Thursday, 19 April 2018 10:54

A graphene roll-out

Scalable manufacturing process spools out strips of graphene for use in ultrathin membranes.
MIT Graphene Roll 01
A new manufacturing process produces strips of graphene, at large scale, for use in membrane technologies and other applications. Image, Christine Daniloff, MIT

MIT engineers have developed a continuous manufacturing process that produces long strips of high-quality graphene.

The team’s results are the first demonstration of an industrial, scalable method for manufacturing high-quality graphene that is tailored for use in membranes that filter a variety of molecules, including salts, larger ions, proteins, or nanoparticles. Such membranes should be useful for desalination, biological separation, and other applications.

“For several years, researchers have thought of graphene as a potential route to ultrathin membranes,” says John Hart, associate professor of mechanical engineering and director of the Laboratory for Manufacturing and Productivity at MIT. “We believe this is the first study that has tailored the manufacturing of graphene toward membrane applications, which require the graphene to be seamless, cover the substrate fully, and be of high quality.”

Hart is the senior author on the paper, which appears online in the journal Applied Materials and Interfaces. The study includes first author Piran Kidambi, a former MIT postdoc who is now an assistant professor at Vanderbilt University; MIT graduate students Dhanushkodi Mariappan and Nicholas Dee; Sui Zhang of the National University of Singapore; Andrey Vyatskikh, a former student at the Skolkovo Institute of Science and Technology who is now at Caltech; and Rohit Karnik, an associate professor of mechanical engineering at MIT.

Growing graphene

For many researchers, graphene is ideal for use in filtration membranes. A single sheet of graphene resembles atomically thin chicken wire and is composed of carbon atoms joined in a pattern that makes the material extremely tough and impervious to even the smallest atom, helium.

Researchers, including Karnik’s group, have developed techniques to fabricate graphene membranes and precisely riddle them with tiny holes, or nanopores, the size of which can be tailored to filter out specific molecules. For the most part, scientists synthesize graphene through a process called chemical vapor deposition, in which they first heat a sample of copper foil and then deposit onto it a combination of carbon and other gases.

Graphene-based membranes have mostly been made in small batches in the laboratory, where researchers can carefully control the material’s growth conditions. However, Hart and his colleagues believe that if graphene membranes are ever to be used commercially they will have to be produced in large quantities, at high rates, and with reliable performance.

“We know that for industrialization, it would need to be a continuous process,” Hart says. “You would never be able to make enough by making just pieces. And membranes that are used commercially need to be fairly big ­— some so big that you would have to send a poster-wide sheet of foil into a furnace to make a membrane.”

A factory roll-out

The researchers set out to build an end-to-end, start-to-finish manufacturing process to make membrane-quality graphene.

The team’s setup combines a roll-to-roll approach — a common industrial approach for continuous processing of thin foils — with the common graphene-fabrication technique of chemical vapor deposition, to manufacture high-quality graphene in large quantities and at a high rate. The system consists of two spools, connected by a conveyor belt that runs through a small furnace. The first spool unfurls a long strip of copper foil, less than 1 centimeter wide. When it enters the furnace, the foil is fed through first one tube and then another, in a “split-zone” design.

While the foil rolls through the first tube, it heats up to a certain ideal temperature, at which point it is ready to roll through the second tube, where the scientists pump in a specified ratio of methane and hydrogen gas, which are deposited onto the heated foil to produce graphene.

“Graphene starts forming in little islands, and then those islands grow together to form a continuous sheet,” Hart says. “By the time it’s out of the oven, the graphene should be fully covering the foil in one layer, kind of like a continuous bed of pizza.”

As the graphene exits the furnace, it’s rolled onto the second spool. The researchers found that they were able to feed the foil continuously through the system, producing high-quality graphene at a rate of 5 centimers per minute. Their longest run lasted almost four hours, during which they produced about 10 meters of continuous graphene.

“If this were in a factory, it would be running 24-7,” Hart says. “You would have big spools of foil feeding through, like a printing press.”

Flexible design

Once the researchers produced graphene using their roll-to-roll method, they unwound the foil from the second spool and cut small samples out. They cast the samples with a polymer mesh, or support, using a method developed by scientists at Harvard University, and subsequently etched away the underlying copper.

