Power/Performance Bits: Dec. 20

Stamping with electronic ink

Engineers at MIT fabricated a stamp made from carbon nanotubes that is able to print electronic inks onto rigid and flexible surfaces.

The team’s stamping process should be able to print transistors small enough to control individual pixels in high-resolution displays and touchscreens, said A. John Hart, associate professor of contemporary technology and mechanical engineering at MIT. “There is a huge need for printing of electronic devices that are extremely inexpensive but provide simple computations and interactive functions.”

The stamp was porous, to allow a solution of “ink” nanoparticles to flow uniformly through the stamp onto the surface and avoid the problems conventional rubber stamp printing has of ink spilling over the borders or uneven prints that lead to incomplete circuits.

To make the stamps, the researchers grew the carbon nanotubes on a surface of silicon in various patterns, including honeycomb-like hexagons and flower-shaped designs. They coated the nanotubes with a thin polymer layer to ensure the ink would penetrate throughout the nanotube forest and the nanotubes would not shrink after the ink was stamped. Then they infused the stamp with a small volume of electronic ink containing nanoparticles such as silver, zinc oxide, or semiconductor quantum dots.

MIT researchers have fabricated a stamp made from forests of carbon nanotubes that is able to print electronic inks onto rigid and flexible surfaces. (Source: Sanha Kim and Dhanushkodi Mariappan/MIT)

The researchers fixed each stamp onto a platform attached to a spring, which they used to control the force used to press the stamp against the substrate.

“This would be a continuous industrial process, where you would have a stamp, and a roller on which you’d have a substrate you want to print on, like a spool of plastic film or specialized paper for electronics,” Hart said. “We found, limited by the motor we used in the printing system, we could print at 200 millimeters per second, continuously, which is already competitive with the rates of industrial printing technologies. This, combined with a tenfold improvement in the printing resolution that we demonstrated, is encouraging.”

After stamping ink patterns of various designs, the team tested the printed patterns’ electrical conductivity. After annealing the designs after stamping, the printed patterns were highly conductive, and could serve as high-performance transparent electrodes.

The team plans to pursue the possibility of fully printed electronics, as well as integration of 2D materials such as graphene.

Doping organic PV films

Researchers at the Georgia Institute of Technology, the University of California at Santa Barbara, Kyushu University in Japan, and the Eindhoven University of Technology developed a new technique for p-type electrical doping in organic semiconductor films. The process would replace a more complex technique that requires vacuum processing.

The new process consists of immersing thin films of organic semiconductors and their blends in polyoxometalate (PMA and PTA) solutions in nitromethane for a brief time, at room temerature. The diffusion of the dopant molecules into the films during immersion leads to efficient p-type electrical doping over a limited depth of 10 to 20 nanometers from the surface of the film. The p-doped regions show increased electrical conductivity and high work function, reduced solubility in the processing solvent, and improved photo-oxidation stability in air.

Close-up of a polymer film on a glass substrate before immersion in a polyoxometalte solution to electrically dope the film over a limited depth. (Source: Christopher Moore/Georgia Tech)

By simplifying the production of organic solar cells, the new processing technique could allow fabrication of solar cells in areas of Africa and Latin America that lack capital-intensive manufacturing capabilities, said Felipe Larrain, a Ph.D. student at Georgia Tech.

“Our goal is to further simplify the fabrication of organic solar cells to the point at which every material required to fabricate them may be included in a single kit that is offered to the public,” Larrain said. “The solar cell product may be different if you are able to provide people with a solution that would allow them to make their own solar cells. It could one day enable people to power themselves and be independent of the grid.”

Organic solar cells have been studied in academic and industrial laboratories for several decades and have experienced a continuous and steady improvement in their power conversion efficiency with laboratory values reaching 13%, compared to around 20% for commercial silicon-based cells. Though polymer-based cells are currently less efficient, they require less energy to produce than silicon cells and can be more easily recycled at the end of their lifetime.

Beyond solar cells, the doping technique could be more broadly used in other areas of organic electronics, noted Ph.D. researcher Wen-Fang Chou. “With its simplicity, this is truly a promising technology offering adjustable conductivity of semiconductors that could be applied to various organic electronics, and could have huge impact on the industry for mass production.”

Building safer batteries with AI

Using techniques adapted from artificial intelligence and machine learning, Stanford University researchers identified 21 solid electrolytes that could act as an alternative to the flammable liquid electrolytes used in lithium-ion batteries.

“The main advantage of solid electrolytes is stability,” said Austin Sendek, a doctoral candidate in applied physics at Stanford. “Solids are far less likely to blow up or vaporize than organic solvents. They’re also much more rigid and would make the battery structurally stronger.”

Despite years of laboratory trial and error, researchers have yet to find an inexpensive solid material that performs as well as liquid electrolytes at room temperature.

Instead of randomly testing individual compounds, the team turned to AI and machine learning to build predictive models from experimental data. They trained a computer algorithm to learn how to identify good and bad compounds based on existing data, which the team spent more than two years gathering.

“The number of known lithium-containing compounds is in the tens of thousands, the vast majority of which are untested,” Sendek said. “Some of them may be excellent conductors. We developed a computational model that learns from the limited data we already have, and then allows us to screen potential candidates from a massive database of materials about a million times faster than current screening methods.”

The model used several criteria to screen promising materials, including stability, cost, abundance and their ability to conduct lithium ions and re-route electrons through the battery’s circuit.

“We screened more than 12,000 lithium-containing compounds and ended up with 21 promising solid electrolytes,” Sendek said. “It only took a few minutes to do the screening. The vast majority of my time was actually spent gathering and curating all the data, and developing metrics to define the confidence of model predictions.”

The researchers eventually plan to test the 21 materials in the laboratory to determine which are best suited for real-world conditions.