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    To design better water filters, MIT engineers look to manta rays

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    Filter feeders are everywhere in the animal world, from tiny crustaceans and certain types of coral and krill, to various molluscs, barnacles, and even massive basking sharks and baleen whales. Now, MIT engineers have found that one filter feeder has evolved to sift food in ways that could improve the design of industrial water filters.In a paper appearing this week in the Proceedings of the National Academy of Sciences, the team characterizes the filter-feeding mechanism of the mobula ray — a family of aquatic rays that includes two manta species and seven devil rays. Mobula rays feed by swimming open-mouthed through plankton-rich regions of the ocean and filtering plankton particles into their gullet as water streams into their mouths and out through their gills.The floor of the mobula ray’s mouth is lined on either side with parallel, comb-like structures, called plates, that siphon water into the ray’s gills. The MIT team has shown that the dimensions of these plates may allow for incoming plankton to bounce all the way across the plates and further into the ray’s cavity, rather than out through the gills. What’s more, the ray’s gills absorb oxygen from the outflowing water, helping the ray to simultaneously breathe while feeding.“We show that the mobula ray has evolved the geometry of these plates to be the perfect size to balance feeding and breathing,” says study author Anette “Peko” Hosoi, the Pappalardo Professor of Mechanical Engineering at MIT.The engineers fabricated a simple water filter modeled after the mobula ray’s plankton-filtering features. They studied how water flowed through the filter when it was fitted with 3D-printed plate-like structures. The team took the results of these experiments and drew up a blueprint, which they say designers can use to optimize industrial cross-flow filters, which are broadly similar in configuration to that of the mobula ray.“We want to expand the design space of traditional cross-flow filtration with new knowledge from the manta ray,” says lead author and MIT postdoc Xinyu Mao PhD ’24. “People can choose a parameter regime of the mobula ray so they could potentially improve overall filter performance.”Hosoi and Mao co-authored the new study with Irmgard Bischofberger, associate professor of mechanical engineering at MIT.A better trade-offThe new study grew out of the group’s focus on filtration during the height of the Covid pandemic, when the researchers were designing face masks to filter out the virus. Since then, Mao has shifted focus to study filtration in animals and how certain filter-feeding mechanisms might improve filters used in industry, such as in water treatment plants.Mao observed that any industrial filter must strike a balance between permeability (how easily fluid can flow through a filter), and selectivity (how successful a filter is at keeping out particles of a target size). For instance, a membrane that is studded with large holes might be highly permeable, meaning a lot of water can be pumped through using very little energy. However, the membrane’s large holes would let many particles through, making it very low in selectivity. Likewise, a membrane with much smaller pores would be more selective yet also require more energy to pump the water through the smaller openings.“We asked ourselves, how do we do better with this tradeoff between permeability and selectivity?” Hosoi says.As Mao looked into filter-feeding animals, he found that the mobula ray has struck an ideal balance between permeability and selectivity: The ray is highly permeable, in that it can let water into its mouth and out through its gills quickly enough to capture oxygen to breathe. At the same time, it is highly selective, filtering and feeding on plankton rather than letting the particles stream out through the gills.The researchers realized that the ray’s filtering features are broadly similar to that of industrial cross-flow filters. These filters are designed such that fluid flows across a permeable membrane that lets through most of the fluid, while any polluting particles continue flowing across the membrane and eventually out into a reservoir of waste.The team wondered whether the mobula ray might inspire design improvements to industrial cross-flow filters. For that, they took a deeper dive into the dynamics of mobula ray filtration.A vortex keyAs part of their new study, the team fabricated a simple filter inspired by the mobula ray. The filter’s design is what engineers refer to as a “leaky channel” — effectively, a pipe with holes along its sides. In this case, the team’s “channel” consists of two flat, transparent acrylic plates that are glued together at the edges, with a slight opening between the plates through which fluid can be pumped. At one end of the channel, the researchers inserted 3D-printed structures resembling the grooved plates that run along the floor of the mobula ray’s mouth.The team then pumped water through the channel at various rates, along with colored dye to visualize the flow. They took images across the channel and observed an interesting transition: At slow pumping rates, the flow was “very peaceful,” and fluid easily slipped through the grooves in the printed plates and out into a reservoir. When the researchers increased the pumping rate, the faster-flowing fluid did not slip through, but appeared to swirl at the mouth of each groove, creating a vortex, similar to a small knot of hair between the tips of a comb’s teeth.“This vortex is not blocking water, but it is blocking particles,” Hosoi explains. “Whereas in a slower flow, particles go through the filter with the water, at higher flow rates, particles try to get through the filter but are blocked by this vortex and are shot down the channel instead. The vortex is helpful because it prevents particles from flowing out.”The team surmised that vortices are the key to mobula rays’ filter-feeding ability. The ray is able to swim at just the right speed that water, streaming into its mouth, can form vortices between the grooved plates. These vortices effectively block any plankton particles — even those that are smaller than the space between plates. The particles then bounce across the plates and head further into the ray’s cavity, while the rest of the water can still flow between the plates and out through the gills.The researchers used the results of their experiments, along with dimensions of the filtering features of mobula rays, to develop a blueprint for cross-flow filtration.“We have provided practical guidance on how to actually filter as the mobula ray does,” Mao offers.“You want to design a filter such that you’re in the regime where you generate vortices,” Hosoi says. “Our guidelines tell you: If you want your plant to pump at a certain rate, then your filter has to have a particular pore diameter and spacing to generate vortices that will filter out particles of this size. The mobula ray is giving us a really nice rule of thumb for rational design.”This work was supported, in part, by the U.S. National Institutes of Health, and the Harvey P. Greenspan Fellowship Fund.  More

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      in Environment

      Q&A: A blueprint for sustainable innovation

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      Atacama Biomaterials is a startup combining architecture, machine learning, and chemical engineering to create eco-friendly materials with multiple applications. Passionate about sustainable innovation, its co-founder Paloma Gonzalez-Rojas SM ’15, PhD ’21 highlights here how MIT has supported the project through several of its entrepreneurship initiatives, and reflects on the role of design in building a holistic vision for an expanding business.

      Q: What role do you see your startup playing in the sustainable materials space?

      A: Atacama Biomaterials is a venture dedicated to advancing sustainable materials through state-of-the-art technology. With my co-founder Jose Tomas Dominguez, we have been working on developing our technology since 2019. We initially started the company in 2020 under another name and received Sandbox funds the next year. In 2021, we went through The Engine’s accelerator, Blueprint, and changed our name to Atacama Biomaterials in 2022 during the MITdesignX program. 

      This technology we have developed allows us to create our own data and material library using artificial intelligence and machine learning, and serves as a platform applicable to various industries horizontally — biofuels, biological drugs, and even mining. Vertically, we produce inexpensive, regionally sourced, and environmentally friendly bio-based polymers and packaging — that is, naturally compostable plastics as a flagship product, along with AI products.

      Q: What motivated you to venture into biomaterials and found Atacama?

      A: I’m from Chile, a country with a beautiful, rich geography and nature where we can see all the problems stemming from industry, waste management, and pollution. We named our company Atacama Biomaterials because the Atacama Desert in Chile — one of the places where you can best see the stars in the world — is becoming a plastic dump, as many other places on Earth. I care deeply about sustainability, and I have an emotional attachment to stop these problems. Considering that manufacturing accounts for 29 percent of global carbon emissions, it is clear that sustainability has a role in how we define technology and entrepreneurship, as well as a socio-economic dimension.

