Researchers make air-stable, ultrathin superconductors, for more scalable quantum devices

Super-thin superconducting materials, which are only one or a few atoms thick, have unique properties scientists can leverage to produce more compact, scalable, and efficient quantum devices. But these fragile materials degrade so rapidly in air that they are difficult to study or manufacture.

Now, researchers from MIT and elsewhere have discovered and harnessed a method to generate a large, uniform area of ultrathin superconducting material that remains stable in air. 

They “grow” the superconducting material, called niobium diselenide, underneath another atomically thin material, carbon-based graphene. The graphene layer protects the fragile superconductor from oxidation, while guiding it to grow in a smooth layer over a large wafer-scale area.

The researchers further integrated this air-stable superconductor into a superconducting microwave circuit. When tested, the material maintained its superconducting properties and exhibited high kinetic inductance, which is a resource for many quantum devices. 

In the long run, this advance could help miniaturize superconducting quantum computing hardware, as well as technologies like ultrasensitive quantum detectors for communications or cosmology.

“Emerging superconductors that are only a monolayer thick have a lot of potential. Thanks to our new process, they are no longer materials that can only be made at a very small scale. There are now exciting opportunities for scientists to study these materials, utilize them in circuits, and explore their practical applications,” says co-lead author Xudong Sheldon Zheng, a graduate student in the MIT Department of Electrical Engineering and Computer Science (EECS).

He is joined on the paper by co-lead authors Sameia Zaman SM ’24, an EECS graduate student, and Kenan Zhang, a recent postdoc in the MIT Research Laboratory of Electronics (RLE); corresponding authors William D. Oliver, the Henry Ellis Warren (1894) Professor of EECS and professor of physics, director of the Center for Quantum Engineering, and associate director of RLE; Joel Î-j. Wang, an assistant professor at New York University; and Jing Kong, the Jerry Mcafee (1940) Professor in Engineering at MIT and a member of RLE; as well as others at MIT and Lincoln Laboratory, Rice University, Yale University, and Pohang University in South Korea. The research appears today in Nature.

Powerful properties

Superconductors are materials that can conduct electricity without resistance, and they are essential for some types of quantum devices. 

Two-dimensional superconducting materials retain their superconducting properties despite being only a few atoms thick. These materials hold the promise to miniaturize superconducting circuitry.

Niobium diselenide, an ultrathin superconductor composed of a single, closely packed layer of niobium atoms sandwiched between a single layer of selenium atoms on either side, has a very high kinetic inductance, as members of the research team recently reported.

This enables the material to store a great deal of inductive energy in a very small area. Large kinetic inductance in a small form-factor is a desirable design element in many quantum devices. 

One commonly used approach to realizing a large kinetic inductance is to string together an array of devices called Josephson junctions.

If scientists could incorporate materials such as thin niobium diselenide with sufficiently large kinetic inductance into a quantum circuit, they could replace the large area of electronic junctions with a tiny piece of thin-film material, making the circuit more compact. But because niobium diselenide degrades rapidly in air, scientists have not been able to reliably fabricate devices at the wafer scale. Instead, they rely on exfoliation techniques that yield small flakes. Furthermore, researchers have struggled to grow material with uniform monolayer thickness. Consequently, it has been challenging to fully probe its properties or test it in practical applications.

“Typically, once we make the material and remove it from its inert environment, it immediately starts to oxidize and degrade, ultimately becoming damaged,” Zheng explains.

Scientists usually grow niobium diselenide by depositing chemical precursors onto a silicon dioxide substrate. Then they place another layer of two-dimensional material, like graphene or hexagonal boron nitride, on top to protect the fragile superconductor from air.

But such postgrowth protection presents a challenge. The superconductor begins to oxidize almost immediately after synthesis, degrading its properties before it is protected. Meanwhile, the protection process requires a stringent inert environment and delicate processing.

Mind the gap

The MIT researchers used a different tactic. They put the layer of graphene on top of the silicon dioxide substrate first. Then they deposited the precursors and grew the superconducting material in the tiny gap between the two layers.

“It took a long time for us to understand how the growth could happen underneath the graphene. Through collaboration and discussion, we eventually uncovered the mechanism for growing the material at the interface, and this solves a lot of problems and allows us to simplify our fabrication steps,” Zheng says.

The silicon dioxide substrate helps trap the precursors long enough for the crystal to begin forming, while the graphene layer allows them to move around easily and spread into a continuous monolayer.

The researchers used this technique to generate a perfectly smooth layer of niobium diselenide more than an inch in size.

“By carefully tuning the growth conditions, we can ensure the material grows between the layers in exactly the way we’ve designed,” Zheng says.

Even though the graphene is placed on top of the silicon dioxide, the weak adhesion between these materials leaves a gap between them less than 1 nanometer thick. The niobium diselenide grows only within that gap. Then, since it is already encapsulated by graphene, the researchers can safely remove it into the ambient environment without causing degradation.

Careful connections

The researchers also designed an oxidation-free transfer technique to peel the graphene-niobium diselenide structure from its growth substrate, building on prior work by members of the team.

Then, they developed a method to integrate the thin film into a quantum circuit without hampering the fragile superconductor or its properties.

“It is challenging to make a good electrical connection between this very thin material, which is only about 1 nanometer in thickness, and our electrodes, which are a few hundred nanometers in thickness,” Zaman says.

