Monday, 26 March 2018 13:42

2018 Summer Scholars selected

MIT Materials Research Laboratory announces 12 recipients of Research Experience for Undergraduates (REU) internships.
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Twelve recipients of Research Experience for Undergraduates (REU) internships will select their own projects from MIT faculty presentations given during the first few days of the Summer Scholars program. Image, Denis Paiste, MRL.

The MIT Materials Research Laboratory [MRL] has selected 12 top-ranking undergraduates to conduct graduate-level research on the MIT campus in Cambridge, Mass., from June 17 to August 11, 2018.

Interns will select their own projects from MIT faculty presentations given during the first few days of the program. Last year’s group, for example, conducted supervised research on projects in materials science, photonics, energy, and biomedical fields.

This year’s Summer Scholars and their major fields of study are:

- Danielle Beatty, University of Utah, Materials Science and Engineering

- Alvin Chang, Oregon State University, Chemical Engineering, Biological Engineering, with minor in Entrepreneurship

- Simon Egner, University of Illinois at Urbana-Champaign, Materials Science and Engineering

- Elizabeth Hallett, University of Arkansas-Fayetteville, Chemical Engineering

- Julianna LaLane, University of Puerto Rico at Mayaguez, Mechanical Engineering

- Michael Molinski, University of Rhode Island, Chemical Engineering

- Abigail Nason, University of Florida, Materials Science and Engineering,

- Fernando Nieves Munoz, University of Puerto Rico, Mayaguez, Mechanical Engineering

- Sarai Patterson, University of Utah, Materials Science and Engineering

- Sabrina Shen, Johns Hopkins University, Materials Science and Engineering

- Ryan Tollefsen, Oregon State University, Physics

- Ekaterina Tsotsos, Brown University, Materials Engineering

Summer Scholars serve as interns through the MIT MRL and are supported in part by the National Science Foundation’s Research Experience for Undergraduates (REU) program, which is administered by the MIT Materials Research Science and Engineering Center, and the AIM Photonics Academy.

The program, started in 1983, has brought hundreds of the best science and engineering undergraduates in the country to MIT for graduate-level materials research.

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MIT professor devises new ways to generate useful chemicals and fuels from renewable resources.
MIT Profile Roman PRESS Web
Newly tenured MIT Department of Chemical Engineering faculty member Yuriy Roman says, "The most rewarding aspect of my profession is to work with these extremely talented and bright students. Image, M. Scott Brauer.

A couple of years into graduate school, Yuriy Roman had what he calls a “tipping point” in his career. He realized that all of the classes he had taken were leading him toward a deep understanding of the concepts he needed to design his own solutions to chemical problems.

“All the classes I had taken suddenly came together, and that’s when I started understanding why I needed to know something about thermodynamics, kinetics, and transport. All of these concepts that I had seen as more theoretical things in my classes, I could now see being applied together to solve a problem. That really was what changed everything for me,” he says.

As a newly tenured faculty member in MIT’s Department of Chemical Engineering, Roman now tries to guide his students toward their own tipping points.
“It’s amazing to see it happen with my students,” says Roman, noting that working with students is one of his favorite things about being an MIT professor. His students also make major contributions to his lab’s mission: coming up with new catalysts to produce fuels, plastics, and other useful substances in a more efficient, sustainable manner.

“To me, the most rewarding aspect of my profession is to work with these extremely talented and bright students,” Roman says. “They really are great at coming up with outside-of-the-box concepts, and I love that. I think MIT’s biggest asset is precisely that, the students. To me it’s a pleasure to work with them and learn from them as well, and hopefully have the opportunity to teach them some of the things that I know.”

Chemical synthesis

Roman, who grew up in Mexico City, loved chemistry from a young age. “I just liked to play with things like soap and bleach, which maybe wasn’t the safest thing,” he recalls. Another favorite activity was juicing cabbages to produce a pH indicator. (Red cabbage contains a chemical called anthocyanin that changes color when exposed to acidic or basic environments.)

Roman’s mother was originally from Belarus, and with his multicultural background he developed a strong interest in learning about other cultures and visiting other countries. He won a full scholarship to Monterrey Institute of Technology and Higher Education, in Mexico, for high school and college, but during his first year of college, he became interested in going abroad to finish his degree.

A friend who was then an undergraduate at MIT encouraged Roman to apply to schools in the United States, and he ended up transferring to the University of Pennsylvania.

“My parents were very surprised. In Mexico, it is common to live with your parents long after finishing college. The concept of leaving for college is almost nonexistent,” Roman says.

Roman decided to study chemical engineering, allowing him to combine his love for chemical reactions and his desire to follow in the footsteps of a brother who was an engineer. After graduating, he planned to look for a job in the chemical industry, but his then-girlfriend, now his wife, was planning to begin medical school. She suggested that he go to graduate school with her, so they both ended up attending the University of Wisconsin at Madison.

There, Roman studied with James Dumesic, a chemistry professor who works on biofuels. For his PhD thesis, Roman devised a process to generate a chemical called hydroxymethylfurfural (HMF) from sugars derived from biomass. HMF is a “platform chemical” that can be converted into many different end products, including fuels.

After finishing graduate school, Roman thought he would go to work for a chemical company, but at Dumesic’s suggestion he decided to go into academia instead.
“When I started interviewing at different universities, I realized that as a professor, you can have a lot of freedom to explore ideas and tackle problems long-term, and you can still have a lot of contact with industry,” he says. “You have more control over your time and where you spend it, in terms of investing effort toward basic science.”

Out of graduate school, he got a job offer at MIT but first spent two years doing a postdoc at Caltech, while his wife did her residency at the University of California at Los Angeles. Working with Mark Davis, a professor of chemical engineering, Roman began studying materials called zeolites, which have pores the same size as many common molecules. Confining molecules in these pores allows for certain chemical reactions to occur much faster than they otherwise would, Roman says.

Davis also instilled in Roman the importance of designing his own catalysts rather than relying on those developed by others, which allows for more control over chemical reactions and the resulting materials. While many research groups focus either on designing catalysts or on using existing catalysts to come up with novel ways to synthesize materials, Roman believes it is critical to work on both. 

“When you are in control of synthesizing your own catalysts, you can do much more systematic studies. You have the ability to manipulate things at will,” he says. “It’s working at this juncture of synthesis and catalysis that is the key to discovering new chemistry.”

Green chemistry

After arriving at MIT in 2010, Roman launched his lab with a focus on designing catalysts that can generate new and interesting materials. One key area of research is the conversion of biomass components, such as lignin, into fuels and chemicals. One of the biggest challenges in this type of synthesis is to selectively remove oxygen atoms from these molecules, which usually have many more oxygen atoms than fuels do.

During a brainstorming session, Roman and his students came up with the idea of using a metal oxide catalyst in which some oxygen atoms were removed from the surface, creating small pockets known as “vacancies.” Oxygenated molecules can be precisely anchored in those vacancies, allowing their carbon-oxygen bonds to be easily broken so the oxygen can be replaced with hydrogen.

