Modelling micro- and mesoscopic scale thermodynamic and transport properties of soft condensed matter hinges upon its representation. This is especially relevant for polar solvents such as water, since these require effective representation of their dielectric nature as driven by molecular charge distributions and molecular network structuring. The dielectric nature of a medium leads to complex phenomena such as local polarisability response and restructuring near interfaces in reaction to changes in local charge distributions. Inclusion of such phenomena when using larger-than-atomistic techniques such as coarse-grained (CG) molecular dynamics and dissipative particle dynamics (DPD) is still an open question, to which we provide a novel way to consider and justify the necessary and suitable coarse-graining level, enabling us to compare new polar CG models' performance against that of an underlying atomistic model. We polarise our previous non-polarnDPD water model to prepare it for use in simulations of liquid electrolytes as well as solvated organic membranes and measure its fitness to serve as a dielectric medium by comparing its properties to those of the TIP3P water model, while simultaneously observing changes to properties already represented well by the non-polar model.

We critically examine a broad class of explicitly polarizable soft solvent models aimed at applications in dissipative particle dynamics. We obtain the dielectric permittivity using the fluctuating box dipole method in linear response theory and verify the models in relation to several test cases, including demonstrating ion desorption from an oil-water interface due to image charge effects. We additionally compute the Kirkwood factor and find that it uniformly lies in the range gK similar or equal to 0.7-0.8, indicating that dipole-dipole correlations are not negligible in these models. This is supported by the measurements of dipole-dipole correlation functions. As a consequence, Onsager theory over-predicts the dielectric permittivity by 20%-30%. The mean square molecular dipole moment can be accurately estimated with a first-order Wertheim perturbation theory.

Modelling micro- and mesoscale transport of soft condensed matter hinges upon its representation, including any complex phenomena, at appropriate length and time scales, especially when using larger-than-atomistic techniques such as dissipative particle dynamics (DPD). Simple repulsive pairwise interactions typically used in DPD calculations can capture some complexity, but certain thermodynamic behaviours such as single-component phase coexistence and transitions are normally unavailable. By extending the commonly-used DPD interactions to include attraction and additional control on repulsion, we have devised a new interaction model for highly coarse-grained and mesoscopic scales. The model, denoted here as nDPD, retains many advantages of the original while enabling more complex thermodynamic behaviours, particularly vapour-liquid coexistence below a critical point and solid-liquid transitions. Some of its features include: changes in liquid curves for vapour-liquid coexistence based on repulsion steepness, comparatively low melting points, contraction of solid phases upon heating (negative thermal expansion) and pressure-induced melting. Here, we demonstrate how nDPD can be parameterised for highly coarse-grained water, and how well it fits potentials for long polymeric chains that have been systematically coarse-grained from atomistic molecular dynamics calculations. These enable further exploration of these materials in the rheological domain using DPD-based modelling.

We critically examine a broad class of explicitly polarisable soft solvent models aimed at applications in dissipative particle dynamics. We obtain the dielectric permittivity using the fluctuating box dipole method in linear response theory, and verify the models in relation to several test cases including demonstrating ion desorption from an oil-water interface due to image charge effects. We additionally compute the Kirkwood factor and find it uniformly lies in the range gK approx 0.7-0.8, indicating that dipole-dipole correlations are not negligible in these models. This is supported by measurements of dipole-dipole correlation functions. As a consequence, Onsager theory over-predicts the dielectric permittivity by approximately 20-30 percent. On the other hand, the mean square molecular dipole moment can be accurately estimated with a first-order Wertheim perturbation theory.

Soft condensed matter structures often challenge us with complex many-body phenomena governed by collective modes spanning wide spatial and temporal domains. In order to successfully tackle such problems, mesoscopic coarse-grained (CG) statistical models are being developed, providing a dramatic reduction in computational complexity. CG models provide an intermediate step in the complex statistical framework of linking the thermodynamics of condensed phases with the properties of their constituent atoms and molecules. These allow us to offload part of the problem to the CG model itself and reformulate the remainder in terms of reduced CG phase space. However, such exchange of pawns to chess pieces, or 'Hamiltonian renormalization', is a radical step and the thermodynamics of the primary atomic and CG models could be quite distinct. Here, we present a comprehensive study of the phase diagram including binodal and interfacial properties of a dissipative particle dynamics (DPD) model, extended to include finite-range attraction to support the liquid-gas equilibrium. Despite the similarities with the atomic model potentials, its phase envelope is markedly different featuring several anomalies such as an unusually broad liquid range, change in concavity of the liquid coexistence branch with variation of the model parameters, volume contraction on fusion, temperature of maximum density in the liquid phase and negative thermal expansion in the solid phase. These results provide new insight into the connection between simple potential models and complex emergent condensed matter phenomena.