They carefully etch the side walls of the thin-film superconductor in a vacuum chamber, which preserves the smooth edge of the material. When they integrate the prepared niobium-graphene structure into a conventional superconducting circuit, it forms a reliable electrical connection. Importantly, the material maintained its superconducting properties and exhibited high kinetic inductance after clean room fabrication and integration into the circuit. This makes it particularly attractive for fabricating compact superconducting quantum devices and other quantum technologies.

Furthermore, the growth strategy is not limited to monolayer niobium diselenide. The researchers demonstrated that it can be extended to a broad family of monolayer quantum materials with diverse and technologically important properties.

In the future, the researchers aim to integrate these ultrathin superconducting materials into functional device architectures to enable the exploration of fundamental physics and the prototyping of quantum devices and other advanced technologies.

“We’ve taken a very good step toward exploring both the physics and the application side of this thin, monolayer superconductor, which we can now grow in wafer scale or in even larger areas. There are a lot of directions we can go in the future,” Zaman says.

This research was funded, in part, by the U.S. Army Research Office, the U.S. National Science Foundation, the Schlumberger Foundation, the U.S. Department of Energy, the U.S. Air Force Office of Scientific Research, the Semiconductor Research Corporation Center, the MIT Institute for Soldier Nanotechnologies, and the National Research Foundation of Korea. This work was carried out, in part, using MIT.nano facilities.

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Scientists unveil more than 600 new tissue models of human cancer

To develop new targeted treatments for cancer, scientists need tissue models that accurately represent the genetic and molecular traits of the cancer they’re studying. An international team led by researchers at MIT’s Koch Institute, the Broad Institute, the Dana-Farber Cancer Institute, the National Cancer Institute, and numerous other partnering institutions has developed nearly 700 new cancer models, derived from patient tumors, which they hope will aid in drug development. 

These cells, which represent 25 different types of cancer, are now available for cancer researchers around the world to use. The project is described in a new paper appearing today in Nature, with contributors from more than two dozen institutions.

The models are the result of a 10-year initiative, funded by the National Cancer Institute, to expand the number of patient-derived tissue models available. For most of these models, the researchers converted tumor cells into organoids — 3D cell cultures that can survive indefinitely and mimic the genetic and molecular features of the tumors that they originally came from.

This type of model could help researchers identify new drug targets and test potential new treatments for many more types of cancer.

“Since the sequencing of the human genome and the analysis of cancer genomes over the last 20 years, we have had many ideas about cancer targets, but we need experimental systems in the lab to validate those targets and launch drug discovery projects,” says Jesse Boehm, a research scientist at the Koch Institute and one of the senior authors of the study.

From tumors to organoids

The Human Cancer Models Initiative was launched in 2016, following the completion of the Cancer Genome Atlas, an effort to catalog the genomic alterations responsible for cancer growth. 

For the atlas project, researchers sequenced cancer cell samples from thousands of patients. That work revealed that the diversity of tumor genetic profiles was not fully captured by the roughly 1,000 patient-derived cancer cell lines that existed at the time.

“We realized that a thousand wasn’t enough, that the international community needed to invest in many more thousands to represent all cancers, all genotypes, all ethnicities,” Boehm says. “Most existing models come from European and Southeast Asian patients, and many rare cancers are missing.”

Funded by the National Cancer Institute and the United Kingdom’s Wellcome Trust, hundreds of scientists across dozens of institutions participated in obtaining patient samples and developing them into cell lines that could be used for research.

“It’s been an enormous initiative, and this Nature paper is the culmination of that 10-year swath of activity,” Boehm says.

More than 2,700 tumor samples were obtained from hospitals participating in the study, from patients who gave their permission for their cells to be used for research. These samples were collected by hospitals in the United States, the United Kingdom, and the Netherlands. 

“A resource of this scale depends on the kind of systematic effort that often happens behind the scenes,” says Mushriq Al-Jazrawe, scientific director of the High Throughput Sciences (HTS) platform at the Koch Institute and one of the lead authors of the study. “I’m especially grateful to the technical and scientific teams across the participating institutes whose careful, expert work turns patient tumor samples into well-characterized models and data that researchers everywhere can use with confidence.”

Most of these samples came from commonly seen cancers such as lung, liver, and pancreatic, but they also included about 150 rare types including tumors of the gallbladder and the small intestine.

To convert these samples into cells that can survive indefinitely in the lab, the researchers developed techniques for culturing the cells in specialized growth media with a scaffold that helps them grow into a 3D structure. Overall, the researchers were able to successfully convert about one-third of the patient samples that they received.

Most of these new models consist of organoids, which in some cases more closely mimic the structure of the tissue that the cells came from. Traditional cancer cell lines, which were developed beginning in the 1950s, exist as single layers of cells grown in a lab dish, while organoids consist of three-dimensional balls of cells embedded in a gelatin-like structure.

Once the organoids and cell lines were established, which can take up to a year, the researchers analyzed them to make sure that their genomic sequences, RNA expression, and epigenomic modifications closely matched those of the tumor cells that they were derived from.

Cancer vulnerabilities

All of the models developed as part of the HCMI were deposited at the American Type Culture Collection (ATCC), a nonprofit distributor of cell lines. Each model also has extensive data from the patient whose cells were used to start the cell line, including mutations that the patient inherited from their parents (germline mutations), and information on the cancer treatments they received.

