A driver swipes her credit card at a gas pump. She fills her tank, starts her car, and then pulls next to a storm drain at the edge of the gas station. With a clear plastic hose in hand, she removes the gas cap and syphons out one-third of the gas that she just paid for. Down the drain.
That’s literally illegal. But, in effect, it happens every day on a global scale—not with gas but with food. “One-third of all food produced in the world is wasted,” says Fengqi You, Chemical and Biomolecular Engineering. “Some food spoils before it’s ever served. Some goes straight from a person’s plate into the garbage bin. A lot of food waste drops out of the nutrient cycle and winds up decomposing in landfills.”
Similar inefficiencies arise if an international shipping service doesn’t figure out the best way to route deliveries, or whenever a burst of sunshine on a cool day transforms a skyscraper into a greenhouse—right after the heating has kicked on. Even molecular-level inefficiencies in a chemical reaction can lead to significant losses when multiplied through an entire industrial or manufacturing process.
These scenarios offer opportunities for greater efficiency that You, as a systems engineer, has sought to address. He has learned to examine big processes as if under a microscope. Discovering the optimal solution to a complex problem is exactly the kind of challenge that motivates him. The potential benefits to society and our planet are huge.
1 + 1 > 2
“For the past several years, I have been pursuing multi-scale systems engineering,” You says. “We address problems ranging from molecular and materials design to climate change, using computing and systems technologies such as quantum computing and artificial intelligence.” He’s tracking down every missed opportunity, every point where energy leaks from a system, and finding ways to plug the hole.
At first, You’s work sounds outrageously abstract. How can a single person apply a single area of expertise to optimize a chemical reaction, a manufacturing process, and an entire food production ecosystem? The answer, You says, is collaboration: “I am always looking for opportunities where one plus one is greater than two.”
You is involved in an imposing constellation of distinct but related projects. “My appointment at the Argonne National Laboratory, after graduate school, was in the Mathematics and Computer Sciences Division, with a strong focus on energy and sustainability,” You says. “When I moved to Cornell, I became intrigued by many interesting challenges in food and agricultural systems that Cornellians are working on. My colleague Abe Stroock, Chemical and Biomolecular Engineering, introduced me to the digital agriculture community. Now my research addresses many aspects of smart manufacturing, digital agriculture, energy systems, and sustainability.”
“I am always looking for opportunities where one plus one is greater than two.”
“Dairy farms produce tons of manure. Poultry farms generate poultry litter. There are tons of food waste everywhere, from grocery stores, kitchens, and restaurants,” You says. “We call this organic waste: waste that’s composed of organic materials and often nutrient-rich. It’s becoming more and more of a problem.”
The disadvantages go beyond lost nutrients and energy. When organic waste isn’t fully utilized, it can wind up as runoff, polluting streams and other waterways.
You is contributing to several projects that, from various angles, try to turn the liabilities of organic waste into a benefit. His many collaborators in this field include Jefferson W. Tester, Chemical and Biomolecular Engineering, Kristan F. Reed, Animal Science, Xingen Lei, Animal Science, and Johannes Lehman, School of Integrative Plant Science, Soil and Crop Sciences—among many other Cornell researchers.
The fundamental idea is what You calls circular economy. “We are working together on technologies that can take poultry litter, manure, and all sorts of organic waste and transform them into value-added products, like biofuels or fertilizers that could be used to grow crops. We are looking for the chemical processes that best recapture and utilize those resources, improve efficiency, and minimize the outside energy required to keep food production going. That's the goal of circular economy: to close the nutrient cycle in food production and processing, reduce resource consumption, produce energy, and protect the watershed.”
“Our unique strength is our highly interdisciplinary team,” You adds. “We use systems analysis and optimization along with life cycle assessment, and then we couple all that with our specific areas of expertise.”
Liquid Crystal Sensors and Artificial Intelligence
You gets a strange gift every so often from Nicholas Abbott, Chemical and Biomolecular Engineering: thousands of tiny photographs that, when magnified, look like hazy Polaroids of abstract paintings by Rothko and De Kooning. The photos record the colorful responses of liquid crystal sensors to toxic gases such as chlorine, carbon monoxide, and ammonia.
You is creating a custom-made system of artificial intelligence (AI) especially designed to interpret these images. “Artificial intelligence started with something called pattern recognition,” You says. “These liquid crystals form a sort of pattern in response to various gases. For a person, detecting the pattern is extremely difficult and time-consuming, but it’s something that AI is very good at it.” Among the many possibilities, You’s collaboration with Abbott could lead to a small sensor, worn like a smart watch, to protect anyone working where toxic gases are a threat.
Because liquid crystals respond to many natural and artificial compounds—not just gases—they are a promising basis for a wide range of sensors. You and Abbott are also working on liquid crystal sensors that will detect amyloids, abnormal proteins associated with Alzheimer's and other neurodegenerative diseases. For another project, their target is microplastics—tiny plastic particles that pollute rivers and oceans and can have deleterious effects on marine life. You and Abbott are contributing to a multi-institutional effort to create a self-powered biological system that will capture microplastics in the ocean and break them down into harmless, biodegradable components.
The collaboration between You and Abbott is built on innovative algorithms—series of logical steps much like a flowchart or decision tree. Algorithms power the artificial intelligence that learns to recognize telltale markers in the colorful data from liquid crystals sensors. In fact, algorithms are key to nearly all of You’s efforts.
You’s expertise in algorithms and optimization has inspired a distinctively practical approach to quantum computing—a burgeoning field that has attracted a growing community of researchers at Cornell.
Quantum computing is in its infancy, but You’s lab has devised algorithms to make the most of quantum technology as it exists today. Despite the current limitations of quantum processors, they already outperform classic digital computers when it comes to certain tasks. “Quantum computers are good for discrete problems, where there is a limited menu of possible solutions,” You says. “But on their own, they can’t guarantee the best solution—what’s called the global optimum.”
You’s lab devised algorithms to maximize the capabilities of a quantum processor. The algorithms break computational tasks into smaller parts and feed to the quantum processor only the tasks that it does best. With this strategy, You has sidestepped one of quantum’s major limitations. “Our particular framework is unique,” he says. “After a sufficient number of iterations, it guarantees global optimality from a quantum processor. It’s a real breakthrough.”
The hybrid quantum-classic algorithms provide a broad platform for large data science problems that a classic computer might take decades or even lifetimes to solve—challenges such as optimization for more sustainable molecular and drug design, manufacturing processes, electric power systems, and supply chains.
Taking a broad view of his research, You says, “To these various projects, we bring artificial intelligence techniques. It’s just a fundamental game changer for everything. It’s interesting to see how software, hardware, theory, materials, physical science, and biology can blend together to come up with new technologies that can be applied to many, many things—from health-care diagnostics and novel proteins to environmental problems and safety, and on and on.”