Despite broad public interest in renewable power sources, only about 5% of U.S. energy comes from biofuels, produced from recently living matter such as trees, grasses and leftover crops.
Researchers at the University of Virginia School of Engineering and Applied Science and the U.S. Department of Energy’s Oak Ridge National Laboratory are combining their technological expertise in a way that may ultimately give the bioenergy sector a boost: helping scientists identify plant-based fuel sources that yield the highest energy with the least amount of work.
Xu Yi, a UVA assistant professor of electrical and computer engineering, leads a team of co-investigators who share his interest and expertise in the physics of sensing and imaging. Yi’s team includes Andreas Beling, a UVA professor of electrical and computer engineering; Ali Passian, a research scientist with Oak Ridge National Laboratory and an adjuct professor of physics; and Raphael Pooser, who leads the Oak Ridge National Laboratory quantum sensing team within the quantum information science group. Passian and Pooser are with Oak Ridge’s Computational Sciences and Engineering Division.
The U.S. Department of Energy awarded the team a $2.1 million, three-year grant from the agency’s biological and environmental research program. Team members aim to provide biofuels engineers with a new imaging system to observe the fermentation processes that convert biomass to energy at a molecular level without damaging or destroying the material.
To draw an analogy, just as the Webb telescope has surpassed Hubble in producing fine resolution images of distant galaxies, Yi’s team is designing a device that will image biomolecules at resolutions inconceivable with today’s microscopes.
“Biomaterials are no different from any other material,” Passian said. “When we take photos, we want to zoom very deeply into the cellular structure and the molecules that make up the cell. This is a grand challenge, to take better and better pictures of materials, to see how molecules are linked together and what they are made of, how they differ from their neighboring molecules and other cells.”
The team is working with a particular type of biomass material called tension wood, which contains higher glucan content and undergoes higher enzymatic conversion to fermentable sugars. Tension wood simply means that the branches bend or lean from the stem as a corrective growth process. Plant biologists grow tension wood by hanging different weights on some of the branches.
“You expect to see some molecular changes between wood that is weighted and wood that is free,” Passian said.
Passian specializes in a microscopy technique called Raman spectroscopy, which is a very good method for quantifying stress at a very small level.
“If I take a piece of wood, let’s say it’s from a poplar tree, I can use Raman spectroscopy to get its molecular signature,” Passian said. “If I then put that sample into a vice, to literally put a squeeze on it, and retest it, the molecular signature will have shifted. But the shift is so very small, we have a hard time differentiating between tension wood and normal wood.”
Passian and Pooser were aware that quantum science and quantum technologies are delivering better and better results in precision measurements.
“Giving us a chance to break the resolution barrier is one thing,” Passian said. “Achieving that resolution with a device that any biologist can use, without having to master quantum technologies or perform physics-based measurements, is quite another.”
Yi and members of his photonics lab had just the thing. They created a scalable quantum computing platform that drastically reduces the number of devices needed to achieve quantum speed on a photonic chip the size of a penny. Pooser was familiar with this path-breaking research, having earned his Ph.D. in physics with Olivier Pfister, a UVA professor of quantum optics and quantum information who champions Yi’s effort to transfer experiments from protected optics labs to field-compatible photonic chips.
Yi explained how quantum enhancement improves image resolution and makes measurements more accurate: “We have two light beams that are entangled in such a way that if we measure the difference between their two levels of intensity, we are able to see which one is brighter.”
One beam travels between a light generating source and the sample that is imaged; Beling’s detectors reside at both the sending and receiving end of the beam. The second beam is kept as a reference. Correlating the active and reference beam reduces distortion or noise, increasing the accuracy of the measurement.
Beling has developed photodiodes with world records in bandwidth and power. He was also the first to integrate highly efficient light detectors in a novel silicon nitride optical platform. Beling and Yi hope to replicate that feat, to integrate a quantum source and quantum detection.
“It’s hard because the quantum source and the quantum detector are made from different materials,” Yi said. “You actually have to go through a complicated process to bring them together without sacrificing quality.”
Not many institutions have experts in quantum detection and quantum source generation working side-by-side in the same department, which is one reason why photonics and quantum materials and devices are research strengths of UVA Engineering’s Department of Electrical and Computer Engineering.
Yi and Beling possess the know-how to modify and customize a quantum source and detector to make it easy to use in a biology lab. They envision a small photonic chip that can be plugged into a standard fiber-and-chip coupling system. Yi’s ambition is to bring the quantum source, the sensing area and the detector onto a single photonic chip — something no one else has done.
“To see any quantum enhancement in a bio measurement is difficult,” Yi said. “With our chip devices, if we can see any enhancement, we can call that a big success. Over the long term, if everything goes wonderfully perfect, we believe it may be possible to enhance sensitivity by three to ten times. There’s not a hard line set by physics; it’s an engineering problem that we can figure out.”
A research team led by Xu Yi, assistant professor of electrical and computer engineering at the University of Virginia School of Engineering and Applied Science, has earned a $2.1 million, three-year grant from the U.S. Dept. of Energy’s biological and environmental research program.
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