Using these models, scientists should be able to perform much larger scale screens that could aid in drug development efforts. 

In another paper also appearing in Nature today, Broad Institute researchers reported that they were able to profile more than 300 of the new models using high-throughput genome-sequencing, RNA sequencing, and more than 100 with CRISPR loss-of-function screens. This enabled them to identify vulnerabilities in each model that could be targeted with new drugs.

These findings have been added to a resource known as the Cancer Dependency Map (DepMap), which now includes information on more than 2,000 types of cancer.

In another Nature companion paper, researchers at the Sanger Institute led an effort to characterize an additional 256 organoids developed through the HCMI project. 

Additionally, even though most aspects of the formal HCMI project are currently winding down, researchers hope to continue developing models derived from additional patient tumor samples, including more pediatric cancers and rare cancers.

“We now have about 2,000, but if we really want to represent all humans with cancer in our preclinical research, more work is needed. We have to invite patients to donate tissue to make research tools that the whole world can use,” Boehm says. “I think this will hopefully be not the end, but the beginning.”

“A major opportunity now is to carry the lessons of HCMI forward, so we can generate as much insight as possible from these precious tissue donations,” says Al-Jazrawe, who is also a researcher in the Broad Institute’s Cancer Program. “Here at HTS, we are continuing the work by developing methods to study patient-derived samples and models reproducibly and at scale, and by providing a platform for close collaboration with clinical and research teams.”

Other senior authors of the HCMI paper are Mathew Garnett of the Wellcome Sanger Institute, David Tuveson of Cold Spring Harbor Laboratory, Andrea Califano of Columbia University Vagelos College of Physicians and Surgeons, Paul Spellman of the University of California at Los Angeles, Keith Ligon of Dana-Farber Cancer Institute, Daniela Gerhard of the NCI Center for Cancer Genomics, and Louis Staudt of the NCI Center for Cancer Research.

In addition to Al-Jazrawe, the paper’s lead authors are Dina El-Harouni of the Broad Institute and Dana Farber, Seongmin Choi of Memorial Sloan Kettering Cancer Center, Merve Dede of the University of Texas MD Anderson Cancer Center, Toshinori Hinoue of the Van Andel Institute, Sean Misek of the Broad Institute and Dana-Farber, Heeju Hoh of the Institute of Systems Biology and the Columbia University Vagelos College of Physicians and Surgeons, and Luca Zanella of the Columbia University Vagelos College of Physicians and Surgeons. 

The research was funded primarily by the National Cancer Institute and the Wellcome Trust.

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These 3D-printed objects can tell you if they’re being used properly

Imagine a bottle of hazardous chemicals sitting on a laboratory shelf that changes its appearance to alert scientists that its lid is not properly secured, potentially preventing a dangerous spill.

A new 3D-printing system created by MIT researchers enables users to produce interactive objects like this chemical bottle, which change their appearance when they are pressed, slid, or turned, without the use of any internal electronics. 

Their system simplifies the process of designing and fabricating 3D objects with mechanically switchable surface appearances, enabling individuals without technical expertise to quickly generate dynamic everyday objects.

The design and fabrication system combines specially arranged optical layers with built-in mechanical parts so a single object can display different images or patterns. The resulting objects change appearance based on user interactions like screwing on a lid or flipping a switch, and they can be manufactured in one pass on a multimaterial 3D printer.

The system can be used to fabricate a range of interactive objects that don’t require fragile electronic circuits, such as adaptable warning signs that could withstand foul weather or dynamic packaging that alerts users if fasteners came loose during shipping. 

The end-to-end system could also streamline rapid prototyping of adaptable objects for artistic, architectural, and engineering applications.

“With our system, an object can tell you whether you are using it properly, without the need for sensors or any complicated electronics. The interactive display is mechanical, so you can create a self-contained, multistate, interactive device that a user can control very intuitively,” says Yunyi Zhu, a graduate student in the MIT Department of Electrical Engineering and Computer Science (EECS) and lead author of a paper on this platform.

Her co-authors include Dingning Cao, an MIT undergraduate; Jeremy Mrzyglocki, a graduate student at the Technical University of Munich; Stefanie Mueller, an associate professor in EECS and the Department of Mechanical Engineering at MIT and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL); and Narjes Pourjafarian, a postdoc at Northeastern University. The research will be presented at the ACM Symposium on User Interface Software and Technology.

Mechanically switchable surfaces

Many interactive products rely on screens and electronics to change their appearance. But if these dynamic objects are exposed to water or harsh chemicals, or are squished, twisted, or pressed with great force, the fragile electronics could be damaged.

On the other hand, conventional methods that use surface optics to change an object’s appearance without electronics typically utilize static labels like stickers or curved lenses to create different visual effects based on where the user is looking, limiting interactivity.

To simplify the process of making dynamic, interactive objects that don’t require electronics, the MIT researchers developed a system that automatically converts a user’s design into a 3D printer-ready model of an object with a mechanically switchable surface appearance.   

Their design, ShiftLens, creates switchable appearances by combining two optical layers on an object’s surface. It places a layer of special lenses over an underlying, patterned backplane. 

The object displays different visual states based on the motion between the two layers. 

