MD Simulation of Crosslinked Epoxy Resin at Different Temperatures

2012 ◽  
Vol 602-604 ◽  
pp. 747-750
Author(s):  
Miao Zhang ◽  
Ping Yang
Keyword(s):  
Experimental Data ◽  
Epoxy Resin ◽  
Md Simulation ◽  
Md Simulations ◽  
Atomic Scale ◽  
Electronic Packages ◽  
Powerful Method ◽  
Wide Range ◽  
Different Temperatures ◽  
The Cross

Epoxy resin is widely used in many electronic packages, the ability to predict properties of cross linked epoxy resin before experiments will facilitate the process of materials design. Molecular dynamics (MD) is a powerful method that can simulate the materials at atomic scale and it can be used to predict the performance and properties of a wide range of materials. In this work, the properties of the cross-linked epoxy resin compound at high temperature were studies by MD simulations. The relations of the glass transition temperature (Tg) and properties of the cross-linked epoxy resin were investigated. The results show that Tg can be estimated by the plot of non-bond energy at different temperatures, and consist with the experimental data.

scholarly journals A hierarchical Bayesian framework for force field selection in molecular dynamics simulations

2016 ◽  
Vol 374 (2060) ◽  
pp. 20150032 ◽  
Author(s):  
S. Wu ◽  
P. Angelikopoulos ◽  
C. Papadimitriou ◽  
R. Moser ◽  
P. Koumoutsakos
Keyword(s):  
Experimental Data ◽  
Molecular Dynamics ◽  
Force Field ◽  
Computational Cost ◽  
Md Simulations ◽  
Bayesian Framework ◽  
Underlying Structure ◽  
Hierarchical Bayesian ◽  
Wide Range ◽  
Selection Of

We present a hierarchical Bayesian framework for the selection of force fields in molecular dynamics (MD) simulations. The framework associates the variability of the optimal parameters of the MD potentials under different environmental conditions with the corresponding variability in experimental data. The high computational cost associated with the hierarchical Bayesian framework is reduced by orders of magnitude through a parallelized Transitional Markov Chain Monte Carlo method combined with the Laplace Asymptotic Approximation. The suitability of the hierarchical approach is demonstrated by performing MD simulations with prescribed parameters to obtain data for transport coefficients under different conditions, which are then used to infer and evaluate the parameters of the MD model. We demonstrate the selection of MD models based on experimental data and verify that the hierarchical model can accurately quantify the uncertainty across experiments; improve the posterior probability density function estimation of the parameters, thus, improve predictions on future experiments; identify the most plausible force field to describe the underlying structure of a given dataset. The framework and associated software are applicable to a wide range of nanoscale simulations associated with experimental data with a hierarchical structure.

A Study of Nanoparticle-Enhanced Heat Transfer

2010 ◽  
Author(s):  
Lawrence M. Jones ◽  
Timothy Sirk ◽  
Eugene Brown
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Molecular Dynamics ◽  
Heat Flux ◽  
Nuclear Power ◽  
Power Plants ◽  
Md Simulations ◽  
Theoretical Description ◽  
Different Temperatures ◽  
Dynamics Simulations

The study of the heat transfer characteristics of nanofluids, i.e. fluids that are suspensions of nanometer size particles, has gained significant attention in the search for new coolants that can effectively service a variety of needs ranging from the increasing heat transfer demands of ever smaller microelectronic devices to mitigating the effects of loss of coolant accidents in nuclear power plants. Experimental data has shown large increases in thermal conductivity and associated increases in the level of critical heat flux in nuclear reactors; however, in some cases the range of the applicability of the experimental results is uncertain and there is a lack of a theory by which this can be resolved. Complicating the theoretical description of heat transfer in nanofluids is the fact that fluids in the vicinity of the nanoparticles are a complex combination of phase transition, interfacial, and transport phenomena. This paper describes a study in which molecular dynamics simulations were used to enhance the understanding of the effect of nanoparticles on heat transfer. The molecular dynamics (MD) simulations presented here model a Lennard-Jones fluid in a channel where the walls are maintained at different temperatures. The heat flux is calculated for a variety of nanoparticle sizes and concentrations. The results are compared to experimental data in order to provide information that will more confidently bound the data and provide information that will guide the development of more comprehensive theories. We also anticipate that this work could contribute to the design of biosensors where suspended molecules are transported through micro- and nano-channels in the presence of heat transfer.

