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Computational Modelling

With modern computational techniques, it is now possible to predict the properties of novel materials from first principles using advanced simulation techniques. This has the advantages of being both quicker and cheaper than a trial-and-error experimentation process, and also yields detailed structural and dynamical information that can provide a stringent test of theoretical models.

As computing power continues to increase at a relentless pace, it is tempting to consider the simulation of large and/or complex systems using brute force atomistic simulation methods alone. However, even extrapolating from current state-of-the-art methodologies, it would still take well over a century of exponential growth in computing resources to achieve parity with ‘real time’ simulations of experimental systems of macroscopic size and, in any case, the sheer amount of data produced would overwhelm any attempt at detailed scientific analysis. Therefore, it is imperative that we now seek to exploit the regions of overlap between well-established techniques for electronic structure calculations, molecular dynamics, mesoscopic simulations and continuum modelling to allow efficient multiscale simulations of increasingly complex condensed phase systems. Multiscale modelling is currently a powerful and widely-used tool in Materials Science, in which there have been significant technical and scientific advances over the last decade, enabling novel fields of application from nanotechnology to biomineralization.

 Computational Modelling


In the MML group we utilise simulation techniques across all of the length scales above. At the electron scale, density functional theory and Hartree-Fock methods are used to calculate parameters ab initio. Expertise in using Materials Studio, CHARMM, AMBER, VMD, NAMD, LAMMPS, DL_POLY and many more force fields and simulation packages allow us to simulate molecular systems. In the mesoscale, coarse-grained molecular dynamics and dissipative particle dynamics are used to simulate even larger systems on timescales more comparable with experiments. Finally at the macroscopic scale the discrete element method and finite element method allow us to simulate processes which the naked eye can see.

[1] Elliott, J.A. "Novel Approaches to Multiscale Modelling in Materials Science", International Materials Reviews, 56, 207-225 (2011). link

People specializing in this area

Postdoctoral Research Associates

Dr Patrick Kiley

I am interested in combining DFT, atomistic modelling, and coarse-graining of atomistic systems to create a multi-scale approach to simulating biological and bioinspired materials.  The hierarchical nature of collagen lends itself to this approach.

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Congratulations to Dr Chunlei Pei

Mar 31, 2017

Dr Chunlei Pei wins a Young Researcher Prize for an oral presentation at the UK Particle Technology forum held at University of Birmingham on 29th March 2017.

MML Fajita Lunch

Feb 20, 2017

MML group had a pleasant Fajita Lunch on Friday 17th February 2017. We wish everyone has a fruitful and successful new year.

Multi-scale modelling of carbon nanotube reinforced crosslinked interfaces

Jan 28, 2017

A new paper by James A. Elliott and his Turkish collaborators Elif Ozden-Yenigun and Canan Atilgan is published in Computational Materials Science

Chirality-independent characteristic crystal length in carbon nanotube textiles measured by Raman spectroscopy

Jan 28, 2017

A new paper by John S. Bulmer, Thurid S. Gspann, Jon S. Barnard and James A. Elliott is published in Carbon.

MML Christmas Dinner 16-12-16

Dec 23, 2016

Wishing you all a Merry Christmas, from the Macromolecular Materials Lab.

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