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    New tool makes generative AI models more likely to create breakthrough materials

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    The artificial intelligence models that turn text into images are also useful for generating new materials. Over the last few years, generative materials models from companies like Google, Microsoft, and Meta have drawn on their training data to help researchers design tens of millions of new materials.But when it comes to designing materials with exotic quantum properties like superconductivity or unique magnetic states, those models struggle. That’s too bad, because humans could use the help. For example, after a decade of research into a class of materials that could revolutionize quantum computing, called quantum spin liquids, only a dozen material candidates have been identified. The bottleneck means there are fewer materials to serve as the basis for technological breakthroughs.Now, MIT researchers have developed a technique that lets popular generative materials models create promising quantum materials by following specific design rules. The rules, or constraints, steer models to create materials with unique structures that give rise to quantum properties.“The models from these large companies generate materials optimized for stability,” says Mingda Li, MIT’s Class of 1947 Career Development Professor. “Our perspective is that’s not usually how materials science advances. We don’t need 10 million new materials to change the world. We just need one really good material.”The approach is described today in a paper published by Nature Materials. The researchers applied their technique to generate millions of candidate materials consisting of geometric lattice structures associated with quantum properties. From that pool, they synthesized two actual materials with exotic magnetic traits.“People in the quantum community really care about these geometric constraints, like the Kagome lattices that are two overlapping, upside-down triangles. We created materials with Kagome lattices because those materials can mimic the behavior of rare earth elements, so they are of high technical importance.” Li says.Li is the senior author of the paper. His MIT co-authors include PhD students Ryotaro Okabe, Mouyang Cheng, Abhijatmedhi Chotrattanapituk, and Denisse Cordova Carrizales; postdoc Manasi Mandal; undergraduate researchers Kiran Mak and Bowen Yu; visiting scholar Nguyen Tuan Hung; Xiang Fu ’22, PhD ’24; and professor of electrical engineering and computer science Tommi Jaakkola, who is an affiliate of the Computer Science and Artificial Intelligence Laboratory (CSAIL) and Institute for Data, Systems, and Society. Additional co-authors include Yao Wang of Emory University, Weiwei Xie of Michigan State University, YQ Cheng of Oak Ridge National Laboratory, and Robert Cava of Princeton University.Steering models toward impactA material’s properties are determined by its structure, and quantum materials are no different. Certain atomic structures are more likely to give rise to exotic quantum properties than others. For instance, square lattices can serve as a platform for high-temperature superconductors, while other shapes known as Kagome and Lieb lattices can support the creation of materials that could be useful for quantum computing.To help a popular class of generative models known as a diffusion models produce materials that conform to particular geometric patterns, the researchers created SCIGEN (short for Structural Constraint Integration in GENerative model). SCIGEN is a computer code that ensures diffusion models adhere to user-defined constraints at each iterative generation step. With SCIGEN, users can give any generative AI diffusion model geometric structural rules to follow as it generates materials.AI diffusion models work by sampling from their training dataset to generate structures that reflect the distribution of structures found in the dataset. SCIGEN blocks generations that don’t align with the structural rules.To test SCIGEN, the researchers applied it to a popular AI materials generation model known as DiffCSP. They had the SCIGEN-equipped model generate materials with unique geometric patterns known as Archimedean lattices, which are collections of 2D lattice tilings of different polygons. Archimedean lattices can lead to a range of quantum phenomena and have been the focus of much research.“Archimedean lattices give rise to quantum spin liquids and so-called flat bands, which can mimic the properties of rare earths without rare earth elements, so they are extremely important,” says Cheng, a co-corresponding author of the work. “Other Archimedean lattice materials have large pores that could be used for carbon capture and other applications, so it’s a collection of special materials. In some cases, there are no known materials with that lattice, so I think it will be really interesting to find the first material that fits in that lattice.”The model generated over 10 million material candidates with Archimedean lattices. One million of those materials survived a screening for stability. Using the supercomputers in Oak Ridge National Laboratory, the researchers then took a smaller sample of 26,000 materials and ran detailed simulations to understand how the materials’ underlying atoms behaved. The researchers found magnetism in 41 percent of those structures.From that subset, the researchers synthesized two previously undiscovered compounds, TiPdBi and TiPbSb, at Xie and Cava’s labs. Subsequent experiments showed the AI model’s predictions largely aligned with the actual material’s properties.“We wanted to discover new materials that could have a huge potential impact by incorporating these structures that have been known to give rise to quantum properties,” says Okabe, the paper’s first author. “We already know that these materials with specific geometric patterns are interesting, so it’s natural to start with them.”Accelerating material breakthroughsQuantum spin liquids could unlock quantum computing by enabling stable, error-resistant qubits that serve as the basis of quantum operations. But no quantum spin liquid materials have been confirmed. Xie and Cava believe SCIGEN could accelerate the search for these materials.“There’s a big search for quantum computer materials and topological superconductors, and these are all related to the geometric patterns of materials,” Xie says. “But experimental progress has been very, very slow,” Cava adds. “Many of these quantum spin liquid materials are subject to constraints: They have to be in a triangular lattice or a Kagome lattice. If the materials satisfy those constraints, the quantum researchers get excited; it’s a necessary but not sufficient condition. So, by generating many, many materials like that, it immediately gives experimentalists hundreds or thousands more candidates to play with to accelerate quantum computer materials research.”“This work presents a new tool, leveraging machine learning, that can predict which materials will have specific elements in a desired geometric pattern,” says Drexel University Professor Steve May, who was not involved in the research. “This should speed up the development of previously unexplored materials for applications in next-generation electronic, magnetic, or optical technologies.”The researchers stress that experimentation is still critical to assess whether AI-generated materials can be synthesized and how their actual properties compare with model predictions. Future work on SCIGEN could incorporate additional design rules into generative models, including chemical and functional constraints.“People who want to change the world care about material properties more than the stability and structure of materials,” Okabe says. “With our approach, the ratio of stable materials goes down, but it opens the door to generate a whole bunch of promising materials.”The work was supported, in part, by the U.S. Department of Energy, the National Energy Research Scientific Computing Center, the National Science Foundation, and Oak Ridge National Laboratory. More

