3D-printing platform rapidly produces complex electric machines

A broken motor in an automated machine can bring production on a busy factory floor to a halt. If engineers can’t find a replacement part, they may have to order one from a distributor hundreds of miles away, leading to costly production delays.

It would be easier, faster, and cheaper to make a new motor onsite, but fabricating electric machines typically requires specialized equipment and complicated processes, which restricts production to a few manufacturing centers.

In an effort to democratize the manufacturing of complex devices, MIT researchers have developed a multimaterial 3D-printing platform that could be used to fully print electric machines in a single step.

They designed their system to process multiple functional materials, including electrically conductive materials and magnetic materials, using four extrusion tools that can handle varied forms of printable material. The printer switches between extruders, which deposit material by squeezing it through a nozzle as it fabricates a device one layer at a time.

The researchers used this system to produce a fully 3D-printed electric linear motor in a matter of hours using five materials. They only needed to perform one post-processing step for the motor to be fully functional.

The assembled device performed as well or better than similar motors that require more complex fabrication methods or additional post-processing steps.

In the long run, this 3D printing platform could be used to rapidly fabricate customizable electronic components for robots, vehicles, or medical equipment with much less waste.

“This is a great feat, but it is just the beginning. We have an opportunity to fundamentally change the way things are made by making hardware onsite in one step, rather than relying on a global supply chain. With this demonstration, we’ve shown that this is feasible,” says Luis Fernando Velásquez-García, a principal research scientist in MIT’s Microsystems Technology Laboratories (MTL) and senior author of a paper describing the 3D-printing platform, which appears today in Virtual and Physical Prototyping.

He is joined on the paper by electrical engineering and computer science (EECS) graduate students Jorge Cañada, who is the lead author, and Zoey Bigelow.

More materials

The researchers focused on extrusion 3D printing, a tried-and-true method that involves squirting material through a nozzle to fabricate an object one layer at a time.

To fabricate an electric machine, the researchers needed to be able to switch between multiple materials that offer different functionalities. For instance, the device would need an electrically conductive material to carry electric current and hard magnetic materials to generate magnetic fields for efficient energy conversion.

Most multimaterial extrusion 3D printing systems can only switch between two materials that come in the same form, such as filament or pellets, so the researchers had to design their own. They retrofit an existing printer with four extruders that can each handle a different form of feedstock.

They carefully designed each extruder to balance the requirements and limitations of the material. For instance, the electrically conductive material must be able to harden without the use of too much heat or UV light because this can degrade the dielectric material.

At the same time, the best-performing electrically conductive materials come in the form of inks which are extruded using a pressure system. This process has vastly different requirements than standard extruders that use heated nozzles to squirt melted filament or pellets.

“There were significant engineering challenges. We had to figure out how to marry together many different expressions of the same printing method — extrusion — seamlessly into one platform,” Velásquez-García says.

The researchers utilized strategically placed sensors and a novel control framework so each tool is picked up and put down consistently by the platform’s robotic arms, and so each nozzle moves precisely and predictably.

This ensures each layer of material lines up properly — even a slight misalignment can derail the performance of the finished machine.

Making a motor

After perfecting the printing platform, the researchers fabricated a linear motor, which generates straight-line motion (as opposed to a rotating motor, like the one in a car). Linear motors are used in applications like pick-and-place robotics, optical systems, and baggage conveyers.

They fabricated the motor in about three hours and only needed to magnetize the hard magnetic materials after printing to enable full functionality. The researchers estimate total material costs would be about 50 cents per device. Their 3D-printed motor was able to generate several times more actuation than a common type of linear engine that relies on complex hydraulic amplifiers. 

“Even though we are excited by this engine and its performance, we are equally inspired because this is just an example of so many other things to come that could dramatically change how electronics are manufactured,” says Velásquez-García.

In the future, the researchers want to integrate the magnetization step into the multimaterial extrusion process, demonstrate the fabrication of fully 3D-printed rotary electrical motors, and add more tools to the platform to enable monolithic fabrication of more complex electronic devices.

This research is funded, in part, by Empiriko Corporation and the La Caixa Foundation.

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New study unveils the mechanism behind “boomerang” earthquakes

An earthquake typically sets off ruptures that ripple out from its underground origins. But on rare occasions, seismologists have observed quakes that reverse course, further shaking up areas that they passed through only seconds before. These “boomerang” earthquakes often occur in regions with complex fault systems. But a new study by MIT researchers predicts that such ricochet ruptures can occur even along simple faults.

The study, which appears today in the journal AGU Advances, reports that boomerang earthquakes can happen along a simple fault under several conditions: if the quake propagates out in just one direction, over a large enough distance, and if friction along the rupturing fault builds and subsides rapidly during the quake. Under these conditions, even a simple straight fault, like some segments of the San Andreas fault in California, could experience a boomerang quake.

