From left, Nathan Woodward, Aram Amassian and Tonhui Wang examine a microscope slide. The three wear white lab coats, and Wang, who is holding the slide, wears black gloves.

Integrating robotics and materials science to capture solar energy

Solar energy is key to fighting climate change, but it is hard to harness. In current solar panels, only 20% of the available energy is converted into electricity. A North Carolina State professor is leading the development of more efficient solar panel cells so that this renewable energy source can replace dwindling fossil fuels. At the same time, this work creates accessible ways to conduct research in STEM fields.

In the 2010s, Aram Amasyan, a professor in the Department of Materials Science and Engineering, has pioneered new processes by which materials can be coated using inks. these On site The experiments allow researchers to gather data about the function of the ink as it is being manufactured rather than being created. In this way, researchers can more accurately determine when and how to intervene to control the different properties of materials. The ink can be basically released closer to real time. Now, Amassian Laboratory is going like this On site Experiments using artificial intelligence and robotics to develop effective materials for solar panels.

“We need to move quickly and develop technologies faster than climate change is happening,” Amassian said. “To do this, we need to change the way we discover new materials, create new solutions and deploy new technologies.”

Multidisciplinarity is vital to Amassian’s work. His lab integrates electrical and computer engineering with materials science to develop artificially intelligent robots that aid in solar energy research. These robots automatically mix, apply and evaluate solutions that can better convert solar energy into electricity, accelerating the development of innovative materials.

“These problems we are trying to solve are really complex,” Amassian said. “At some point, they are beyond the capabilities of one person or one discipline and require data science.”

Tongwi “Tony” Wang, Ph.D. filter in Department of Materials Science and Engineeringand Nathan Woodward, Ph.D. student in Department of Electrical and Computer Engineering, is the driving force of this robotics initiative. Wang, who joined the Amassian Laboratory in 2018, developed the first iteration of robotic tools that generate large data sets for the structure and properties of solar materials. Woodward, who joined the lab in 2019, has advanced the lab’s capabilities by building robots that make decisions and perform certain tasks independently.

Woodward’s background in electrical engineering isn’t the only different perspective he brings to the materials science lab. As someone with muscular dystrophy, Woodward has had to face the challenges of living in a world that is hard to come by.

“People with disabilities are natural engineers because we have to solve problems every day,” he said.

Nathan Woodward holding a microscope slide coated with experimental solution.

In the process of automating their research process, Amassian, Wang, Woodward and the rest of the lab are creating methods that are less labor-intensive than current practices. The machines complete repetitive tasks the same way each time and record all the data. This means that scientists can spend less time mixing, drawing, painting and testing and more time and energy discovering and solving problems and innovating.

“We are excited to develop companions that help students and researchers become more productive in the lab,” Amassian said. “Today, we ask our Ph.D. Students and candidates do a lot of basic manual chores, mixing, and cleaning, from morning to evening. In the age of data, we are increasingly asking students to record everything they do in a database, which can be a huge time inconvenience.” By automating them in the lab, we can get a highly educated Ph.D. scientist and use more of their brains to solve a complex problem rather than these tasks.”

The team’s interdisciplinary focus helps its members grow as scientists and engineers. Woodward studied the intricacies of material handling while developing automated platforms. Wang learned more about software and data science as well as building on its foundations in materials science. Such collaboration could change the landscape of materials research.

“The way we think about these problems classically in materials science is by using trial and error,” Wang said. “But since moving towards automation and digitization, we have started using big-picture and planning data science approaches in our research. We can access a larger parameter space easily, and data is available in an instant. The use of robotics and artificial intelligence makes it possible to solve the most complex problems and helps us move towards A smarter life.

The tweezers pick up a microscopic slide that was in a machine.
Robots in Amassian’s lab can automatically mix, apply and evaluate solutions on materials.

The lab could have a greater impact beyond its contributions to materials science and solar energy. Woodward has first-hand demonstrated the challenges faced by people with physical disabilities, which extend to research laboratories. The two have worked to make Amassian’s lab more accessible, and hope that their efforts with robotics in the lab will pave the way for more accessible research opportunities across the board.

“There are very few people with disabilities in STEM fields to begin with, and that number is even lower than from bachelor’s to doctoral programs. This has potential for people with greater physical limitations than I have to,” Woodward said. I work with it in satisfactory careers in the sciences.”


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