A ����ԭ��-led center for optoelectronics — technologies that combine light and electronics — brings researchers from 14 universities across the U.S. together with the mission to develop new materials to transform information technology with light. This research has broad ranging applications, from enabling photorealistic virtual reality displays for telehealth calls, to secure, optical quantum communication links to ensure that data remains private on the internet.

Founded in 2021 as a , the , or NSF IMOD, has received a second round of funding from the NSF to continue its work for the next five years.

The research tackled by NSF IMOD is so interdisciplinary that it requires researchers from backgrounds such as chemistry, physics, engineering and materials science to work together.

“There’s still this idea that scientists go in their labs, put on their safety goggles and lab coats, and then work alone for hours at a time. The point of this center is to tackle problems that are too big for one scientist or even two or three to tackle by themselves,” said NSF IMOD director , UW professor of chemistry. “We have all these people from different disciplines working together to advance optoelectronics and semiconductor technology that we couldn’t do just as individual scientists.”

“Until our center came along, quantum dots were thought of as something you made in a beaker in a chemistry lab. And if you could paint them on a TV or phone display, that was great,” said Ginger, who is also the B. Seymour Rabinovitch Endowed Chair in Chemistry and the chief scientist at the UW . “But they weren’t something that you could put as a discrete component in an optoelectronic circuit. That’s something that we’ve proven you can do.”

With chemists, material scientists, mechanical engineers, chemical engineers, physicists and electrical engineers on the team, researchers at NSF IMOD created something unprecedented: a way to print quantum dots, . The team showed that they could strategically place quantum dots into specific cavities, which could one day be the building blocks for quantum communication, and possibly even quantum computing.

The team hopes to continue this research direction over the next five years, further refining quantum dots as well as the cavities the dots get placed into.

NSF IMOD’s interdisciplinary nature gets passed down to its students as well. One of the center’s main goals is to develop researchers into leaders in the fields of semiconductor and optoelectronic technology. Every summer, NSF IMOD trainees from different disciplines come together at the UW for in multiple disciplines. The students synthesize quantum dots, study single photons of light in UW’s , make quantum dots, and learn to calculate the electronic structures of advanced materials. The collaborations established during this course and throughout the NSF IMOD training program helps students graduate with the ability to work in complex, interdisciplinary teams.

Trainees also gain real-world experience in the form of internships at a variety of companies, including some of NSF IMOD’s industry and national lab partners. A partial list of NSF IMOD’s partners includes ; ; ; ; ; and More partner information can be found on .

“We’re already seeing our students get hired at everything from startup companies to large semiconductor firms for the exact skills they’re being trained for in the center,” Ginger said. “We’re really excited to see our students start taking important roles, and then eventually we hope they move into leadership roles in this space of commercializing new semiconductor materials.”

And it’s not just graduate students who benefit from NSF IMOD. The center hosts a program, and has programming for younger students as well. As part of their science communication training, NSF IMOD trainees become who can facilitate outreach events, such as at the Pacific Science Center. The team has also developed a for K-12 teachers to find lesson plans to use in their own classrooms.

“Just as the atomic structure of a quantum dot produces unique and exciting properties, the exceptionally interdisciplinary structure of NSF IMOD is enabling foundational science and technological innovations that would not otherwise be possible,” said , a program director in the NSF Directorate for Mathematical and Physical Sciences, which manages NSF IMOD.

Over the past five years, NSF IMOD has published 140 papers, hosted 36 undergraduate students through its REU program and hosted more than 85 outreach events.

“One day I hope that we’ll have photonic computing where we’re massively reducing the energy cost for computation by using a computing paradigm that’s based on the research we’re doing now,” Ginger said. “That’s the kind of thing that’s probably still a decade or more away. But that’s why the government invests in basic science now, because the basic science research of the materials today leads to technology that exists 15 years from now.”

NSF is expected to provide NSF IMOD $22 million over the five-year term of the award. The 14 academic institutions that make up NSF IMOD are the ����ԭ��; University of California, Berkeley; Columbia University; University of Chicago; Northwestern University; University of Pennsylvania; University of Maryland; Georgia Institute of Technology; University of Colorado Boulder; Arizona State University; Rice University; Lehigh University; City College of New York; and University of Maryland, Baltimore County.