In another project, Roman’s lab developed a more sustainable alternative to catalysts made from precious metals such as platinum and palladium. These metals are used in many renewable-energy technologies, including fuel cells and lithium-air batteries, but they are among the Earth’s scarcest metals.

“If we were to go from our current fleet of vehicles with internal combustion engines to a fuel cell fleet, there’s not enough platinum in the world to sustain that amount,” Roman says. “You need to use Earth-abundant materials because there simply aren’t enough of these other precious materials to do it.”

In 2014, Roman and his students showed that they could create powerful catalysts from compounds called metal carbides, made from plentiful metals such as tungsten, coated with just a thin layer of a rare metal such as platinum.

Developing and promoting this kind of sustainable technology is one of Roman’s biggest research priorities.

“It’s a tremendous battle because the energy sector is just so large. The scale is so big and the infrastructure that’s already in place for petroleum-based fuel is so extensive. But it’s important for us to develop technologies for renewable resources and really curb our emissions of greenhouse gases,” he says. “Big, hard problems. That’s what we’re going after.”

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Anne Trafton | MIT News Office
March 22, 2018

With an atomic structure resembling a Japanese basketweaving pattern, “kagome metal” exhibits exotic, quantum behavior.

MIT Kagome Metal 01 PRESS Web
An illustration depicting a kagome metal — an electrically conducting crystal, made from layers of iron and tin atoms, with each atomic layer arranged in the repeating pattern of a kagome lattice. Images by Felice Frankel; Illustration overlays by Chelsea Turner

A motif of Japanese basketweaving known as the kagome pattern has preoccupied physicists for decades. Kagome baskets are typically made from strips of bamboo woven into a highly symmetrical pattern of interlaced, corner-sharing triangles.

If a metal or other conductive material could be made to resemble such a kagome pattern at the atomic scale, with individual atoms arranged in similar triangular patterns, it should in theory exhibit exotic electronic properties.

In a paper published March 19, 2018, in Nature, physicists from MIT, Harvard University, and Lawrence Berkeley National Laboratory report that they have for the first time produced a kagome metal — an electrically conducting crystal, made from layers of iron and tin atoms, with each atomic layer arranged in the repeating pattern of a kagome lattice.

When they flowed a current across the kagome layers within the crystal, the researchers observed that the triangular arrangement of atoms induced strange, quantum-like behaviors in the passing current. Instead of flowing straight through the lattice, electrons instead veered, or bent back within the lattice.

This behavior is a three-dimensional cousin of the so-called Quantum Hall effect, in which electrons flowing through a two-dimensional material will exhibit a “chiral, topological state,” in which they bend into tight, circular paths and flow along edges without losing energy.

“By constructing the kagome network of iron, which is inherently magnetic, this exotic behavior persists to room temperature and higher,” says Joseph Checkelsky, assistant professor of physics at MIT. “The charges in the crystal feel not only the magnetic fields from these atoms, but also a purely quantum-mechanical magnetic force from the lattice. This could lead to perfect conduction, akin to superconductivity, in future generations of materials.”

To explore these findings, the team measured the energy spectrum within the crystal, using a modern version of an effect first discovered by Heinrich Hertz and explained by Einstein, known as the photoelectric effect.

“Fundamentally, the electrons are first ejected from the material’s surface and are then detected as a function of takeoff angle and kinetic energy,” says Riccardo Comin, an assistant professor of physics at MIT. “The resulting images are a very direct snapshot of the electronic levels occupied by electrons, and in this case they revealed the creation of nearly massless ‘Dirac’ particles, an electrically charged version of photons, the quanta of light.”

The spectra revealed that electrons flow through the crystal in a way that suggests the originally massless electrons gained a relativistic mass, similar to particles known as massive Dirac fermions. Theoretically, this is explained by the presence of the lattice’s constituent iron and tin atoms. The former are magnetic and give rise to a “handedness,” or chirality. The latter possess a heavier nuclear charge, producing a large local electric field. As an external current flows by, it senses the tin’s field not as an electric field but as a magnetic one, and bends away.

The research team was led by Checkelsky and Comin, as well as graduate students Linda Ye and Min Gu Kang in collaboration with Liang Fu, the Biedenharn Associate Professor of Physics, and postdoc Junwei Liu. The team also includes Christina Wicker ’17, research scientist Takehito Suzuki of MIT, Felix von Cube and David Bell of Harvard, and Chris Jozwiak, Aaron Bostwick, and Eli Rotenberg of Lawrence Berkeley National Laboratory.

“No alchemy required”

Physicists have theorized for decades that electronic materials could support exotic Quantum Hall behavior with their inherent magnetic character and lattice geometry. It wasn’t until several years ago that researchers made progress in realizing such materials.

“The community realized, why not make the system out of something magnetic, and then the system’s inherent magnetism could perhaps drive this behavior,” says Checkelsky, who at the time was working as a researcher at the University of Tokyo.

This eliminated the need for laboratory produced fields, typically 1 million times as strong as the Earth’s magnetic field, needed to observe this behavior.

“Several research groups were able to induce a Quantum Hall effect this way, but still at ultracold temperatures a few degrees above absolute zero — the result of shoehorning magnetism into a material where it did not naturally occur,” Checkelsky says.

MIT Kagome Metal 02 PRESS Web
Assistant professor of physics at MIT Joe Checkelsky (left to right), graduate students Linda Ye and Min Gu Kang, and assistant professor of physics at MIT Riccardo Comin. Image, Takehito

At MIT, Checkelsky has instead looked for ways to drive this behavior with “instrinsic magnetism.” A key insight, motivated by the doctoral work of Evelyn Tang PhD ’15 and Professor Xiao-Gang Wen, was to seek this behavior in the kagome lattice. To do so, first author Ye ground together iron and tin, then heated the resulting powder in a furnace, producing crystals at about 750 degrees Celsius — the temperature at which iron and tin atoms prefer to arrange in a kagome-like pattern. She then submerged the crystals in an ice bath to enable the lattice patterns to remain stable at room temperature.

“The kagome pattern has big empty spaces that might be easy to weave by hand, but are often unstable in crystalline solids which prefer the best packing of atoms,” Ye says. “The trick here was to fill these voids with a second type of atom in a structure that was at least stable at high temperatures. Realizing these quantum materials doesn’t need alchemy, but instead materials science and patience.”

Bending and skipping toward zero-energy loss

Once the researchers grew several samples of crystals, each about a millimeter wide, they handed the samples off to collaborators at Harvard, who imaged the individual atomic layers within each crystal using transmission electron microscopy. The resulting images revealed that the arrangement of iron and tin atoms within each layer resembled the triangular patterns of the kagome lattice. Specifically, iron atoms were positioned at the corners of each triangle, while a single tin atom sat within the larger hexagonal space created between the interlacing triangles.