      When I first came to MIT, it was to develop software in the Department of Architecture’s Design and Computation Group, with MIT professors Svafa Gronfeldt as co-advisor and Regina Barzilay as committee member. During my PhD, I studied machine-learning methods simulating pedestrian motion to understand how people move in space. In my work, I would use lots of plastics for 3D printing and I couldn’t stop thinking about sustainability and climate change, so I reached out to material science and mechanical engineering professors to look into biopolymers and degradable bio-based materials. This is how I met my co-founder, as we were both working with MIT Professor Neil Gershenfeld. Together, we were part of one of the first teams in the world to 3D print wood fibers, which is difficult — it’s slow and expensive — and quickly pivoted to sustainable packaging. 

      I then won a fellowship from MCSC [the MIT Climate and Sustainability Consortium], which gave me freedom to explore further, and I eventually got a postdoc in MIT chemical engineering, guided by MIT Professor Gregory Rutledge, a polymer physicist. This was unexpected in my career path. Winning Nucleate Eco Track 2022 and the MITdesignX Innovation Award in 2022 profiled Atacama Biomaterials as one of the rising startups in Boston’s biotechnology and climate-tech scene.

      Q: What is your process to develop new biomaterials?

      A: My PhD research, coupled with my background in material development and molecular dynamics, sparked the realization that principles I studied simulating pedestrian motion could also apply to molecular engineering. This connection may seem unconventional, but for me, it was a natural progression. Early in my career, I developed an intuition for materials, understanding their mechanics and physics.

      Using my experience and skills, and leveraging machine learning as a technology jump, I applied a similar conceptual framework to simulate the trajectories of molecules and find potential applications in biomaterials. Making that parallel and shift was amazing. It allowed me to optimize a state-of-the-art molecular dynamic software to run twice as fast as more traditional technologies through my algorithm presented at the International Conference of Machine Learning this year. This is very important, because this kind of simulation usually takes a week, so narrowing it down to two days has major implications for scientists and industry, in material science, chemical engineering, computer science and related fields. Such work greatly influenced the foundation of Atacama Biomaterials, where we developed our own AI to deploy our materials. In an effort to mitigate the environmental impact of manufacturing, Atacama is targeting a 16.7 percent reduction in carbon dioxide emissions associated with the manufacturing process of its polymers, through the use of renewable energy. 

      Another thing is that I was trained as an architect in Chile, and my degree had a design component. I think design allows me to understand problems at a very high level, and how things interconnect. It contributed to developing a holistic vision for Atacama, because it allowed me to jump from one technology or discipline to another and understand broader applications on a conceptual level. Our design approach also meant that sustainability came to the center of our work from the very beginning, not just a plus or an added cost.

      Q: What was the role of MITdesignX in Atacama’s development?

      A: I have known Svafa Grönfeldt, MITdesignX’s faculty director, for almost six years. She was the co-advisor of my PhD, and we had a mentor-mentee relationship. I admire the fact that she created a space for people interested in business and entrepreneurship to grow within the Department of Architecture. She and Executive Director Gilad Rosenzweig gave us fantastic advice, and we received significant support from mentors. For example, Daniel Tsai helped us with intellectual property, including a crucial patent for Atacama. And we’re still in touch with the rest of the cohort. I really like this “design your company” approach, which I find quite unique, because it gives us the opportunity to reflect on who we want to be as designers, technologists, and entrepreneurs. Studying user insights also allowed us to understand the broad applicability of our research, and align our vision with market demands, ultimately shaping Atacama into a company with a holistic perspective on sustainable material development.

      Q: How does Atacama approach scaling, and what are the immediate next steps for the company?

      A: When I think about accomplishing our vision, I feel really inspired by my 3-year-old daughter. I want her to experience a world with trees and wildlife when she’s 100 years old, and I hope Atacama will contribute to such a future.

      Going back to the designer’s perspective, we designed the whole process holistically, from feedstock to material development, incorporating AI and advanced manufacturing. Having proved that there is a demand for the materials we are developing, and having tested our products, manufacturing process, and technology in critical environments, we are now ready to scale. Our level of technology-readiness is comparable to the one used by NASA (level 4).

      We have proof of concept: a biodegradable and recyclable packaging material which is cost- and energy-efficient as a clean energy enabler in large-scale manufacturing. We have received pre-seed funding, and are sustainably scaling by taking advantage of available resources around the world, like repurposing machinery from the paper industry. As presented in the MIT Industrial Liaison and STEX Program’s recent Sustainability Conference, unlike our competitors, we have cost-parity with current packaging materials, as well as low-energy processes. And we also proved the demand for our products, which was an important milestone. Our next steps involve strategically expanding our manufacturing capabilities and research facilities and we are currently evaluating building a factory in Chile and establishing an R&D lab plus a manufacturing plant in the U.S. More

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      in Energy

      Printing a new approach to fusion power plant materials

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      When Alexander O’Brien sent in his application for graduate school at MIT’s Department of Nuclear Science and Engineering, he had a germ of a research idea already brewing. So when he received a phone call from Professor Mingda Li, he shared it: The student from Arkansas wanted to explore the design of materials that could hold nuclear reactors together.

      Li listened to him patiently and then said, “I think you’d be a really good fit for Professor Ju Li,” O’Brien remembers. Ju Li, the Battelle Energy Alliance Professor in Nuclear Engineering, had wanted to explore 3D printing for nuclear reactors and O’Brien seemed like the right candidate. “At that moment I decided to go to MIT if they accepted me,” O’Brien remembers.

      And they did.

      Under the advisement of Ju Li, the fourth-year doctoral student now explores 3D printing of ceramic-metal composites, materials that can be used to construct fusion power plants.

      An early interest in the sciences

      Growing up in Springdale, Arkansas as a self-described “band nerd,” O’Brien was particularly interested in chemistry and physics. It was one thing to mix baking soda and vinegar to make a “volcano” and quite another to understand why that was happening. “I just enjoyed understanding things on a deeper level and being able to figure out how the world works,” he says.

      At the same time, it was difficult to ignore the economics of energy playing out in his own backyard. When Arkansas, a place that had hardly ever seen earthquakes, started registering them in the wake of fracking in neighboring Oklahoma, it was “like a lightbulb moment” for O’Brien. “I knew this was going to create problems down the line, I knew there’s got to be a better way to do [energy],” he says.

      With the idea of energy alternatives simmering on the back burner, O’Brien enrolled for undergraduate studies at the University of Arkansas. He participated in the school’s marching band — “you show up a week before everyone else and there’s 400 people who automatically become your friends” — and enjoyed the social environment that a large state school could offer.

      O’Brien double-majored in chemical engineering and physics and appreciated “the ability to get your hands dirty on machinery to make things work.” Deciding to begin exploring his interest in energy alternatives, O’Brien researched transition metal dichalcogenides, coatings of which could catalyze the hydrogen evolution reaction and more easily create hydrogen gas, a green energy alternative.

      It was shortly after his sophomore year, however, that O’Brien really found his way in the field of energy alternatives — in nuclear engineering. The American Chemical Society was soliciting student applications for summer study of nuclear chemistry in San Jose, California. O’Brien applied and got accepted. “After years of knowing I wanted to work in green energy but not knowing what that looked like, I very quickly fell in love with [nuclear engineering],” he says. That summer also cemented O’Brien’s decision to attend graduate school. “I came away with this idea of ‘I need to go to grad school because I need to know more about this,’” he says.