These newly identified conditions are relatively common, suggesting that many earthquakes that have occurred along simple faults may have experienced a boomerang effect, or what scientists term “back-propagating fronts.”

“Our work suggests that these boomerang quakes may have been undetected in a number of cases,” says study author Yudong Sun, a graduate student in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS). “We do think this behavior may be more common than we have seen so far in the seismic data.”

The new results could help scientists better assess future hazards in simple fault zones where boomerang quakes could potentially strike twice.

“In most cases, it would be impossible for a person to tell that an earthquake has propagated back just from the ground shaking, because ground motion is complex and affected by many factors,” says co-author Camilla Cattania, the Cecil and Ida Green Career Development Professor of Geophysics at MIT. “However, we know that shaking is amplified in the direction of rupture, and buildings would shake more in response. So there is a real effect in terms of the damage that results. That’s why understanding where these boomerang events could occur matters.”

Keep it simple

There have been a handful of instances where scientists have recorded seismic data suggesting that a quake reversed direction. In 2016, an earthquake in the middle of the Atlantic Ocean rippled eastward, and then seconds later richocheted back west. Similar return rumblers may have occurred in 2011 during the magnitude 9 earthquake in Tohoku, Japan, and in 2023 during the destructive magnitude 7.8 quake in Turkey and Syria, among others.

These events took place in various fault regions, from complex zones of multiple intersecting fault lines to regions with just a single, straight fault. While seismologists have assumed that such complex quakes would be more likely to occur in multifault systems, the rare examples along simple faults got Sun and Cattania wondering: Could an earthquake reverse course along a simple fault? And if so, what could cause such a bounce-back in a seemingly simple system?

“When you see this boomerang-like behavior, it is tempting to explain this in terms of some complexity in the Earth,” Cattania says. “For instance, there may be many faults that interact, with earthquakes jumping between fault segments, or fault surfaces with prominent kinks and bends. In many cases, this could explain back-propagating behavior. But what we found was, you could have a very simple fault and still get this complex behavior.”

Faulty friction

In their new study, the team looked to simulate an earthquake along a simple fault system. In geology, a fault is a crack or fracture that runs through the Earth’s crust. An earthquake begins when the stress between rocks on either side of the fault, suddenly decreases, and one side slides against the other, setting off seismic waves that rupture rocks all along the fault. This seismic activity, which initiates deep in the crust, can sometimes reach and shake up the surface.

Cattania and Sun used a computer model to represent the fundamental physics at play during an earthquake along a simple fault. In their model, they simulated the Earth’s crust as a simple elastic material, in which they embedded a single straight fault. They then simulated how the fault would exhibit an earthquake under different scenarios. For instance, the team varied the length of the fault and the location of the quake’s initation point below the surface, as well as whether the quake traveled in one versus two directions.

Over multiple simulations, they observed that only the unilateral quakes — those that traveled in one direction — exhibited a boomerang effect. Specifically, these quakes seemed to include a type that seismologists term “back-propagating” events, in which the rumbler splits at some point along the fault, partly continuing in the same direction and partly reversing back the way it came.

“When you look at a simulation, sometimes you don’t fully understand what causes a given behavior,” Cattania says. “So we developed mathematical models to understand it. And we went back and forth, to ultimately develop a simple theory that tells you should only see this back-propagation under these certain conditions.”

Those conditions, as the team’s new theory lays out, have to do with the friction along the fault. In standard earthquake physics, it’s generally understood that an earthquake is triggered when the stress built up between rocks on either side of a fault, is suddenly released. Rocks slide against each other in response, decreasing a fault’s friction. The reduction in fault friction creates a positive feedback that facilitates further sliding, sustaining the earthquake.

However, in their simulations, the team observed that when a quake travels along a fault in one direction, it can back-propagate when friction along the fault goes down, then up, and then down again.

“When the quake propagates in one direction, it produces a “breaking’’ effect that reduces the sliding velocity, increases friction, and allows only a narrow section of the fault to slide at a time,” Cattania says. “The region behind the quake, which stops sliding, can then rupture again, because it has accumulated more stress to slide again.”

The team found that, in addition to traveling in one direction and along a fault with changing friction, a boomerang is likely to occur if a quake has traveled over a large enough distance.

“This implies that large earthquakes are not simply ‘scaled-up’ versions of small earthquakes, but instead they have their own unique rupture behavior,” Sun says.

The team suspects that back-propagating quakes may be more common than scientists have thought, and they may occur along simple, straight faults, which are typically older than more complex fault systems.

“You shouldn’t only expect this complex behavior on a young, complex fault system. You can also see it on mature, simple faults,” Cattania says. “The key open question now is how often rupture reversals, or ‘boomerang’ earthquakes, occur in nature. Many observational studies so far have used methods that can’t detect back-propagating fronts. Our work motivates actively looking for them, to further advance our understanding of earthquake physics and ultimately mitigate seismic risk.”