In this paper, we present an infrastructure for executing multiscale scientific workflows in hybrid cloud environment. We use an end-to-end modelling of mayonnaise production as an example of an industrially relevant problem involving modelling of materials properties and their corresponding processing methods. We present a container image design which allows an integration of alternative simulation services operating at atomistic, mesoscopic and continuum levels. The image allows adjustment at runtime to carry out different multiscale studies following diverse parallel execution patterns. We then discuss a prototype of the on-demand high-performance computing (HPC) facility implemented on two variants of the virtualized infrastructure to handle these workflows in the context of hybrid cloud deployments.

DL_MESO is a highly-scalable general purpose software package for mesoscale modelling. Created and developed at Daresbury Laboratory for the UK Collaborative Computational Project CCP5, it was intended to be a companion package to the flagship molecular dynamics code DL_POLY. One of DL_MESO component codes, DL_MESO_DPD, is based on dissipative particle dynamics, a mesoscale modelling technique with many similarities to classical molecular dynamics. While this code and DL_POLY were created with different applications in mind, they share a significant amount of functionality and development history. This article gives an overview on how DL_MESO_DPD has been developed, including its shared history with DL_POLY and information on its current performance, and a selection of applications for which the code has been used.

We develop a three-dimensional immersed boundary chromodynamic multicomponent lattice Boltzmann method capable of simulating vesicles, such as erythrocytes. The presented method is encapsulated in a single framework, where the application of the immersed boundary force in the automatically adaptive interfacial region results in correct vesicle behavior. We also set down a methodology for computing the principal curvatures of a surface in a three-dimensional, physical space which is defined solely in terms of its surface normal vectors. The benefits of such a model are its transparent methodology, stability at high levels of deformation, automatic-adaptive interface, and potential for the simulation of many erythrocytes. We demonstrate the utility of the model by examining the steady-state properties, as well as dynamical behavior within shear flow. The stability of the method is highlighted through its handling of high deformations, as well as interaction with another vesicle.

Pragmatic interoperability between platforms and service-oriented architectures exists whenever there is an agreement on the roles of participants and components as well as minimum standards for good practice. In this work, it is argued that open platforms require pragmatic interoperability, complementing syntactic interoperability (e.g., through common file formats), and semantic interoperability by ontologies that provide agreed definitions for entities and relations. For consistent data management and the provision of services in computational molecular engineering, community-governed agreements on pragmatics need to be established and formalized. For this purpose, if ontology-based semantic interoperability is already present, the same ontologies can be used. This is illustrated here by the role of the “translator” and procedural definitions for the process of “translation” in materials modelling, which refers to mapping industrial research and development problems onto solutions by modelling and simulation. For associated roles and processes, substantial previous standardization efforts have been carried out by the European Materials Modelling Council (EMMC ASBL). In the present work, the Materials Modelling Translation Ontology (MMTO) is introduced, and it is discussed how the MMTO can contribute to formalizing the pragmatic interoperability standards developed by EMMC ASBL.

This work describes the ontology OSMO, i.e. , an ontologization and extension of MODA, a workflow metadata standard that constitutes a mandatory requirement within a number of European calls and projects in the context of materials modelling. OSMO was developed within the Horizon 2020 project VIMMP (Virtual Materials Marketplace) and is part of a larger effort in ontology engineering driven by the European Materials Modelling Council, with the Elementary Multiperspective Material Ontology (EMMO) as its core. As such, OSMO provides connections and alignments with other related domain ontologies in computational engineering, including the EMMO itself. This work summarizes the domain, purpose, and design choices underlying OSMO, commenting on the implementation of OSMO and its applications.

Disclaimer: This document is intended for joint dissemination with the ontologies developed by the Virtual Materials Marketplace (VIMMP) project. Its contents are included in VIMMP project deliverable 1.4 and made available to the public through CORDIS; the material (ontologies and this document) can be reused and further developed under the terms and conditions of LGPL version 3 , provided that proper attribution is made to the original authors and any additional contributors as well as the VIMMP project consortium. The VIMMP project is funded from the EU’s Horizon 2020 research and innovation programme under grant agreement no. 760907. The authors retain the right to publication and dissemination by additional means , following procedures and regulations in line with the terms and conditions from the VIMMP consortial agreement.

We validate the chromo-dynamic multi-component lattice Boltzmann equation (MCLBE) simulation for immiscible fluids with a density contrast against analytical results for complex flow geometries, with particular emphasis on the fundamentals of the method, i.e. compliance with inter-facial boundary conditions of continuum hydrodynamics. To achieve the necessary regimes for the chosen validations, we develop, from a three-dimensional, axially-symmetric flow formulation, a novel, two-dimensional, pseudo Cartesian, MCLBE scheme. This requires the inclusion in lattice Boltzmann methodology of a continuously distributed source and a velocity-dependent force density (here, the metric force terms of the cylindrical Navier–Stokes equations). Specifically, we apply our model to the problem of flow past a spherical liquid drop in Re  =  0, Ca regime and, also, flow past a lightly deformed drop. The resulting simulation data, once corrected for the simulation’s inter-facial micro-current (using a method we also advance herein, based on freezing the phase field) show good agreement with theory over a small range of density contrasts. In particular, our data extend verified compliance with the kinematic condition from flat (Burgin et al 2019 Phys. Rev. E 100 043310) to the case of curved fluid–fluid interfaces. More generally, our results indicate a route to eliminate the influence of the inter-facial micro-current.