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      Developing materials for stellar performance in fusion power plants

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      When Zoe Fisher was in fourth grade, her art teacher asked her to draw her vision of a dream job on paper. At the time, those goals changed like the flavor of the week in an ice cream shop — “zookeeper” featured prominently for a while — but Zoe immediately knew what she wanted to put down: a mad scientist.When Fisher stumbled upon the drawing in her parents’ Chicago home recently, it felt serendipitous because, by all measures, she has realized that childhood dream. The second-year doctoral student at MIT’s Department of Nuclear Science and Engineering (NSE) is studying materials for fusion power plants at the Plasma Science and Fusion Center (PSFC) under the advisement of Michael Short, associate professor at NSE. Dennis Whyte, Hitachi America Professor of Engineering at NSE, serves as co-advisor.On track to an MIT educationGrowing up in Chicago, Fisher had heard her parents remarking on her reasoning abilities. When she was barely a preschooler she argued that she couldn’t have been found in a purple speckled egg, as her parents claimed they had done.Fisher didn’t put together just how much she had gravitated toward science until a high school physics teacher encouraged her to apply to MIT. Passionate about both the arts and sciences, she initially worried that pursuing science would be very rigid, without room for creativity. But she knows now that exploring solutions to problems requires plenty of creative thinking.It was a visit to MIT through the Weekend Immersion in Science and Engineering (WISE) that truly opened her eyes to the potential of an MIT education. “It just seemed like the undergraduate experience here is where you can be very unapologetically yourself. There’s no fronting something you don’t want to be like. There’s so much authenticity compared to most other colleges I looked at,” Fisher says. Once admitted, Campus Preview Weekend confirmed that she belonged. “We got to be silly and weird — a version of the Mafia game was a hit — and I was like, ‘These are my people,’” Fisher laughs.Pursuing fusion at NSEBefore she officially started as a first-year in 2018, Fisher enrolled in the Freshman Pre-Orientation Program (FPOP), which starts a week before orientation starts. Each FPOP zooms into one field. “I’d applied to the nuclear one simply because it sounded cool and I didn’t know anything about it,” Fisher says. She was intrigued right away. “They really got me with that ‘star in a bottle’ line,” she laughs. (The quest for commercial fusion is to create the energy equivalent of a star in a bottle). Excited by a talk by Zachary Hartwig, Robert N. Noyce Career Development Professor at NSE, Fisher asked if she could work on fusion as an undergraduate as part of an Undergraduate Research Opportunities Program (UROP) project. She started with modeling solders for power plants and was hooked. When Fisher requested more experimental work, Hartwig put her in touch with Research Scientist David Fischer at the Plasma Science and Fusion Center (PSFC). Fisher eventually moved on to explore superconductors, which eventually morphed into research for her master’s thesis.For her doctoral research, Fisher is extending her master’s work to explore defects in ceramics, specifically in alumina (aluminum oxide). Sapphire coatings are the single-crystal equivalent of alumina, an insulator being explored for use in fusion power plants. “I eventually want to figure out what types of charge defects form in ceramics during radiation damage so we can ultimately engineer radiation-resistant sapphire,” Fisher says.When you introduce a material in a fusion power plant, stray high-energy neutrons born from the plasma can collide and fundamentally reorder the lattice, which is likely to change a range of thermal, electrical, and structural properties. “Think of a scaffolding