The lens layer contains an array of tiny lenticular lenses, curved lenses which steer light differently depending on the viewing angle of the user. The pattern layer contains strips of images that correspond to multiple appearances of the object surface.

When the user shifts the lens layer, different parts of the backplane come into view. The lenses magnify these parts of the backplane image, changing the surface appearance.

“The biggest challenge in this project was to make sure all moving parts align. We need to make sure that the optical effect, mechanical linkages, and computational graphics align with one another,” Zhu says.

A straightforward system

To simplify the design process, the researchers created a user-friendly tool that does all this work behind the scenes. 

It automatically generates a ShiftLens structure based on a few inputs, including images of the visual states the user wants to achieve and the desired shape and curves of the object.

“Another challenge is to communicate to users who are not familiar with optics or mechanical structures and let them specify and achieve what they have in mind,” she says.

The researchers thought carefully about how to communicate the limitations of the ShiftLens design tool to the user. For instance, ShiftLens is not compatible with all objects, since it requires a shifting motion to enable interaction between the two layers.

Users can either incorporate a ShiftLens into the design of an object that has this type of interaction built-in, like the rotation of a lipstick tube, or integrate an actuation mechanism like a switch, knob, or roller. 

“With ShiftLens, users can control what an object looks like while they are using it,” she says.

The researchers showcased how someone might use ShiftLens by fabricating a range of interactive objects.

In one experiment, they created a chemical bottle that turns green and displays a check mark when the cap is securely tightened, but turns red and displays an exclamation mark when it is loose. For another demonstration, they fabricated a tic-tac-toe game with squares that can display a red X, a blue O, or no letter, depending on which direction a user turns a knob.

While the ShiftLens tool is designed to simplify the fabrication process for makers, the techniques could be scaled up for commercial and industrial applications, Zhu says. For instance, it could be used to design piping that can change its appearance to identify a damaged connection that is causing a leak.

“The leaking sink in my apartment would be a lot easier to fix if it could tell me where the leak was coming from,” Zhu adds.

The researchers want to explore additional applications in future work. They also plan to develop an algorithm that can generate a ShiftLens structure with fewer user inputs, simplifying the design process. In addition, they plan to enhance the design tool so users can incorporate a wider variety of actuation mechanisms.

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Past is prologue for geopolitical developments

The end of World War II marked a turning point for global empires; weakened by years of conflict, European nations could no longer hold onto their colonies. A wave of independence followed. This shift was fueled by local anti-colonial activists, the heavy economic toll of the war, and the strategic interests of the new global superpowers, the United States and the Soviet Union. Yet these transformations also raised an important question: How would these developing nations approach economic independence?

In his latest book, “Constructing Economic Nationalisms in Brazil and India” (Cambridge University Press, 2026), MIT Department of Urban Studies and Planning (DUSP) Associate Professor Jason Jackson tracks how two of these emerging nations developed different brands of economic nationalism from the late 1800s through the early post-World War II era.

The timing of the book is prescient. The rise of globalization in the 1980s, 1990s, and 2000s led many observers to declare nationalism a relic of the past. Yet economic nationalism has returned with a vengeance over the past few years, making clear the importance of understanding this phenomenon in its historical and contemporary forms. 

Although the idea of economic nationalism is commonly used, it is often misleadingly defined as “anti-foreign,” says Jackson. Instead, Jackson’s research provides a more nuanced definition of how Brazil and India regulated foreign investment after World War II to advance their standing in the industrialized world.

“Brazil and India typically come to mind if one were to ask which countries in Latin America or Asia pursued a lot of nationalist policies, but their approaches to economic nationalism manifested in very different ways,” says Jackson. 

The two countries offer compelling comparisons of how economic policies and development strategies can diverge. Especially during the postwar era, both countries were driven to boost national income and secure economic sovereignty, and both aggressively pursued rapid industrialization. In addition to these shared goals, both countries faced the same basic hurdles: limited access to finance and technology that were deemed essential to building a modern industrial nation.

Jackson argues that it was Brazil’s and India’s colonial past and early independence experiences that formed their diverse approaches to economic growth. He selected two industries — oil and automobiles — to contrast their foreign direct investment policies. By focusing on the colonial experience, he explains how economic policies were born from a mix of cultural identity and material reality.

Jackson’s research relies on primary archival materials, including diplomatic correspondence between American officials in both countries and the U.S. Department of State. Because these officials served as boots-on-the-ground observers and intermediaries, their reports offer unique insights into the motivations of local business and government elites and the strategic concerns of American multinational firms.

“Nationalism manifested in very different ways in both places,” says Jackson. “In Brazil, I found that what was really salient and drove the parameters of economic nationalism was tied to the idea of protecting their natural resources. There was a strong belief that Brazil was very resource-rich and that outsiders — from neighboring countries to global powers — wanted its resources.”

This view was exemplified by oil. The link between anti-colonialism and oil in Brazil dates to the 19th century, beginning with the struggle between landed elites and the imperial court over subsoil property rights. By 1923, this sentiment was so strong that a law was proposed to ban oil concessions to foreigners. Notably, this law occurred before any oil had even been discovered.

By contrast, Brazilians were much less concerned about foreign ownership and control of other areas of industrial production such as manufacturing. To establish their automobile industry, they actively encouraged foreign firms to enter Brazil and to be the dominant partner in joint ventures, with local companies with Brazilian firms playing a more supportive, and often explicitly subordinate, role.

