FUSION IS THE POWER SOURCE OF THE SUN AND STARS. IT OCCURS WHEN FORMS OF THE LIGHTEST ATOM, HYDROGEN, COMBINE TO MAKE HELIUM IN A VERY HOT (100 MILLION DEGREE CENTIGRADE) IONIZED GAS, OR PLASMA.
Source – U.S. Department of Energy, Public Domain
Researchers have long searched for alternatives to iridium, an extremely rare, incredibly expensive metal used in the production of clean hydrogen fuels.
Now, a new AI tool has discovered one. This is software, invented and developed at Northwestern University called a megalibrary. This is the world’s first nanomaterial “data factory,” each megalibrary contains millions of uniquely designed nanoparticles on one tiny chip.
In collaboration with researchers from the Toyota Research Institute (TRI), the academics used this technology to discover commercially relevant catalysts for hydrogen production. Following this, they scaled up the material and demonstrated it could work within a device.
With a megalibrary, scientists rapidly screened vast combinations of four abundant, inexpensive metals — each known for its catalytic performance — to find a new material with performance comparable to iridium.
The researchers discovered a wholly new material that, in laboratory experiments, matched or in some cases even exceeded the performance of commercial iridium-based materials, but at a fraction of the cost.
This discovery does not only make affordable green hydrogen a possibility; it also proves the effectiveness of the new megalibrary approach, which could completely change how researchers find new materials for any number of applications.
‘Not enough iridium in the world’
As the world moves away from fossil fuels and toward decarbonization, affordable green hydrogen has emerged as a critical component. To produce clean hydrogen energy, scientists have turned to water splitting, a process that uses electricity to split water molecules into their two constituent components — hydrogen and oxygen.
The oxygen part of this reaction, called the oxygen evolution reaction (OER), however, is difficult and inefficient. OER is most effective when scientists use iridium-based catalysts, which have significant disadvantages. Iridium is rare, expensive and often obtained as a byproduct from platinum mining. More valuable than gold, iridium costs nearly $5,000 per ounce.
‘Full army deployed on a chip’
While materials discovery is traditionally a slow and daunting task filled with trial and error, megalibraries enable scientists to pinpoint optimal compositions at breakneck speeds. Each megalibrary is created with arrays of hundreds of thousands of tiny, pyramid-shaped tips to print individual “dots” onto a surface. Each dot contains an intentionally designed mix of metal salts. When heated, the metal salts are reduced to form single nanoparticles, each with a precise composition and size.
New solution?
In the new study, the chip contained 156 million particles, each made from different combinations of ruthenium, cobalt, manganese and chromium. A robotic scanner then assessed how well the most promising particles could perform an OER. Based on these tests, Mirkin and his team selected the best-performing candidates to undergo further testing in the laboratory.
Eventually, one composition stood out: a precise combination of all four metals (Ru52Co33Mn9Cr6 oxide). Multi-metal catalysts are known to elicit synergistic effects that can make them more active than single-metal catalysts.
By generating massive high-quality materials datasets, the megalibrary approach also lays the groundwork for using artificial intelligence (AI) and machine learning to design the next generation of new materials.
The study appears in the Journal of the American Chemical Society (JACS). It is titled “Accelerating the pace of oxygen evolution reaction catalyst discovery through megalibraries.”
