$3M NSF grant to boost state-of-the-art solar manufacturing

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A new breed of semiconductors that could enable breakthroughs in solar cells and LEDs will benefit from cutting-edge manufacturing approaches, through a new project led by the University of Michigan.

Backed by $3 million from the National Science Foundation, it includes partners at the University of California, San Diego.

The effort combines hands-on work that improves upon the process of layer-by-layer deposition of semiconductor materials during production with an information-sharing approach that boosts cooperation between companies while protecting proprietary information and worker interests.

Halide perovskites, a class of materials that has been largely developed over the past decade, represent a promising new semiconductor material that can, among other things, boost solar cell efficiency. How promising? In less than 15 years of study, solar cells utilizing perovskites have increased their efficiency from 10% to 26%.

A photo of a Ph.D. student in a lab.
Clare Langhan, a Ph.D. student in mechanical engineering, spincoats thin-film perovskite samples in a glovebox, a key step in the creation of perovskite solar cells. (Photo by Marcin Szczepanski, College of Engineering)

“What’s amazing is the rapid rate of how perovskites have caught up to silicon,” said Neil Dasgupta, associate professor of mechanical engineering and of materials science and engineering in the College of Engineering, and the principal investigator of the grant.

“From a manufacturing standpoint, they can be less energy intensive to process. You can print them almost like an ink onto materials. They’re also very tuneable and customizable.”

This means perovskites can be optimized to capture different parts of the spectrum. It also means that they may ultimately be cheaper to produce.

Newer technologies like perovskite semiconductors inevitably pit companies against each other in a race to improve performance, streamline manufacturing and bring products to market. But pure competition slows progress down as companies perform similar experiments, covering the same ground.

The team led by U-M will seek to incorporate “federated learning” into the process — an approach that allows multiple entities to feed test results into a predictive model that helps all parties improve their manufacturing process while protecting their trade secrets.

“With something like perovskite manufacturing, you have different sources of data on factors such as the optimal processing parameters,” said Raed Al Kontar, assistant professor of industrial and operations engineering. “The question becomes how these different companies that are doing their own research can optimally collaborate and distribute the data they’re collecting through trial-and-error testing.”

Engineers at U-M, and their partners at UCSD, will conduct isolated experiments with perovskite semiconductors. Al Kontar will take data collected from each to build predictive models that forecast product quality and performance — helping to narrow down key parameters such as optimal pressure and temperature during manufacturing.

Pooling information in this way allows for faster development progress and reduces costs. The NSF considers it a form of “cyber manufacturing,” which “exploits opportunities at the intersection of computing and manufacturing with the potential to radically transform concepts of manufacturing.”

A photo of a layer of perovskite atop a semiconductor.
A layer of perovskite atop a semiconductor. (Marcin Szczepanski, College of Engineering)

It also couples with the College of Engineering’s people-first approach, ensuring that the solution will be relevant to those working in solar cell manufacturing.

“We’re thinking about how we can use technology to make smaller and medium-sized enterprises competitive in the production of these products,” said Chinedum Okwudire, professor of mechanical engineering and of integrative systems and design.

To do that, the team has Sarah Crane, research manager at U-M’s Economic Growth Institute, and Julie Hui, assistant professor of information in the School of Information, who studies how technology influences access to work and employment.

“Sarah and Julie will help us make sure we understand the landscape out there for those companies — what their needs are in this space, how we can bring them into this ecosystem and how we can help them create jobs,” Okwudire said.

In addition to Dasgupta, Okwudire, Al Kontar, Crane and Hui, U-M’s team includes Wei Lu, professor of mechanical engineering, who will lead efforts to model the mechanical and material aspects of the process.

Partners at UCSD include David Fenning, assistant professor of nanoengineering, who will lead the solar cell testing and design aspects of the project.

The four-year, $3 million grant is part of the NSF’s Future Manufacturing program supporting “fundamental research and education of a future workforce to overcome scientific, technological, educational, economic and social barriers in order to catalyze new manufacturing capabilities that do not exist today.”

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