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Journal ArticleDOI

Multimodel approach for accurate determination of industry-driven properties for Polymer Nanocomposite Materials

TL;DR: This work describes the application of multiscale molecular modeling techniques for the choice of PNC materials for aerospace applications and the results are obtained in the framework of the European project Multi-scale Composite Material Selection Platform.
About: This article is published in Journal of Computational Science.The article was published on 2018-05-01 and is currently open access. It has received 8 citations till now. The article focuses on the topics: Material selection.
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01 Jan 2006
TL;DR: In this article, a hierarchical procedure for bridging the gap between atomistic and macroscopic modeling passing through mesoscopic simulations is presented, and examples of applications of multiscale procedures to polymer-organoclay nanocomposites are discussed.
Abstract: Atomistic-based simulations such as molecular mechanics (MM), molecular dynamics (MD), and Monte Carlo-based methods (MC) have come into wide use for materials design. Using these atomistic simulation tools, one can analyze molecular structure on the scale of 0.1–10 nm. Although molecular structures can be studied easily and extensively by these atom-based simulations, it is less realistic to predict structures defined on the scale of 100–1000 nm with these methods. For the morphology on these scales, mesoscopic modeling techniques such as the dynamic mean field density functional theory (Mesodyn) and dissipative particle dynamics (DPD) are now available as effective simulation tools. Furthermore, it is possible to transfer the simulated mesoscopic structure to finite element modeling tools (FEM) for calculating macroscopic properties for a given system of interest. In this paper, we present a hierarchical procedure for bridging the gap between atomistic and macroscopic modeling passing through mesoscopic simulations. In particular, we will discuss the concept of multiscale modeling, and present examples of applications of multiscale procedures to polymer–organoclay nanocomposites. Examples of application of multiscale modeling to immiscible polymer blends and polymer–carbon nanotubes systems will also be presented. © 2006 Elsevier B.V. All rights reserved.

103 citations

01 Jan 2003
TL;DR: In this paper, molecular simulation techniques are used to explore and characterize the atomic scale structure, and to predict binding energies and basal spacing of polymer/clay nanocomposites based on polypropylene (PP) and maleated polypropylon (PPMA), montmorillonite (MMT), and different alkylammonium ions (quats) as surfactants.
Abstract: Molecular simulation techniques are used to explore and characterize the atomic scale structure, and to predict binding energies and basal spacing of polymer/clay nanocomposites based on polypropylene (PP) and maleated polypropylene (PPMA), montmorillonite (MMT), and different alkylammonium ions (quats) as surfactants. Our evidences suggest that shorter hydrocarbonic chains are more effective in producing favorable binding energies with respect to longer ones, and the substitutions of hydrogen atoms with polar groups on the quaternary ammonium salt (quat) generally results in greater interaction between quat and both polymer and clay. Under the hypothesis, that montmorillonite platelets are uniformly dispersed in a polymer matrix, the modified polypropylene yields higher interfacial strength with clay than neat polypropylene. The use of neat PP and quats with higher molecular volume offer the higher values of the basal spacing and thus, in principle, they should be more effective in the exfoliation process.

87 citations

Journal ArticleDOI
02 Nov 2020
TL;DR: The main goal of this objective is to show how multiscale in silico experiments in molecular systems design and engineering is at the same time theoretically sound and mature enough for its full exploitation.
Abstract: One of the major goals of computational materials science is the rapid and accurate prediction of properties of new materials. In order to design new materials and compositions for specific, high-performance applications, it is essential to rely on predictive tools for the estimation of the desired properties before material preparation, characterization and processing. In the future, new materials and systems will be characterized by progressively higher degrees of complexity, due to the strong relationship between nanotechnology, biotechnology, computer science and cognitive disciplines. However, computer power and simulation algorithms are also quickly evolving, opening new avenues for novel material and system design based on virtual (aka in silico) experiments. Notwithstanding the great advances achieved in the simulation of structural, thermal, mechanical and transport properties of materials at the macroscopic level, the accurate property prediction for complex nanostructured materials remains a critical issue in the material design strategy. This hurdle arises from the strong dependence of the material properties on the underlying nanostructure. Atomistic simulations based on molecular dynamics or Monte Carlo methods allow such structure–property relationships to be derived already for systems of noticeable size and time scales; yet, the study of highly complex systems (e.g., polymer nanocomposites and self-assembled nanomaterials) is still out of current reach at such a fine level of detail. Indeed, the fast advancement of high-performance computing has already expanded these time/scale windows, and the upcoming advent of hexascale and/or quantum-based computers will indeed further contribute to this expansion; yet, the investigation of many critical phenomena will remain inaccessible to atomistic-based simulations. To circumvent this limitation, multiscale simulation techniques have been developed to create a seamless bridge across different time/scale domains (from electronic to continuum methods), thereby providing reliable predictive tools to design engineers. Accordingly, in this review work we present a selection of case studies based on our own experience in multiscale molecular modeling of nanostructured, complex systems of industrial interest. The main goal of this objective is to show how multiscale in silico experiments in molecular systems design and engineering is at the same time theoretically sound and mature enough for its full exploitation.