      O’Brien especially appreciated an independent project, assigned as part of the summer program: He chose to research nuclear-powered spacecraft. In digging deeper, O’Brien discovered the challenges of powering spacecraft — nuclear was the most viable alternative, but it had to work around extraneous radiation sources in space. Getting to explore national laboratories near San Jose sealed the deal. “I got to visit the National Ignition Facility, which is the big fusion center up there, and just seeing that massive facility entirely designed around this one idea of fusion was kind of mind-blowing to me,” O’Brien says.

      A fresh blueprint for fusion power plants

      O’Brien’s current research at MIT’s Department of Nuclear Science and Engineering (NSE) is equally mind-blowing.

      As the design of new fusion devices kicks into gear, it’s becoming increasingly apparent that the materials we have been using just don’t hold up to the higher temperatures and radiation levels in operating environments, O’Brien says. Additive manufacturing, another term for 3D printing, “opens up a whole new realm of possibilities for what you can do with metals, which is exactly what you’re going to need [to build the next generation of fusion power plants],” he says.

      Metals and ceramics by themselves might not do the job of withstanding high temperatures (750 degrees Celsius is the target) and stresses and radiation, but together they might get there. Although such metal matrix composites have been around for decades, they have been impractical for use in reactors because they’re “difficult to make with any kind of uniformity and really limited in size scale,” O’Brien says. That’s because when you try to place ceramic nanoparticles into a pool of molten metal, they’re going to fall out in whichever direction they want. “3D printing quickly changes that story entirely, to the point where if you want to add these nanoparticles in very specific regions, you have the capability to do that,” O’Brien says.

      O’Brien’s work, which forms the basis of his doctoral thesis and a research paper in the journal Additive Manufacturing, involves implanting metals with ceramic nanoparticles. The net result is a metal matrix composite that is an ideal candidate for fusion devices, especially for the vacuum vessel component, which must be able to withstand high temperatures, extremely corrosive molten salts, and internal helium gas from nuclear transmutation.

      O’Brien’s work focuses on nickel superalloys like Inconel 718, which are especially robust candidates because they can withstand higher operating temperatures while retaining strength. Helium embrittlement, where bubbles of helium caused by fusion neutrons lead to weakness and failure, is a problem with Inconel 718, but composites exhibit potential to overcome this challenge.

      To create the composites, first a mechanical milling process coats the ceramic onto the metal particles. The ceramic nanoparticles act as reinforcing strength agents, especially at high temperatures, and make materials last longer. The nanoparticles also absorb helium and radiation defects when uniformly dispersed, which prevent these damage agents from all getting to the grain boundaries.

      The composite then goes through a 3D printing process called powder bed fusion (non-nuclear fusion), where a laser passes over a bed of this powder melting it into desired shapes. “By coating these particles with the ceramic and then only melting very specific regions, we keep the ceramics in the areas that we want, and then you can build up and have a uniform structure,” O’Brien says.

      Printing an exciting future

      The 3D printing of nuclear materials exhibits such promise that O’Brien is looking at pursuing the prospect after his doctoral studies. “The concept of these metal matrix composites and how they can enhance material property is really interesting,” he says. Scaling it up commercially through a startup company is on his radar.

      For now, O’Brien is enjoying research and catching an occasional Broadway show with his wife. While the band nerd doesn’t pick up his saxophone much anymore, he does enjoy driving up to New Hampshire and going backpacking. “That’s my newfound hobby,” O’Brien says, “since I started grad school.” More

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      in Energy

      Manufacturing a cleaner future

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      Manufacturing had a big summer. The CHIPS and Science Act, signed into law in August, represents a massive investment in U.S. domestic manufacturing. The act aims to drastically expand the U.S. semiconductor industry, strengthen supply chains, and invest in R&D for new technological breakthroughs. According to John Hart, professor of mechanical engineering and director of the Laboratory for Manufacturing and Productivity at MIT, the CHIPS Act is just the latest example of significantly increased interest in manufacturing in recent years.

      “You have multiple forces working together: reflections from the pandemic’s impact on supply chains, the geopolitical situation around the world, and the urgency and importance of sustainability,” says Hart. “This has now aligned incentives among government, industry, and the investment community to accelerate innovation in manufacturing and industrial technology.”

      Hand-in-hand with this increased focus on manufacturing is a need to prioritize sustainability.

      Roughly one-quarter of greenhouse gas emissions came from industry and manufacturing in 2020. Factories and plants can also deplete local water reserves and generate vast amounts of waste, some of which can be toxic.

      To address these issues and drive the transition to a low-carbon economy, new products and industrial processes must be developed alongside sustainable manufacturing technologies. Hart sees mechanical engineers as playing a crucial role in this transition.

      “Mechanical engineers can uniquely solve critical problems that require next-generation hardware technologies, and know how to bring their solutions to scale,” says Hart.

      Several fast-growing companies founded by faculty and alumni from MIT’s Department of Mechanical Engineering offer solutions for manufacturing’s environmental problem, paving the path for a more sustainable future.

      Gradiant: Cleantech water solutions

      Manufacturing requires water, and lots of it. A medium-sized semiconductor fabrication plant uses upward of 10 million gallons of water a day. In a world increasingly plagued by droughts, this dependence on water poses a major challenge.

      Gradiant offers a solution to this water problem. Co-founded by Anurag Bajpayee SM ’08, PhD ’12 and Prakash Govindan PhD ’12, the company is a pioneer in sustainable — or “cleantech” — water projects.

      As doctoral students in the Rohsenow Kendall Heat Transfer Laboratory, Bajpayee and Govindan shared a pragmatism and penchant for action. They both worked on desalination research — Bajpayee with Professor Gang Chen and Govindan with Professor John Lienhard.

      Inspired by a childhood spent during a severe drought in Chennai, India, Govindan developed for his PhD a humidification-dehumidification technology that mimicked natural rainfall cycles. It was with this piece of technology, which they named Carrier Gas Extraction (CGE), that the duo founded Gradiant in 2013.

      The key to CGE lies in a proprietary algorithm that accounts for variability in the quality and quantity in wastewater feed. At the heart of the algorithm is a nondimensional number, which Govindan proposes one day be called the “Lienhard Number,” after his doctoral advisor.

      “When the water quality varies in the system, our technology automatically sends a signal to motors within the plant to adjust the flow rates to bring back the nondimensional number to a value of one. Once it’s brought back to a value of one, you’re running in optimal condition,” explains Govindan, who serves as chief operating officer of Gradiant.

      This system can treat and clean the wastewater produced by a manufacturing plant for reuse, ultimately conserving millions of gallons of water each year.

      As the company has grown, the Gradiant team has added new technologies to their arsenal, including Selective Contaminant Extraction, a cost-efficient method that removes only specific contaminants, and a brine-concentration method called Counter-Flow Reverse Osmosis. They now offer a full technology stack of water and wastewater treatment solutions to clients in industries including pharmaceuticals, energy, mining, food and beverage, and the ever-growing semiconductor industry.

      “We are an end-to-end water solutions provider. We have a portfolio of proprietary technologies and will pick and choose from our ‘quiver’ depending on a customer’s needs,” says Bajpayee, who serves as CEO of Gradiant. “Customers look at us as their water partner. We can take care of their water problem end-to-end so they can focus on their core business.”