In addition to Ginger, other UW faculty involved with NSF IMOD include , associate professor of physics and of electrical and computer engineering at the UW; , a UW professor of chemistry; , professor of electrical and computer engineering; , associate professor of mechanical engineering and of materials science and engineering, and technical director of the Washington Clean Energy Testbeds; and , professor of physics and of electrical and computer engineering. Fu chairs UW . Fu, Lin and Majumdar are faculty members with the UW . Cossairt, Fu, Lin, Majumdar and MacKenzie are member faculty at the Clean Energy Institute. Ginger, Fu, Lin, Majumdar and MacKenzie are faculty researchers with the UW .��

For more information, contact Ginger at dginger@uw.edu.

Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the U.S. National Science Foundation.

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Quantum materials are a class of exotic materials with special properties that are governed by rather than . Those properties — like , and unusual forms of magnetism — often originate in the tiny repeating patterns of atoms inside crystals, but through clever engineering they can be observed and controlled at a more human scale. Quantum materials are helping to power the quickly growing field of , and could find their way into future generations of energy-efficient electronics.��

Designing new materials from the atomic scale up, however, requires intense modeling and simulation. Some materials may appear ordinary when viewed as small clusters of atoms, yet reveal new and useful properties when their atomic building blocks repeat and interact over larger distances. Researchers must be able to accurately predict behaviors at large scales in order to find materials with practical applications — otherwise designing new materials is a slow and costly trial-and-error process.

In the past 50 years, supercomputers have helped materials scientists solve some of those thorny prediction problems, but two recent studies from the ����ԭ�� demonstrate how newer computing techniques can help researchers sniff out promising quantum materials to pursue. , published June 2 in the Proceedings of the National Academy of Sciences, shows how researchers can use artificial intelligence to simulate dozens of sheets of atoms stacked in intricate patterns, a process that produces complex and potentially useful quantum behaviors. , published June 8 in Nature Communications, shows how quantum computers can create a self-improving design loop by discovering new materials that could themselves be components of future quantum computers.��

“What is exciting is that AI and quantum computing are beginning to change not just what problems we can solve, but how we do research,” said , a UW associate professor of materials science and engineering and the senior author of both studies.

These two new tools — AI and quantum computing — are complementary in that they each excel at a different kind of simulation problem. With the right training, an AI model can act as a fast and relatively inexpensive surrogate of a supercomputer, extrapolating the behavior of huge material systems from a relatively small dataset. Cao and collaborators used this approach to stack virtual sheets of atoms on top of one another over and over — a process that created completely new phenomena that were absent on a smaller scale, but would have been impractical to model by traditional supercomputing. From there, researchers can try to make the most promising materials in the lab to prove out the simulations.

Quantum computers, on the other hand, are essentially powered by the same quantum phenomena — like entanglement — that Cao and other materials researchers want to study. Such phenomena can be difficult to simulate using traditional computers or AI systems, but quantum computers are naturally suited to the task. In the study, Cao and his team used a quantum computer to study an exotic phase of matter known as a .��

Moving forward, Cao and his team plan to further build out their datasets and eventually develop models that can simulate a much wider range of materials. They also hope to combine their AI and quantum computing systems into a more powerful and flexible hybrid tool.

“The next step is to bring these tools together,” Cao said. “We can use AI to guide quantum simulations, and quantum computers to generate new data and insights that improve AI models.”

“We are at the start of a new era,” said , UW professor and chair of materials science and engineering and co-author of both studies. “Our field is fundamentally changing. Things that were literally impossible a couple of years ago are now becoming routine. And we are only beginning to see what AI and quantum computing will make possible for quantum materials.”

was led by , a UW doctoral student of materials science and engineering. was led by , a UW doctoral student of physics. A complete list of authors is included with the studies.

The authors acknowledge the support of Amazon and the Department of Energy.

For more information, contact Cao at tingcao@uw.edu.

