Metamaterials are artificially engineered materials. Scientists create them by combining multiple elements from composite materials such as metal and dielectric. The result is an entirely new material with properties not found in nature.
To achieve invisibility, a metamaterial needs to possess certain optical properties. Specifically, scientists would have to design the material so that they could control how light moves around an object without being reflected or absorbed. This design is possible, but it would take just the right material with just the right structure.
There are hundreds of thousands of potential material structures with optical responses that fall somewhere along the optical spectrum. Sifting through them to find a new material design has traditionally taken hours or even days.
Now, Northeastern professor Yongmin Liu has developed a new method for quickly discovering materials that have desirable qualities, such as invisibility. In a paper published recently in ACS Nano, Liu and his co-authors describe a machine learning algorithm they developed and trained to identify new metamaterial structures. The new method is much faster and more accurate than previous approaches, paving the way for engineers to design next-generation materials.
A number of metamaterials were almost accidentally discovered as a result of what amounts to tinkering and noticing unforeseen physical effects from such materials. Developing a viable theoretical methodology for designing metamaterials for specific purposes would be revolutionary, to say the least. To read more, click here.