outside a building, with each one of those joints as a different atom that holds your material in place. If you go in and you pull a joint out, there’s a chance that you pulled out a joint that wasn’t structurally sound, in which case everything would be fine. But there’s also a chance that you pull a joint out and everything alters. And [such unpredictability] is a problem,” Fisher says. “We need to be able to account for exactly how these neutrons are going to alter the lattice property,” Fisher says, and it’s one of the topics her research explores.The studies, in turn, can function as a jumping-off point for irradiating superconductors. The goals are two-fold: “I want to figure out how I can make an industry-usable ceramic you can use to insulate the inside of a fusion power plant, and then also figure out if I can take this information that I’m getting with ceramics and make it superconductor-relevant,” Fisher says. “Superconductors are the electromagnets we will use to contain the plasma inside fusion power plants. However, they prove pretty difficult to study. Since they are also ceramic, you can draw a lot of parallels between alumina and yttrium barium copper oxide (YBCO), the specific superconductor we use,” she adds. Fisher is also excited about the many experiments she performs using a particle accelerator, one of which involves measuring exactly how surface thermal properties change during radiation.Sailing new pathsIt’s not just her research that Fisher loves. As an undergrad, and during her master’s, she was on the varsity sailing team. “I worked my way into sailing with literal Olympians, I did not see that coming,” she says. Fisher participates in Chicago’s Race to Mackinac and the Melges 15 Series every chance she gets. Of all the types of boats she has sailed, she prefers dinghy sailing the most. “It’s more physical, you have to throw yourself around a lot and there’s this immediate cause and effect, which I like,” Fisher says. She also teaches sailing lessons in the summer at MIT’s Sailing Pavilion — you can find her on a small motorboat, issuing orders through a speaker.Teaching has figured prominently throughout Fisher’s time at MIT. Through MISTI, Fisher has taught high school classes in Germany and a radiation and materials class in Armenia in her senior year. She was delighted by the food and culture in Armenia and by how excited people were to learn new ideas. Her love of teaching continues, as she has reached out to high schools in the Boston area. “I like talking to groups and getting them excited about fusion, or even maybe just the concept of attending graduate school,” Fisher says, adding that teaching the ropes of an experiment one-on-one is “one of the most rewarding things.”She also learned the value of resilience and quick thinking on various other MISTI trips. Despite her love of travel, Fisher has had a few harrowing experiences with tough situations and plans falling through at the last minute. It’s when she tells herself, “Well, the only thing that you’re gonna do is you’re gonna keep doing what you wanted to do.”That eyes-on-the-prize focus has stood Fisher in good stead, and continues to serve her well in her research today. More

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      Simple superconducting device could dramatically cut energy use in computing, other applications

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      MIT scientists and their colleagues have created a simple superconducting device that could transfer current through electronic devices much more efficiently than is possible today. As a result, the new diode, a kind of switch, could dramatically cut the amount of energy used in high-power computing systems, a major problem that is estimated to become much worse. Even though it is in the early stages of development, the diode is more than twice as efficient as similar ones reported by others. It could even be integral to emerging quantum computing technologies.