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Even on a campus like the ����ԭ��’s — home to particle accelerators, wave tanks and countless other bespoke pieces of equipment — the machinery in the stands out. Take the dilution fridge, a large, white, cylindrical device that can cool a small chamber to one hundredth of a kelvin above absolute zero — the coldest possible temperature in the universe.��

“This is the coldest fridge money can buy,” said , a UW assistant professor of electrical and computer engineering and the former director of the lab, which goes by the nickname QT3. “When it’s running, the chamber inside this device is about 100 times colder than outer space. At that temperature, it’s much easier to study and manipulate a material’s quantum properties.”

The lab also houses a photon qubit tabletop lab: a nondescript set of boxes, lasers and lenses that can demonstrate the “spooky” — a term scientists actually use — phenomenon known as quantum entanglement, where two particles appear to communicate instantaneously with each other despite being physically apart.

Or there’s the lab’s latest acquisition, the scanning tunneling microscope, which can image individual atoms within a solid material, allowing researchers to study the structure of materials at the smallest scales.

An interdisciplinary group of researchers has been marshalling resources and expertise to create QT3 for three years, and now, the lab is opening its doors as a unique one-stop shop resource for quantum researchers and educators at the UW.

“The idea of this lab is to improve access to quantum hardware,” Parsons said. “It’s rather hard to acquire equipment like this. And there are a lot of researchers that may have good ideas that they want to test, but don’t have the resources yet for their own equipment. So we’re inviting researchers, initially from across campus, but also from other universities and from industry, to come in and test their ideas. This can be a hub for quantum experts to share their ideas and collaborate.”

The lab also boasts hardware that can demonstrate known quantum principles and techniques, making it useful for students in quantum fields. In addition to the entanglement device, Parsons’ students developed a machine that can suspend charged particles — in this case, tiny grains of pollen — in midair using electric fields. Researchers use the same technique to trap single atoms and manipulate their quantum properties, making the lab’s ion-trapping machine good practice for more complex work.

Some students even work at the lab through an undergraduate staffing program, and have helped install instrumentation, write code to power equipment and build parts for custom microscopes. The program provides yet another avenue for students to get hands-on experience with unusual machinery and techniques.��

“Quantum mechanics is inherently counterintuitive, and that makes it a powerful teaching tool,” Parsons said. “In the QT3 lab, students will encounter systems where their everyday intuition breaks down, and they must rely on careful reasoning and experimentation instead. They learn how to debug when results don’t match expectations, how to test simple cases and how to build understanding about hardware step by step.”

The cosmically cold dilution fridge remains something of a centerpiece, even as the lab fills up with specialized equipment. The extreme environment within the device strips heat, light and other stray energy away from materials, allowing researchers to observe the peculiar quantum properties that remain. One such property is superposition, or the ability of a particle like an electron to maintain multiple mutually exclusive properties at the same time. Scientists use superposition to create a powerful, tiny piece of technology: a quantum bit, or qubit.��

“Traditional computers use bits, which can only be one or zero. A qubit, on the other hand, we can make one plus zero,” Parsons said. “It’s both at the same time, and only when we measure it do we find out which one it is. We can use this unusual property to build a new class of computers that excel at tasks like communications and encryption.”

QT3 is part of a collaborative effort to solidify UW as a leader in quantum research and applications. Most of the lab hardware was funded by a congressional earmark championed by Senator Maria Cantwell’s office. Departmental funding from across the College of Engineering and the College of Arts and Sciences helped rehab the lab space. The National Science Foundation provided seed funding for the instructional lab equipment.

The UW has also spent the past decade investing heavily in faculty with quantum expertise.

“Very few places have expertise across the full quantum stack, from materials up to algorithms,” said , a UW professor of physics and founder of QT3. “The UW has quantum faculty in electrical and mechanical engineering, physics, computer science, materials science and chemistry. Our faculty work on superconducting qubits, spin defects, photons, trapped ions, neutral atoms and topological qubits. Our advantage is the breadth of our investment.”

The lab is now available to researchers and students across the UW, and private companies are encouraged to reach out about partnering. Parsons has already used the lab to teach a graduate-level class in electrical and computer engineering for students who included employees from Boeing, Microsoft and quantum computing company IonQ. The lab is hiring for a full-time manager to maintain the equipment and help users make the most of the facility.��

“Here in academia, we can improve the building blocks for applied technologies like quantum computing, and then transfer those learnings to industry for further scaling,” Parsons said.

For more information, contact Parsons at mfpars@uw.edu.

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