      Gradiant has seen explosive growth over the past decade. With 450 water and wastewater treatment plants built to date, they treat the equivalent of 5 million households’ worth of water each day. Recent acquisitions saw their total employees rise to above 500.

      The diversity of Gradiant’s solutions is reflected in their clients, who include Pfizer, AB InBev, and Coca-Cola. They also count semiconductor giants like Micron Technology, GlobalFoundries, Intel, and TSMC among their customers.

      “Over the last few years, we have really developed our capabilities and reputation serving semiconductor wastewater and semiconductor ultrapure water,” says Bajpayee.

      Semiconductor manufacturers require ultrapure water for fabrication. Unlike drinking water, which has a total dissolved solids range in the parts per million, water used to manufacture microchips has a range in the parts per billion or quadrillion.

      Currently, the average recycling rate at semiconductor fabrication plants — or fabs — in Singapore is only 43 percent. Using Gradiant’s technologies, these fabs can recycle 98-99 percent of the 10 million gallons of water they require daily. This reused water is pure enough to be put back into the manufacturing process.

      “What we’ve done is eliminated the discharge of this contaminated water and nearly eliminated the dependence of the semiconductor fab on the public water supply,” adds Bajpayee.

      With new regulations being introduced, pressure is increasing for fabs to improve their water use, making sustainability even more important to brand owners and their stakeholders.

      As the domestic semiconductor industry expands in light of the CHIPS and Science Act, Gradiant sees an opportunity to bring their semiconductor water treatment technologies to more factories in the United States.

      Via Separations: Efficient chemical filtration

      Like Bajpayee and Govindan, Shreya Dave ’09, SM ’12, PhD ’16 focused on desalination for her doctoral thesis. Under the guidance of her advisor Jeffrey Grossman, professor of materials science and engineering, Dave built a membrane that could enable more efficient and cheaper desalination.

      A thorough cost and market analysis brought Dave to the conclusion that the desalination membrane she developed would not make it to commercialization.

      “The current technologies are just really good at what they do. They’re low-cost, mass produced, and they worked. There was no room in the market for our technology,” says Dave.

      Shortly after defending her thesis, she read a commentary article in the journal Nature that changed everything. The article outlined a problem. Chemical separations that are central to many manufacturing processes require a huge amount of energy. Industry needed more efficient and cheaper membranes. Dave thought she might have a solution.

      After determining there was an economic opportunity, Dave, Grossman, and Brent Keller PhD ’16 founded Via Separations in 2017. Shortly thereafter, they were chosen as one of the first companies to receive funding from MIT’s venture firm, The Engine.

      Currently, industrial filtration is done by heating chemicals at very high temperatures to separate compounds. Dave likens it to making pasta by boiling all of the water off until it evaporates and all you are left with is the pasta noodles. In manufacturing, this method of chemical separation is extremely energy-intensive and inefficient.

      Via Separations has created the chemical equivalent of a “pasta strainer.” Rather than using heat to separate, their membranes “strain” chemical compounds. This method of chemical filtration uses 90 percent less energy than standard methods.

      While most membranes are made of polymers, Via Separations’ membranes are made with graphene oxide, which can withstand high temperatures and harsh conditions. The membrane is calibrated to the customer’s needs by altering the pore size and tuning the surface chemistry.

      Currently, Dave and her team are focusing on the pulp and paper industry as their beachhead market. They have developed a system that makes the recovery of a substance known as “black liquor” more energy efficient.

      “When tree becomes paper, only one-third of the biomass is used for the paper. Currently the most valuable use for the remaining two-thirds not needed for paper is to take it from a pretty dilute stream to a pretty concentrated stream using evaporators by boiling off the water,” says Dave.

      This black liquor is then burned. Most of the resulting energy is used to power the filtration process.

      “This closed-loop system accounts for an enormous amount of energy consumption in the U.S. We can make that process 84 percent more efficient by putting the ‘pasta strainer’ in front of the boiler,” adds Dave.

      VulcanForms: Additive manufacturing at industrial scale

      The first semester John Hart taught at MIT was a fruitful one. He taught a course on 3D printing, broadly known as additive manufacturing (AM). While it wasn’t his main research focus at the time, he found the topic fascinating. So did many of the students in the class, including Martin Feldmann MEng ’14.

      After graduating with his MEng in advanced manufacturing, Feldmann joined Hart’s research group full time. There, they bonded over their shared interest in AM. They saw an opportunity to innovate with an established metal AM technology, known as laser powder bed fusion, and came up with a concept to realize metal AM at an industrial scale.

      The pair co-founded VulcanForms in 2015.

      “We have developed a machine architecture for metal AM that can build parts with exceptional quality and productivity,” says Hart. “And, we have integrated our machines in a fully digital production system, combining AM, postprocessing, and precision machining.”

      Unlike other companies that sell 3D printers for others to produce parts, VulcanForms makes and sells parts for their customers using their fleet of industrial machines. VulcanForms has grown to nearly 400 employees. Last year, the team opened their first production factory, known as “VulcanOne,” in Devens, Massachusetts.

      The quality and precision with which VulcanForms produces parts is critical for products like medical implants, heat exchangers, and aircraft engines. Their machines can print layers of metal thinner than a human hair.

      “We’re producing components that are difficult, or in some cases impossible to manufacture otherwise,” adds Hart, who sits on the company’s board of directors.

      The technologies developed at VulcanForms may help lead to a more sustainable way to manufacture parts and products, both directly through the additive process and indirectly through more efficient, agile supply chains.

      One way that VulcanForms, and AM in general, promotes sustainability is through material savings.

      Many of the materials VulcanForms uses, such as titanium alloys, require a great deal of energy to produce. When titanium parts are 3D-printed, substantially less of the material is used than in a traditional machining process. This material efficiency is where Hart sees AM making a large impact in terms of energy savings.

      Hart also points out that AM can accelerate innovation in clean energy technologies, ranging from more efficient jet engines to future fusion reactors.

      “Companies seeking to de-risk and scale clean energy technologies require know-how and access to advanced manufacturing capability, and industrial additive manufacturing is transformative in this regard,” Hart adds.

      LiquiGlide: Reducing waste by removing friction

      There is an unlikely culprit when it comes to waste in manufacturing and consumer products: friction. Kripa Varanasi, professor of mechanical engineering, and the team at LiquiGlide are on a mission to create a frictionless future, and substantially reduce waste in the process.

      Founded in 2012 by Varanasi and alum David Smith SM ’11, LiquiGlide designs custom coatings that enable liquids to “glide” on surfaces. Every last drop of a product can be used, whether it’s being squeezed out of a tube of toothpaste or drained from a 500-liter tank at a manufacturing plant. Making containers frictionless substantially minimizes wasted product, and eliminates the need to clean a container before recycling or reusing.

      Since launching, the company has found great success in consumer products. Customer Colgate utilized LiquiGlide’s technologies in the design of the Colgate Elixir toothpaste bottle, which has been honored with several industry awards for design. In a collaboration with world- renowned designer Yves Béhar, LiquiGlide is applying their technology to beauty and personal care product packaging. Meanwhile, the U.S. Food and Drug Administration has granted them a Device Master Filing, opening up opportunities for the technology to be used in medical devices, drug delivery, and biopharmaceuticals.