Ye then ran an electric current through the crystalline layers and monitored their flow via electrical voltages they produced. She found that the charges deflected in a manner that seemed two-dimensional, despite the three-dimensional nature of the crystals. The definitive proof came from the photoelectron experiments conducted by co-first author Kang who, in concert with the LBNL team, was able to show that the electronic spectra corresponded to effectively two-dimensional electrons.

“As we looked closely at the electronic bands, we noticed something unusual,” Kang adds. “The electrons in this magnetic material behaved as massive Dirac particles, something that had been predicted long ago but never been seen before in these systems.”

“The unique ability of this material to intertwine magnetism and topology suggests that they may well engender other emergent phenomena,” Comin says. “Our next goal is to detect and manipulate the edge states which are the very consequence of the topological nature of these newly discovered quantum electronic phases.”

Looking further, the team is now investigating ways to stabilize other more highly two-dimensional kagome lattice structures. Such materials, if they can be synthesized, could be used to explore not only devices with zero energy loss, such as dissipationless power lines, but also applications toward quantum computing.

“For new directions in quantum information science there is a growing interest in novel quantum circuits with pathways that are dissipationless and chiral,” Checkelsky says. “These kagome metals offer a new materials design pathway to realizing such new platforms for quantum circuitry.”

This research was supported in part by the Gordon and Betty Moore Foundation and the National Science Foundation.

– Jennifer Chu | MIT News Office
March 19, 2018

Wednesday, 28 February 2018 14:34

Study reveals why polymer stents failed

Microscopic flaws in material structure can lead to stent deformation after implantation.
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Researchers hope that their work will lead to a new approach to designing and evaluating polymer stents and other types of degradable medical devices. Image, Pei-Jiang Wang

Many patients with heart disease have a metal stent implanted to keep their coronary artery open and prevent blood clotting that can lead to heart attacks. One drawback to these stents is that long-term use can eventually damage the artery.

Several years ago, in hopes of overcoming that issue, a new type of stent made from biodegradable polymers was introduced. Stent designers hoped that these devices would eventually be absorbed by the blood vessel walls, removing the risk of long-term implantation. At first, these stents appeared to be working well in patients, but after a few years these patients experienced more heart attacks than patients with metal stents, and the polymer stents were taken off the market.

MIT researchers in the Institute for Medical Engineering and Science and the Department of Materials Science and Engineering have now discovered why these stents failed. Their study also reveals why the problems were not uncovered during the development process: The evaluation procedures, which were based on those used for metal stents, were not well-suited to evaluating polymer stents.

“People have been evaluating polymer materials as if they were metals, but metals and polymers don’t behave the same way,” says Elazer Edelman, the Thomas D. and Virginia W. Cabot Professor of Health Sciences and Technology at MIT. “People were looking at the wrong metrics, they were looking at the wrong timescales, and they didn’t have the right tools.”

The researchers hope that their work will lead to a new approach to designing and evaluating polymer stents and other types of degradable medical devices.

“When we use polymers to make these devices, we need to start thinking about how the fabrication techniques will affect the microstructure, and how the microstructure will affect the device performance,” says lead author Pei-Jiang Wang, a Boston University graduate student who is doing his PhD thesis with Edelman.

Edelman is the senior author of the paper, which appears in the Proceedings of the National Academy of Sciences the week of Feb. 26. Other authors include MIT research scientist Nicola Ferralis, MIT professor of materials science and engineering Jeffrey Grossman, and National University of Ireland Galway professor of engineering Claire Conway.

Microstructural flaws

The degradable stents are made from a polymer called poly-l-lactic acid (pLLA), which is also used in dissolvable sutures. Preclinical testing (studies done in the lab and with animal models) did not reveal any cause for concern. In human patients the stents appeared stable for the first year, but then problems began to arise. After three years, over 10 percent of patients had experienced a heart attack, including fatal heart attacks, or had to go through another medical intervention. That is double the rate seen in patients with metal stents.

After the stents were taken off the market, the team decided to try to figure out if there were any warning signs that could have been detected earlier. To do this, they used Raman spectroscopy to analyze the microstructure of the stents. This technique, which uses light to measure energy shifts in molecular vibrations, offers detailed information about the chemical composition of a material. Ferralis and Grossman modified and optimized the technique for studying stents.

The researchers found that at the microscopic level, polymer stents have a heterogeneous structure that eventually leads to structural collapse. While the outer layers of the stent have a smooth crystalline structure made of highly aligned polymers, the inner core tends to have a less ordered structure. When the stent is inflated, these regions are disrupted, potentially causing early loss of integrity in parts of the structure.

“Because the nonuniform degradation will cause certain locations to degrade faster, it will promote large deformations, potentially causing flow disruption,” Wang says.

When the stents become deformed, they can block blood flow, leading to clotting and potentially heart attacks. The researchers believe that the information they gained in this study could help stent designers come up with alternative approaches to fabricating stents, allowing them to possibly eliminate some of the structural irregularities.

A silent problem

Another reason that these problems weren’t detected earlier, according to the researchers, is that many preclinical tests were conducted for only about six months. During this time, the polymer devices were beginning to degrade at the microscopic level, but these flaws couldn’t be detected with the tools scientists were using to analyze them. Visible deformations did not appear until much later.

“In this period of time, they don’t visibly erode. The problem is silent,” Edelman says. “But by the end of three years, there’s a huge problem.”

The researchers believe that their new method for analyzing the device’s microstructure could help scientists better evaluate new stents as well as other types of degradable polymer devices.

“This method provides a tool that allows you to look at a metric that very early on tells you something about what will happen much later,” Edelman says. “If you know about potential issues in advance, you can have a better idea of where to look in animal models and clinical models for safety issues.”back to newsletter

The research was funded by Boston Scientific Corporation and the National Institutes of Health.

Anne Trafton | MIT News Office
February 26, 2018

Friday, 23 February 2018 16:13

Physicists create new form of light

Newly observed optical state could enable quantum computing with photons.
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Scientists at MIT, Harvard University, and elsewhere have now demonstrated that photons can be made to interact — an accomplishment that could open a path toward using photons in quantum computing, if not in light sabers. Image, Christine Daniloff, MIT

Try a quick experiment: Take two flashlights into a dark room and shine them so that their light beams cross. Notice anything peculiar? The rather anticlimactic answer is, probably not. That’s because the individual photons that make up light do not interact. Instead, they simply pass each other by, like indifferent spirits in the night.

But what if light particles could be made to interact, attracting and repelling each other like atoms in ordinary matter? One tantalizing, albeit sci-fi possibility: light sabers — beams of light that can pull and push on each other, making for dazzling, epic confrontations. Or, in a more likely scenario, two beams of light could meet and merge into one single, luminous stream.

It may seem like such optical behavior would require bending the rules of physics, but in fact, scientists at MIT, Harvard University, and elsewhere have now demonstrated that photons can indeed be made to interact — an accomplishment that could open a path toward using photons in quantum computing, if not in light sabers.