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MIT community members elected to the National Academy of Engineering for 2026

Seven MIT researchers are among the 130 new members and 28 international members recently elected to the National Academy of Engineering (NAE) for 2026. Twelve additional MIT alumni were also elected as new members.

One of the highest professional distinctions for engineers, membership in the NAE is given to individuals who have made outstanding contributions to “engineering research, practice, or education,” and to “the pioneering of new and developing fields of technology, making major advancements in traditional fields of engineering, or developing/implementing innovative approaches to engineering education.”

The seven MIT electees this year include:

Moungi Gabriel Bawendi, the Lester Wolfe Professor of Chemistry in the Department of Chemistry, was honored for the synthesis and characterization of semiconductor quantum dots and their applications in displays, photovoltaics, and biology.

Charles Harvey, a professor in the Department of Civil and Environmental Engineering, was honored for contributions to hydrogeology regarding groundwater arsenic contamination, transport, and consequences.

Piotr Indyk, the Thomas D. and Virginia W. Cabot Professor in the Department of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory, was honored for contributions to approximate nearest neighbor search, streaming, and sketching algorithms for massive data processing.

John Henry Lienhard, the Abdul Latif Jameel Professor of Water and Mechanical Engineering in the Department of Mechanical Engineering, was honored for advances and technological innovations in desalination.

Ram Sasisekharan, the Alfred H. Caspary Professor of Biological Physics and Physics in the Department of Biological Engineering, was honored for discovering the U.S. heparin contaminant in 2008 and creating clinical antibodies for Zika, dengue, SARS-CoV-2, and other diseases.

Frances Ross, the TDK Professor in the Department of Materials Science and Engineering, was honored for ultra-high vacuum and liquid-cell transmission electron microscopies and their worldwide adoptions for materials research and semiconductor technology development.

Zoltán Sandor Spakovszky SM ’99, PhD ’01, the T. Wilson (1953) Professor in Aeronautics in the Department of Aeronautics and Astronautics, was honored for contributions, through rigorous discoveries and advancements, in aeroengine aerodynamic and aerostructural stability and acoustics.

“Each of the MIT faculty and alumni elected to the National Academy of Engineering has made extraordinary contributions to their fields through research, education, and innovation,” says Paula T. Hammond, dean of the School of Engineering and Institute Professor in the Department of Chemical Engineering. "They represent the breadth of excellence we have here at MIT. This honor reflects the impact of their work, and I’m proud to celebrate their achievement and offer my warmest congratulations.”

Twelve additional alumni were elected to the National Academy of Engineering this year. They are: Anne Hammons Aunins PhD ’91; Lars James Blackmore PhD ’07; John-Paul Clarke ’91, SM ’92, SCD ’97; Michael Fardis SM ’77, SM ’78, PhD ’79; David Hays PhD ’98; Stephen Thomas Kent ’76, EE ’78, ENG ’78, PhD ’81; Randal D. Koster SM ’85, SCD ’88; Fred Mannering PhD ’83; Peyman Milanfar SM ’91, EE ’93, ENG ’93, PhD ’93; Amnon Shashua PhD ’93; Michael Paul Thien SCD ’88; and Terry A. Winograd PhD ’70.

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The strength of “infinite hope”

Dean of Engineering Paula Hammond ’84 PhD ’93 made a resounding call for the MIT community to “embrace endless hope” and “never stop looking forward,” in a keynote address at the Institute’s annual MLK Celebration on Wednesday, Feb. 11.

“We each have a role to play in contributing to our future, and we each must embrace endless hope and continuously renew our faith in ourselves to accomplish that dream,” Hammond said, to an audience of hundreds at the event.

She added: “Whether it is through caring for those in our community, teaching others, providing inspiration, leadership, or critical support to others in their moment of need, we provide support for one another on our journey … It is that future that will feed the optimism and faith that we need to move forward, to inspire and encourage, and to never stop looking forward.”

The MLK Celebration is an annual tribute to the life and legacy of Martin Luther King Jr., and is always thematically organized around a quotation of King’s. This year, that passage was, “We must accept finite disappointment, but never lose infinite hope.”

Hammond and multiple other speakers at the event organized their remarks around that idea, while weaving in personal reflections about the importance of community, family, and mentorship.

As Hammond noted, “We can lay the path toward a better, greater time with the steps that we take today even in the face of incredible disappointment, shock and disruption.” She added: “Principles founded in fear, ignorance, or injustice ultimately fail because they do not meet the needs of a growing and prosperous nation and world.”

The event, which took place in MIT’s Walker Memorial (Building 50), featured remarks by students, staff, and campus leaders, as well as musical performances by the recently reconstituted MIT Gospel Choir. (Listen to one of those performances by clicking on the player at the end of this article.)