In India, the policies for the development of the petroleum sector and automobile manufacturing were completely reversed. 

Long before the British had arrived in India or the Industrial Revolution began, India was a global leader in textiles. Their rich artisanal history is defined by centuries-old expertise in weaving and dyeing — skills that made Indian fabrics highly sought-after for generations. 

Jackson argues that Indian economic nationalists strongly believed that British “free trade” economic policies toward the Indian colony decimated this age-old industry. “Free trade,” says Jackson, “derailed India from its natural path towards industrialization from the perspective of Indian nationalists. They saw the British as having enforced a trading system that brought in cheap manufactured goods from industrial sites such as Lancashire and Manchester in North West England and undermined artisanal production in India. In fact, many nationalists thought India would have ‘naturally’ had its own industrial revolution had the British never arrived.” 

After winning independence, Indian nationalist elites were determined to address this colonial-era policy structure that had favored British capital. With a “manufacturing” mindset to grow its economic base, foreign automobile firms were restricted from having majority ownership or managerial control of companies in the emerging automobile industry in India. In fact, General Motors, which had been operating in India since the 1920s, was forced out of India in the post-war years, both for their failure to do “real” manufacturing (GM simply imported “complete knock-down kits” that were easily assembled with hand tools, rather than doing “real” manufacturing in the country) and because the government was intent on allowing domestic firms to flourish. 

With oil production, however, Indians did not harbor concerns of foreign control or foreign multinationals taking the lead in extracting India’s petroleum. Despite explicitly recognizing oil multinationals as potential instruments of neo-imperial control, they allowed British and American oil companies to establish dominant positions. 

For Jackson, the biggest takeaway from comparing these two countries and the directions they took to achieve economic independence is that to understand contemporary geopolitics, it's “crucially important” to understand nationalism.

“Up until recently, many scholars thought that economic nationalism was a thing of the past. Yet we now live in a world where it’s fairly undeniable that nationalism is a force,” says Jackson. “In this context, there’s a tension between those that want to retain the kind of liberal, global international order of a few years ago, while there are others pushing for a global economy that is more nationally centered and regionally organized. We see this kind of battle playing out in a variety of ways between the European Union, Russia, China, and the United States.

“If you want to understand today’s complex and ever-shifting geopolitical environment, particularly from the perspective of people in other parts of the world, it’s useful to be able to understand how they interpret the actions of the current global powers. One of the things we can take directly from this book is that we can understand how different kinds of nationalisms shape the ways in which people make sense of not just historical developments or things that have happened in the past, but contemporary geopolitical developments. Together, these help us to assess the present and to imagine possible futures.” 

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Reframing leadership as a design problem

When Nicholas de Monchaux became head of the Department of Architecture at the School of Architecture and Planning (SA+P) in 2020, he stepped into an unusual set of leadership conditions. He had been due to start in July 2020. Instead, a springtime visit to Cambridge, Massachusetts, coincided with the first Covid-19 lockdowns, and he found himself taking on the role earlier than planned — several months before faculty, students, and staff were able to gather in the same room.

As he concludes his tenure as head of the department before becoming dean of the University of California at Berkeley’s College of Environmental Design, de Monchaux reflects on a period of disruption that became an opportunity to strengthen the department’s infrastructure and advance new models for architectural education and research: “One of the key accomplishments of my time as head of the department has involved finding ways to teach one of MIT’s most physical and collaborative subjects remotely, while keeping the community together and rebuilding our studio culture once we were back on campus,” he says. 

Engaging complexity

The questions that have motivated de Monchaux’s research became central to the challenge of leading the department. As an architect and design theorist, his work draws on the science of adaptive complex systems to examine how design can shape resilient forms of organization under changing conditions.

His first book, “Spacesuit: Fashioning Apollo,” argues that the design of the Apollo spacesuit succeeded through continual adaptation across materials, manufacturing practices, and institutional networks, rather than through engineering optimization alone. His subsequent book, “Local Code: 3,659 Proposals About Data, Design, and the Nature of Cities,” shifts this inquiry from the body to the city, using geospatial data to show how thousands of marginal city-owned vacant lots could collectively support new forms of ecological and civic infrastructure, replacing top-down master planning with coordinated, site-specific interventions. If the impacts of the pandemic could be characterized as an emergent complex system at the scale of the body, the city, the planet — then leadership could be framed as a design problem.

De Monchaux’s understanding of design in relation to complexity science is influenced by his long-standing engagement with the Santa Fe Institute, where he serves as external faculty alongside researchers in the natural sciences, social sciences, and humanities. His instinct for combining multiple forms of knowledge can be traced back to MIT — he spent formative years here, where his father, John de Monchaux, served as dean of SA+P from 1981 to 1992. “I was shaped by the ethos of curiosity at MIT,” he says. “Not just when it comes to questions of science and technology, but also those of art, design, and culture.”

Paradox and works in progress

That way of thinking becomes especially relevant in the context of climate change. According to the U.N. Environment Program, the construction and operation of buildings account for almost 40 percent of global greenhouse gas emissions, an even larger share when urbanization, transportation, and the wider built environment are taken into account. For architects, this presents a paradox: The systems they work within have contributed substantially to the problems they now seek to solve.