In a paper published Feb. 15, 2018, in the journal Science, the team, led by Vladan Vuletic, the Lester Wolfe Professor of Physics at MIT, and Professor Mikhail Lukin from Harvard University, reports that it has observed groups of three photons interacting and, in effect, sticking together to form a completely new kind of photonic matter.

In controlled experiments, the researchers found that when they shone a very weak laser beam through a dense cloud of ultracold rubidium atoms, rather than exiting the cloud as single, randomly spaced photons, the photons bound together in pairs or triplets, suggesting some kind of interaction — in this case, attraction — taking place among them.

While photons normally have no mass and travel at 300,000 kilometers per second (the speed of light), the researchers found that the bound photons actually acquired a fraction of an electron’s mass. These newly weighed-down light particles were also relatively sluggish, traveling about 100,000 times slower than normal noninteracting photons.

Vuletic says the results demonstrate that photons can indeed attract, or entangle each other. If they can be made to interact in other ways, photons may be harnessed to perform extremely fast, incredibly complex quantum computations.

“The interaction of individual photons has been a very long dream for decades,” Vuletic says.
Vuletic’s co-authors include Qi-Yung Liang, Sergio Cantu, and Travis Nicholson from MIT, Lukin and Aditya Venkatramani of Harvard, Michael Gullans and Alexey Gorshkov of the University of Maryland, Jeff Thompson from Princeton University, and Cheng Ching of the University of Chicago.

Biggering and biggering

Vuletic and Lukin lead the MIT-Harvard Center for Ultracold Atoms, and together they have been looking for ways, both theoretical and experimental, to encourage interactions between photons. In 2013, the effort paid off, as the team observed pairs of photons interacting and binding together for the first time, creating an entirely new state of matter.

In their new work, the researchers wondered whether interactions could take place between not only two photons, but more.

“For example, you can combine oxygen molecules to form O2 and O3 (ozone), but not O4, and for some molecules you can’t form even a three-particle molecule,” Vuletic says. “So it was an open question: Can you add more photons to a molecule to make bigger and bigger things?”

To find out, the team used the same experimental approach they used to observe two-photon interactions. The process begins with cooling a cloud of rubidium atoms to ultracold temperatures, just a millionth of a degree above absolute zero. Cooling the atoms slows them to a near standstill. Through this cloud of immobilized atoms, the researchers then shine a very weak laser beam — so weak, in fact, that only a handful of photons travel through the cloud at any one time.

The researchers then measure the photons as they come out the other side of the atom cloud. In the new experiment, they found that the photons streamed out as pairs and triplets, rather than exiting the cloud at random intervals, as single photons having nothing to do with each other.

In addition to tracking the number and rate of photons, the team measured the phase of photons, before and after traveling through the atom cloud. A photon’s phase indicates its frequency of oscillation.

“The phase tells you how strongly they’re interacting, and the larger the phase, the stronger they are bound together,” Venkatramani explains. The team observed that as three-photon particles exited the atom cloud simultaneously, their phase was shifted compared to what it was when the photons didn’t interact at all, and was three times larger than the phase shift of two-photon molecules. “This means these photons are not just each of them independently interacting, but they’re all together interacting strongly.”

Memorable encounters

The researchers then developed a hypothesis to explain what might have caused the photons to interact in the first place. Their model, based on physical principles, puts forth the following scenario: As a single photon moves through the cloud of rubidium atoms, it briefly lands on a nearby atom before skipping to another atom, like a bee flitting between flowers, until it reaches the other end.

If another photon is simultaneously traveling through the cloud, it can also spend some time on a rubidium atom, forming a polariton — a hybrid that is part photon, part atom. Then two polaritons can interact with each other via their atomic component. At the edge of the cloud, the atoms remain where they are, while the photons exit, still bound together. The researchers found that this same phenomenon can occur with three photons, forming an even stronger bond than the interactions between two photons.

“What was interesting was that these triplets formed at all,” Vuletic says. “It was also not known whether they would be equally, less, or more strongly bound compared with photon pairs.”

The entire interaction within the atom cloud occurs over a millionth of a second. And it is this interaction that triggers photons to remain bound together, even after they’ve left the cloud.

“What’s neat about this is, when photons go through the medium, anything that happens in the medium, they ‘remember’ when they get out,” Cantu says.

This means that photons that have interacted with each other, in this case through an attraction between them, can be thought of as strongly correlated, or entangled — a key property for any quantum computing bit.

“Photons can travel very fast over long distances, and people have been using light to transmit information, such as in optical fibers,” Vuletic says. “If photons can influence one another, then if you can entangle these photons, and we’ve done that, you can use them to distribute quantum information in an interesting and useful way.”

Going forward, the team will look for ways to coerce other interactions such as repulsion, where photons may scatter off each other like billiard balls.

“It’s completely novel in the sense that we don’t even know sometimes qualitatively what to expect,” Vuletic says. “With repulsion of photons, can they be such that they form a regular pattern, like a crystal of light? Or will something else happen? It’s very uncharted territory.”

This research was supported in part by the National Science Foundation.back to newsletter

– Jennifer Chu | MIT News Office
February 15, 2018

MIT researchers create predictable patterns from unpredictable carbon nanotubes.

Integrating nanoscale fibers such as carbon nanotubes (CNTs) into commercial applications, from coatings for aircraft wings to heat sinks for mobile computing, requires them to be produced in large scale and at low cost. Chemical vapor deposition is a promising approach to manufacture CNTs in the needed scales, but it produces CNTs that are too sparse and compliant for most applications. Applying and evaporating a few drops of a liquid such as acetone to the CNTs is an easy, cost-effective method to more tightly pack them together and increase their stiffness, but until now, there was no way to forecast the geometry of these CNT cells.

MIT researchers have now developed a systematic method to predict the two-dimensional patterns CNT arrays form after they are packed together, or densified, by evaporating drops of either acetone or ethanol. CNT cell size and wall stiffness grow proportionally with cell height, they report in a Communication in the Feb. 14, 2018, issue of Physical Chemistry Chemical Physics [PCCP].

View the embedded image gallery online at:
https://mrl.mit.edu/index.php/tag/research#sigProId61dc469920

One way to think of this CNT behavior is to imagine how entangled fibers such as wet hair or spaghetti collectively reinforce each other. The larger this entangled region is, the higher its resistance to bending will be. Similarly, longer CNTs can better reinforce one another in a cell wall. The researchers also find that CNT binding strength to the base on which they are produced, in this case, silicon, makes an important contribution to predicting the cellular patterns that these CNTs will form.

“These findings are directly applicable to industry because when you use CVD, you get nanotubes that have curvature, randomness and are wavy, and there is a great need for a method that can easily mitigate these defects without breaking the bank,” AeroAstro Postdoc Itai Y. Stein [SM '13, PhD '16] says. Co-authors include materials science and engineering graduate student Ashley L. Kaiser, MechE Postdoc Kehang Cui, and senior author Brian L. Wardle, Professor of Aeronautics and Astronautics.