“If you don’t support graphene adequately, it will just curl up on itself,” Kidambi says. “So you etch copper out from underneath and have graphene directly supported by a porous polymer — which is basically a membrane.”

MIT Graphene Roll 02
The process consists of a “roll-to-roll” system that spools out a ribbon of copper foil from one end, which is fed through a furnace. Methane and hydrogen gas are deposited onto the foil to form graphene, which then exits the furnace and is rolled up for further development. Courtesy of the researchers

The polymer covering contains holes that are larger than graphene’s pores, which Hart says act as microscopic “drumheads,” keeping the graphene sturdy and its tiny pores open.

The researchers performed diffusion tests with the graphene membranes, flowing a solution of water, salts, and other molecules across each membrane. They found that overall, the membranes were able to withstand the flow while filtering out molecules. Their performance was comparable to graphene membranes made using conventional, small-batch approaches.

The team also ran the process at different speeds, with different ratios of methane and hydrogen gas, and characterized the quality of the resulting graphene after each run. They drew up plots to show the relationship between graphene’s quality and the speed and gas ratios of the manufacturing process. Kidambi says that if other designers can build similar setups, they can use the team’s plots to identify the settings they would need to produce a certain quality of graphene.

“The system gives you a great degree of flexibility in terms of what you’d like to tune graphene for, all the way from electronic to membrane applications,” Kidambi says.

Looking forward, Hart says he would like to find ways to include polymer casting and other steps that currently are performed by hand, in the roll-to-roll system.

“In the end-to-end process, we would need to integrate more operations into the manufacturing line,” Hart says. “For now, we’ve demonstrated that this process can be scaled up, and we hope this increases confidence and interest in graphene-based membrane technologies, and provides a pathway to commercialization.”

– Jennifer Chu | MIT News Office
April 17, 2018



MIT graduate engineering, business, science programs ranked highly by U.S. News and World Report for 2019.
MIT Lobby 7 Belcher CPS Web
MIT’s graduate program in engineering has again earned a No. 1 spot in U.S. News and World Report’s annual rankings, a place it has held since 1990, when the magazine first ranked such programs. Pictured is MIT Lobby 7. Photo by Jake Belcher

MIT’s graduate program in engineering has again earned a No. 1 spot in U.S. News and World Report’s annual rankings, a place it has held since 1990, when the magazine first ranked such programs.

The MIT Sloan School of Management also placed highly, occupying the No. 5 spot for the best graduate business program.

This year, U.S. News also ranked the nation’s top PhD programs in the sciences, which it last evaluated in 2014. The magazine awarded No. 1 spots to MIT programs in biology (tied with Stanford University and the University of California at Berkeley), computer science (tied with Carnegie Mellon University, Stanford, and Berkeley), and physics (tied with Stanford). No. 2 spots went to MIT programs in chemistry (tied with Harvard University, Stanford, and Berkeley), earth sciences (tied with Stanford and Berkeley); and mathematics (tied with Harvard, Stanford, and Berkeley).

Among individual engineering disciplines, MIT placed first in six areas: aerospace/aeronautical/astronautical engineering (tied with Caltech), chemical engineering, computer engineering, electrical/electronic/communications engineering (tied with Stanford and Berkeley), materials engineering, and mechanical engineering. It placed second in nuclear engineering.

In the rankings of individual MBA specialties, MIT placed first in information systems and production/operations. It placed second in supply chain/logistics and third in entrepreneurship.

U.S. News does not issue annual rankings for all doctoral programs but revisits many every few years. This year, MIT ranked in the top five for 24 of the 37 science disciplines evaluated.

The magazine bases its rankings of graduate schools of engineering and business on two types of data: reputational surveys of deans and other academic officials, and statistical indicators that measure the quality of a school’s faculty, research, and students. The magazine’s less-frequent rankings of programs in the sciences, social sciences, and humanities are based solely on reputational surveys.

back to newsletterMIT News Office
March 20, 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.
MIT Stent Failure PRESS WEB
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

Thursday, 22 February 2018 14:44

Mapping photonic systems needs through 2035

AIM Photonics participants to take long view at Roadmap Meeting at MIT March 26-27, 2018.
AIM Photonics Academy Fall 2017 Web
Tom Marrapode, Director of Advanced Technology Development at Molex Optical Solutions Group, speaks about work on board-level optical interconnects at the AIM Photonics Academy fall 2017 meeting. Photo, Melissa Renzi, SUNY Polytechnic Institute.

