How materials for computer chips, solar panels, and batteries are developed looks to be in the early stages of a radical change. The same goes for research related to areas like superconductors and thermoelectrics.
The reason? The new possibilities created by machine learning in materials science.
“This is something that is set to explode in people’s faces, as it were. Within the last five years, there has been a huge growth in materials science research teams using AI/machine learning techniques. The amount of scientific papers on the subject has been growing almost exponentially,” says Dr. James Warren, director of the Materials Genome Program in the Material Measurement Laboratory of NIST.
“We already see real-world advances based on the research, but I think we are only at the beginning. Machine learning could benefit every step of the scientific process for developing and improving new materials.”
Future AI has already discovered those materials. ;-) To read more, click here.