It is explored how physicalist mereotopology and Peircean semiotics can be applied to represent models, simulations, and workflows in multiscale modelling and simulation of physical systems within a top-level ontology. It is argued that to conceptualize modelling and simulation in such a framework, two major types of semiosis need to be formalized and combined with each other: Interpretation, where a sign and a represented object yield an interpretant (another representamen for the same object), and metonymization, where the represented object and a sign are in a three-way relationship with another object to which the signification is transferred. It is outlined how the main elements of the pre-existing simulation workflow descriptions MODA and OSMO, i.e., use cases, models, solvers, and processors, can be aligned with a top-level ontology that implements this ontological paradigm, which is here referred to as mereosemiotic physicalism. Implications are discussed for the development of the European Materials and Modelling Ontology, an implementation of mereosemiotic physicalism.

The European Materials and Modelling Ontology (EMMO) has recently been advanced in the computational molecular engineering and multiscale modelling communities as a top-level ontology, aiming to support semantic interoperability and data integration solutions, e.g., for research data infrastructures. The present work explores how top-level ontologies that are based on the same paradigm - the same set of fundamental postulates - as the EMMO can be applied to models of physical systems and their use in computational engineering practice. This paradigm, which combines mereology (in its extension as mereotopology) and semiotics (following Peirce's approach), is here referred to as mereosemiotics. Multiple conceivable ways of implementing mereosemiotics are compared, and the design space consisting of the possible types of top-level ontologies following this paradigm is characterized.

A multi-GPGPU development for Mesoscale Simulations using the Dissipative Particle Dynamics method is presented. This distributed GPU acceleration development is an extension of the DL_MESO package to MPI+CUDA in order to exploit the computational power of the latest NVIDIA cards on hybrid CPU–GPU architectures. Details about the extensively applicable algorithm implementation and memory coalescing data structures are presented. The key algorithms’ optimizations for the nearest-neighbour list searching of particle pairs for short range forces, exchange of data and overlapping between computation and communications are also given. We have carried out strong and weak scaling performance analyses with up to 4096 GPUs. A two phase mixture separation test case with 1.8 billion particles has been run on the Piz Daint supercomputer from the Swiss National Supercomputer Center. With CUDA aware MPI, proper GPU affinity, communication and computation overlap optimizations for multi-GPU version, the final optimization results demonstrated more than 94% efficiency for weak scaling and more than 80% efficiency for strong scaling. As far as we know, this is the first report in the literature of DPD simulations being run on this large number of GPUs. The remaining challenges and future work are also discussed at the end of the paper.

It is explored how foundational ontologies based on physicalist materialism, nominalism, and Peircean semiotics can be applied to represent signs, models of physical systems, and their use in engineering modelling and simulation practice. It is argued that to conceptualize modelling of physical systems in such a framework, various kinds of Peircean semiotic triads need to be combined. Thereby, a sign (representamen) and a represented object either yield an interpretant, i.e., another representamen of the same object, or the representation is transferred to another object by semantic change through metonymization or metaphorization, retaining the same symbol. Multiple conceivable ways of implementing this ontological paradigm are compared, and a demonstrator implementation is discussed.

By introducing a common representational system for metadata that describe the employed simulation workflows, diverse sources of data and platforms in computational molecular engineering, such as workflow management systems, can become interoperable at the semantic level. To achieve semantic interoperability, the present work introduces two ontologies that provide a formal specification of the entities occurring in a simulation workflow and the relations between them: The software ontology VISO is developed to represent software packages and their features, and OSMO, an ontology for simulation, modelling, and optimization, is introduced on the basis of MODA, a previously developed semi-intuitive graph notation for workflows in materials modelling. As a proof of concept, OSMO is employed to describe a use case of the TaLPas workflow management system, a scheduler and workflow optimizer for particle-based simulations.

The Virtual Materials Marketplace (VIMMP) project, which develops an open platform for providing and accessing services related to materials modelling, is presented with a focus on its ontology development and data technology aspects. Within VIMMP, a system of marketplace-level ontologies is developed to characterize services, models, and interactions between users; the European Materials and Modelling Ontology is employed as a top-level ontology. The ontologies are used to annotate data that are stored in the ZONTAL Space component of VIMMP and to support the ingest and retrieval of data and metadata at the VIMMP marketplace frontend.