Today, the ‘heavy lifting’ is being done by computers. Let’s look, as an example, at the project undertaken by Harvard – in association with MIT and Samsung – to identify new molecules for blue OLEDs. The team started out with 1.6million so called ‘candidates’, refining them using ‘a simple quantum chemical calculation’. It might have been a simple equation, but it still needed 12 hours of computing per molecule to determine if it had the suitable colour and brightness.
Now, the team has narrowed the field significantly and say it has identified ‘hundreds’ of molecules that, in theory, will perform as well as, if not better than, those currently in use.
Batteries are another area where this approach could bring significant benefits. Apparently, there are 110m possible combinations of materials that could be used to create a battery, but only 30 combinations have been put to practical use. Using computer models to examine the possibilities seems a good idea and that’s something which solid state battery pioneer Ilika has done. By creating datasets that define how families of materials perform, it says it can make, characterise and test potential materials up to 100 times more quickly than traditional techniques.
With most areas of technology, electronics notwithstanding, crying out for materials which offer better performance than available from today’s products, it makes sense to use the processing power available to identify these ‘designer molecules’ and to then apply them.