Electron transport and conduction band structure of GaSb

1981 ◽  
Vol 59 (12) ◽  
pp. 1844-1850 ◽  
Author(s):  
Hyung Jae Lee ◽  
John C. Woolley
Keyword(s):  
Magnetic Field ◽  
Experimental Data ◽  
Electrical Conductivity ◽  
Conduction Band ◽  
Room Temperature ◽  
Energy Gap ◽  
Band Model ◽  
Scattering Coefficients ◽  
Wide Range ◽  
Different Temperatures

Calculations have been made using the Fletcher and Butcher method in a three conduction band model to fit a wide range of experimental transport data for n-type samples of GaSb: viz. Hall coefficient and electrical conductivity as a function of temperature and as a function of pressure at room temperature, magnetoresistance as a function of magnetic field at different temperatures, and Nernst–Ettingshausen coefficients as a function of magnetic field. Various energy gap parameters and scattering coefficients have been taken as adjustable and values determined for these which give good fits to all of the experimental data. Values of mobility for each of the Γ, L, and X bands have then been calculated as a function of temperature.

Investigation of Mechanical Properties of Epoxy EPON 862 Cured With TETA by Molecular Dynamics

2015 ◽  
Vol 4 (2) ◽  
Author(s):  
Ashwini Kumar Rai ◽  
Amit Porwal ◽  
S. B. Mishra
Keyword(s):  
Molecular Dynamics ◽  
Epoxy Resin ◽  
Material Properties ◽  
Linear Thermal Expansion ◽  
Md Simulations ◽  
Amorphous Structure ◽  
Thermal Expansion Coefficients ◽  
The Cross ◽  
Predicted Values ◽  
Experimental Values

Molecular dynamics (MD) simulations were conducted to estimate the material properties of the cross-linked epoxy resin compound. A periodic amorphous structure of the cross-linked epoxy resin compound was constructed and it was simulated by continuous accumulation of structure configurations at various temperatures. Based on the simulation results, glass transition temperature (Tg), linear thermal expansion coefficients and Young's modulus of the cross-linked epoxy resin compound were predicted. The predicted values of these material properties are in good agreement with the experimental values in the literature.

STUDY OF AFFINITIES BETWEEN SINGLE-WALLED NANOTUBE AND EPOXY RESIN USING MOLECULAR DYNAMICS SIMULATION

2006 ◽  
Vol 05 (01) ◽  
pp. 131-144 ◽  
Author(s):  
JIHUA GOU ◽  
BIN FAN ◽  
GANGBING SONG ◽  
AURANGZEB KHAN
Keyword(s):  
Molecular Dynamics ◽  
Epoxy Resin ◽  
Md Simulation ◽  
Average Distance ◽  
Md Simulations ◽  
Dynamics Simulation ◽  
Repulsive Interaction ◽  
Curing Agent ◽  
Single Walled Nanotubes ◽  
Simulation Results

In the processing of carbon nanotube/polymer composites, the interactions between the nanotube and polymer matrix will occur at the molecular level. Understanding their interactions before curing is crucial for nanocomposites processing. In this study, molecular dynamics (MD) simulations were employed to reveal molecular interactions between (10, 10) single-walled nanotube and two kinds of epoxy resin systems. The two kinds of resin systems were EPON 862/EPI-CURE W curing agent (DETDA) and DGEBA (diglycidylether of bisphenol A)diethylenetriamine (DETA) curing agent. The MD simulation results show that the EPON 862, DETDA and DGEBA molecules had strong attractive interactions with single-walled nanotubes and their molecules changed their conformation to align their aromatic rings parallel to the nanotube surface due to π-stacking effect, whereas the DETA molecule had a repulsive interaction with the single-walled nanotubes. The interaction energies of the molecular systems were also calculated. Furthermore, an affinity index (AI) of the average distance between the atoms of the resin molecule and nanotube surface was defined to quantify the affinities between the nanotubes and resin molecules. The MD simulation results show that the EPON 862/EPI-CURE W curing agent system has good affinities with single-walled nanotubes.