Industry and academic leaders from across the country and around the world will gather at MIT on Monday and Tuesday, March 26-27, 2018, for the spring AIM Photonics Technical Roadmap Meeting, titled “Photonic Integration 2035: Economics, Technology and Manufacturing.”

This marks the 20th year that the Photonics Roadmap meetings have been held. Begun under the Microphotonics Center at MIT as gatherings of 50 experts, the Roadmap meetings have grown to more than 200 people representing the technology supply chain, from materials to systems to end-users.

“This is the premier gathering of leaders implementing photonics technology,” says Professor Lionel Kimerling, executive of AIM Photonics Academy, which is the MIT-based education and workforce development arm of AIM Photonics. AIM Photonics is one of 14 public-private manufacturing innovation institutes created as part of a federal initiative to revitalize American manufacturing.

Participants will “gauge the system requirements and technology needs to maintain the ongoing exponential product ramp in the field,” Kimerling says. The March meeting includes time for breakout groups that focus on different technology areas covered in the Roadmap, where companies that normally compete against one another can participate in productive pre-competitive discussions.

“I have been very engaged in AIM Photonics Academy’s Roadmap meetings and technical working groups,” said Yi Qian, vice president of product management at MRSI. “I want to be part of the discussion with some of the world’s top experts of where integrated photonics is headed.”

At the spring meeting, AIM Photonics Academy and the International Electronics Manufacturing Initiative (iNEMI) plan to incubate Application Interest Groups (AIGs) in sensors, data centers, analog RF signal applications, LIDAR and phased array imaging. These industry-led initiatives have the potential to turn into AIM Photonics-funded technical projects.

The Integrated Photonic Systems Roadmap (IPSR), which can be downloaded from the iNEMI and AIM Photonics Academy websites, is more than 400 pages long, and continues to be updated to include new chapters and findings. Close to 1,000 people from more than 300 organizations in 17 countries have participated in the creation of the Roadmap.

AIM Photonics Academy and iNEMI are also collaborating on a Roadmap workshop at the Optical Fiber Communication Conference March 12, 2018, in San Diego. At that conference, Kimerling and Director of Roadmapping Robert Pfahl will discuss grand challenges and key needs for commercially viable, high-volume manufacturing of photonic-enabled functionality.
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Julie Diop, Materials Research Laboratory, AIM Photonics Academy
February 26, 2018

AIM Photonics Smit Group DP Spring 2017 Web
Eindhoven University of Technology Professor Meint Smit speaks about “Photonic Integrated Circuits: How Foundries Transform Prototyping” during the spring 2017 AIM Photonics Roadmap meeting at MIT. Photo, Denis Paiste, MIT MRL

Assistant professor in EECS and DMSE is developing materials with novel structures and useful applications, including renewable energy and information storage.


Ceramics research Jennifer Rupp headshot MIT Webm
Jennifer Rupp's current ceramics research applications range from battery-based storage for renewable energy, to energy-harvesting systems, to devices used to store data during computation. Photo courtesy of Jennifer Rupp.

Ensuring that her research contributes to society’s well-being is a major driving force for Jennifer Rupp.

“Even if my work is fundamental, I want to think about how it can be useful for society,” says Rupp, the Thomas Lord Assistant Professor of Materials Science and Engineering and an assistant professor in the Department of Electrical Engineering and Computer Science (EECS) at MIT.

Since joining the Department of Materials Science and Engineering in February 2017, she has been focusing not only on the basics of ceramics processing techniques but also on how to further develop those techniques to design new practical devices as well as materials with novel structures. Her current research applications range from battery-based storage for renewable energy, to energy-harvesting systems, to devices used to store data during computation.

Rupp first became intrigued with ceramics during her doctoral studies at ETH Zurich.

“I got particularly interested in how they can influence structures to gain certain functionalities and properties,” she says. During this time, she also became fascinated with how ceramics can contribute to the conversion and storage of energy. The need to transition to a low-carbon energy future motivates much of her work at MIT. “Climate change is happening,” she says. “Even though not everybody may agree on that, it’s a fact.”

One way to tackle the climate change problem is by capitalizing on solar energy. Sunshine falling on the Earth delivers roughly 170,000 terawatts per year — about 10,000 times the energy consumed annually worldwide. “So we have a lot of solar energy,” says Rupp. “The question is, how do we profit the most from it?”

