONS IN POLYMORPHISM OF MEFENAMIC ACID IN ETHYL ACETATE SOLUTION

2017 ◽  
Vol 79 (5-3) ◽  
Author(s):  
Siti Kholijah Abdul Mudalip ◽  
Mohd. Rushdi Abu Bakar ◽  
Fatmawati Adam ◽  
Parveen Jamal ◽  
Zahangir Md. Alam
Keyword(s):  
Molecular Dynamics ◽  
Ethyl Acetate ◽  
Mefenamic Acid ◽  
Polymorphic Form ◽  
Dynamics Simulation ◽  
Acetate Solution ◽  
Constant Number ◽  
Scanning Calorimetry ◽  
Time Step ◽  
Dynamics Simulations

Mefenamic acid, a widely used nonsteroidal anti-inflammatory and analgesic agent, is one of the active pharmaceutical ingredients that exhibit polymorphisms. This study reports a combined experimental and molecular dynamics simulation study of mefenamic acid crystallization in ethyl acetate. The solid-state characterization of the polymorph produced using Fourier transform infrared spectroscopy (FTIR), X-Ray powder diffractometer (XPRD), and differential scanning calorimetry (DSC) analysis show the characteristic of Form I, which were N-H stretching at 3313cm-1, two endothermic  peaks, and significant XPRD peaks at 6.3°, 13.8°, 15.9°, 21.3°, and 26.3°. The molecular dynamics simulations were performed using COMPASS force field available in the Material Studio 5.5 simulation package. The simulations were run for equilibration with a time step of 1 fs for a period of 250 ps and 2000 ps simulation in NVE (constant number of atoms, volume and energy) and NPT (constant number of atoms, pressure and temperature) thermodynamic ensemble, respectively. The trajectory files from the simulation were analyzed for radial distribution function (RDF) to investigate the intermolecular interactions. The simulation results showed strong solute-solute and solute-solvent interactions, which were O1MA•••H15MA and O1EA•••H15MA. These findings revealed the presence of hydrogen bonds that contributes to the solvation and formation of hydrogen motif in polymorphic Form I of mefenamic acid during crystallization with ethyl acetate as a solvent.

scholarly journals Machine Learning-Assisted High-Throughput Molecular Dynamics Simulation of High-Mechanical Performance Carbon Nanotube Structure

Nanomaterials ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 2459
Author(s):  
Yi Xiang ◽  
Koji Shimoyama ◽  
Keiichi Shirasu ◽  
Go Yamamoto
Keyword(s):  
Machine Learning ◽  
Molecular Dynamics ◽  
Tensile Strength ◽  
High Throughput ◽  
Crosslink Density ◽  
Mechanical Performance ◽  
Dynamics Simulation ◽  
Optimal Structure ◽  
Outer Diameter ◽  
Nominal Tensile Strength

Carbon nanotubes (CNTs) are novel materials with extraordinary mechanical properties. To gain insight on the design of high-mechanical-performance CNT-reinforced composites, the optimal structure of CNTs with high nominal tensile strength was determined in this study, where the nominal values correspond to the cross-sectional area of the entire specimen, including the hollow core. By using machine learning-assisted high-throughput molecular dynamics (HTMD) simulation, the relationship among the following structural parameters/properties was investigated: diameter, number of walls, chirality, and crosslink density. A database, comprising the various tensile test simulation results, was analyzed using a self-organizing map (SOM). It was observed that the influence of crosslink density on the nominal tensile strength tends to gradually decrease from the outside to the inside; generally, the crosslink density between the outermost wall and its adjacent wall is highly significant. In particular, based on our calculation conditions, five-walled, armchair-type CNTs with an outer diameter of 43.39 Å and crosslink densities (between the inner wall and outer wall) of 1.38 ± 1.16%, 1.13 ± 0.69%, 1.54 ± 0.57%, and 1.36 ± 0.35% were believed to be the optimal structure, with the nominal tensile strength and nominal Young’s modulus reaching approximately 58–64 GPa and 677–698 GPa.

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