“From our previous work on aligned carbon nanotubes (CNTs) and their composites, we learned that more tightly packing the CNTs is a highly effective way to engineer their properties,” Wardle says. “The challenging part is to develop a facile way of doing this at scales that are relevant to commercial aircraft (100’s of meters), and the predictive capabilities that we developed here are a large step in that direction."

Detailed measurements

Carbon nanotubes are highly desirable because of their thermal, electrical, and mechanical properties, which are directionally dependent. Earlier work in Wardle’s lab demonstrated that waviness reduces the stiffness of CNT arrays by as little as 100 times, and up to 100,000 times. The technical term for this stiffness, or ability to bend without breaking, is elastic modulus. Carbon nanotubes are from 1,000 to 10,000 times longer than they are thick, so they deform principally along their length.

For an earlier Applied Physics Letters paper, Stein and colleagues used nanoindentation techniques to measure stiffness of aligned carbon nanotube arrays and found them to be 1,000 to 10,000 times less stiff than the theoretical stiffness of individual carbon nanotubes. Stein, Wardle and former visiting MIT graduate student Hülya Cebeci also developed a theoretical model explaining changes at different packing densities of the nanofibers. [Cebeci is now a professor of aerospace engineering at Istanbul Technical University.]

The new work shows that CNTs compacted by the capillary forces from first wetting them with acetone or ethanol and then evaporating the liquid also produces CNTs that are 100s to 1000s of times less stiff than expected by theoretical values. This capillary effect, known as elastocapillarity, is similar to a how a sponge often dries into a more compact shape after being wetted and then dried.

“Our findings all point to the fact that the CNT wall modulus is much lower than the normally assumed value for perfect CNTs because the underlying CNTs are not straight. Our calculations show that the CNT wall is at least two orders of magnitude less stiff than we expect for straight CNTs, so we can conclude that the CNTs must be wavy,” Stein says.

Heat adds strength

The researchers used a heating technique to increase the adhesion of their original, undensified CNT arrays to their silicon wafer substrate. CNTs densified after heat treatment were about four times harder to separate from the silicon base than untreated CNTs. Kaiser and Stein, who share first authorship of the paper, are currently developing an analytical model to describe this phenomenon and tune the adhesion force, which would further enable prediction and control of such structures.

“Many applications of vertically aligned carbon nanotubes (VACNTs), such as electrical interconnects, require much denser arrays of nanotubes than what is typically obtained for as-grown VACNTs synthesized by chemical vapor deposition (CVD),” says Mostafa Bedewy, assistant professor at the University of Pittsburgh, who was not involved in this work. “Hence, methods for post-growth densification, such as those based on leveraging elastocapillarity have previously been shown to create interesting densified CNT structures. However, there is still a need for a better quantitative understanding of the factors that govern cell formation in densified large-area arrays of VACNTs. The new study by the authors contributes to addressing this need by providing experimental results, coupled with modeling insights, correlating parameters such as VACNT height and VACNT-substrate adhesion to the resulting cellular morphology after densification.”

“There are still remaining questions about how the spatial variation of CNT density, tortuosity [twist], and diameter distribution across the VACNT height affects the capillary densification process, especially that vertical gradients of these features can be different when comparing two VACNT arrays having different heights,” Bedewy notes. “Further work incorporating spatial mapping of internal VACNT morphology would be illuminating, although it will be challenging as it requires combining a suite of characterization techniques.”

The variety of length scales and physical and chemical mechanisms present in carbon nanotubes and other nanoscale materials makes it easy to either oversimplify or to focus on the wrong mechanism, Stein cautions. “Our current predictive capabilities from this paper are very useful, because we give other researchers in the field a pragmatic solution for how they could at least get some predictability, so that they can accelerate their materials design process, and have a working prototype sooner,” Stein says. “In the meantime, while other groups can utilize this new information, which is the best we can do given our current data, we are going to work on collecting a richer dataset that will allow us to investigate the underlying mechanisms and thereby enable even better prediction in the future,” he adds.

Picturesque patterns

Graduate student Kaiser, who was a 2016 MIT Summer Scholar, analyzed the densified CNT arrays with scanning electron microscopy [SEM] in the MIT Materials Research Laboratory’s NSF-MRSEC supported Shared Experimental Facilities. While gently applying liquid to the CNT arrays in this study caused them to densify into predictable cells, vigorously immersing the CNTs in liquid imparts much stronger forces to them, forming randomly shaped CNT networks. “When we first started exploring densification methods, I found that this forceful technique densified our CNT arrays into highly unpredictable and interesting patterns. As seen optically and via SEM, these patterns often resembled animals, faces, and even a heart – it was a bit like searching for shapes in the clouds,” Kaiser says. A colorized version of her optical image showing a CNT heart is featured on the cover of the Feb. 14, 2018, print edition of Physical Chemistry Chemical Physics, which coincides with Valentine’s Day.

“I think there is an underlying beauty in this nanofiber self-assembly and densification process, in addition to its practical applications,” Kaiser adds. “The CNTs densify so easily and quickly into patterns after simply being wet by a liquid. Being able to accurately quantify this behavior is exciting, as it may enable the design and manufacture of scalable nanomaterials.”

The ultimate goal of this research is to be able to precisely predict the post-processing nanofiber pattern beforehand, Kaiser says. “When we have a specific end-goal structure in mind, such as this cellular pattern, we’d like to be able to accurately design its geometry based on our process,” Kaiser says. “With that capability, this liquid-based densification technique could be used to create large-scale nanofiber systems for a wide range of applications.”

This work made use of the MIT Materials Research Laboratory Shared Experimental Facilities, which are supported in part by the MRSEC Program of the National Science Foundation, and MIT Microsystems Technology Laboratories. This research was supported in part by Airbus, ANSYS, Embraer, Lockheed Martin, Saab AB, Saertex, and TohoTenax through MIT's Nano-Engineered Composite Aerospace Structures Consortium and by NASA through the Space Technology Research Institute for Ultra-Strong Composites by Computational Design.

Denis Paiste, Materials Research Laboratory
February 14, 2018
 

Machine-learning system finds patterns in materials “recipes,” even when training data is lacking.

 

MIT Materials Synthesis Web
A new machine-learning system for analyzing materials “recipes” uses a variational autoencoder, which squeezes data (left-hand circles) down into a more compact form (center circles) before attempting to re-expand it into its original form (right-hand circles). If the autoencoder is successfully trained, the compact representation will capture the data’s most salient characteristics. Image, Chelsea Turner, MIT

Last month, three MIT materials scientists and their colleagues published a paper describing a new artificial-intelligence system that can pore through scientific papers and extract “recipes” for producing particular types of materials.
That work was envisioned as the first step toward a system that can originate recipes for materials that have been described only theoretically. Now, in a paper in the journal npj Computational Materials, the same three materials scientists, with a colleague in MIT’s Department of Electrical Engineering and Computer Science (EECS), take a further step in that direction, with a new artificial-intelligence system that can recognize higher-level patterns that are consistent across recipes.