      In 2016, the company developed a system to make manufacturing containers frictionless. Called CleanTanX, the technology is used to treat the surfaces of tanks, funnels, and hoppers, preventing materials from sticking to the side. The system can reduce material waste by up to 99 percent.

      “This could really change the game. It saves wasted product, reduces wastewater generated from cleaning tanks, and can help make the manufacturing process zero-waste,” says Varanasi, who serves as chair at LiquiGlide.

      LiquiGlide works by creating a coating made of a textured solid and liquid lubricant on the container surface. When applied to a container, the lubricant remains infused within the texture. Capillary forces stabilize and allow the liquid to spread on the surface, creating a continuously lubricated surface that any viscous material can slide right down. The company uses a thermodynamic algorithm to determine the combinations of safe solids and liquids depending on the product, whether it’s toothpaste or paint.

      The company has built a robotic spraying system that can treat large vats and tanks at manufacturing plants on site. In addition to saving companies millions of dollars in wasted product, LiquiGlide drastically reduces the amount of water needed to regularly clean these containers, which normally have product stuck to the sides.

      “Normally when you empty everything out of a tank, you still have residue that needs to be cleaned with a tremendous amount of water. In agrochemicals, for example, there are strict regulations about how to deal with the resulting wastewater, which is toxic. All of that can be eliminated with LiquiGlide,” says Varanasi.

      While the closure of many manufacturing facilities early in the pandemic slowed down the rollout of CleanTanX pilots at plants, things have picked up in recent months. As manufacturing ramps up both globally and domestically, Varanasi sees a growing need for LiquiGlide’s technologies, especially for liquids like semiconductor slurry.

      Companies like Gradiant, Via Separations, VulcanForms, and LiquiGlide demonstrate that an expansion in manufacturing industries does not need to come at a steep environmental cost. It is possible for manufacturing to be scaled up in a sustainable way.

      “Manufacturing has always been the backbone of what we do as mechanical engineers. At MIT in particular, there is always a drive to make manufacturing sustainable,” says Evelyn Wang, Ford Professor of Engineering and former head of the Department of Mechanical Engineering. “It’s amazing to see how startups that have an origin in our department are looking at every aspect of the manufacturing process and figuring out how to improve it for the health of our planet.”

      As legislation like the CHIPS and Science Act fuels growth in manufacturing, there will be an increased need for startups and companies that develop solutions to mitigate the environmental impact, bringing us closer to a more sustainable future. More

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      in Energy

      With new heat treatment, 3D-printed metals can withstand extreme conditions

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      A new MIT-developed heat treatment transforms the microscopic structure of 3D-printed metals, making the materials stronger and more resilient in extreme thermal environments. The technique could make it possible to 3D print high-performance blades and vanes for power-generating gas turbines and jet engines, which would enable new designs with improved fuel consumption and energy efficiency.

      Today’s gas turbine blades are manufactured through conventional casting processes in which molten metal is poured into complex molds and directionally solidified. These components are made from some of the most heat-resistant metal alloys on Earth, as they are designed to rotate at high speeds in extremely hot gas, extracting work to generate electricity in power plants and thrust in jet engines.

      There is growing interest in manufacturing turbine blades through 3D-printing, which, in addition to its environmental and cost benefits, could allow manufacturers to quickly produce more intricate, energy-efficient blade geometries. But efforts to 3D-print turbine blades have yet to clear a big hurdle: creep.

      In metallurgy, creep refers to a metal’s tendency to permanently deform in the face of persistent mechanical stress and high temperatures. While researchers have explored printing turbine blades, they have found that the printing process produces fine grains on the order of tens to hundreds of microns in size — a microstructure that is especially vulnerable to creep.

      “In practice, this would mean a gas turbine would have a shorter life or less fuel efficiency,” says Zachary Cordero, the Boeing Career Development Professor in Aeronautics and Astronautics at MIT. “These are costly, undesirable outcomes.”

      Cordero and his colleagues found a way to improve the structure of 3D-printed alloys by adding an additional heat-treating step, which transforms the as-printed material’s fine grains into much larger “columnar” grains — a sturdier microstructure that should minimize the material’s creep potential, since the “columns” are aligned with the axis of greatest stress. The researchers say the method, outlined today in Additive Manufacturing, clears the way for industrial 3D-printing of gas turbine blades.

      “In the near future, we envision gas turbine manufacturers will print their blades and vanes at large-scale additive manufacturing plants, then post-process them using our heat treatment,” Cordero says. “3D-printing will enable new cooling architectures that can improve the thermal efficiency of a turbine, so that it produces the same amount of power while burning less fuel and ultimately emits less carbon dioxide.”

      Cordero’s co-authors on the study are lead author Dominic Peachey, Christopher Carter, and Andres Garcia-Jimenez at MIT, Anugrahaprada Mukundan and Marie-Agathe Charpagne of the University of Illinois at Urbana-Champaign, and Donovan Leonard of Oak Ridge National Laboratory.

      Triggering a transformation

      The team’s new method is a form of directional recrystallization — a heat treatment that passes a material through a hot zone at a precisely controlled speed to meld a material’s many microscopic grains into larger, sturdier, and more uniform crystals.

      Directional recrystallization was invented more than 80 years ago and has been applied to wrought materials. In their new study, the MIT team adapted directional recrystallization for 3D-printed superalloys.

      The team tested the method on 3D-printed nickel-based superalloys — metals that are typically cast and used in gas turbines. In a series of experiments, the researchers placed 3D-printed samples of rod-shaped superalloys in a room-temperature water bath placed just below an induction coil. They slowly drew each rod out of the water and through the coil at various speeds, dramatically heating the rods to temperatures varying between 1,200 and 1,245 degrees Celsius.

      They found that drawing the rods at a particular speed (2.5 millimeters per hour) and through a specific temperature (1,235 degrees Celsius) created a steep thermal gradient that triggered a transformation in the material’s printed, fine-grained microstructure.

      “The material starts as small grains with defects called dislocations, that are like a mangled spaghetti,” Cordero explains. “When you heat this material up, those defects can annihilate and reconfigure, and the grains are able to grow. We’re continuously elongating the grains by consuming the defective material and smaller grains — a process termed recrystallization.”

      Creep away

      After cooling the heat-treated rods, the researchers examined their microstructure using optical and electron microscopy, and found that the material’s printed microscopic grains were replaced with “columnar” grains, or long crystal-like regions that were significantly larger than the original grains.

      “We’ve completely transformed the structure,” says lead author Dominic Peachey. “We show we can increase the grain size by orders of magnitude, to massive columnar grains, which theoretically should lead to dramatic improvements in creep properties.”

      The team also showed they could manipulate the draw speed and temperature of the rod samples to tailor the material’s growing grains, creating regions of specific grain size and orientation. This level of control, Cordero says, can enable manufacturers to print turbine blades with site-specific microstructures that are resilient to specific operating conditions.

      Cordero plans to test the heat treatment on 3D-printed geometries that more closely resemble turbine blades. The team is also exploring ways to speed up the draw rate, as well as test a heat-treated structure’s resistance to creep. Then, they envision that the heat treatment could enable the practical application of 3D-printing to produce industrial-grade turbine blades, with more complex shapes and patterns.

      “New blade and vane geometries will enable more energy-efficient land-based gas turbines, as well as, eventually, aeroengines,” Cordero notes. “This could from a baseline perspective lead to lower carbon dioxide emissions, just through improved efficiency of these devices.”