11 citations

Journal ArticleDOI
TL;DR: In this paper, a multi-disciplinary, multi-model approach for the accurate, reliable, efficient and cost-effective industry-driven KPIs determination for PNC materials is presented.
Abstract: erik.laurini@dia.units.itThe integration of modelling and simulation techniques to support material selection processes (MSPs) is one of the most compelling needs in advancing material industry and manufactory, due to the necessity of effective/efficient design and production of sophisticated materials, components and systems with advanced/extreme performance on a competitive time scale. In this arena, and specifically for complex structural materials such as polymer-based nanocomposites (PNCs) there is a strong industrial demand for chemistry/physics-based models and modelling workflows able to predict relevant materials properties (aka Key Performance Indicators or KPIs) in an accurate and reliable way and prior to any experimental set-up. With the aim of filling the gap between business processes and materials science/engineering workflows, this work reports the application – within the framework of the EU H2020 project COMPOSELECTOR – of a multi-disciplinary, multi-model approach for the accurate, reliable, efficient and cost-effective industry-driven KPIs determination for PNC materials. Specifically, three examples of questions and answers pertaining to aerospace and automotive applications are presented and discussed.

3 citations


Cites methods from "Multimodel approach for accurate de..."

  • ...In fact, the possibility of replacing steel with, e.g., PNCs might ultimately result in a substantial weight (up to 50...

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  • ...To answer the question, specific computational procedures based on atomistic molecular dynamics (MD) simulations were developed and applied, starting from well-validated methodologies established for other thermoplastic-based PNCs (Laurini et al. 2018; Laurini et al., 2016;)....

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  • ...Therefore, the DOI: 10.3303/CET1974104 Paper Received: 6 March 2018; Revised: 27 July 2018; Accepted: 3 November 2018 Please cite this article as: Laurini E., Marson D., Aulic S., Mio A., Fermeglia M., Pricl S., 2019, Integrating Multiscale Simulations for Composite Materials with Industrial Business Decisions: the Eu H2020 Composelector Project Experience, Chemical Engineering Transactions, 74, 619- 624 DOI:10.3303/CET1974104 major aim of the European Project COMPOSELECTOR, supported by the European Commission in the H2020 Research and Innovation Programme, is to contribute to a ground-breaking vision consisting in the integration of material modelling and simulation techniques into industrial manufacturing processes of materials characterized by increasing complexity such as PNCs, with specific regard to three industrial user cases, i.e., high performance PNCs for aeronautical (AIRBUS Industries) and automotive applications (DOW Corporation and Goodyear Tire and Rubber Company)....

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  • ...To find a computational answer these questions, a combination of mesoscopic and MD simulation techniques has been adopted and adapted from our previous work in the field (Laurini et al., 2018; Posocco et al., 2016; Fermeglia and Pricl, 2009; Maly et al., 2008b;)....

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  • ...This reflects into an enhancement factor for the Young modulus of the PNCs with respect to the pure PEEK matrix (Ef = EPNC/Ematrix) of 1.2, 1.4, and 1.5 at 5%, 10% and 15% wt/wt CF loading, respectively....