“Over the past six years, our department has focused on two fundamental climate-related challenges,” says de Monchaux. “One is how to build differently through new approaches to circularity and material reuse. The other is how to make our social, cultural, and physical systems more resilient.”

Those priorities find expression in the Climate Studios, a research and teaching initiative nestled under the Option Studios (course number 4.154) that brings together faculty members — including architects, engineers, and historians — to collaborate with students on impact-driven research projects related to climate across multiple years of integrated research and pedagogy. 

“The studios reorganize teaching in the department because students aren’t just working on speculative exercises, they’re working on real issues,” says de Monchaux. “Likewise, the studios reorganize research by allowing faculty to benefit from the boundless energy and imagination of our design students.”

The Climate Studios are part of a wider constellation of climate action initiatives in collaboration with the MIT Department of Urban Studies and Planning (DUSP). One example is a collaboration with DUSP and outgoing Department Head Chris Zegras, toward creating an MIT Civilian Climate Corps. Including seminars and workshops on community-focused design for MIT and its neighbors, and student-staffed work on circular material use, the initiative served as an incubator for the MIT Farm. Other projects at different stages of development were presented in the exhibition “Climate Work: Un/Worlding the Planet,” the department’s exhibition at the 2025 Venice Architecture Biennale, curated by de Monchaux alongside incoming department head Ana Miljački and exhibition designer Calvin Zhong ’18, MA ’24, MCP ’24. The exhibition embodied its own principles of circularity: The modular display tables, fabricated in Venice, were designed for reuse, and have since been installed as worktables in the department’s forthcoming home, the Metropolitan Storage Warehouse (the Met) — a space designed, like the exhibition, to invite continual experimentation. 

Building connections

The transformation of the Met has provided another opportunity for de Monchaux to think about architecture as a process of adaptation and collaboration. Having previously worked at Diller Scofidio + Renfro, the architecture firm engaged for the renovation project, he brought a unique perspective to the process, acting as “a translator between two different languages.” Recognizing the shared culture of experimentation that linked the architecture firm and the department, he advocated for a more radical approach to the renovation, pushing the boundaries of what might be expected from an institutional building. 

“It was important that the building remain open-ended and a little raw, because there’s a long tradition at MIT of students and faculty shaping their own studios and spaces,” he explains.

While de Monchaux is proud of the initiatives that took shape during his tenure, as a scholar of complex systems he knows better than to claim ownership over any single project. He describes both architecture and administration as acts of organization and rearrangement, evolving the work of predecessors and making way for those who follow.

One of the clearest examples is the department’s collaboration with Tuskegee University, which will be carried forward by Miljački. The Robert R. Taylor Project builds on a relationship dating back to 1893, when MIT’s first Black graduate and the nation’s first professionally trained Black architect left Cambridge to design much of Tuskegee’s campus, playing an influential role in defining the university’s approach to architectural education. De Monchaux worked closely with Kwesi Daniels, head of architecture at Tuskegee, to establish an exchange program connecting students and faculty through complementary forms of expertise, from the study of historic preservation at Tuskegee to digital fabrication and entrepreneurship at MIT. 

“A relationship that was purely symbolic has now become part of the fabric of the two institutions, expanding access to different programs and ways of teaching,” says de Monchaux. 

Invisible infrastructure 

Less visible, but equally consequential, is the impact of strengthening the department’s underlying social and physical infrastructure. During de Monchaux’s tenure, this has included expanding student governance and community forums, increasing minimum fellowship support for MArch graduate students from 50 to 90 percent of tuition, earning accreditation for the department’s professional degree in architecture, and ensuring that every MArch student has access to a department-provided workstation in studio.

“What we’re really talking about is unlocking the latent curiosity and passion of every person in the department, providing the infrastructure that allows them to accomplish what they wouldn’t be able to do otherwise,” says de Monchaux. 

That statement resonates with an idea he put forth in a 2023 essay for MIT Technology Review, which argued for a return to the roots of the word “design.” Successful designers, he proposed, “reshape not just objects, but also the culture and institutions that create them.” And so, if leadership is a design problem, the goal is to create the conditions for continually new and productive outcomes. The infrastructures built during this period — physical, academic, and social — provide a strong foundation for the leadership of de Monchaux’s colleague and successor, “the incredibly capable and visionary Ana Miljački.”

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Solving the solvent problem

Lithium-ion batteries are the leading choice in today’s electric vehicle and battery energy storage system industries, but they contain a number of critical minerals — including lithium, cobalt, nickel, and graphite — that are considered essential for economic and national security reasons, and therefore vulnerable to supply chain disruptions. As renewable energy, electrified infrastructure, and high-power digital technologies continue to grow, there is an increasing need for energy storage systems that are low-cost, resource-abundant, and capable of fast charging and discharging. 

That need, among other reasons, has motivated a group of researchers — based at MIT and led by Ju Li, the Carl Richard Soderberg Professor of Power Engineering in the departments of Nuclear Science and Engineering (NSE) and Materials Science and Engineering — to develop complementary energy storage solutions. 

The team is looking, in particular, at sodium-metal batteries, which offer several attractive features. Sodium is about 1,000 times more abundant than lithium and, pound for pound, about one-hundredth the cost. A key challenge, however, is that sodium metal is highly reactive, making it difficult for these batteries to achieve both long-term stability and fast cycling. 