MIT President Sally A. Kornbluth provided introductory remarks, noting that this year’s event was occurring during “a time when feeling fractured, isolated, and pitted against each other feels exhaustingly routine. A time when it’s easy to feel discouraged.” As such, she added, “the solace we take from [coming together at this event] couldn’t be more relevant now.”

Kornbluth also offered laudatory thoughts about Hammond, a highly accomplished research scientist who has held numerous leadership roles at MIT and elsewhere. Hammond, a chemical engineer, was named dean of the MIT School of Engineering in December. Prior to that, she has served as vice provost for faculty, from 2023 to 2025, and head of the Department of Chemical Engineering, from 2015 to 2023. In honor of her accomplishments, Hammond was named an Institute Professor, MIT’s highest faculty honor. A member of MIT’s Koch Institute for Integrative Cancer Research, Hammond has developed polymers and nanoscale materials with multiple applications, including drug delivery, imaging, and even battery advances.

Hammond was awarded the National Medal of Technology and Innovation in 2024. That year she also received MIT’s Killian Award, for faculty achievement. And she has earned the rare distinction of having been elected to all three national academies — the National Academy of Engineering, the National Academy of Medicine, and the National Academy of Sciences.

“I’ve never met anyone who better represents MIT’s highest values and aspirations than Paula Hammond,” Kornbluth said, citing both Hammond’s record of academic excellence and Institute service.

Among other things, Kornbluth observed, “Paula has been a longtime champion of MIT’s culture of openness to people and ideas from everywhere. In fact, it’s hard to think of anyone more open to sharing what she knows — and more interested in hearing your point of view. And the respect she shows to everyone — no matter their job or background — is an example for us all.”

Michael Ewing ’27, a mechanical engineering major, provided welcoming remarks while introducing the speakers as well as the MLK Celebration planning committee.

Ewing noted that the event remains “extremely and vitally important” to the MIT community, and reflected on the meaning of this year’s motif, for individuals and larger communities.

“Dr. King’s hope constitutes the belief that one can make things better, even when current conditions are poor,” Ewing said. “In the face of adversity, we must remain connected to what’s most important, be grateful for both the challenges and the opportunities, and hold on to the long-term belief that no matter what, no matter what, there’s an opportunity for us to learn, grow, and improve.”

The annual MLK Celebration also highlighted further reflections from students and staff on King’s life and legacy and the value of his work.

“Everyone that has fought for a greater good in this world has left the battle without something that they came with,” said Oluwadara Deru, a senior in mechanical engineering and the featured undergraduate speaker. “But what they gained is invaluable.”

Ekua Beneman, a graduate student in chemistry, offered thoughts relating matters of academic achievement, and helping others in a university setting, to the larger themes of the celebration.

“Hope is not pretending disappointment doesn’t exist,” Beneman said. “Hope is choosing to pass forward what was once given to you. At a place like MIT, infinite hope looks like mentorship. It looks like making space. It looks like sharing knowledge instead of guarding or gatekeeping it. If we truly want to honor Dr. King’s legacy, beyond this beautiful celebration today, we do it by choosing community, mentorship, and hope in action.”

Denzil Streete, associate dean and director of the Office of Graduate Education, related the annual theme to everyday life at the Institute, as well as social life everywhere.

“Hope lies in small, often uncelebrated acts,” Streete said. “Showing up. Being present. Responding with patience. Translating complicated processes into next steps. Making one more call. Sending one more email.”

He concluded: “See your daily work as moral work … Every day, through joy and care, we choose infinite hope, for our students, and for one another.”

Reverend Thea Keith-Lucas, chaplain to the Institute and associate dean in the Office of Religious, Spiritual, and Ethical Life, offered both an invocation and a benediction at the event.

The annual celebration includes the Dr. Martin Luther King Jr. Leadership Awards Recipients, given this year to Melissa Smith PhD ’12, Fred Harris, Carissma McGee, Janine Medrano, and Edwin Marrero.

For all the turbulence in the world, Hammond said toward the conclusion of her address, people can continue to make progress in their own communities, and can be intentional about focusing, in part, on the possibilities of progress ahead.

At MIT, Hammond noted, “The commitment of our faculty, students, and staff to continuously learn, to ask deep questions and to apply our knowledge, our perspectives and our insights to the biggest world problems is something that gives me infinite hope and optimism for the future.”

MIT News · MIT Gospel Choir, MLK Luncheon 2026

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Exploring the promise of regenerative aquaculture at an Arkansas fish farm

In many academic circles, innovation is imagined as a lab-to-market pipeline that travels through patent filings, venture rounds, and coastal research hubs. But a growing movement inside U.S. universities is pushing students toward a different frontier: solving real engineering problems alongside rural communities whose challenges directly shape national food security. 

A compelling example of this shift can be found in the story of Kiyoko “Kik” Hayano, a second-year mechanical engineering student at MIT, and her work through MIT D-Lab with Keo Fish Farms, a commercial aquaculture operation in the Arkansas Delta.

