Skip to main content

No more panels? A.I. helps create sprayable solar cells that can be painted on

Solar power is enormously promising when it comes to providing a source of sustainable energy. But solar panels take up a lot of space, which can limit their appeal and practicality. Enormous solar farms stretching as far as the eye can see might be an option in rural locations where space is readily available. However, go into a city and the number of places you might be able to deploy photovoltaics drastically decreases. Unless robots have anything to say about it, that is.

At the University of Central Florida, researchers have been using machine learning to optimize the materials used to make special solar cells. Their goal? To develop the insights that will make spray-on solar cells, which are applicable just about antwhere, a reality. Such sprayable cells could be used to paint anything from bridges to skyscrapers. It would then capture light and turn it into energy for the electrical grid.

“We [used] artificial intelligence to develop new material compositions to make a comparatively new type of solar cells called perovskite solar cells,” Dr. Jayan Thomas, an associate professor in the university’s NanoScience Technology Center, told Digital Trends. “Unlike the currently available commercial silicon solar cells, these devices are much thinner and the materials can be deposited from solutions. Making the solar cells from [a] solution enables the use of techniques like roll-to-roll or spray coating to make large-area devices very rapidly. This considerably reduces the cost of production.”

In Thomas’ words, the materials to make these kind of solar cells are “dirt cheap.” But the downside is that they’re also toxic and have inferior environmental stability. The researchers hope that, by using artificial intelligence, they can develop better, safer, higher-quality perovskite solar cells. To that end, they fed solar cell performance data from more than 2,000 scientific publications into a machine-learning neural network. The system was able to analyze this information to better predict which perovskites recipe would work best.

“Based on these results, we synthesized new solar cell material composites and measured their properties to test the validity of the model,” Thomas said. “It found that the measured properties match very well with the predicted values.”

While the researchers have yet to develop their own sprayable solar cells, they have laid out important research that others can now use to develop their own materials. Those other researchers had better hurry, though.

“Our next goal is to make new material compositions that can make highly stable solution-processible solar cells based on our predictions,” Thomas said. “Our intention is to make highly flexible solar cells by spray-coating techniques.”

Luke Dormehl
I'm a UK-based tech writer covering Cool Tech at Digital Trends. I've also written for Fast Company, Wired, the Guardian…
Scientists are using A.I. to create artificial human genetic code
Profile of head on computer chip artificial intelligence.

Since at least 1950, when Alan Turing’s famous “Computing Machinery and Intelligence” paper was first published in the journal Mind, computer scientists interested in artificial intelligence have been fascinated by the notion of coding the mind. The mind, so the theory goes, is substrate independent, meaning that its processing ability does not, by necessity, have to be attached to the wetware of the brain. We could upload minds to computers or, conceivably, build entirely new ones wholly in the world of software.

This is all familiar stuff. While we have yet to build or re-create a mind in software, outside of the lowest-resolution abstractions that are modern neural networks, there are no shortage of computer scientists working on this effort right this moment.

Read more
A.I. teaching assistants could help fill the gaps created by virtual classrooms
AI in education kid with robot

There didn’t seem to be anything strange about the new teaching assistant, Jill Watson, who messaged students about assignments and due dates in professor Ashok Goel’s artificial intelligence class at the Georgia Institute of Technology. Her responses were brief but informative, and it wasn’t until the semester ended that the students learned Jill wasn’t actually a “she” at all, let alone a human being. Jill was a chatbot, built by Goel to help lighten the load on his eight other human TAs.

"We thought that if an A.I. TA would automatically answer routine questions that typically have crisp answers, then the (human) teaching staff could engage the students on the more open-ended questions," Goel told Digital Trends. "It is only later that we became motivated by the goal of building human-like A.I. TAs so that the students cannot easily tell the difference between human and A.I. TAs. Now we are interested in building A.I. TAs that enhance student engagement, retention, performance, and learning."

Read more
Can A.I. solve one of the oldest mysteries of linguistics?
can ai solve lost languages heiroglyphics

There are many things that distinguish humans from other species, but one of the most important is language. The ability to string together various elements in essentially infinite combinations is a trait that “has often in the past been considered to be the core defining feature of modern humans, the source of human creativity, cultural enrichment, and complex social structure,” as linguist Noam Chomsky once said.

But as important as language has been in the evolution of humans, there is still much we don’t know about how language has evolved. While dead languages like Latin have a wealth of written records and descendants through which we can better understand it, some languages are lost to history.

Read more