Bertoni working at the frontier of solar energy engineering
Above: The 2017 U.S. Frontiers of Engineering symposium hosted by the National Academy of Engineering brought together 100 young engineers from varied backgrounds to share their expertise and perspectives with colleagues from around the country. The goal was to help them develop research collaboration across engineering disciplines. Photograph courtesy of the National Academy of Engineering
A select group of 100 young engineers met in Hartford, Connecticut from September 25 to 27 for the 2017 U.S. Frontiers of Engineering, hosted by the National Academy of Engineering.
The gathering brought together young engineers between the ages of 35 and 45 whose expertise spans a range of engineering-related technical areas, perspectives and experiences in industry, academia and government.
The participants were nominated by fellow engineers to attend the conference. Among them was Mariana Bertoni, an assistant professor of electrical engineering in the Ira A. Fulton Schools of Engineering at Arizona State University.
Bertoni was one of four early-career research leaders to give a presentation as part the event’s session entitled “Energy Strategies to Power Our Future.” Each presented an overview and a roadmap of different aspects of the energy sphere — the future of the power grid, wind and solar energy, and wireless charging of electric devices.
“My talk in particular covered the progress of solar energy in the last decade, and where photovoltaics is going in terms of widespread implementation and integration,” Bertoni says.
She highlighted the use of data analytics and machine learning in the design of next next-generation solar materials.
Her talk detailed how solar materials research will be advanced through image analysis tools targeted to high-performance computing platforms have shown the ability to analyze high-resolution scanning and electron microscopy data in 2D in real time.
Such advances in high-resolution experimental imaging and high-performance computing will undoubtedly propel materials discovery and ultimately enable “materials by design.”
The first step toward full information recovery from high-resolution multifunctional imaging data is the adoption of big-data analytics, Bertoni says. This means implementation of dimensionality reduction, clustering techniques and statistical unsupervised learning.
“The meeting was an incredible experience, I got to share the frontiers of my work with incredibly smart engineers across disciplines,” It was a pleasure and an honor to be selected to speak at this venue,” she says.
“I have a broader view of other fields, like brain science or mega-tall buildings” Bertoni says. “I also acquired a different perspective on my own field. Many of the participants are eager to collaborate across disciplines and I’m sure great things will come out of this.”