Hayano’s journey — from a small, windswept town in rural Wyoming to MIT’s campus in Cambridge, Massachusetts, and on to a working Arkansas fish farm — offers a tangible glimpse into how applied engineering, academic partnerships, and on-the-ground innovation can create new models for regenerative agriculture in the United States.

Wyoming childhood and an engineering dream

Hayano grew up in Powell, Wyoming (population ~6,400), a community defined by agriculture, water scarcity, and long distances. Her early interests in gardening with her grandmother and tinkering with irrigation projects through her high school’s agricultural center formed the foundation for a more ambitious goal: studying mechanical engineering at MIT.

That ambition paid off. Shortly after arriving in Cambridge, Hayano connected with MIT D-Lab, a program founded to co-create engineering solutions with communities, rather than for them — especially in regions facing poverty, resource constraints, or climate-related disruptions. For many MIT students, D-Lab is their entry point into field-based development work across Africa, Latin America, and Southeast Asia. Increasingly, however, the program has expanded its domestic mission to include rural areas of the United States experiencing food, water, and energy insecurity.

MIT D-Lab meets the Arkansas Delta

That domestic shift set the stage for a new joint effort. In 2024, Keo Fish Farms — a commercial aquaculture farm near Keo, Arkansas — contacted D-Lab seeking technical collaboration on a growing water quality challenge. The farm had begun to observe elevated iron levels in its groundwater, leading to fish mortality events during peak summer conditions. The problem was both biological and mechanical: Aquaculture species like hybrid striped bass and triploid grass carp require consistent, clean water inputs, and well systems tapping iron-rich geologic layers were compromising fish health, hatchery performance, and long-term viability.

Kendra Leith, MIT D-Lab associate director for research, saw an opportunity. The Delta region represents a collision of three major realities that matter deeply to both public policy and academic research: high-value protein production, aging or inadequate water infrastructure, and generational rural decline.

For Hayano, the chance to work on an important engineering problem with environmental, agricultural, and economic implications was exactly why she chose mechanical engineering in the first place.

Applied engineering in a living laboratory

When Hayano arrived at Keo Fish Farms, the project was structured as a co-creative engineering engagement — D-Lab’s core model. She documented the existing water intake system, analyzed the well depth relative to geological iron strata, and evaluated filtration options including aeration, sedimentation, and emerging biochar-based media.

The collaboration generated three immediate academic values. First, the team reviewed real constraints, a process known as ground truthing. Constraints in this situation included iron levels that shift seasonally, capital budgets that do not assume infinite funding, and labor cycles tied to harvest seasons. The team then scoped out the technology that might be used to mitigate problem areas. Iron-reduction solutions ranged from drilling deeper wells to incorporating biochar and other regenerative filtration mediums capable of binding contaminants while improving soil and plant health elsewhere on the farm. Finally, they reviewed policy relevance: Water quality in aquaculture sits at the intersection of U.S. Department of Agriculture (USDA) conservation, Environmental Protection Agency (EPA) water standards, climate-driven aquifer variability, and domestic protein security — issues central to U.S. food systems.

Leith notes that “the most transformative experiences happen when students and communities learn from one another.” The Keo project, she adds, is an example of how domestic food production systems can act as test beds for innovation that previously would have been deployed exclusively abroad.

Regenerative agriculture as a national opportunity

While Keo Fish Farms played a supporting role in the narrative, the project highlighted a broader challenge and opportunity: Can U.S. aquaculture transition toward regenerative agriculture principles?

Regenerative agriculture — long associated with row crops, grazing systems, and soil carbon — rarely includes aquaculture in the national conversation. Yet aquaculture sits at the nexus of water chemistry, nutrient cycling, renewable energy integration, biochar and filtration research, protein production, and greenhouse gas mitigation.

Hayano’s work helped illuminate that regenerative aquaculture will likely depend on regenerative water systems, where filtration, biochar, solar energy, and nutrient reuse form a closed-loop infrastructure, rather than a linear extract–use–discharge model.

D-Lab’s domestic projects increasingly intersect with this space, creating pathways for MIT students and faculty to collaborate with USDA, the U.S. Department of Energy (DoE), and National Science Foundation (NSF) priorities around rural innovation, renewable energy, and water systems engineering.

The role of industry partners: less spotlight, more signal

Keo Fish Farms’ involvement served as a platform — not a spotlight — for the engineering and policy implications emerging from the project. The farm provided three critical ingredients academic institutions often lack: a real commercial engineering problem with economic consequences, a living laboratory for field research and prototyping, and a pathway for future regenerative adoption at scale.

The farm’s leadership has stated that its long-term goal is to become a first-in-class demonstration site for regenerative aquaculture in the United States, combining advanced iron and sediment filtration, biochar production from local rice hull waste streams, renewable solar energy systems, water recycling and nutrient recovery, reduced chemical inputs, and habitat and biodiversity considerations.