To help convert that solar energy into a renewable fuel, her team is designing a ceramic material that can be used in a solar reactor in which incoming sunlight is controlled to create a heat cycle. During the temperature shifts, the ceramic material incorporates and releases oxygen. At the higher temperature, it loses oxygen; at the lower temperature, it regains the oxygen. When carbon dioxide and water are flushed into the solar reactor during this oxidation process, a split reaction occurs, yielding a combination of carbon monoxide and hydrogen known as syngas, which can be converted catalytically into ethanol, methanol, or other liquid fuels.

While the challenges are many, Rupp says she feels bolstered by the humanitarian ethos at MIT. “At MIT, there are scientists and engineers who care about social issues and try to contribute with science and their problem-solving skills to do more,” she says. “I think this is quite important. MIT gives you strong support to try out even very risky things.”

In addition to continuing her work on new materials, Rupp looks forward to exploring new concepts with her students. During the fall of 2017, she taught two recitation sections of 3.091 (Introduction to Solid State Chemistry), a class that has given thousands of MIT undergraduates a foundation in chemistry from an engineering perspective. This spring, she will begin teaching a new elective for graduate students on ceramics processing and engineering that will delve into making ceramic materials not only on the conventional large-scale level but also as nanofabricated structures and small-system structures for devices that can store and convert energy, compute information, or sense carbon dioxide or various environmental pollutants.

To further engage with students, Rupp has proposed an extracurricular club for them to develop materials science comic strips. The first iteration is available on Instagram (@materialcomics) and it depicts three heroes who jump into various structures to investigate their composition and, naturally, to have adventures. Rupp sees the comics as an exciting avenue to engage the nonscientific community as a whole and to illustrate the structures and compositions of various everyday materials.

“I think it is important to create interest in the topic of materials science across various ages and simply to enjoy the fun in it,” she says.

Rupp says MIT is proving to be a stimulating environment. “Everybody is really committed and open to being creative,” she says. “I think a scientist is not only a teacher or a student; a scientist is someone of any age, of any rank, someone who simply enjoys unlocking creativity to design new materials and devices.”

This article appears in the Autumn 2017 issue of Energy Futures, the magazine of the MIT Energy Initiative.

Kelley Travers | MIT Energy Initiative
MIT News Office, February 9, 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].

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



Scholars will engage in a year of postgraduate leadership studies at Beijing’s Tshingua University. 
MIT Schwarzman 0
Schwarzman Scholars from top left, clockwise: Katheryn Scott, Han Wu, Henry Aspegren, Joshua Woodard. Images courtesy of Schwarzman Scholars. Images courtesy of Schwarzman Scholars.

Three MIT students — Henry Aspegren '17, Katheryn Scott, and Joshua Woodard — were selected as Schwarzman Scholars and will begin postgraduate studies at Tsinghua University in Beijing next fall. An alumnus, Han Wu MEng '15, was also selected for this highly competitive program.

Schwarzman Scholars are chosen based on demonstrated leadership qualities and potential to bridge and understand cultural and political differences. They will live in Beijing for a year of study and cultural immersion, attending lectures, traveling, and developing a better understanding of China.

This year’s four Schwarzman Scholars bring to 11 the total number of MIT winners honored since the scholarship’s inception in 2015. In all, 142 Schwarzman Scholars were selected from over 4,000 applicants. The new class is comprised of students from 39 countries and 97 universities with 41 percent from the United States, 20 percent from China, and 39 percent from the rest of the world. The currently enrolled MIT students were supported by MIT’s Office of Distinguished Fellowships the Presidential Committee on Distinguished Fellowships.

“This year’s winners of the Schwarzman Scholarship exemplify the combination of intellectual prowess and public mindedness that characterizes MIT students at their best,” says Professor William Broadhead, co-chair of the Presidential Committee for Distinguished Fellowships alongside Professor Rebecca Saxe. “Those of us who have had the pleasure of working with them through the application process have been impressed at every turn by their immense potential for local and global leadership. It’s exciting to celebrate with them now; and it will be exciting to see what they do next!”

Henry Aspegren

Henry Aspegren, from Ann Arbor, Michigan, is an MIT master’s student in engineering. He received his BS in electrical engineering and computer science from MIT earlier this year. Aspegren aspires to develop public policy for addressing the new challenges and opportunities created by technology.