For instance, the new system was able to identify correlations between “precursor” chemicals used in materials recipes and the crystal structures of the resulting products. The same correlations, it turned out, had been documented in the literature.

The system also relies on statistical methods that provide a natural mechanism for generating original recipes. In the paper, the researchers use this mechanism to suggest alternative recipes for known materials, and the suggestions accord well with real recipes.

The first author on the new paper is Edward Kim, a graduate student in materials science and engineering. The senior author is his advisor, Elsa Olivetti, the Atlantic Richfield Assistant Professor of Energy Studies in the Department of Materials Science and Engineering (DMSE). They’re joined by Kevin Huang, a postdoc in DMSE, and by Stefanie Jegelka, the X-Window Consortium Career Development Assistant Professor in EECS.

Sparse and scarce

Like many of the best-performing artificial-intelligence systems of the past 10 years, the MIT researchers’ new system is a so-called neural network, which learns to perform computational tasks by analyzing huge sets of training data. Traditionally, attempts to use neural networks to generate materials recipes have run up against two problems, which the researchers describe as sparsity and scarcity.

Any recipe for a material can be represented as a vector, which is essentially a long string of numbers. Each number represents a feature of the recipe, such as the concentration of a particular chemical, the solvent in which it’s dissolved, or the temperature at which a reaction takes place.

Since any given recipe will use only a few of the many chemicals and solvents described in the literature, most of those numbers will be zero. That’s what the researchers mean by “sparse.”

Similarly, to learn how modifying reaction parameters — such as chemical concentrations and temperatures — can affect final products, a system would ideally be trained on a huge number of examples in which those parameters are varied. But for some materials — particularly newer ones — the literature may contain only a few recipes. That’s scarcity.

“People think that with machine learning, you need a lot of data, and if it’s sparse, you need more data,” Kim says. “When you’re trying to focus on a very specific system, where you’re forced to use high-dimensional data but you don’t have a lot of it, can you still use these neural machine-learning techniques?”

Neural networks are typically arranged into layers, each consisting of thousands of simple processing units, or nodes. Each node is connected to several nodes in the layers above and below. Data is fed into the bottom layer, which manipulates it and passes it to the next layer, which manipulates it and passes it to the next, and so on. During training, the connections between nodes are constantly readjusted until the output of the final layer consistently approximates the result of some computation.

The problem with sparse, high-dimensional data is that for any given training example, most nodes in the bottom layer receive no data. It would take a prohibitively large training set to ensure that the network as a whole sees enough data to learn to make reliable generalizations.

Artificial bottleneck

The purpose of the MIT researchers’ network is to distill input vectors into much smaller vectors, all of whose numbers are meaningful for every input. To that end, the network has a middle layer with just a few nodes in it — only two, in some experiments.

The goal of training is simply to configure the network so that its output is as close as possible to its input. If training is successful, then the handful of nodes in the middle layer must somehow represent most of the information contained in the input vector, but in a much more compressed form. Such systems, in which the output attempts to match the input, are called “autoencoders.”

Autoencoding compensates for sparsity, but to handle scarcity, the researchers trained their network on not only recipes for producing particular materials, but also on recipes for producing very similar materials. They used three measures of similarity, one of which seeks to minimize the number of differences between materials — substituting, say, just one atom for another — while preserving crystal structure.

During training, the weight that the network gives example recipes varies according to their similarity scores.

Playing the odds

In fact, the researchers’ network is not just an autoencoder, but what’s called a variational autoencoder. That means that during training, the network is evaluated not only on how well its outputs match its inputs, but also on how well the values taken on by the middle layer accord with some statistical model — say, the familiar bell curve, or normal distribution. That is, across the whole training set, the values taken on by the middle layer should cluster around a central value and then taper off at a regular rate in all directions.

After training a variational autoencoder with a two-node middle layer on recipes for manganese dioxide and related compounds, the researchers constructed a two-dimensional map depicting the values that the two middle nodes took on for each example in the training set.
Remarkably, training examples that used the same precursor chemicals stuck to the same regions of the map, with sharp boundaries between regions. The same was true of training examples that yielded four of manganese dioxide’s common “polymorphs,” or crystal structures. And combining those two mappings indicated correlations between particular precursors and particular crystal structures.

“We thought it was cool that the regions were continuous,” Olivetti says, “because there’s no reason that that should necessarily be true.”

Variational autoencoding is also what enables the researchers’ system to generate new recipes. Because the values taken on by the middle layer adhere to a probability distribution, picking a value from that distribution at random is likely to yield a plausible recipe.

“This actually touches upon various topics that are currently of great interest in machine learning,” Jegelka says. “Learning with structured objects, allowing interpretability by and interaction with experts, and generating structured complex data — we integrate all of these.”

“‘Synthesizability’ is an example of a concept that is central to materials science yet lacks a good physics-based description,” says Bryce Meredig, founder and chief scientist at Citrine Informatics, a company that brings big-data and artificial-intelligence techniques to bear on materials science research. “As a result, computational screens for new materials have been hamstrung for many years by synthetic inaccessibility of the predicted materials. Olivetti and colleagues have taken a novel, data-driven approach to mapping materials syntheses and made an important contribution toward enabling us to computationally identify materials that not only have exciting properties but also can be made practically in the laboratory.”

The research was supported by the National Science Foundation, the Natural Sciences and Engineering Research Council of Canada, the U.S. Office of Naval Research, the MIT Energy Initiative, and the U.S. Department of Energy’s Basic Energy Science Program.

Larry Hardesty | MIT News Office
December 21, 2017

 

 

Tuesday, 19 December 2017 14:36

Engineers create plants that glow

Illumination from nanobionic plants might one day replace some electrical lighting.

 

MIT Glowing Plants Web
Illumination of a book (“Paradise Lost,” by John Milton) with the nanobionic light-emitting plants (two 3.5-week-old watercress plants). The book and the light-emitting watercress plants were placed in front of a reflective paper to increase the influence from the light emitting plants to the book pages. Image, Seon-Yeong Kwak

Imagine that instead of switching on a lamp when it gets dark, you could read by the light of a glowing plant on your desk.

MIT engineers have taken a critical first step toward making that vision a reality. By embedding specialized nanoparticles into the leaves of a watercress plant, they induced the plants to give off dim light for nearly four hours. They believe that, with further optimization, such plants will one day be bright enough to illuminate a workspace.

“The vision is to make a plant that will function as a desk lamp — a lamp that you don’t have to plug in. The light is ultimately powered by the energy metabolism of the plant itself,” says Michael Strano, the Carbon P. Dubbs Professor of Chemical Engineering at MIT and the senior author of the study.

This technology could also be used to provide low-intensity indoor lighting, or to transform trees into self-powered streetlights, the researchers say. MIT postdoc Seon-Yeong Kwak is the lead author of the study, which appears in the journal Nano Letters.