      This research was supported, in part, by the U.S. Office of Naval Research. More

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      in Security

      MIT engineers introduce the Oreometer

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      When you twist open an Oreo cookie to get to the creamy center, you’re mimicking a standard test in rheology — the study of how a non-Newtonian material flows when twisted, pressed, or otherwise stressed. MIT engineers have now subjected the sandwich cookie to rigorous materials tests to get to the center of a tantalizing question: Why does the cookie’s cream stick to just one wafer when twisted apart?

      “There’s the fascinating problem of trying to get the cream to distribute evenly between the two wafers, which turns out to be really hard,” says Max Fan, an undergraduate in MIT’s Department of Mechanical Engineering.

      In pursuit of an answer, the team subjected cookies to standard rheology tests in the lab and found that no matter the flavor or amount of stuffing, the cream at the center of an Oreo almost always sticks to one wafer when twisted open. Only for older boxes of cookies does the cream sometimes separate more evenly between both wafers.

      The researchers also measured the torque required to twist open an Oreo, and found it to be similar to the torque required to turn a doorknob and about 1/10th what’s needed to twist open a bottlecap. The cream’s failure stress — i.e. the force per area required to get the cream to flow, or deform — is twice that of cream cheese and peanut butter, and about the same magnitude as mozzarella cheese. Judging from the cream’s response to stress, the team classifies its texture as “mushy,” rather than brittle, tough, or rubbery.

      So, why does the cookie’s cream glom to one side rather than splitting evenly between both? The manufacturing process may be to blame.

      “Videos of the manufacturing process show that they put the first wafer down, then dispense a ball of cream onto that wafer before putting the second wafer on top,” says Crystal Owens, an MIT mechanical engineering PhD candidate who studies the properties of complex fluids. “Apparently that little time delay may make the cream stick better to the first wafer.”

      The team’s study isn’t simply a sweet diversion from bread-and-butter research; it’s also an opportunity to make the science of rheology accessible to others. To that end, the researchers have designed a 3D-printable “Oreometer” — a simple device that firmly grasps an Oreo cookie and uses pennies and rubber bands to control the twisting force that progressively twists the cookie open. Instructions for the tabletop device can be found here.

      The new study, “On Oreology, the fracture and flow of ‘milk’s favorite cookie,’” appears today in Kitchen Flows, a special issue of the journal Physics of Fluids. It was conceived of early in the Covid-19 pandemic, when many scientists’ labs were closed or difficult to access. In addition to Owens and Fan, co-authors are mechanical engineering professors Gareth McKinley and A. John Hart.

      Confection connection

      A standard test in rheology places a fluid, slurry, or other flowable material onto the base of an instrument known as a rheometer. A parallel plate above the base can be lowered onto the test material. The plate is then twisted as sensors track the applied rotation and torque.

      Owens, who regularly uses a laboratory rheometer to test fluid materials such as 3D-printable inks, couldn’t help noting a similarity with sandwich cookies. As she writes in the new study:

      “Scientifically, sandwich cookies present a paradigmatic model of parallel plate rheometry in which a fluid sample, the cream, is held between two parallel plates, the wafers. When the wafers are counter-rotated, the cream deforms, flows, and ultimately fractures, leading to separation of the cookie into two pieces.”

      While Oreo cream may not appear to possess fluid-like properties, it is considered a “yield stress fluid” — a soft solid when unperturbed that can start to flow under enough stress, the way toothpaste, frosting, certain cosmetics, and concrete do.

      Curious as to whether others had explored the connection between Oreos and rheology, Owens found mention of a 2016 Princeton University study in which physicists first reported that indeed, when twisting Oreos by hand, the cream almost always came off on one wafer.

      “We wanted to build on this to see what actually causes this effect and if we could control it if we mounted the Oreos carefully onto our rheometer,” she says.

      Play video

      Cookie twist

      In an experiment that they would repeat for multiple cookies of various fillings and flavors, the researchers glued an Oreo to both the top and bottom plates of a rheometer and applied varying degrees of torque and angular rotation, noting the values  that successfully twisted each cookie apart. They plugged the measurements into equations to calculate the cream’s viscoelasticity, or flowability. For each experiment, they also noted the cream’s “post-mortem distribution,” or where the cream ended up after twisting open.

      In all, the team went through about 20 boxes of Oreos, including regular, Double Stuf, and Mega Stuf levels of filling, and regular, dark chocolate, and “golden” wafer flavors. Surprisingly, they found that no matter the amount of cream filling or flavor, the cream almost always separated onto one wafer.

      “We had expected an effect based on size,” Owens says. “If there was more cream between layers, it should be easier to deform. But that’s not actually the case.”

      Curiously, when they mapped each cookie’s result to its original position in the box, they noticed the cream tended to stick to the inward-facing wafer: Cookies on the left side of the box twisted such that the cream ended up on the right wafer, whereas cookies on the right side separated with cream mostly on the left wafer. They suspect this box distribution may be a result of post-manufacturing environmental effects, such as heating or jostling that may cause cream to peel slightly away from the outer wafers, even before twisting.

      The understanding gained from the properties of Oreo cream could potentially be applied to the design of other complex fluid materials.

      “My 3D printing fluids are in the same class of materials as Oreo cream,” she says. “So, this new understanding can help me better design ink when I’m trying to print flexible electronics from a slurry of carbon nanotubes, because they deform in almost exactly the same way.”

      As for the cookie itself, she suggests that if the inside of Oreo wafers were more textured, the cream might grip better onto both sides and split more evenly when twisted.

      “As they are now, we found there’s no trick to twisting that would split the cream evenly,” Owens concludes.

      This research was supported, in part, by the MIT UROP program and by the National Defense Science and Engineering Graduate Fellowship Program. More

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      in Environment

      How molecular biology could reduce global food insecurity

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      Staple crops like rice, maize, and wheat feed over half of the global population, but they are increasingly vulnerable to severe environmental risks. The effects of climate change, including changing temperatures, rainfall variability, shifting patterns of agricultural pests and diseases, and saltwater intrusion from sea-level rise, all contribute to decreased crop yields. As these effects continue to worsen, there will be less food available for a rapidly growing population. 

      Mary Gehring, associate professor of biology and a member of the Whitehead Institute for Biomedical Research, is growing increasingly concerned about the potentially catastrophic impacts of climate change and has resolved to do something about it.

      The Gehring Lab’s primary research focus is plant epigenetics, which refers to the heritable information that influences plant cellular function but is not encoded in the DNA sequence itself. This research is adding to our fundamental understanding of plant biology and could have agricultural applications in the future. “I’ve been working with seeds for many years,” says Gehring. “Understanding how seeds work is going to be critical to agriculture and food security,” she explains.

      Laying the foundation

      Gehring is using her expertise to help crops develop climate resilience through a 2021 seed grant from MIT’s Abdul Latif Jameel Water and Food Systems Lab (J-WAFS). Her research is aimed at discovering how we can accelerate the production of genetic diversity to generate plant populations that are better suited to challenging environmental conditions.

      Genetic variation gives rise to phenotypic variations that can help plants adapt to a wider range of climates. Traits such as flood resistance and salt tolerance will become more important as the effects of climate change are realized. However, many important plant species do not appear to have much standing genetic variation, which could become an issue if farmers need to breed their crops quickly to adapt to a changing climate. 