Effect of Chain Morphology and Carbon-Nanotube Additives on the Glass Transition Temperature of Polyethylene

2013 ◽  
Vol 23 ◽  
pp. 16-23 ◽  
Author(s):  
S. Herasati ◽  
H.H. Ruan ◽  
Liang Chi Zhang
Keyword(s):  
Experimental Data ◽  
Mechanical Properties ◽  
Glass Transition ◽  
Carbon Nanotube ◽  
Transition Temperature ◽  
Glass Transition Temperature ◽  
Md Simulation ◽  
Md Simulations ◽  
Crystalline Polymers ◽  
Good Agreement

Glass transition temperature Tg is the most important parameter affecting the mechanical properties of amorphous and semi-crystalline polymers. However, the atomistic origin of glass transition is not yet well understood. Using Polyethylene (PE) as an example, this paper investigates the glass transition temperature Tg of PE with the aid of molecular dynamics (MD) simulation. The effects of PE chain branches, crystallinity and carbon-nanotube (CNT) additives on the glass transition temperature are analyzed. The MD simulations render a good agreement with the relevant experimental data of semi-crystalline PE and show the significant effects of crystallinity and addition of CNTs on Tg.

Atomic-scale simulations of multiple ion–solid interactions and structural evolution in silicon carbide

2002 ◽  
Vol 17 (2) ◽  
pp. 259-262 ◽  
Author(s):  
F. Gao ◽  
W. J. Weber
Keyword(s):  
Md Simulation ◽  
Structural Evolution ◽  
Md Simulations ◽  
Atomic Level ◽  
Atomic Scale ◽  
Defect Clusters ◽  
Transmission Electron ◽  
Small Defect ◽  
Defect Accumulation ◽  
Antisite Defects

Molecular dynamics (MD) were employed in atomic-level simulations of fundamental damage production processes due to multiple ion–solid collision events in cubic SiC. Isolated collision cascades produce single interstitials, vacancies, antisite defects, and small defect clusters. As the number of cascades (or equivalent dose) increases, the concentration of defects increases, and the collision cascades begin to overlap. The coalescence of defects and clusters with increasing dose is an important mechanism leading to amorphization in SiC and is consistent with the homogeneous amorphization process observed experimentally in SiC. The driving force for the crystalline– amorphous (c–a) transition is the accumulation of both interstitials and antisite defects. High-resolution transmission electron microscopy (HRTEM) images of the defect accumulation process and loss of long-range order in the MD simulation cell are consistent with experimental HRTEM images and disorder measurements. Thus, the MD simulations provide atomic-level insights into the interpretation of experimentally observed features associated with multiple ion–solid collision events in SiC.

Construction, Validation, and Application of Digital Oil: Investigation of Asphaltene Association Toward Asphaltene-Precipitation Prediction

SPE Journal ◽  
2018 ◽  
Vol 23 (03) ◽  
pp. 952-968 ◽  
Author(s):  
S.. Sugiyama ◽  
Y.. Liang ◽  
S.. Murata ◽  
T.. Matsuoka ◽  
M.. Morimoto ◽  
...  
Keyword(s):  
Experimental Data ◽  
Liquid Phase ◽  
Crude Oil ◽  
Md Simulation ◽  
Heavy Fraction ◽  
Liquid Density ◽  
Asphaltene Precipitation ◽  
Viscosity Change ◽  
Light Crude Oil ◽  
Wide Range

