System Bits: April 8

Teaching computers; saltwater batteries; metamaterials.


Computers trained to design materials
Researchers in the University of Missouri’s College of Engineering are applying deep learning technology to educate high-performance computers in the field of materials science, with the goal of having those computers design billions of potential materials.

“You can train a computer to do what it would take many years for people to otherwise do,” said Yuan Dong, a research assistant professor of mechanical and aerospace engineering and lead researcher on the study. “This is a good starting point.”

Dong worked with Jian Lin, an assistant professor of mechanical and aerospace engineering, to determine if there was a way to predict the billions of possibilities of material structures created when certain carbon atoms in graphene are replaced with non-carbon atoms.

“If you put atoms in certain configurations, the material will behave differently,” Lin said. “Structures determine the properties. How can you predict these properties without doing experiments? That’s where computational principles come in.”

Lin and Dong partnered with Jianlin Cheng, a William and Nancy Thompson Professor of Electrical Engineering and Computer Science at MU, to input a few thousand known combinations of graphene structures and their properties into deep learning models. From there, it took about two days for the high-performance computer to learn and predict the properties of the billions of other possible structures of graphene without having to test each one separately.

Photo credit: University of Missouri

Researchers envision future uses of this artificial intelligence assistive technology in designing many different graphene-related or other two-dimensional materials. These materials could be applied to the construction of LED televisions, touch screens, smartphones, solar cells, missiles and explosive devices.

“Give an intelligent computer system any design, and it can predict the properties,” Cheng said. “This trend is emerging in the material science field. It’s a great example of applying artificial intelligence to change the standard process of material design in this field.”

A paper on the study was published in the npj Computational Materials journal.

Research team develops prototype of a new battery type
Research is going on around the world on developing alternatives to lithium-ion battery technology. At Imperial College London, researchers in the Departments of Physics and Chemistry worked on developing a battery prototype employing thin films of specially designed plastics and simple salt water.

While it can hold less charge than conventional lithium-ion batteries, the prototype, which is made from polymers – long chains of molecules that make up plastics – can charge and discharge in a matter of seconds. As an added benefit of the materials it uses, it also changes color as it charges, giving users an easy way to read out the state of charge of the battery.

The prototype, the details of which were published in the Energy & Environmental Science journal, could pave the way for improving the charging rate and toxicity of existing batteries, or provide a route for making entirely new kinds of batteries, according to the university.

Co-lead author Dr. Alexander Giovannitti, who worked on the project while at the Departments of Physics and Chemistry at Imperial, said: “The materials we used to create the battery prototype could potentially be made at low cost and combined with the use of non-toxic and non-flammable water-based electrolytes. This approach could be a viable route to develop recyclable batteries.”

The team says their prototype would need more work to be suited to these areas, but that the principles behind its design could be applicable to a wide range of energy storage devices in development.

Designing metamaterials that can solve equations
Fascinating research is going on in the field of metamaterials. These materials involve complicated, composite structures, some of which have the capability to manipulate electromagnetic waves.

For Nader Engheta of the University of Pennsylvania’s School of Engineering and Applied Science, one of the loftier goals in this field has been to design metamaterials that can solve equations. This “photonic calculus” would work by encoding parameters into the properties of an incoming electromagnetic wave and sending it through a metamaterial device; once inside, the device’s unique structure would manipulate the wave in such a way that it would exit encoded with the solution to a pre-set integral equation for that arbitrary input.

In a paper published in Science, Engheta and his team demonstrated such a device for the first time.

Their proof-of-concept experiment was conducted with microwaves, as the long wavelengths allowed for an easier-to-construct macro-scale device. The principles behind their findings, however, can be scaled down to light waves, eventually fitting onto a microchip. Such metamaterial devices would function as analog computers that operate with light, rather than electricity. They could solve integral equations—ubiquitous problems in every branch of science and engineering—orders of magnitude faster than their digital counterparts, while using less power.

Engheta, the H. Nedwill Ramsey Professor in the Department of Electrical and Systems Engineering, conducted the study along with lab members Nasim Mohammadi Estakhri and Brian Edwards.

This approach has its roots in analog computing. The first analog computers solved mathematical problems using physical elements, such as slide-rules and sets of gears, that were manipulated in precise ways to arrive at a solution. In the mid-20th century, electronic analog computers replaced the mechanical ones, with series of resistors, capacitors, inductors, and amplifiers replacing their predecessors’ clockworks.

Such computers were state-of-the-art, as they could solve large tables of information all at once, but were limited to the class of problems they were pre-designed to handle. The advent of reconfigurable, programmable digital computers, starting with ENIAC, constructed at Penn in 1945, made them obsolete.

As the field of metamaterials developed, Engheta and his team devised a way of bringing the concepts behind analog computing into the 21st century. Publishing a theoretical outline for “photonic calculus” in Science in 2014, they showed how a carefully designed metamaterial could perform mathematical operations on the profile of a wave passing thought it, such as finding its first or second derivative.

Now, Engheta and his team have performed physical experiments validating this theory and expanding it to solve equations.
“Our device contains a block of dielectric material that has a very specific distribution of air holes,” Engheta says. “Our team likes to call it ‘Swiss cheese.’”

The Swiss cheese material is a kind of polystyrene plastic; its intricate shape is carved by a CNC milling machine.

“Controlling the interactions of electromagnetic waves with this Swiss cheese metastructure is the key to solving the equation,” Estakhri says. “Once the system is properly assembled, what you get out of the system is the solution to an integral equation.”

“This structure,” Edwards adds, “was calculated through a computational process known as ‘inverse design,’ which can be used to find shapes that no human would think of trying.”

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