Aspegren recognized the economic disparities of the Detroit area growing up, when he played ice hockey on a team with players from manufacturing towns around metro Detroit that had been hit hard by the decline of the auto industry. This reality drew him to think about how economic incentives can stimulate economies, which fueled his academic interests in currency and financial institutions.

At MIT, Aspegren began conducting research in the MIT Media Lab’s Viral Communications Group, where he worked to help build a voting and ranking algorithm to quantify subjective qualities such as emotion across the internet in real time. During his junior year, he participated in the Cambridge MIT Exchange program and received a first from Cambridge University and a full blue in ice hockey.
This past January, Aspegren traveled to Korea through the MIT International Science and Technology Initiatives' Global Teaching Laboratory to lead a robotics workshop in which students programmed a Roomba vaccum cleaner to drive around an obstacle course. He has also interned with the electronic trading team at Goldman Sachs in New York and London, and worked as a software engineer with BetterWorks in Palo Alto.

Aspegren is now completing his MEng degree and conducting research with the MIT Media Lab’s Digital Currency Initiative to examine injustices in financing. This led him to design a block chain-based system for agricultural financing in Latin America in collaboration with the InterAmerican Development Bank.

Aspegren has been an active participant in MIT Athletics, playing club ice hockey throughout his undergraduate and graduate career, and playing on the varsity lacrosse team his freshman year. He is also a brother of Theta Chi Fraternity.

Katheryn Scott

Katheryn "Kate" Scott, from Barrington, Illinois, is an MIT senior majoring in materials science and engineering. She studied abroad at Oxford University in her junior year through the Department of Materials Science and Engineering’s exchange program. Scott seeks to pursue a future career bridging the gap between science and communications, and eventually plans to found her own communications firm.

In the summer of her freshman year, Scott traveled to Singapore to conduct materials research, fabricating thin-film membranes to create nano-filtration systems for smog. She later began research with the MIT Libraries Conservation Lab, prototyping two different devices for reversible flattening of manuscripts, which would automate part of the conservation process. At Oxford, Scott conducted polymer research with the Polymer Group and Ashmolean Museum.

Scott has a keen interest in industry, and worked as a chemical engineering intern at Honeywell UOP. While there, she worked to improve wastewater filtration by developing a disinfectant and low temperature tolerant bacteria. The system saves 400,000 gallons of wastewater per day, results that led to the adoption of her system in October 2016.

Scott is a sorority sister of Sigma Kappa, and has held the role of continuing membership chair and new member assistant coordinator. She was elected as vice president of programming for the MIT Panhellenic Association.
Since Scott’s freshman year, she has been a member of MIT’s only Division I sport, rowing. She and her boat earned a bid to the 2016 national competition, and placed 5th, and Scott was named a Collegiate Rowing Coaches Association Scholar Athlete. When she was at Oxford University, she joined the university’s lightweight rowing club.

Joshua Woodard

Joshua Charles Woodard, from Chicago, Illinois, is an MIT senior majoring in mechanical engineering with a minor in Mandarin Chinese. At Tsinghua, Woodard will earn a degree in politics, with a focus on comparative government. He plans a future career in diplomacy and public policy, with the goal of enacting effective strategies for social change.

Woodard’s dedication to social justice issues began prior to arriving at MIT. As a junior in high school, he applied for and was granted a Boeing Scholars Academy award to research Chicago’s gun violence and devise solutions. He then coordinated a city-wide brainstorming event between youth and government officials.

At MIT, Woodard has been a pivotal voice on issues of diversity and inclusion. As a student advisor on MIT President L. Rafael Reif’s Presidential Advisory Committee, he has provided guidance on important campus issues and policies ranging from diversity initiatives to the influence of the current political climate. Woodard has also demonstrated his leadership skills as co-chair of the student community and living group Chocolate City, and has been instrumental in increasing campus awareness of the Black Lives Matter movement and creating opportunities for dialogue.

Woodard participated in the Internationally Genetically Engineered Machines (iGEM) worldwide competition for synthetic biology, and he has interned in industrial design at the Charles Stark Draper Laboratory and HTC. He has also advocated to help local Boston high school students from underrepresented communities gain access to STEM experiences by co-founding the summer leadership program MIT BoSTEM Scholars Academy.