Summary Digital oil, a realistic molecular model of crude oil for a target reservoir, opens a new door to understand properties of crude oil under a wide range of thermodynamic conditions. In this study, we constructed a digital oil to model a light crude oil using analytical experiments after separating the light crude oil into gas, light and heavy fractions, and asphaltenes. The gas and light fractions were analyzed by gas chromatography (GC), and 105 kinds of molecules, including normal alkanes, isoalkanes, naphthenes, alkylbenzenes, and polyaromatics (with a maximum of three aromatic rings), were directly identified. The heavy fraction and asphaltenes were analyzed by elemental analysis, molecular-weight (MW) measurement with gel-permeation chromatography (GPC), and hydrogen and carbon nuclear-magnetic-resonance (NMR) spectroscopy, and represented by the quantitative molecular-representation method, which provides a mixture model imitating distributions of the crude-oil sample. Because of the low weight concentration of asphaltenes in the light crude oil (approximately 0.1 wt%), the digital oil model was constructed by mixing the gas, light-, and heavy-fraction models. To confirm the validity of the digital oil, density and viscosity were calculated over a wide range of pressures at the reservoir temperature by molecular-dynamics (MD) simulations. Because only experimental data for the liquid phase were available, we predicted the liquid components of the digital oil at pressures lower than 16.3 MPa (i.e., the bubblepoint pressure) by flash calculation, and calculated the liquid density by MD simulation. The calculated densities coincided with the experimental values at all pressures in the range from 0.1 to 29.5 MPa. We calculated the viscosity of the liquid phase at the same pressures by two independent methods. The calculated viscosities were in good agreement with each other. Moreover, the viscosity change with pressure was consistent with the experimental data. As a step for application of digital oil to predict asphaltene-precipitation risk, we calculated dimerization free energy of asphaltenes (which we regarded as asphaltene self-association energy) in the digital oil at the reservoir condition, using MD simulation with the umbrella sampling method. The calculated value is consistent with reported values used in phase-equilibrium calculation. Digital oil is a powerful tool to help us understand mechanisms of molecular-scale phenomena in oil reservoirs and solve problems in the upstream and downstream petroleum industry.

scholarly journals Modelling the Dielectric Behaviour of Composites of Epoxy Resin and Kevlar Fibres

1995 ◽  
Vol 4 (6) ◽  
pp. 096369359500400 ◽  
Author(s):  
G.M. Tsangaris ◽  
G.C. Psarras ◽  
N. Kouloumbi
Keyword(s):  
Experimental Data ◽  
Aspect Ratio ◽  
Epoxy Resin ◽  
Satisfactory Agreement ◽  
Volume Fraction ◽  
Polymeric Composites ◽  
Dielectric Behaviour ◽  
Wide Range ◽  
Conductive Fillers ◽  
Logarithmic Law

The logarithmic law of mixtures can be suitably extended to form equations which can describe the dielectric behaviour of polymeric composites containing non conductive fillers. The proposed equations can give the permittivity and loss of the composites as a function of the permittivities of the constituents, the volume fraction of the inclusions and their aspect ratio. The proposed equation are tested with experimental data obtained in a wide range of frequency and temperature from composites with epoxy resin and Kevlar fibres. Satisfactory agreement is observed and existing discrepancies must be attributed to the intrinsic weakness of the logarithmic law of mixtures on which the proposed equations are based.

Prediction and Analysis on Chemorheology of MeHHPA/Hydantoin Epoxy Resin

2017 ◽  
Vol 727 ◽  
pp. 497-502
Author(s):  
Ya Quan Xin ◽  
Ling Li ◽  
Li Yuan Fan
Keyword(s):  
Experimental Data ◽  
Epoxy Resin ◽  
Good Accuracy ◽  
Viscosity Model ◽  
Curing Process ◽  
Ann Model ◽  
Scanning Calorimetry ◽  
Low Viscosity ◽  
Different Temperatures ◽  
Hidden Neurons

Hydantoin epoxy resin, with a hydantoin group, is a kind of low viscosity nitrigen-containing epoxy resin. We prepared methyl hexahydrophalic anhydride (MeHHPY)/ hydantin epoxy resin, in which MeHHPA was used as cure agent. Non-isothermal differential scanning calorimetry was examined to follow the curing process. The variation of viscosity was measured the isothermal curing process by rotating viscometer respectively (70-90°C). A viscosity model, which parameters were determined by Arrhenius equation, was established on the basis of experimental data at three different temperatures. As the result showed, there is a minimum deviation comparing the dual Arrhenius viscosity model data and experimental data in the temperature range of this research. The potential of artificial neural network techniques (ANN) was employed to analyze and predict the chemorheological behavior of MeHHPA/hydatoin epoxy resin. A three layer feed forward ANN model having two input neurons, one output neuron and fourteen hidden neurons was developed to predict the chemorheologica behaviour of MeHHPA/hydatoin epoxy resin. The learning of ANN was accomplished by a backpropagation algorithm. The results display that prediction model has very good accuracy in the process of the whole experiment. Through the established ANN model, the variation characteristic of viscosity can be exactly predicted. Studying on chemorheology by ANN model can help to formulate and optimize technical process.

Sign in / Sign up

Export Citation Format

Share Document