      In researching a nutritious crop that has little genetic variation, Gehring came across the pigeon pea, a species she had never worked with before. Pigeon peas are a legume eaten in Asia, Africa, and Latin America. They have some of the highest levels of protein in a seed, so eating more pigeon peas could decrease our dependence on meat, which has numerous negative environmental impacts. Pigeon peas also have a positive impact on the environment; as perennial plants, they live for three to five years and sequester carbon for longer periods of time. They can also help with soil restoration. “Legumes are very interesting because they’re nitrogen-fixers, so they create symbioses with microbes in the soil and fix nitrogen, which can renew soils,” says Gehring. Furthermore, pigeon peas are known to be drought-resistant, so they will likely become more attractive as many farmers transition away from water-intensive crops.

      Developing a strategy

      Using the pigeon pea plant, Gehring began to explore a universal technology that would increase the amount of genetic diversity in plants. One method her research group chose is to enhance transposable element proliferation. Genomes are made up of genes that make proteins, but large fractions are also made up of transposable elements. In fact, about 45 percent of the human genome is made up of transposable elements, Gehring notes. The primary function of transposable elements is to make more copies of themselves. Since our bodies do not need an infinite number of these copies, there are systems in place to “silence” them from copying. 

      Gehring is trying to reverse that silencing so that the transposable elements can move freely throughout the genome, which could create genetic variation by creating mutations or altering the promoter of a gene — that is, what controls a certain gene’s expression. Scientists have traditionally initiated mutagenesis by using a chemical that changes single base pairs in DNA, or by using X-rays, which can cause very large chromosome breaks. Gehring’s research team is attempting to induce transposable element proliferation by treatment with a suite of chemicals that inhibit transposable element silencing. The goal is to impact multiple sites in the genome simultaneously. “This is unexplored territory where you’re changing 50 genes at a time, or 100, rather than just one,” she explains. “It’s a fairly risky project, but sometimes you have to be ambitious and take risks.”

      Looking forward

      Less than one year after receiving the J-WAFS seed grant, the research project is still in its early stages. Despite various restrictions due to the ongoing pandemic, the Gehring Lab is now generating data on the Arabidopsis plant that will be applied to pigeon pea plants. However, Gehring expects it will take a good amount of time to complete this research phase, considering the pigeon pea plants can take upward of 100 days just to flower. While it might take time, this technology could help crops withstand the effects of climate change, ultimately contributing to J-WAFS’ goal of finding solutions to food system challenges.

      “Climate change is not something any of us can ignore. … If one of us has the ability to address it, even in a very small way, that’s important to try to pursue,” Gehring remarks. “It’s part of our responsibility as scientists to take what knowledge we have and try to apply it to these sorts of problems.” More

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      in Energy

      Design’s new frontier

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      In the 1960s, the advent of computer-aided design (CAD) sparked a revolution in design. For his PhD thesis in 1963, MIT Professor Ivan Sutherland developed Sketchpad, a game-changing software program that enabled users to draw, move, and resize shapes on a computer. Over the course of the next few decades, CAD software reshaped how everything from consumer products to buildings and airplanes were designed.

      “CAD was part of the first wave in computing in design. The ability of researchers and practitioners to represent and model designs using computers was a major breakthrough and still is one of the biggest outcomes of design research, in my opinion,” says Maria Yang, Gail E. Kendall Professor and director of MIT’s Ideation Lab.

      Innovations in 3D printing during the 1980s and 1990s expanded CAD’s capabilities beyond traditional injection molding and casting methods, providing designers even more flexibility. Designers could sketch, ideate, and develop prototypes or models faster and more efficiently. Meanwhile, with the push of a button, software like that developed by Professor Emeritus David Gossard of MIT’s CAD Lab could solve equations simultaneously to produce a new geometry on the fly.

      In recent years, mechanical engineers have expanded the computing tools they use to ideate, design, and prototype. More sophisticated algorithms and the explosion of machine learning and artificial intelligence technologies have sparked a second revolution in design engineering.

      Researchers and faculty at MIT’s Department of Mechanical Engineering are utilizing these technologies to re-imagine how the products, systems, and infrastructures we use are designed. These researchers are at the forefront of the new frontier in design.

      Computational design

      Faez Ahmed wants to reinvent the wheel, or at least the bicycle wheel. He and his team at MIT’s Design Computation & Digital Engineering Lab (DeCoDE) use an artificial intelligence-driven design method that can generate entirely novel and improved designs for a range of products — including the traditional bicycle. They create advanced computational methods to blend human-driven design with simulation-based design.

      “The focus of our DeCoDE lab is computational design. We are looking at how we can create machine learning and AI algorithms to help us discover new designs that are optimized based on specific performance parameters,” says Ahmed, an assistant professor of mechanical engineering at MIT.

      For their work using AI-driven design for bicycles, Ahmed and his collaborator Professor Daniel Frey wanted to make it easier to design customizable bicycles, and by extension, encourage more people to use bicycles over transportation methods that emit greenhouse gases.

      To start, the group gathered a dataset of 4,500 bicycle designs. Using this massive dataset, they tested the limits of what machine learning could do. First, they developed algorithms to group bicycles that looked similar together and explore the design space. They then created machine learning models that could successfully predict what components are key in identifying a bicycle style, such as a road bike versus a mountain bike.

      Once the algorithms were good enough at identifying bicycle designs and parts, the team proposed novel machine learning tools that could use this data to create a unique and creative design for a bicycle based on certain performance parameters and rider dimensions.

      Ahmed used a generative adversarial network — or GAN — as the basis of this model. GAN models utilize neural networks that can create new designs based on vast amounts of data. However, using GAN models alone would result in homogeneous designs that lack novelty and can’t be assessed in terms of performance. To address these issues in design problems, Ahmed has developed a new method which he calls “PaDGAN,” performance augmented diverse GAN.

      “When we apply this type of model, what we see is that we can get large improvements in the diversity, quality, as well as novelty of the designs,” Ahmed explains.

      Using this approach, Ahmed’s team developed an open-source computational design tool for bicycles freely available on their lab website. They hope to further develop a set of generalizable tools that can be used across industries and products.

      Longer term, Ahmed has his sights set on loftier goals. He hopes the computational design tools he develops could lead to “design democratization,” putting more power in the hands of the end user.

      “With these algorithms, you can have more individualization where the algorithm assists a customer in understanding their needs and helps them create a product that satisfies their exact requirements,” he adds.

      Using algorithms to democratize the design process is a goal shared by Stefanie Mueller, an associate professor in electrical engineering and computer science and mechanical engineering.

      Personal fabrication

      Platforms like Instagram give users the freedom to instantly edit their photographs or videos using filters. In one click, users can alter the palette, tone, and brightness of their content by applying filters that range from bold colors to sepia-toned or black-and-white. Mueller, X-Window Consortium Career Development Professor, wants to bring this concept of the Instagram filter to the physical world.

      “We want to explore how digital capabilities can be applied to tangible objects. Our goal is to bring reprogrammable appearance to the physical world,” explains Mueller, director of the HCI Engineering Group based out of MIT’s Computer Science and Artificial Intelligence Laboratory.

      Mueller’s team utilizes a combination of smart materials, optics, and computation to advance personal fabrication technologies that would allow end users to alter the design and appearance of the products they own. They tested this concept in a project they dubbed “Photo-Chromeleon.”