      The work, which is reported in the July 13 online issue of Physical Review Letters, is also the subject of a news story in Physics Magazine.

      “This paper showcases that the superconducting diode is an entirely solved problem from an engineering perspective,” says Philip Moll, director of the Max Planck Institute for the Structure and Dynamics of Matter in Germany. Moll was not involved in the work. “The beauty of [this] work is that [Moodera and colleagues] obtained record efficiencies without even trying [and] their structures are far from optimized yet.”

      “Our engineering of a superconducting diode effect that is robust and can operate over a wide temperature range in simple systems can potentially open the door for novel technologies,” says Jagadeesh Moodera, leader of the current work and a senior research scientist in MIT’s Department of Physics. Moodera is also affiliated with the Materials Research Laboratory, the Francis Bitter Magnet Laboratory, and the Plasma Science and Fusion Center (PSFC).

      The nanoscopic rectangular diode — about 1,000 times thinner than the diameter of a human hair — is easily scalable. Millions could be produced on a single silicon wafer.

      Toward a superconducting switch

      Diodes, devices that allow current to travel easily in one direction but not in the reverse, are ubiquitous in computing systems. Modern semiconductor computer chips contain billions of diode-like devices known as transistors. However, these devices can get very hot due to electrical resistance, requiring vast amounts of energy to cool the high-power systems in the data centers behind myriad modern technologies, including cloud computing. According to a 2018 news feature in Nature, these systems could use nearly 20 percent of the world’s power in 10 years.

      As a result, work toward creating diodes made of superconductors has been a hot topic in condensed matter physics. That’s because superconductors transmit current with no resistance at all below a certain low temperature (the critical temperature), and are therefore much more efficient than their semiconducting cousins, which have noticeable energy loss in the form of heat.

      Until now, however, other approaches to the problem have involved much more complicated physics. “The effect we found is due [in part] to a ubiquitous property of superconductors that can be realized in a very simple, straightforward manner. It just stares you in the face,” says Moodera.

      Says Moll of the Max Planck Institute, “The work is an important counterpoint to the current fashion to associate superconducting diodes [with] exotic physics, such as finite-momentum pairing states. While in reality, a superconducting diode is a common and widespread phenomenon present in classical materials, as a result of certain broken symmetries.”

      A somewhat serendipitous discovery

      In 2020 Moodera and colleagues observed evidence of an exotic particle pair known as Majorana fermions. These particle pairs could lead to a new family of topological qubits, the building blocks of quantum computers. While pondering approaches to creating superconducting diodes, the team realized that the material platform they developed for the Majorana work might also be applied to the diode problem.

      They were right. Using that general platform, they developed different iterations of superconducting diodes, each more efficient than the last. The first, for example, consisted of a nanoscopically thin layer of vanadium, a superconductor, which was patterned into a structure common to electronics (the Hall bar). When they applied a tiny magnetic field comparable to the Earth’s magnetic field, they saw the diode effect — a giant polarity dependence for current flow.

      They then created another diode, this time layering a superconductor with a ferromagnet (a ferromagnetic insulator in their case), a material that produces its own tiny magnetic field. After applying a tiny magnetic field to magnetize the ferromagnet so that it produces its own field, they found an even bigger diode effect that was stable even after the original magnetic field was turned off.

      Ubiquitous properties

      The team went on to figure out what was happening.