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References
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Journal ArticleDOI
TL;DR: In this paper, a method is described to realize coupling to an external bath with constant temperature or pressure with adjustable time constants for the coupling, which can be easily extendable to other variables and to gradients, and can be applied also to polyatomic molecules involving internal constraints.
Abstract: In molecular dynamics (MD) simulations the need often arises to maintain such parameters as temperature or pressure rather than energy and volume, or to impose gradients for studying transport properties in nonequilibrium MD A method is described to realize coupling to an external bath with constant temperature or pressure with adjustable time constants for the coupling The method is easily extendable to other variables and to gradients, and can be applied also to polyatomic molecules involving internal constraints The influence of coupling time constants on dynamical variables is evaluated A leap‐frog algorithm is presented for the general case involving constraints with coupling to both a constant temperature and a constant pressure bath

25,256 citations

Journal ArticleDOI
TL;DR: In this paper, a general all-atom force field for atomistic simulation of common organic molecules, inorganic small molecules, and polymers was developed using state-of-the-art ab initio and empirical parametrization techniques.
Abstract: A general all-atom force field for atomistic simulation of common organic molecules, inorganic small molecules, and polymers was developed using state-of-the-art ab initio and empirical parametrization techniques. The valence parameters and atomic partial charges were derived by fitting to ab initio data, and the van der Waals (vdW) parameters were derived by conducting MD simulations of molecular liquids and fitting the simulated cohesive energies and equilibrium densities to experimental data. The combined parametrization procedure significantly improves the quality of a general force field. Validation studies based on large number of isolated molecules, molecular liquids and molecular crystals, representing 28 molecular classes, show that the present force field enables accurate and simultaneous prediction of structural, conformational, vibrational, and thermophysical properties for a broad range of molecules in isolation and in condensed phases. Detailed results of the parametrization and validation f...

4,722 citations

Journal ArticleDOI
TL;DR: In this article, a review of dissipative particle dynamics (DPD) as a mesoscopic simulation method is presented, and a link between these parameters and χ-parameters in Flory-Huggins-type models is made.
Abstract: We critically review dissipative particle dynamics (DPD) as a mesoscopic simulation method. We have established useful parameter ranges for simulations, and have made a link between these parameters and χ-parameters in Flory-Huggins-type models. This is possible because the equation of state of the DPD fluid is essentially quadratic in density. This link opens the way to do large scale simulations, effectively describing millions of atoms, by firstly performing simulations of molecular fragments retaining all atomistic details to derive χ-parameters, then secondly using these results as input to a DPD simulation to study the formation of micelles, networks, mesophases and so forth. As an example application, we have calculated the interfacial tension σ between homopolymer melts as a function of χ and N and have found a universal scaling collapse when σ/ρkBTχ0.4 is plotted against χN for N>1. We also discuss the use of DPD to simulate the dynamics of mesoscopic systems, and indicate a possible problem with...

3,837 citations

Journal ArticleDOI
TL;DR: Some simulations have been carried out to determine the rupture properties of mixed bilayers of phosphatidylethanolamine and C(12)E(6), and indicate that the area of a pure lipid bilayer can be increased by a factor 2, and why dividing cells are more at risk than static cells.

921 citations

Journal ArticleDOI
TL;DR: In this paper, the dissipative particle dynamics (DPD) simulation method has been used to study mesophase formation of linear (AmBn) diblock copolymer melts.
Abstract: The dissipative particle dynamics (DPD) simulation method has been used to study mesophase formation of linear (AmBn) diblock copolymer melts. The polymers are represented by relatively short strings of soft spheres, connected by harmonic springs. These melts spontaneously form a mesocopically ordered structure, depending on the length ratio of the two blocks and on the Flory–Huggins χ-parameter. The main emphasis here is on validation of the method and model by comparing the predicted equilibrium phases to existing mean-field theory and to experimental results. The real strength of the DPD method, however, lies in its capability to predict the dynamical pathway along which a block copolymer melt finds its equilibrium structure after a temperature quench. The present work has led to the following results: (1) As the polymer becomes more asymmetric, we qualitatively find the order of the equilibrium structures as lamellar, perforated lamellar, hexagonal rods, micelles. Qualitatively this is in agreement wi...

810 citations