Can AI really help us discover new materials? Judging from headlines and social media posts in recent years, one might reasonably assume that AI is going to fix the power grid, cure the world's diseases, and finish my holiday shopping for me. This week, we published a new package called Hype Correction . The collection of stories takes a look at how the world is starting to reckon with the reality of what AI can do, and what's just fluff. One of my favorite stories in that package comes from my colleague David Rotman, who took a hard look at AI for materials research . AI could transform the process of discovering new materials--innovation that could be especially useful in the world of climate tech, which needs new batteries, semiconductors, magnets, and more.

MolGX, a part of IBM's overarching strategy that aims to accelerate the discovery of new materials by 10 to 100 times, uncovers materials from the property targets of a given product. By observing and selecting a dataset, MolGX leverages generative models to produce molecules from chemical properties like "solubility in water" and "heatability." The platform trains an AI model to predict chemical characteristics within given parameters and synthesizes molecular structures based on the model built. Breakthroughs in the discovery of new materials span from pure chance, to trial-and-error approaches, to design by analogy to existing systems," Seiji Takeda, technical lead of material discovery at IBM, wrote in a blog post. IBM has released a free trial version of MolGX trained using a built-in dataset, which the company applied internally to the development of a new photoacid generator -- a key material in electronics manufacturing.

Scientists at the U.S. Department of Energy's (DOE) Brookhaven National Laboratory have successfully demonstrated that autonomous methods can discover new materials. The artificial intelligence (AI)-driven technique led to the discovery of three new nanostructures, including a first-of-its-kind nanoscale "ladder." The research was published today in Science Advances.. The newly discovered structures were formed by a process called self-assembly, in which a material's molecules organize themselves into unique patterns. Scientists at Brookhaven's Center for Functional Nanomaterials (CFN) are experts at directing the self-assembly process, creating templates for materials to form desirable arrangements for applications in microelectronics, catalysis, and more.

IBM today announced the launch of the Molecule Generation Experience (MolGX), a cloud-based, AI-driven molecular design platform that automatically invents new molecular structures. MolGX, a part of IBM's overarching strategy that aims to accelerate the discovery of new materials by 10 to 100 times, uncovers materials from the property targets of a given product. The chemical sciences have made strides in the discovery of novel and useful materials over the past decades. For example, in the area of polymers, the recent development of thermoplastics has had an influence on applications ranging from new paints to clothing fibers. But while the discovery of new materials is the driving force in the expansion and improvement of industrial products, the vastness of chemical space likely exceeds the ability of human experts to explore even a fraction of it.

Kebotix, a technology company ushering in the future of new materials discovery, came out of stealth mode with a $5 million seed round led by One Way Ventures. Investors also include Baidu Ventures, an independent venture fund with backing and resources from Baidu; Boston-based Flybridge Capital Partners; Los Angeles-based Embark Ventures; Norway-based Propagator Ventures; and New York-based WorldQuant Ventures. Developing the world's first self-driving lab for materials discovery powered by artificial intelligence (AI) and robotics, Kebotix is committed to accelerating the exploration, discovery, applications, and production of new molecules and materials. "We are building the materials company of the 21st century because how scientists discover new materials has not evolved since the 18th century," said CEO Dr. Jill S. Becker. "Being stuck in the 18th century significantly adds to the challenge of tackling climate change, antibiotic-resistant bacteria, water pollution, and other urgent problems facing the world today."

Scientists teamed up to use artificial intelligence to discover new alternatives to steel in record time. As a result, they discovered three new blends to form metallic glass and did this 200 times faster than it has ever been done before. Fang Ren, who developed algorithms to analyze data on the fly while a postdoctoral scholar at SLAC, at a Stanford Synchrotron Radiation Lightsource beamline where the system has been put to use. Metallic glass is essentially an alloy of the future. Normally, a few metals can be mixed together so that the ideal properties of each metal are'added' together to make a'super-metal'.