To be sure, the D-Lab collaboration did not solve that entire puzzle, but it created the blueprint for a pathway, showing how academic partnerships can accelerate regenerative transitions in rural U.S. agriculture and aquaculture systems.

Lessons for universities and policymakers

For universities, the Keo–MIT D-Lab partnership offers a replicable model for experiential learning for STEM students, field-based regenerative research, technology validation in live agricultural systems, and cross-disciplinary collaboration. And for federal and state policymakers, it illustrates how rural communities can serve as innovation sites, why water infrastructure modernization matters to food security, how regenerative agriculture can expand beyond soil and grazing, and why public-private-academic partnerships deserve new funding pathways.

All of this aligns with emerging priorities at the USDA, DoE, NSF, and EPA around sustainability, climate resilience, and domestic protein systems.

For Hayano, the experience reinforced that engineering careers can be rooted not only in Silicon Valley labs or aerospace firms, but also in overlooked rural systems that feed the country. 

“I’m really grateful for the experience,” she reflected after the project. “It opened my eyes to how engineering can support sustainable food systems and rural communities.”

The sentiment echoes a broader trend among students seeking careers at the intersection of technology, environment, and public good. Whether Hayano returns to the Arkansas Delta or not, her path captures something deeply relevant to America’s innovation story: talent emerging from rural places, innovating at world-class institutions, and returning engineering capacity back into the country’s agricultural heartland.

It is, in many ways, a modern form of the American dream — one grounded not in abstraction, but in water, food, soil, and the systems that will define our next century.

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New AI model could cut the costs of developing protein drugs

Industrial yeasts are a powerhouse of protein production, used to manufacture vaccines, biopharmaceuticals, and other useful compounds. In a new study, MIT chemical engineers have harnessed artificial intelligence to optimize the development of new protein manufacturing processes, which could reduce the overall costs of developing and manufacturing these drugs.

Using a large language model (LLM), the MIT team analyzed the genetic code of the industrial yeast Komagataella phaffii — specifically, the codons that it uses. There are multiple possible codons, or three-letter DNA sequences, that can be used to encode a particular amino acid, and the patterns of codon usage are different for every organism.

The new MIT model learned those patterns for K. phaffii and then used them to predict which codons would work best for manufacturing a given protein. This allowed the researchers to boost the efficiency of the yeast’s production of six different proteins, including human growth hormone and a monoclonal antibody used to treat cancer.

“Having predictive tools that consistently work well is really important to help shorten the time from having an idea to getting it into production. Taking away uncertainty ultimately saves time and money,” says J. Christopher Love, the Raymond A. and Helen E. St. Laurent Professor of Chemical Engineering at MIT, a member of the Koch Institute for Integrative Cancer Research, and faculty co-director of the MIT Initiative for New Manufacturing (MIT INM).

Love is the senior author of the new study, which appears this week in the Proceedings of the National Academy of Sciences. Former MIT postdoc Harini Narayanan is the paper’s lead author.

Codon optimization

Yeast such as K. phaffii and Saccharomyces cerevisiae (baker’s yeast) are the workhorses of the biopharmaceutical industry, producing billions of dollars of protein drugs and vaccines every year.

To engineer yeast for industrial protein production, researchers take a gene from another organism, such as the insulin gene, and modify it so that the microbe will produce it in large quantities. This requires coming up with an optimal DNA sequence for the yeast cells, integrating it into the yeast’s genome, devising favorable growth conditions for it, and finally purifying the end product.

For new biologic drugs — large, complex drugs produced by living organisms — this development process might account for 15 to 20 percent of the overall cost of commercializing the drug.

“Today, those steps are all done by very laborious experimental tasks,” Love says. “We have been looking at the question of where could we take some of the concepts that are emerging in machine learning and apply them to make different aspects of the process more reliable and simpler to predict.”

In this study, the researchers wanted to try to optimize the sequence of DNA codons that make up the gene for a protein of interest. There are 20 naturally occurring amino acids, but 64 possible codon sequences, so most of these amino acids can be encoded by more than one codon. Each codon corresponds to a unique transfer RNA (tRNA) molecule, which carries the correct amino acid to the ribosome, where amino acids are strung together into proteins.

Different organisms use each of these codons at different rates, and designers of engineered proteins often optimize the production of their proteins by choosing the codons that occur the most frequently in the host organism. However, this doesn’t necessarily produce the best results. If the same codon is always used to encode arginine, for example, the cell may run low on the tRNA molecules that correspond to that codon.

To take a more nuanced approach, the MIT team deployed a type of large language model known as an encoder-decoder. Instead of analyzing text, the researchers used it to analyze DNA sequences and learn the relationships between codons that are used in specific genes.

Their training data, which came from a publicly available dataset from the National Center for Biotechnology Information, consisted of the amino acid sequences and corresponding DNA sequences for all of the approximately 5,000 proteins naturally produced by K. phaffii.