      In addition to transmitting current with no resistance, superconductors also have other, less well-known but just as ubiquitous properties. For example, they don’t like magnetic fields getting inside. When exposed to a tiny magnetic field, superconductors produce an internal supercurrent that induces its own magnetic flux that cancels the external field, thereby maintaining their superconducting state. This phenomenon, known as the Meissner screening effect, can be thought of as akin to our bodies’ immune system releasing antibodies to fight the infection of bacteria and other pathogens. This works, however, only up to some limit. Similarly, superconductors cannot entirely keep out large magnetic fields.

      The diodes the team created make use of this universal Meissner screening effect. The tiny magnetic field they applied — either directly, or through the adjacent ferromagnetic layer — activates the material’s screening current mechanism for expelling the external magnetic field and maintaining superconductivity.

      The team also found that another key factor in optimizing these superconductor diodes is tiny differences between the two sides, or edges, of the diode devices. These differences “create some sort of asymmetry in the way the magnetic field enters the superconductor,” Moodera says.

      By engineering their own form of edges on diodes to optimize these differences — for example, one edge with sawtooth features, while the other edge not intentionally altered — the team found that they could increase the efficiency from 20 percent to more than 50 percent. This discovery opens the door for devices whose edges could be “tuned” for even higher efficiencies, Moodera says.

      In sum, the team discovered that the edge asymmetries within superconducting diodes, the ubiquitous Meissner screening effect found in all superconductors, and a third property of superconductors known as vortex pinning all came together to produce the diode effect.

      “It is fascinating to see how inconspicuous yet ubiquitous factors can create a significant effect in observing the diode effect,” says Yasen Hou, first author of the paper and a postdoc at the Francis Bitter Magnet Laboratory and the PSFC. “What’s more exciting is that [this work] provides a straightforward approach with huge potential to further improve the efficiency.”

      Christoph Strunk is a professor at the University of Regensburg in Germany. Says Strunk, who was not involved in the research, “the present work demonstrates that the supercurrent in simple superconducting strips can become nonreciprocal. Moreover, when combined with a ferromagnetic insulator, the diode effect can even be maintained in the absence of an external magnetic field. The rectification direction can be programmed by the remnant magnetization of the magnetic layer, which may have high potential for future applications. The work is important and appealing both from the basic research and from the applications point of view.”

      Teenage contributors

      Moodera noted that the two researchers who created the engineered edges did so while still in high school during a summer at Moodera’s lab. They are Ourania Glezakou-Elbert of Richland, Washington, who will be going to Princeton University this fall, and Amith Varambally of Vestavia Hills, Alabama, who will be entering Caltech.

      Says Varambally, “I didn’t know what to expect when I set foot in Boston last summer, and certainly never expected to [be] a coauthor in a Physical Review Letters paper.

      “Every day was exciting, whether I was reading dozens of papers to better understand the diode phenomena, or operating machinery to fabricate new diodes for study, or engaging in conversations with Ourania, Dr. Hou, and Dr. Moodera about our research.

      “I am profoundly grateful to Dr. Moodera and Dr. Hou for providing me with the opportunity to work on such a fascinating project, and to Ourania for being a great research partner and friend.”

      In addition to Moodera and Hou, corresponding authors of the paper are professors Patrick A. Lee of the MIT Department of Physics and Akashdeep Kamra of Autonomous University of Madrid. Other authors from MIT are Liang Fu and Margarita Davydova of the Department of Physics, and Hang Chi, Alessandro Lodesani, and Yingying Wu, all of the Francis Bitter Magnet Laboratory and the Plasma Science and Fusion Center. Chi is also affiliated with the U.S. Army CCDC Research Laboratory.

      Authors also include Fabrizio Nichele, Markus F. Ritter, and Daniel Z. Haxwell of IBM Research Europe; Stefan Ilićof Materials Physics Center (CFM-MPC); and F. Sebastian Bergeret of CFM-MPC and Donostia International Physics Center.

      This work was supported by the Air Force Office of Sponsored Research, the Office of Naval Research, the National Science Foundation, and the Army Research Office. Additional funders are the European Research Council, the European Union’s Horizon 2020 Research and Innovation Framework Programme, the Spanish Ministry of Science and Innovation, the A. v. Humboldt Foundation, and the Department of Energy’s Office of Basic Sciences. More