A new paper in the journal Joule — written by 15 members of the MIT team and published online this week — shows how this dilemma can be addressed by finding the right electrolyte for this battery system.

Electrolytes behaving badly

An electrolyte is one of three main components of a battery, along with the negative electrode (the anode) and the positive electrode (the cathode). The electrolyte acts like the “blood” of the battery, allowing electrically charged ions to move between the two electrodes. “The electrolyte is supposed to just transmit those ions,” explains Li. “It’s supposed to be an ion conductor.” But unfortunately, most electrolytes get involved in unwanted chemical reactions with the electrodes, which can greatly undermine battery stability.

The consequences of these “side reactions” can be severe, says Weiyin Chen, a postdoc in NSE and one of four lead authors of the Joule paper. Insoluble compounds produced during the reactions can build up on the electrodes, creating a barrier that blocks ion transport and can eventually cause the battery to fail. 

Until recently, Chen says, no electrolyte used in sodium-metal batteries was fully stable against these unwanted reactions at both the anode and cathode, even though such stability is essential for rechargeable batteries to achieve a long cycle life. An initial breakthrough occurred in 2021, when the Li group and their collaborators identified a “sulfonamide” molecule — consisting of sulfur, oxygen, and nitrogen atoms — that, when used as a solvent, “is magically stable at both electrodes in lithium batteries,” according to Li. This molecule is known as DMTMSA. 

Building on that discovery, Li and his colleagues set out to see if related molecules could improve sodium batteries. The goal was not only to maintain stability, but also to enable fast charging and discharging. If charging is too slow, it could take all night to recharge, and if discharging is too slow, the battery cannot deliver much power when needed.

How did the solvent cross the road?

Chen explains the idea with an analogy: Suppose you need to cross a street jam-packed with pedestrians, much like ions traveling from one electrode to another. “You can move more quickly through the crowd with a small backpack that is snug against your body, rather than dragging a bulky suitcase on wheels,” Chen says. 

A similar situation occurs in batteries: When sodium ions are surrounded by smaller solvents, they can move faster than when they are surrounded by larger, bulkier solvents. Faster ion transport enables more-rapid charging and discharging. The team’s goal, accordingly, was to identify solvent molecules that are small enough to improve ion transport while still maintaining electrolyte stability.

There is, however, a complicating factor — a trade-off to be addressed: Faster ion transport often comes at the expense of electrolyte stability. Many highly conductive electrolytes react more easily with the electrodes, shortening battery life. Fortunately for their plan, Li says, “reducing the size of solvents provides a new pathway to overcome this trade-off.” 

The question then becomes how to find a smaller solvent that has other desirable properties. The idea they adopted is to look for molecules that are “congeneric,” says Li, “meaning that they belong to a similar family and are molecularly similar.” In particular, they searched for molecules related to DMTMSA, hoping to find candidates that were smaller but could retain the stability that made DMTMSA so promising.

Chia-Wei Hsu, an MIT PhD student in materials science and engineering, created an AI-guided algorithm, which designed 100,000 candidate molecules on his computer within 24 hours. Hsu then narrowed down the pool to 200 candidates by applying a set of technical criteria — including similarity in shape to DMTMSA and comparable electronic properties. Twenty-seven representative candidates covering the full range of possibilities were selected for experimental tests. 

“We tested them all under the same conditions to make it a fair, head-to-head competition,” Chen says. A clear winner emerged, a solvent called DMFSA, which was both the smallest and the best.

Small is beautiful

This work, claims Jinhyuk Lee, an associate professor of materials engineering at McGill University who is not part of the study, “addresses one of the most persistent challenges in battery research: improving battery performance at high charging and discharging rates without sacrificing long-term stability. By carefully tailoring the size of solvent molecules, the authors demonstrate a new design strategy that could enable lower-cost, higher performance batteries.” 

The group is not done. A new search is underway to find an even better solvent. This time, the approach is similar, but DMFSA (rather than the larger DMTMSA molecule) serves as the starting point. Chen believes the new solvents they are uncovering could eventually lead to rechargeable sodium-metal batteries that combine low-cost, abundant materials with fast charging and high-power performance, opening the door to broader energy storage applications.

The overriding goal of this work, the authors emphasize, is not only to advance sodium batteries. It’s also to introduce a new approach to electrolyte design that uses solvent size and molecular similarity as the key guideposts. Viewing the research in this light, sodium-metal batteries serve as a model system for demonstrating a more general design principle.

“Because the concept is broadly applicable,” Lee comments, “its impact could extend well beyond sodium batteries and influence the design of a wide range of future energy storage technologies.”

This work was supported, in part, by a National Research Foundation of Korea grant funded by the government of Korea government, as well as U.S. National Science Foundation graduate research fellowship. The characterization equipment used in this project is partly from the MIT.nano Characterization Facilities. 

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The benefits of medical AI assistance vary based on user expertise

A one-size-fits-all approach likely isn’t the best strategy when designing artificial intelligence systems that assist users in disease diagnosis.

A new study by researchers at MIT and elsewhere found that, while AI assistance generally improved the accuracy of non-experts and clinicians in diagnosing skin diseases, AI explainability methods had different impacts depending on the users’ knowledge level. 

Explainable AI methods help users know when to trust a model’s predictions by describing or validating the model’s decision-making. For instance, a model might use a heat map to highlight image regions that were most important in its diagnosis or a large language model (LLM) to explain the prediction in plain language.