A talented artist and musician, Woodard has studied and performed Beijing Opera at the Shanghai Theater Academy in China, runs his own freelance photography business, JC Woodard Photography, and has performed on violin and viola with the MIT Jazz Band.

Han Wu

Han Wu graduated from MIT in 2015 with a master's degree in structural engineering focusing on high performance structures.

Prior to enrolling at MIT, he received a bachelor’s degree from the University of California at Los Angeles majoring in civil and environmental engineering and minoring in accounting. Currently, he works at Ove Arup and Partners Hong Kong (one of the worldwide leading engineering consulting firms) as a structural engineer and the chairman of Young Engineer’s Group.

Besides tackling challenging design problems, Wu also plays a key role in researching and implementing industry leading design tools as well as conducting training sessions. Upon completion of Schwarzman Scholars, he hopes to pursue a career in which he can combine his experience and knowledge in design and business development.

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Kim Benard | Office of Distinguished Fellowships
MIT News Office
December 4, 2017

BASF P380 D17 ScienceAward 001 Rupp Full Web
BASF and Volkswagen Science Award Electrochemistry presentation Dec. 1, 2017, at Karlsruhe Institute of Technology in Germany. Standing (l-r): Volkswagen AG Research and Development Group Head Ulrich Eichhorn, Catalytic Innovations founder and CEO Stafford Sheehan, who received a special prize for applied research MIT Assistant Professor of Materials Science and Engineering Jennifer Rupp, who received the Science Award Electrochemistry, BASF Chief Technology Officer and Vice Chairman of the Board of Executive Directors Martin Brudermüller, and Karlsruhe Institute of Technology President Holger Hanselka. BASF photo.

Jennifer L. M. Rupp, who holds joint appointments at MIT as an assistant professor in the Departments of Materials Science and Engineering [DMSE] and Electrical Engineering and Computer Science [EECS], won the 2017 “Science Award Electrochemistry,” awarded by Volkswagen and BASF. Rupp was honored for her work on energy storage systems.

Rupp received the award, which is worth about $47,000, on Dec. 1, 2017, at ceremonies held at Karlsruhe Institute of Technology (KIT) in Germany. Rupp’s Electrochemical Materials Laboratory at MIT is working to replace the flammable liquid electrolyte in lithium batteries with a safer solid-state lithium electrolyte.

“The team was honored to receive the award for their work on processing and designing new solid-state, garnet-type batteries and for their commitment to integrate cathodes with socio-economically acceptable elements," Rupp says. “Designing lithium conducting glass-ceramics and battery electrode alloys can be interesting strategies for future battery architectures based on garnets to avoid lithium dendrites that often lead to performance failure," Rupp says. Dendrites are lithium filaments shaped like tree leaves or snowflakes that can form in rechargeable lithium metal batteries, and their unchecked growth can cause a cell to short-circuit.

“The winners of our Science Award are an excellent example of innovative and creative ideas in this field,” says Dr. Ulrich Eichhorn, head of Group Research and Development for Volkswagen AG. The German automaker plans to reach a goal of 25 percent battery-powered electric vehicles by 2025.

The Science Award Electrochemistry noted Rupp’s work on ceramic engineering for fast lithium transfer in garnet-type batteries and a novel glassy-type lithium ion conductor that may lead to new design principles for solid-state batteries. “BASF creates chemistry for a sustainable future. We all know that batteries are at the core of electromobility, and there is great potential for specific technological progress in this area. Yet, there are scientific hurdles we must first overcome,” says Martin Brudermüller, Vice Chairman of the Board of Executive Directors and Chief Technology Officer at BASF. “Electrochemistry is a key technology for sustainable future mobility. That is why we need first-class research around the globe conducted by excellent scientists who inspire each other to continuously develop new and better solutions.”

Rupp joined the MIT Department of Materials Science and Engineering in January 2017 as the Thomas Lord Assistant Professor of Materials Science and Engineering at MIT, and recently was appointed as an assistant professor in the Department of Electrical Engineering and Computer Science. She also conducts research on materials for solid oxide fuel cells, electrochemical sensors and information storage devices.

The BASF and Volkswagen International “Science Award Electrochemistry” has been awarded yearly since 2012.

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– Materials Research Laboratory
December 19, 2017

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