      First, a mix of photochromic cyan, magenta, and yellow dies are airbrushed onto an object — in this instance, a 3D sculpture of a chameleon. Using software they developed, the team sketches the exact color pattern they want to achieve on the object itself. An ultraviolet light shines on the object to activate the dyes.

      To actually create the physical pattern on the object, Mueller has developed an optimization algorithm to use alongside a normal office projector outfitted with red, green, and blue LED lights. These lights shine on specific pixels on the object for a given period of time to physically change the makeup of the photochromic pigments.

      “This fancy algorithm tells us exactly how long we have to shine the red, green, and blue light on every single pixel of an object to get the exact pattern we’ve programmed in our software,” says Mueller.

      Giving this freedom to the end user enables limitless possibilities. Mueller’s team has applied this technology to iPhone cases, shoes, and even cars. In the case of shoes, Mueller envisions a shoebox embedded with UV and LED light projectors. Users could put their shoes in the box overnight and the next day have a pair of shoes in a completely new pattern.

      Mueller wants to expand her personal fabrication methods to the clothes we wear. Rather than utilize the light projection technique developed in the PhotoChromeleon project, her team is exploring the possibility of weaving LEDs directly into clothing fibers, allowing people to change their shirt’s appearance as they wear it. These personal fabrication technologies could completely alter consumer habits.

      “It’s very interesting for me to think about how these computational techniques will change product design on a high level,” adds Mueller. “In the future, a consumer could buy a blank iPhone case and update the design on a weekly or daily basis.”

      Computational fluid dynamics and participatory design

      Another team of mechanical engineers, including Sili Deng, the Brit (1961) & Alex (1949) d’Arbeloff Career Development Professor, are developing a different kind of design tool that could have a large impact on individuals in low- and middle-income countries across the world.

      As Deng walked down the hallway of Building 1 on MIT’s campus, a monitor playing a video caught her eye. The video featured work done by mechanical engineers and MIT D-Lab on developing cleaner burning briquettes for cookstoves in Uganda. Deng immediately knew she wanted to get involved.

      “As a combustion scientist, I’ve always wanted to work on such a tangible real-world problem, but the field of combustion tends to focus more heavily on the academic side of things,” explains Deng.

      After reaching out to colleagues in MIT D-Lab, Deng joined a collaborative effort to develop a new cookstove design tool for the 3 billion people across the world who burn solid fuels to cook and heat their homes. These stoves often emit soot and carbon monoxide, leading not only to millions of deaths each year, but also worsening the world’s greenhouse gas emission problem.

      The team is taking a three-pronged approach to developing this solution, using a combination of participatory design, physical modeling, and experimental validation to create a tool that will lead to the production of high-performing, low-cost energy products.

      Deng and her team in the Deng Energy and Nanotechnology Group use physics-based modeling for the combustion and emission process in cookstoves.

      “My team is focused on computational fluid dynamics. We use computational and numerical studies to understand the flow field where the fuel is burned and releases heat,” says Deng.

      These flow mechanics are crucial to understanding how to minimize heat loss and make cookstoves more efficient, as well as learning how dangerous pollutants are formed and released in the process.

      Using computational methods, Deng’s team performs three-dimensional simulations of the complex chemistry and transport coupling at play in the combustion and emission processes. They then use these simulations to build a combustion model for how fuel is burned and a pollution model that predicts carbon monoxide emissions.

      Deng’s models are used by a group led by Daniel Sweeney in MIT D-Lab to test the experimental validation in prototypes of stoves. Finally, Professor Maria Yang uses participatory design methods to integrate user feedback, ensuring the design tool can actually be used by people across the world.

      The end goal for this collaborative team is to not only provide local manufacturers with a prototype they could produce themselves, but to also provide them with a tool that can tweak the design based on local needs and available materials.

      Deng sees wide-ranging applications for the computational fluid dynamics her team is developing.

      “We see an opportunity to use physics-based modeling, augmented with a machine learning approach, to come up with chemical models for practical fuels that help us better understand combustion. Therefore, we can design new methods to minimize carbon emissions,” she adds.

      While Deng is utilizing simulations and machine learning at the molecular level to improve designs, others are taking a more macro approach.

      Designing intelligent systems

      When it comes to intelligent design, Navid Azizan thinks big. He hopes to help create future intelligent systems that are capable of making decisions autonomously by using the enormous amounts of data emerging from the physical world. From smart robots and autonomous vehicles to smart power grids and smart cities, Azizan focuses on the analysis, design, and control of intelligent systems.

      Achieving such massive feats takes a truly interdisciplinary approach that draws upon various fields such as machine learning, dynamical systems, control, optimization, statistics, and network science, among others.

      “Developing intelligent systems is a multifaceted problem, and it really requires a confluence of disciplines,” says Azizan, assistant professor of mechanical engineering with a dual appointment in MIT’s Institute for Data, Systems, and Society (IDSS). “To create such systems, we need to go beyond standard approaches to machine learning, such as those commonly used in computer vision, and devise algorithms that can enable safe, efficient, real-time decision-making for physical systems.”

      For robot control to work in the complex dynamic environments that arise in the real world, real-time adaptation is key. If, for example, an autonomous vehicle is going to drive in icy conditions or a drone is operating in windy conditions, they need to be able to adapt to their new environment quickly.

      To address this challenge, Azizan and his collaborators at MIT and Stanford University have developed a new algorithm that combines adaptive control, a powerful methodology from control theory, with meta learning, a new machine learning paradigm.

      “This ‘control-oriented’ learning approach outperforms the existing ‘regression-oriented’ methods, which are mostly focused on just fitting the data, by a wide margin,” says Azizan.

      Another critical aspect of deploying machine learning algorithms in physical systems that Azizan and his team hope to address is safety. Deep neural networks are a crucial part of autonomous systems. They are used for interpreting complex visual inputs and making data-driven predictions of future behavior in real time. However, Azizan urges caution.

      “These deep neural networks are only as good as their training data, and their predictions can often be untrustworthy in scenarios not covered by their training data,” he says. Making decisions based on such untrustworthy predictions could lead to fatal accidents in autonomous vehicles or other safety-critical systems.

      To avoid these potentially catastrophic events, Azizan proposes that it is imperative to equip neural networks with a measure of their uncertainty. When the uncertainty is high, they can then be switched to a “safe policy.”

      In pursuit of this goal, Azizan and his collaborators have developed a new algorithm known as SCOD — Sketching Curvature of Out-of-Distribution Detection. This framework could be embedded within any deep neural network to equip them with a measure of their uncertainty.

      “This algorithm is model-agnostic and can be applied to neural networks used in various kinds of autonomous systems, whether it’s drones, vehicles, or robots,” says Azizan.

      Azizan hopes to continue working on algorithms for even larger-scale systems. He and his team are designing efficient algorithms to better control supply and demand in smart energy grids. According to Azizan, even if we create the most efficient solar panels and batteries, we can never achieve a sustainable grid powered by renewable resources without the right control mechanisms.

      Mechanical engineers like Ahmed, Mueller, Deng, and Azizan serve as the key to realizing the next revolution of computing in design.

      “MechE is in a unique position at the intersection of the computational and physical worlds,” Azizan says. “Mechanical engineers build a bridge between theoretical, algorithmic tools and real, physical world applications.”

      Sophisticated computational tools, coupled with the ground truth mechanical engineers have in the physical world, could unlock limitless possibilities for design engineering, well beyond what could have been imagined in those early days of CAD. More