Nanobionic plants

Plant nanobionics, a new research area pioneered by Strano’s lab, aims to give plants novel features by embedding them with different types of nanoparticles. The group’s goal is to engineer plants to take over many of the functions now performed by electrical devices. The researchers have previously designed plants that can detect explosives and communicate that information to a smartphone, as well as plants that can monitor drought conditions.

Lighting, which accounts for about 20 percent of worldwide energy consumption, seemed like a logical next target. “Plants can self-repair, they have their own energy, and they are already adapted to the outdoor environment,” Strano says. “We think this is an idea whose time has come. It’s a perfect problem for plant nanobionics.”

To create their glowing plants, the MIT team turned to luciferase, the enzyme that gives fireflies their glow. Luciferase acts on a molecule called luciferin, causing it to emit light. Another molecule called co-enzyme A helps the process along by removing a reaction byproduct that can inhibit luciferase activity.

The MIT team packaged each of these three components into a different type of nanoparticle carrier. The nanoparticles, which are all made of materials that the U.S. Food and Drug Administration classifies as “generally regarded as safe,” help each component get to the right part of the plant. They also prevent the components from reaching concentrations that could be toxic to the plants.

The researchers used silica nanoparticles about 10 nanometers in diameter to carry luciferase, and they used slightly larger particles of the polymers PLGA and chitosan to carry luciferin and coenzyme A, respectively. To get the particles into plant leaves, the researchers first suspended the particles in a solution. Plants were immersed in the solution and then exposed to high pressure, allowing the particles to enter the leaves through tiny pores called stomata.

Particles releasing luciferin and coenzyme A were designed to accumulate in the extracellular space of the mesophyll, an inner layer of the leaf, while the smaller particles carrying luciferase enter the cells that make up the mesophyll. The PLGA particles gradually release luciferin, which then enters the plant cells, where luciferase performs the chemical reaction that makes luciferin glow.

Video: Melanie Gonick/MIT

The researchers’ early efforts at the start of the project yielded plants that could glow for about 45 minutes, which they have since improved to 3.5 hours. The light generated by one 10-centimeter watercress seedling is currently about one-thousandth of the amount needed to read by, but the researchers believe they can boost the light emitted, as well as the duration of light, by further optimizing the concentration and release rates of the components.

Plant transformation

Previous efforts to create light-emitting plants have relied on genetically engineering plants to express the gene for luciferase, but this is a laborious process that yields extremely dim light. Those studies were performed on tobacco plants and Arabidopsis thaliana, which are commonly used for plant genetic studies. However, the method developed by Strano’s lab could be used on any type of plant. So far, they have demonstrated it with arugula, kale, and spinach, in addition to watercress.

For future versions of this technology, the researchers hope to develop a way to paint or spray the nanoparticles onto plant leaves, which could make it possible to transform trees and other large plants into light sources.

“Our target is to perform one treatment when the plant is a seedling or a mature plant, and have it last for the lifetime of the plant,” Strano says. “Our work very seriously opens up the doorway to streetlamps that are nothing but treated trees, and to indirect lighting around homes.”

The researchers have also demonstrated that they can turn the light off by adding nanoparticles carrying a luciferase inhibitor. This could enable them to eventually create plants that shut off their light emission in response to environmental conditions such as sunlight, the researchers say.

The research was funded by the U.S. Department of Energy.

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Anne Trafton | MIT News Office 
December 12, 2017

 

More than half of Roxbury, Bunker Hill, students who get summer lab experience at MIT go on to earn a four-year degree.
Susan Rosevear Fall 2017 MRS 0541 DP Web
Community college students who experience a summer of research at MIT develop greater self-confidence and better academic skills, with a majority completing a four-year degree, MIT Materials Research Laboratory Education Officer Susan Rosevear told a symposium at the Materials Research Society Fall meeting in Boston on Monday, Nov. 27, 2017. Photo, Denis Paiste, MIT MRL

A summer of research at MIT gives inner-city Boston community college students a pathway toward greater self-confidence, better academic skills and a four-year college degree, MIT Materials Research Laboratory Education Officer Susan Rosevear said Monday, Nov. 27, 2017, during a symposium at the Materials Research Society [MRS] Fall meeting in Boston.

“Many of them have barely heard about materials science when they come to MIT, and by the end of the summer, they get sort of a full dunk into the world of materials science, so they are better informed to go forward,” Rosevear says. Over the past dozen years, 63 students from Roxbury and Bunker Hill Community Colleges have participated in the program at MIT. Of these, 45 went on to earn a four-year degree, with 34 pursuing degrees in science or engineering. Five continued on to graduate school in science or medicine.

The Research Experience for Undergraduates (REU) program is primarily funded through the MIT Materials Research Laboratory’s National Science Foundation-funded Materials Research Science and Engineering Center [NSF-MRSEC]. Bringing in underrepresented, or non-traditional, students from the community colleges broadens the diversity of students in the REU program.

“We are trying, and I think succeeding, in providing opportunities to community college students that they don’t have at their home institutions,” Rosevear says. Students learn to use electron microscopes, X-ray diffraction spectrometers and other advanced materials science characterization tools. Rosevear addressed a session at MRS highlighting collaborations between community colleges and four-year colleges.

In 2005, the MIT MRSEC, then part of the Center for Materials Science and Engineering, began the partnership with Roxbury Community College with seven students participating during its first year. In recent years, the summer program expanded to include community college professors in materials research on campus led by MIT faculty. So far, nine community college professors have participated. CMSE merged in October 2017 with the Materials Processing Center to form the MIT Materials Research Laboratory.

During the fall 2017 semester, Roxbury Community College Chemistry and Biotechnology Professor Kimberly Stieglitz offered a new course at Roxbury Community College, Research Science, [SCI 281] that brought students to the X-ray diffraction facility at MIT to examine their lab samples. “We keep finding new ways to leverage this partnership,” Rosevear says. Stieglitz and other teachers who have participated in the summer teachers’ program at MIT, also have incorporated material from their summer research into their classroom teaching, Rosevear notes.

Students must complete a basic engineering or science course, such as chemistry or biology, to be accepted into the MIT summer program. Community college teachers select the students based on academic record, statements of interest and faculty letters of recommendation. “They’ve been great partners for us, which is really key to the whole thing,” Rosevear explains. “Kimberly [Stieglitz] has told me, once they are selected, just knowing they are going to MIT changes their performance, they become more serious about themselves, their performance, motivation increases, and they have an increased commitment to STEM,” Rosevear says.

CMSE Scholar Kimberly Stieglitz Jode Lavine 9157 DP Web
Roxbury Community College Chemistry and Biotechnology Professor Kimberly Stieglitz [left] discusses her summer research at MIT with JoDe M. Lavine, Bunker Hill Community College Professor and Chairperson of the Engineering & Physical Sciences Department, during the annual Summer Scholars Poster Session on Aug. 3, 2017. Stieglitz worked in the lab of AMAX Career Development Assistant Professor in Materials Science and Engineering Robert J. Macfarlane. Photo, Denis Paiste, MIT MRL.

