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Journal ArticleDOI

MoDeNa Nanotools: An integrated multiscale simulation workflow to predict thermophysical properties of thermoplastic polyurethanes

TL;DR: The predicted results obtained with Nanotools for density, thermal conductivity, surface tension, gas permeability, and Young modulus are in good agreement with the relevant experimental data, thus paving the way for the use of Nanotool in the current design of new TPUs for advanced applications.
About: This article is published in Journal of Computational Science.The article was published on 2016-07-01. It has received 12 citations till now. The article focuses on the topics: Multiscale modeling.
Citations
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Journal ArticleDOI
TL;DR: This work proposes multiscale computing patterns as a generic vehicle to realise load balanced, fault tolerant and energy aware high performance multiscaling, and discusses the vision of how this may shape multiscales computing in the exascale era.

56 citations

Posted Content
TL;DR: In this article, the authors propose multiscale computing patterns as a generic vehicle to realize load balanced, fault tolerant and energy aware high performance multi-scale computing in the exascale era.
Abstract: We expect that multiscale simulations will be one of the main high performance computing workloads in the exascale era. We propose multiscale computing patterns as a generic vehicle to realise load balanced, fault tolerant and energy aware high performance multiscale computing. Multiscale computing patterns should lead to a separation of concerns, whereby application developers can compose multiscale models and execute multiscale simulations, while pattern software realises optimized, fault tolerant and energy aware multiscale computing. We introduce three multiscale computing patterns, present an example of the extreme scaling pattern, and discuss our vision of how this may shape multiscale computing in the exascale era.

42 citations

Journal ArticleDOI
TL;DR: It is argued that although applications could scale to exascale performance relying on weak scaling and maybe even on strong scaling, there are also clear arguments that such scaling may no longer apply for many applications on these emerging exASCale machines and that the authors need to resort to multi-scaling.
Abstract: In this position paper, we discuss two relevant topics: (i) generic multiscale computing on emerging exascale high-performing computing environments, and (ii) the scaling of such applications towards the exascale. We will introduce the different phases when developing a multiscale model and simulating it on available computing infrastructure, and argue that we could rely on it both on the conceptual modelling level and also when actually executing the multiscale simulation, and maybe should further develop generic frameworks and software tools to facilitate multiscale computing. Next, we focus on simulating multiscale models on high-end computing resources in the face of emerging exascale performance levels. We will argue that although applications could scale to exascale performance relying on weak scaling and maybe even on strong scaling, there are also clear arguments that such scaling may no longer apply for many applications on these emerging exascale machines and that we need to resort to what we would call multi-scaling.

24 citations

Journal ArticleDOI
TL;DR: In this article, a multi-scale approach to reacting and expanding polyurethane (PU) foams modeling and simulation is presented. The modeling strategy relies on two pillars: an atomistic model (molecular dynamics (MD)/Grand Canonical Monte Carlo (GCMC)) that provides liquid mixture density and reactant solubility and a continuum model in which the expansion characteristics of the foam is modeled exploiting the results of the atomistic simulations.

18 citations


Cites background or methods from "MoDeNa Nanotools: An integrated mul..."

  • ...…accurate in the prediction of thermophysical properties of both condensed and gas phase 134 systems (P Cosoli et al., 2008a, 2008b, Fermeglia and Pricl, 1999a, 1999b, 1999c; Laurini et al., 2016; 135 Mensitieri et al., 2008; Milocco et al., 2002; Pricl and Fermeglia, 2003; Toth et al., 2012)....

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  • ...…66 information is computed at a smaller (finer) scale and passed to a model at a larger (coarser) scale by 67 leaving out (i.e. coarse graining) degrees of freedom (P Cosoli et al., 2008a; Fermeglia and Pricl, 2007; 68 Laurini et al., 2016; Scocchi et al., 2009, 2007a, 2007b; Toth et al., 2012)....

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  • ...In particular, 87 molecular dynamics (MD) simulations are run to calculate the density of the networking polymer (Ferkl 88 et al., 2017; Laurini et al., 2016; Maly et al., 2008) while Grand Canonical Monte Carlo (GCMC) are 89 carried out to predict the different gases solubility as a function of…...

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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

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: FireWorks has been used to complete over 50 million CPU‐hours worth of computational chemistry and materials science calculations at the National Energy Research Supercomputing Center, and its implementation strategy that rests on Python and NoSQL databases (MongoDB) is discussed.
Abstract: This paper introduces FireWorks, a workflow software for running high-throughput calculation workflows at supercomputing centers. FireWorks has been used to complete over 50 million CPU-hours worth of computational chemistry and materials science calculations at the National Energy Research Supercomputing Center. It has been designed to serve the demanding high-throughput computing needs of these applications, with extensive support for i concurrent execution through job packing, ii failure detection and correction, iii provenance and reporting for long-running projects, iv automated duplicate detection, and v dynamic workflows i.e., modifying the workflow graph during runtime. We have found that these features are highly relevant to enabling modern data-driven and high-throughput science applications, and we discuss our implementation strategy that rests on Python and NoSQL databases MongoDB. Finally, we present performance data and limitations of our approach along with planned future work. Copyright © 2015 John Wiley & Sons, Ltd.

405 citations

Journal ArticleDOI
TL;DR: In this article, the authors have implemented classical Ewald and particle-mesh Ewald (PME) based treatments of fixed and induced point dipoles into the sander molecular dynamics (MD) module of AMBER 6.
Abstract: We have implemented classical Ewald and particle-mesh Ewald (PME) based treatments of fixed and induced point dipoles into the sander molecular dynamics (MD) module of AMBER 6. During MD the induced dipoles can be propagated along with the atomic positions either by iteration to self-consistency at each time step, or by a Car–Parrinello (CP) technique using an extended Lagrangian formalism. In this paper we present the derivation of the new algorithms and compare the various options with respect to accuracy, efficiency, and effect on calculated properties of a polarizable water model. The use of PME for electrostatics of fixed charges and induced dipoles together with a CP treatment of dipole propagation in MD simulations leads to a cost overhead of only 33% above that of MD simulations using standard PME with fixed charges, allowing the study of polarizability in large macromolecular systems.

401 citations

Journal ArticleDOI
10 Feb 2015-Polymer
TL;DR: In this paper, a comprehensive discussion is provided of the critical physical, chemical and structural parameters, such as soft and hard segment structures and their molecular weights, polymer composition, solubility parameters, competitive intermolecular interactions and others, which strongly affect the morphology and bulk and surface properties of segmented thermoplastic polyurethanes.

396 citations