Shulou(Shulou.com)12/24 Report--

CTOnews.com, Nov. 30 (Xinhua)-- Google's DeepMind has used artificial intelligence (AI) to predict the structure of more than 2 million new materials, a breakthrough that the company says will drive technological improvements in the real world.

The results of the study were published in Nature on Wednesday under the title "An autonomous laboratory for the accelerated synthesis of novel materials". CTOnews.com is attached with DOI:10.1038/s41586-023,06734Murw.

DeepMind researchers pointed out in the paper that most of its hypothetical nearly 400000 material designs will soon be produced under laboratory conditions. The research could help produce better-performing batteries, solar panels and computer chips.

After predicting the stability of these new materials using AI, DeepMind says the next research focus will shift to predicting how easy it will be to synthesize them in the laboratory.

▲ source: nature in fact, the discovery and synthesis of new materials is actually a very expensive and time-consuming process. For example, the commercial application of lithium-ion batteries that we can see everywhere has gone through about 20 years, during which countless costs and painstaking efforts have been spent.

"We hope to shorten this 10-to 20-year period to a more manageable range through experiments, autonomous synthesis and huge improvements in machine learning models," said Ekin Dogus Cubuk, a researcher at DeepMind.

According to reports, DeepMind's AI is based on Materials Project data for training. This is an international research organization founded at Lawrence Berkeley National Laboratory in 2011 and currently has the research results of about 50,000 known materials.

The company said it would now share its data with the research community with a view to accelerating further breakthroughs in material discovery.

"when it comes to cost increases, the industry tends to be a little risk-averse, and new materials usually take a while to become cost-effective," said Kristin Persson, head of Materials Project. "if we can further shorten that time, that's a real breakthrough."

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