For hundreds of years, new materials were discovered through trial and error, or luck and serendipity. Now, scientists are using artificial intelligence to speed up the process.
Recently, researchers at Northwestern University used to figure out how to make new metal-glass hybrids 200 times faster than they would have doing experiments in the lab. Other scientists are building databases of thousands of compounds so that An algorithm is a fixed set of instructions for a computer. It can be very simple like "as long as the incoming number is smaller than 10, print "Hello World!". It can also be very complicated such as the algorithms behind self-driving cars. can predict which ones combine to form interesting new materials. Others yet are using to mine published papers for “recipes” to make these materials.
In the past, scientists and builders mixed materials together to see what formed. This is how cement, for instance, was discovered. Over time, they learned the physical properties of various compounds, but much of the knowledge was still based on intuition. “If you asked why Japanese watered steel was better at making knives, I don’t think anybody could have told you,” says James Warren , director of the Materials Genome Initiative at the National Institute of Standards and Technology . “They just had an artisan’s understanding of the relationship between that internal structure and awesomeness.”
Now, instead of using artisan’s knowledge, we can use databases and computations to quickly map out exactly what makes a material so much stronger or lighter — and that has the potential to revolutionize industry after industry, according to Warren. The time between discovering a material and integrating it into a product like a battery can be more than 20 years, he adds, and speeding up the process is bound to lead us to better batteries and glass for cell phones, better alloys for rockets, and better sensors for health devices. “Anything made out of matter,” says Warren, “we can improve.”
To understand how new materials are made, it’s helpful to think of a materials scientist like a cook, according to Warren. Say you have eggs, and you’re in the mood for something chewy and firm. Those are the properties of the dish you want, but how do you get there? To create a structure where both the white and the yolk are solid, you need a recipe that includes the step-by-step instructions for processing the egg — hardboiling it — just the way you want it. Materials science uses these same concepts: If a scientist wants certain material properties (say, light and hard to fracture), she will look for the physical and chemical structures that would create these properties, and the processes — like melting or beating metal — that would create these structures.
Databases and computations can help find answers. “We do quantum mechanical-level calculations of materials, calculations sophisticated enough that we can actually predict the properties of a possible new material on a computer before it’s ever made in a laboratory,” says Chris Wolverton, a materials scientist at Northwestern University who runs the Open Quantum Materials Database. (Other major databases include the Materials Project and the Materials .) The databases aren’t complete, but they’re growing, and already giving us exciting discoveries. […]