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computers, as well as grid-connected, high- performance computers, has led to simulations of a size and complexity of real relevance to industry partners,’ said Greenwell, who added that he can run simulations on tens of thousands of cores. ‘Access to large-scale HPC facilities

(ARCHER, HECToR, STFC Hartree and N8 HPC) is a requirement for the fundamental research we are interested in,’ agreed Teobaldi. ‘Te substantial increase in computational powers, coupled with continuous progress in novel and more efficient algorithms and numerical libraries has markedly benefit the whole scientific community with interest in atomistic modelling. In the group, we routinely work on systems that are between one and two orders of magnitude larger than I could do when I started my PhD roughly 10 years ago.’

Pushing the limits But there are still significant limitations, argued Teobaldi. ‘In spite of the remarkable advances in efficiency of atomistic-modelling scientific soſtware and increase in academically-available computational power, the accuracy-viability tradeoff is far from ideal. More method- development work (which in turns requires more dedicated research funds) is needed,’ he explained. In terms of hardware, Teobaldi would like

to see ‘cost- and energy-effective multi-core processors with sufficiently large memory (ideally more than 1GB/core)’. With soſtware, he would like to see ‘more

performing numerical libraries tuned to emerging hardware solutions and the possibility of facile porting and tuning of existing code to novel hardware solutions’. ‘Companies are very active in this but there

are huge challenges. It needs a concerted effort between business and academia,’ he explained. (See John Barr’s article on page 18 for more

discussion of the role of independent soſtware vendors and porting code to different hardware architectures.) Mark Mackey, CSO of Cresset, agreed

about these challenges: ‘In the computational chemistry industry, the main trend is the acceptance by virtually all modellers that the existing force fields (the sets of parameters that we use to describe molecules) are inadequate. In particular, their modelling of electrostatics is poor, and this leads to very misleading or incorrect results in some cases.’ Mackey noted that there are

‘a lot of tools are developed by academics but take-up by a wider community cannot happen if, for any project, highly-skilled, specialist researchers are needed every time the code/tool is to be deployed.’ Stevens of Accelrys agreed that usability is


a number of major academic efforts to produce improved force fields, with varying degrees of success. ‘It’s fair to say that the problem has turned out to be more difficult than was first thought. However, I expect that by the end of the decade there will be a major shiſt away from the first-generation force fields and towards the second- generation polarisable ones for day-to-day calculations.’ He added that Cresset has its own force field,





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an important feature for commercial soſtware too. ‘One of the strongest messages we get from users is that they don’t have two weeks to read the manual and learn how to use the soſtware,’ he said. He added that there is a trend towards building guided workflow tools that allow users to do the tasks they are most likely to do by following steps, so they don’t need to read the manual again. A related usability request is

for cross-integration of tools, for example, to be able to open a chemical modelling tool when looking at data in Excel and then export the result. ‘Our products have become much more integrated and cross- product integration is now built in,’ he said.

Meanwhile, as soſtware and computing

which, he said takes a slightly unusual approach to the problem with a good deal of success. ‘We are proactively looking into ways to improve our force field in this area, and we are also keeping an eye on the academic research.’

Biosciences bias In the area of modelling materials, Greenwell sees another challenge for researchers. ‘By and large, most development has gone into codes for biological applications, which are oſten not optimal for materials chemistry or geoscience applications.’ He noted that simulations designed for

biological molecules tend to be very different. ‘Proteins tend to be discrete molecules, whereas with minerals science you want to have periodic, continuous models. Tis becomes a challenge, especially in inputting conditions.’ ‘It is certainly true, especially for large

systems, that inorganic materials are set back compared with biological ones,’ agreed Teobaldi. ‘When you do models of biological systems, the pharmaceutical industry is very interested. I’m not sure that there is such a high realisation of the importance of modelling with inorganic materials.’ And this difference in interest, he said,

Computer-assisted screening of novel photo-catalytic strategies: it is possible to couple different sunlight- fuelled photochemical reactions on different sides of open-ended inorganic nanotubes l

corresponds to a different level of investment in modelling solutions – and a difference in the accuracy of the resulting models. Another development that would benefit modellers is improvements in usability. Greenwell noted that


power develops, there is a corresponding increase in the tasks that modelling is applied to. ‘We definitely expect use of modelling to increase as the range and size of problems you can solve increases,’ noted Aglave from CD-adapco. ‘New problems are being created as new materials – such as nanoparticles, photovoltaics, semiconductor materials and thin films – are being created, and, as you manufacture new materials, there are new processes. You can deploy modelling to shorten the development process.’ Another trend that he observes is the desire

for optimisation, doing multiple simulations to come to the best design as quickly as possible. But computational studies will not answer

everything. Stevens of Accelrys pointed to a 19th century quote that says all models are wrong but some are useful. ‘Some modellers have thought in the past that everything is useful. Somewhere between the two is where the reality is,’ he said. In other words, successful projects need to continue to span the boundaries between laboratory and computer.

References Huskinson, B.; Marshak, M. P.; Suh, C.; Er, S. L.; Gerhardt, M. R.; Galvin, C. J.; Chen, X.; Aspuru-Guzik, A. N.; Gordon, R. G.; Aziz, M. J. (2014). “A metal-free organic–inorganic aqueous flow battery”. Nature 505 (7482): 195–198. doi:10.1038/nature12909


EPSRC UK EP/I004483/1

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