Over the course of the summer, community college students attend weekly luncheon meetings covering topics such as crafting a high-quality poster presentation, applying to graduate school, understanding patents and trademarks, and pursuing careers in materials science and other engineering fields.

Interest among MIT faculty in hosting community college students continues to grow. “I have people coming to me and say, how do I get one of these students?
The students have sold themselves, is essentially what’s happened,” Rosevear says.

The community college program is distinct from the Summer Scholars program, which is open to undergraduates in science and engineering from across the U.S. and Puerto Rico who are citizens or legal residents. Applications for summer 2018 must be submitted by Feb. 16, 2018.

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Denis Paiste, MIT Materials Research Laboratory
December 19, 2017

Thursday, 07 December 2017 17:31

Engineers 3-D print a “living tattoo”

New technique 3-D prints programmed cells into living devices for first time. 
MIT 3D Living Tattoo
MIT engineers have devised a 3-D printing technique that uses a new kind of ink made from genetically programmed living cells. Courtesy of the researchers

MIT engineers have devised a 3-D printing technique that uses a new kind of ink made from genetically programmed living cells.

The cells are engineered to light up in response to a variety of stimuli. When mixed with a slurry of hydrogel and nutrients, the cells can be printed, layer by layer, to form three-dimensional, interactive structures and devices.

The team has then demonstrated its technique by printing a “living tattoo” — a thin, transparent patch patterned with live bacteria cells in the shape of a tree. Each branch of the tree is lined with cells sensitive to a different chemical or molecular compound. When the patch is adhered to skin that has been exposed to the same compounds, corresponding regions of the tree light up in response.

The researchers, led by Xuanhe Zhao, the Noyce Career Development Professor in MIT’s Department of Mechanical Engineering, and Timothy Lu, associate professor of biological engineering and of electrical engineering and computer science, say that their technique can be used to fabricate “active” materials for wearable sensors and interactive displays. Such materials can be patterned with live cells engineered to sense environmental chemicals and pollutants as well as changes in pH and temperature.

What’s more, the team developed a model to predict the interactions between cells within a given 3-D-printed structure, under a variety of conditions. The team says researchers can use the model as a guide in designing responsive living materials.

Zhao, Lu, and their colleagues have published their results Dec. 5, 2017,  in the journal Advanced Materials. The paper’s co-authors are graduate students Xinyue Liu, Hyunwoo Yuk, Shaoting Lin, German Alberto Parada, Tzu-Chieh Tang, Eléonore Tham, and postdoc Cesar de la Fuente-Nunez.

A hardy alternative

In recent years, scientists have explored a variety of responsive materials as the basis for 3D-printed inks. For instance, scientists have used inks made from temperature-sensitive polymers to print heat-responsive shape-shifting objects. Others have printed photoactivated structures from polymers that shrink and stretch in response to light.

Zhao’s team, working with bioengineers in Lu’s lab, realized that live cells might also serve as responsive materials for 3D-printed inks, particularly as they can be genetically engineered to respond to a variety of stimuli. The researchers are not the first to consider 3-D printing genetically engineered cells; others have attempted to do so using live mammalian cells, but with little success.

“It turns out those cells were dying during the printing process, because mammalian cells are basically lipid bilayer balloons,” Yuk says. “They are too weak, and they easily rupture.”
Instead, the team identified a hardier cell type in bacteria. Bacterial cells have tough cell walls that are able to survive relatively harsh conditions, such as the forces applied to ink as it is pushed through a printer’s nozzle. Furthermore, bacteria, unlike mammalian cells, are compatible with most hydrogels — gel-like materials that are made from a mix of mostly water and a bit of polymer. The group found that hydrogels can provide an aqueous environment that can support living bacteria.

The researchers carried out a screening test to identify the type of hydrogel that would best host bacterial cells. After an extensive search, a hydrogel with pluronic acid was found to be the most compatible material. The hydrogel also exhibited an ideal consistency for 3-D printing.

“This hydrogel has ideal flow characteristics for printing through a nozzle,” Zhao says. “It’s like squeezing out toothpaste. You need [the ink] to flow out of a nozzle like toothpaste, and it can maintain its shape after it’s printed

Video Abstract for Advanced Materials, 2017, 29, 1704821. Reproduced with permission. ©2017, Wiley-VCH Verlag GmbH & Co. KGaA.

From tattoos to living computers

Lu provided the team with bacterial cells engineered to light up in response to a variety of chemical stimuli. The researchers then came up with a recipe for their 3-D ink, using a combination of bacteria, hydrogel, and nutrients to sustain the cells and maintain their functionality. “We found this new ink formula works very well and can print at a high resolution of about 30 micrometers per feature,” Zhao says. “That means each line we print contains only a few cells. We can also print relatively large-scale structures, measuring several centimeters.”

They printed the ink using a custom 3-D printer that they built using standard elements combined with fixtures they machined themselves. To demonstrate the technique, the team printed a pattern of hydrogel with cells in the shape of a tree on an elastomer layer. After printing, they solidified, or cured, the patch by exposing it to ultraviolet radiation. They then adhere the transparent elastomer layer with the living patterns on it, to skin.

To test the patch, the researchers smeared several chemical compounds onto the back of a test subject’s hand, then pressed the hydrogel patch over the exposed skin. Over several hours, branches of the patch’s tree lit up when bacteria sensed their corresponding chemical stimuli. The researchers also engineered bacteria to communicate with each other; for instance they programmed some cells to light up only when they receive a certain signal from another cell. To test this type of communication in a 3-D structure, they printed a thin sheet of hydrogel filaments with “input,” or signal-producing bacteria and chemicals, overlaid with another layer of filaments of an “output,” or signal-receiving bacteria. They found the output filaments lit up only when they overlapped and received input signals from corresponding bacteria .

Yuk says in the future, researchers may use the team’s technique to print “living computers” — structures with multiple types of cells that communicate with each other, passing signals back and forth, much like transistors on a microchip. “This is very future work, but we expect to be able to print living computational platforms that could be wearable,” Yuk says.

For more near-term applications, the researchers are aiming to fabricate customized sensors, in the form of flexible patches and stickers that could be engineered to detect a variety of chemical and molecular compounds. They also envision their technique may be used to manufacture drug capsules and surgical implants, containing cells engineered produce compounds such as glucose, to be released therapeutically over time.

“We can use bacterial cells like workers in a 3-D factory,” Liu says. “They can be engineered to produce drugs within a 3-D scaffold, and applications should not be confined to epidermal devices. As long as the fabrication method and approach are viable, applications such as implants and ingestibles should be possible.”
This research was supported, in part, by the Office of Naval Research, National Science Foundation, National Institutes of Health, and MIT Institute for Soldier Nanotechnologies. 

Jennifer Chu | MIT News Office
December 5, 2017   

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