“The model learns the syntax or the language of how these codons are used,” Love says. “It takes into account how codons are placed next to each other, and also the long-distance relationships between them.”

Once the model was trained, the researchers asked it to optimize the codon sequences of six different proteins, including human growth hormone, human serum albumin, and trastuzumab, a monoclonal antibody used to treat cancer.

They also generated optimized sequences of these proteins using four commercially available codon optimization tools. The researchers inserted each of these sequences into K. phaffii cells and measured how much of the target protein each sequence generated. For five of the six proteins, the sequences from the new MIT model worked the best, and for the sixth, it was the second-best.

“We made sure to cover a variety of different philosophies of doing codon optimization and benchmarked them against our approach,” Narayanan says. “We’ve experimentally compared these approaches and showed that our approach outperforms the others.”

Learning the language of proteins

K. phaffii, formerly known as Pichia pastoris, is used to produce dozens of commercial products, including insulin, hepatitis B vaccines, and a monoclonal antibody used to treat chronic migraines. It is also used in the production of nutrients added to foods, such as hemoglobin.

Researchers in Love’s lab have started using the new model to optimize proteins of interest for K. phaffii, and they have made the code available for other researchers who wish to use it for K. phaffii or other organisms.

The researchers also tested this approach on datasets from different organisms, including humans and cows. Each of the resulting models generated different predictions, suggesting that species-specific models are needed to optimize codons of target proteins.

By looking into the inner workings of the model, the researchers found that it appeared to learn some of the biological principles of how the genome works, including things that the researchers did not teach it. For example, it learned not to include negative repeat elements — DNA sequences that can inhibit the expression of nearby genes. The model also learned to categorize amino acids based on traits such as hydrophobicity and hydrophilicity.

“Not only was it learning this language, but it was also contextualizing it through aspects of biophysical and biochemical features, which gives us additional confidence that it is learning something that’s actually meaningful and not simply an optimization of the task that we gave it,” Love says.

The research was funded by the Daniel I.C. Wang Faculty Research Innovation Fund at MIT, the MIT AltHost Research Consortium, the Mazumdar-Shaw International Oncology Fellowship, and the Koch Institute.

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A new way to make steel could reduce America’s reliance on imports

America has been making steel from iron ore the same way for hundreds of years. Unfortunately, it hasn’t been making enough of it. Today the U.S. is the world’s largest steel importer, relying on other countries to produce a material that serves as the backbone of our society.

That’s not to say the U.S. is alone: Globally, most steel today is made in enormous, multi-billion-dollar plants using a coal-based process that hasn’t changed much in 300 years.

Now Hertha Metals, founded by CEO Laureen Meroueh SM ’18, PhD ’20, is scaling up a new steel production system powered by natural gas and electricity. The process, which can also run on hydrogen, uses a continuous electric arc furnace within which iron ore of any grade and format is reduced and carburized into molten steel in a single step. It also eliminates the need for coking and sintering plants, along with other dangerous and expensive components of traditional systems. As a result, the company says its process uses 30 percent less energy and costs less to operate than conventional steel mills in America.

“The real headline is the fact that we can make steel from iron ore more cost-competitive by 25 percent in the United States, while also reducing emissions.” Meroueh says. “The United States hasn’t been competitive in steelmaking in decades. Now we’re enabling that.”

Since late 2024, Hertha has been operating a 1-tonne-per-day pilot plant at its first production facility outside Houston, Texas. The company calls it the world’s largest demonstration of a single-step steelmaking process. This year, the company will begin construction of a plant that will be able to produce 10,000 tons of steel each year. That plant, which Hertha expects to reach full production capacity at the end 2027, will also produce high-purity iron for the magnet industry, helping America onshore another critical material.

“By importing so much of our pig iron and steel, we are completely reliant on global trade mechanisms and geopolitics remaining the way they are today for us to continue making the materials that are critical for our infrastructure, our defense systems, and our energy systems,” Meroueh says. “Steel is the most foundational material to our society. It is simply irreplaceable.”

Streamlining steelmaking

Meroueh earned her master’s degree in the lab of Gang Chen, MIT’s Carl Richard Soderberg Professor of Power Engineering. She studied thermal energy storage and the fundamental physics of heat transfer, eventually getting her first taste of entrepreneurship when she explored commercializing some of that research. Meroueh received a grant from the MIT Sandbox Innovation Fund and considers Executive Director Jinane Abounadi a close mentor today.

The experience taught Meroueh a lot about startups, but she ultimately decided to stay at MIT to pursue her PhD in metallurgy and hydrogen production in the lab of Douglas Hart, MIT professor of mechanical engineering. After earning her PhD in 2020, she was recruited to lead a hydrogen production startup for a year and a half.

