Data background

The Nanotechnology Consortium legacy

I am always  happy to see the strong innovation legacy of the Nanotechnology Consortium that I ran from 2004-2010 grow in the Materials Studio releases. The leading edge tools that the Consortium progressed from an academic code to a commercial release include ONETEP (linear scaling DFT), QMERA (coupled electronic-atomistic modelling) as well as the new GULP (atomistic modelling incl reactive forcefield) and DFTB+ (fast, tight binding based DFT). All have been further enhanced and by now are clearly a core part of the Dassault Systemès discrete modelling package. Particularly pleasing is the recent release of the reaction Kinetic Monte Carlo module Kinetix for the general public, about 10 years after it became available to Nanotechnology Consortium members. As other Reaction Kinetic MC tools have moved from academia to a wider industry use (see e.g. Zacros) it is clear that the Nanotech Consortium and all companies that supported it were leading the innovation. I am curious to see where the next wave of Dassault Systemès innovation in materials modelling is going to come from, as sadly the time of consortia seems to be over.

Gerhard Goldbeck

Data background

Nanotech going downstream

At the Techconnect Nanotech 2011 conference in Boston a couple of weeks ago, the emphasis was clearly on the ‘downstream’, i.e. realising the potential of nanotechnology in new and exciting products. I was impressed by the progress made at Nanocomp in manufacturing huge sheets and yarns from nanotubes for applications such as EMI shielding and heat straps. Having shared the lab with folks wondering how one could process this stuff in the nineties [1] the presentation brought it home how far the field has developed in the last 15 years.

Going from the large size applications to the small, Tom Russell presented the latest in his quest to reach addressable arrays of 10 tera-dots per square inch by self-assembly of block copolymers. A fascinating journey, from the enhanced ordering obtained by solvent annealing which gives grain sizes of about 20 micron (“not good enough”), lithography guided assembly (“still not good enough”), to spin coated and solvent annealed copolymer on faceted sapphire wafers, which eventually lead to cylinder phase perpendicular to the sapphire ridges with translational and orientational order persisting over centimetres! Looks like the next generations of memory devices is well on its way.

Big strides are also being made in catalysis. Nanostellar, who design new materials based on a so-called Rational Design Methodology which relies heavily on simulation, presented advances in diesel emission catalysts.  It was interesting to hear from CEO Pankaj Dhingra that their focus has changed from using modelling for wide range screening to a more focussed application on uncovering the key selection criteria within a more targeted phase space, in this case Strontium doped Lanthanum perovskites.

The downstream theme was also echoed in the modelling session. Apart from my talk about the ‘landscape’ of integration of atomistic simulation into engineering optimisation, which I’ll come to in another blog, Simon McGrother from CULGI highlighted some great successes of polymer and mesoscale modelling in product development.  Despite that, he made the point that these methods have still not reached the ‘democratization’ that was anticipated ten years ago. Based on the growth figures of the modelling community presented in my previous blog, I would actually dispute that. Nevertheless, the impact on ‘downstream’ development and products remains limited, and that’s where I agree with Simon.

On the other hand, the engineering simulation community is showing an interest in molecular modelling, as highlighted in a presentation by Carlos Alguin, Head of the Nanotechnology Group at Autodesk with some cool graphics based on the Maya software and Molecular Maya toolkit. Clearly, the ease of use of and interactivity their design tools and the superb visualization have much to offer the molecular modelling community. The question is though how we achieve further awareness and utilisation of materials modelling back in the engineering world.

[1] M.S.P Shaffer, X.F. Fan and A.H. Windle, Dispersion and packing of carbon nanotubes, Carbon, Vol. 36, No. 11, pp.1603-1612 (1998)