Facebook and Carnegie Mellon University have announced they are trying to use artificial intelligence (AI) to find new “electrocatalysts” that can help to store electricity generated by renewable energy sources.
Electrocatalysts can be used to convert excess solar and wind power into other fuels, such as hydrogen and ethanol, that are easier to store. However, today’s electrocatalysts are rare and expensive, with platinum being a good example, and finding new ones hasn’t been easy as there are billions of ways that elements can be combined to make them.
Researchers in the catalysis community can currently test tens of thousands of potential catalysts a year but Facebook and Carniegie Mellon believe they can increase the number to millions, or even billions, of catalysts with the help of AI.
The social media giant and the university on Wednesday released some of their own AI software “models” that can help to find new catalysts but they want other scientists to have a go as well.
To support these scientists, Facebook and Carnegie Mellon have released a data set with information on potential catalysts that scientists can use to create new pieces of software.
Facebook said the “Open Catalyst 2020” data set required 70 million hours of compute time to produce. The data set includes “relaxation” calculations for a million possible catalysts as well as supplemental calculations.
Relaxations, a widely used measurement in catalysis, are calculated to see if a particular combination of elements will make a good catalyst.
Each relaxation calculation, which simulates how atoms from different elements will interact, takes scientists around eight hours on average to work out, but Facebook says AI software can potentially do the same calculations in under a second.
If you study catalysis, “that’s going to dramatically change how you do your work and how you do your research,” said Larry Zitnick, a research scientist at Facebook AI Research, on a call ahead of the announcement.
In recent years, tech giants like Facebook and Google have attempted to use AI to speed up scientific calculations and observations across multiple fields.
For example, DeepMind, an AI-lab owned by Google parent Alphabet, developed AI software capable of spotting tumors in mammograms faster and more accurately than human researchers.