“After that experience, I was looking at all of the hard-to-abate, high-emissions sectors of the economy to find the one receiving the least attention,” Meroueh says. “I stumbled onto steel and fell in love.”

Meroueh became an Innovators Fellow at the climate and energy startup investment firm Breakthrough Energy and officially founded Hertha Metals in 2022.

The company is named after Hertha Ayrton, a 19th-century physicist and inventor who advanced our understanding of electric arcs, which the company uses in its furnaces.

Globally, most steel today is made by combining iron ore with coke (from coal) and limestone in a blast furnace to make molten iron. That “pig iron” is then sent to another furnace to burn off excess carbon and impurities. Alloying elements are then added, and the steel is sent for casting and finishing, requiring additional machinery.

The U.S. makes most of its steel from recycled scrap metal, but it still must import iron made from a blast furnace to reach useful grades of steel.

“The United States has a massive need to make steel from iron ore, not just scrap, so we can stop relying on importing so much,” Meroueh explains. “We only have about 11 operational blast furnaces in the U.S., so we end up importing about 90 percent of the pig iron needed to feed into domestic scrap steel furnaces.”

To solve the problem, Meroueh leveraged a fuel America has in abundance: natural gas. Hertha’s system uses natural gas (the process also works with hydrogen) to reduce iron ore while using electricity to melt it in a single step. She says the closest competing technology requires scarce and expensive pelletized, high-grade iron ore and multiple furnaces to produce liquid steel. Meroueh’s process uses iron ore of any format or grade, producing refined liquid steel in a single furnace, cutting both cost and emissions.

“Many reactions that were previously run sequentially though a conventional steelmaking process are now occurring simultaneously, within a single furnace,” Meroueh explains. “We’re melting, we’re reducing, and we’re carburizing the steel to the exact amount we need. What exits our furnace is a refined molten steel. We can process any grade and format of iron ore because everything is occurring in the molten phase. It doesn’t matter whether the ore came in as a pellet or clumps and fines out of the ground.”

Meroueh says the company’s biggest innovation is performing the gaseous reduction when the iron oxide is a molten liquid using proprietary gas technologies.     

“All of the conventional steelmaking technologies perform reduction while the iron ore is in a solid state, and they use gas — whether that’s combusted coke or natural gas — to perform that reduction,” Meroueh says. “We saw the inefficiency in doing that and how it restricted the grade and form of usable iron ore, because at the end of the day you have to melt the ore anyway.”

Hertha’s system is modular and uses standard off-gas handling equipment, steam turbines, and heat exchangers. It also recycles natural gas to regenerate electricity from the hot off-gas leaving the furnace.

“Our steel mill has its own little power plant attached that leads to 35 percent recovery in energy and minimizes grid power demand in an age in which we are competing with data centers,” Meroueh says.

Onshoring critical materials

Today’s steel mills are the result of enormous investments and are designed to run for at least 50 years. Hertha Metals doesn’t envision replacing those entirely — at least not anytime soon.

“You’re not just going to shut off a steel mill in the middle of its life,” Meroueh says. “Sure, you can build new steel mills, but we really want to be able to displace the blast furnace and the basic oxygen furnace while still utilizing all the mill’s downstream equipment.”

The company’s Houston plant began producing one ton of steel per day just two years after Hertha’s founding and less than one year after Meroueh opened up Hertha’s headquarters. She calls it an important first step.

“This is the largest-scale demonstration of a single-step steelmaking company,” Meroueh says. “It’s a true breakthrough in terms of scalability, pace of progress, and capital efficiency.”

The company’s next plant, which will be capable of producing 10,000 tons of steel each year, will also be producing high-purity iron for permanent magnets, which are used in electric motors, robotics, consumer electronics, aerospace and military hardware.

“It’s insane that we don’t make rare earth magnets domestically,” Meroueh says. “It’s insane that any country doesn’t make their own rare earth magnets. Most rare earth magnets are permanent magnets, so neodymium magnets. What’s interesting is that by weight, 70 percent of that magnet is not a rare earth, it’s high-purity iron. America doesn’t currently make any high-purity iron, but Hertha has already made it in our pilot plant.”

Hertha plans to quickly scale up its production of high-purity iron so that, by 2030, it will be able to meet about a quarter of total projected demand for magnets in the U.S.

After that, the company plans to run a full-scale commercial steel plant in partnership with a steel manufacturer in America. Meroueh says that plant, which will be able to produce around half a million tons of steel each year, should be operational by 2030.

“We are eager to partner with today’s steel producers so that we can collectively leverage the existing infrastructure alongside Hertha’s innovation,” Meroueh says. “That includes the $1.5 billion of capital downstream of a melt shop that Hertha’s process can integrate into. The melt shop is the ore-to-liquid steel portion of the steel mill. That’s just the start.  It’s a smaller scale than a conventional plant in which we still economically out compete traditional production processes. Then we’re going to scale to 2 million tons per year once we build up our balance sheet.”

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