In this study, researchers tested non-experts and primary care providers in skin disease diagnosis, with and without the help of different explainable AI systems. 

They found that non-experts’ diagnostic accuracy improved, but it was largely due to deference to the AI system. Non-experts trusted LLM-based explanations whether they were right or wrong, and found explanations more convincing when they were vague or generic.

By contrast, clinicians were not tripped up by incorrect AI assistance and performed best when given only a model’s prediction, with no accompanying explanation. 

“Good AI systems can improve performance in some health settings, but this has to be balanced carefully with algorithmic deference that can lead to more error. We know that both AI and explainability methods can engage automation bias in humans, and this anchoring effect is something that must be accounted for when we design AI systems,” says Marzyeh Ghassemi, an associate professor in MIT’s Department of Electrical Engineering and Computer Science (EECS), a member of the Institute for Medical Engineering and Science, and a principal investigator at the Laboratory for Information and Decision Systems and the Abdul Latif Jameel Clinic for Machine Learning in Health.

“These findings are important as patients increasingly turn to AI to help with their health care. Our findings show that those with the least medical knowledge are most likely to be led astray when explainable AI models give an erroneous output,” says Roxana Daneshjou, a co-author and assistant professor of biomedical data science and dermatology at Stanford University.

These results underscore the importance of building AI systems with users in mind and of developing explainability methods that encourage critical thinking rather than overreliance on the model, the researchers say.

“It’s getting obvious that we cannot just assume a good AI will solve all problems. We need to pay careful attention to the users who will be using the AI system, because the same explanation can help an expert and mislead a beginner. Often the people who could benefit most from AI are the ones most likely to be led astray by it, so how we present a recommendation matters as much as whether it’s correct,” says lead author Orson Xu, an assistant professor in the Department of Biomedical Informatics at Columbia University.

Ghassemi, Xu, and Daneshjou are joined on the paper by many authors, including MIT graduate student Haoran Zhang, undergraduate Reina Wang, and Luis Soenksen PhD ’20, a research affiliate at the Jameel Clinic, along with clinicians and researchers. A description of the work appears today in Nature Medicine.

Exploring explanations

Several FDA-approved AI interfaces are being used to help clinicians identify skin conditions in medical images, as a way to streamline early diagnosis. In addition to providing a prediction of whether disease is present in the image, these tools often use one of several methods that explain the model’s decision-making.

At the same time, non-experts can perform digital diagnosis on their own using AI-powered search engines that predict skin diseases based on user prompts. These systems often use LLMs to explain the model’s prediction in simpler terms.

The researchers explored the effects and potential benefits of these explainable AI tools on primary care physicians and non-experts in dermatological disease detection. They tested users by showing them medical images plus an AI prediction of skin disease, employing different explainable AI approaches. 

These approaches included: an AI prediction and confidence level with no explanation, a method that provides similar images to reinforce its prediction, a heat map-based approach that highlights important image regions, and an LLM that explains the model’s reasoning in plain language.

Non-experts were tasked with deciding whether an image of a skin mole was cancerous, with and without the help of explainable AI. Clinicians were given the more challenging task of providing a differential diagnosis of dermatological disease.

The researchers found that all explainable AI approaches improved the accuracy of non-experts, mostly because the tools helped users diagnose non-cancerous moles. 

In addition, when they employed a fairness-constrained model designed to combat bias against darker skin tones, the system significantly improved accuracy and reduced diagnostic disparities based on skin tone.

“But the reason non-expert users are better is because they are more reliant on the models. When the model is wrong, it hurts performance more than it helps performance when the model is right. We were just able to train very good AI models for this setting,” Ghassemi says.

This deference effect is largest with LLM explanations, and users were more confident about their wrong answers when aided by an LLM.

On the other hand, clinicians were resilient to incorrect AI explanations and, of all the explainability methods, LLMs boost their accuracy the least.

“It really comes down to how each group uses the explanation. A clinician already has a diagnosis in mind and checks the AI against their own training, so a bad explanation gets caught. Meanwhile, a non-expert can use that exact same explanation to form an opinion in the first place, so a plausible, confident-sounding rationale can pull them toward the wrong answer. The same tool ends up being an asset for one user and a liability for another,” Xu says.

Overcoming the deference effect

When the researchers dug deeper, they found that users who were most deferential to AI assistance were the worst performers on the task without the help of AI. 

They also found that the time at which users were presented with AI explanations influenced their behavior. If an explanation is given first, before the user can perform the diagnosis on their own, they tend to become more deferential to the model.

In addition, AI systems outperformed humans when the presentation of disease was subtle, but humans performed much better if there are atypical symptoms or unrelated features in an image.

Taken together, these results indicate that explainable AI can cause overreliance on models and lead users to blindly follow AI recommendations even when they are wrong. 

Rather than using LLMs to generate more detailed explanations, it might be more effective to force users to give a diagnostic hypothesis first, then provide an AI-based suggestion to highlight other possible conditions for consideration. 

“We really want AI to improve creativity and either upskill or fill in gaps where users are missing subtle presentations. Otherwise, we risk engaging automation bias and then, when the model is wrong, users can’t recover,” Ghassemi says. 

This research was funded, in part, by the National Science Foundation, Schmidt Sciences, the National Bureau of Economic Research, and Columbia University.

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