How are you going to use science to construct a greater gingerbread house?
That was something Miranda Schwacke spent a whole lot of time excited about. The MIT graduate student within the Department of Materials Science and Engineering (DMSE) is an element of Kitchen Matters, a gaggle of grad students who use food and kitchen tools to elucidate scientific concepts through short videos and outreach events. Past topics included why chocolate “seizes,” or becomes difficult to work with when melting (spoiler: water gets in), and the right way to make isomalt, the sugar glass that stunt performers jump through in motion movies.
Two years ago, when the group was making a video on the right way to construct a structurally sound gingerbread house, Schwacke scoured cookbooks for a variable that will produce probably the most dramatic difference within the cookies.
“I used to be reading about what determines the feel of cookies, after which tried several recipes in my kitchen until I got two gingerbread recipes that I used to be completely happy with,” Schwacke says.
She focused on butter, which accommodates water that turns to steam at high baking temperatures, creating air pockets in cookies. Schwacke predicted that decreasing the quantity of butter would yield denser gingerbread, strong enough to carry together as a house.
“This hypothesis is an example of how changing the structure can influence the properties and performance of fabric,” Schwacke said within the eight-minute video.
That very same curiosity about materials properties and performance drives her research on the high energy cost of computing, especially for artificial intelligence. Schwacke develops recent materials and devices for neuromorphic computing, which mimics the brain by processing and storing information in the identical place. She studies electrochemical ionic synapses — tiny devices that will be “tuned” to regulate conductivity, very similar to neurons strengthening or weakening connections within the brain.
“In the event you take a look at AI particularly — to train these really large models — that consumes a whole lot of energy. And for those who compare that to the quantity of energy that we devour as humans after we’re learning things, the brain consumes loads less energy,” Schwacke says. “That’s what led to this concept to search out more brain-inspired, energy-efficient ways of doing AI.”
Her advisor, Bilge Yildiz, underscores the purpose: One reason the brain is so efficient is that data doesn’t should be moved forwards and backwards.
“Within the brain, the connections between our neurons, called synapses, are where we process information. Signal transmission is there. It’s processed, programmed, and in addition stored in the identical place,” says Yildiz, the Breene M. Kerr (1951) Professor within the Department of Nuclear Science and Engineering and DMSE. Schwacke’s devices aim to duplicate that efficiency.
Scientific roots
The daughter of a marine biologist mom and an electrical engineer dad, Schwacke was immersed in science from a young age. Science was “all the time an element of how I understood the world.”
“I used to be obsessive about dinosaurs. I desired to be a paleontologist after I grew up,” she says. But her interests broadened. At her middle school in Charleston, South Carolina, she joined a FIRST Lego League robotics competition, constructing robots to finish tasks like pushing or pulling objects. “My parents, my dad especially, got very involved in the varsity team and helping us design and construct our little robot for the competition.”
Her mother, meanwhile, studied how dolphin populations are affected by pollution for the National Oceanic and Atmospheric Administration. That had a long-lasting impact.
“That was an example of how science will be used to grasp the world, and in addition to determine how we will improve the world,” Schwacke says. “And that’s what I’ve all the time desired to do with science.”
Her interest in materials science got here later, in her highschool magnet program. There, she was introduced to the interdisciplinary subject, a mix of physics, chemistry, and engineering that studies the structure and properties of materials and uses that knowledge to design recent ones.
“I all the time liked that it goes from this very basic science, where we’re studying how atoms are ordering, all the way in which up to those solid materials that we interact with in our on a regular basis lives — and the way that provides them their properties that we will see and play with,” Schwacke says.
As a senior, she participated in a research program with a thesis project on dye-sensitized solar cells, a low-cost, lightweight solar technology that uses dye molecules to soak up light and generate electricity.
“What drove me was really understanding, that is how we go from light to energy that we will use — and in addition seeing how this might help us with having more renewable energy sources,” Schwacke says.
After highschool, she headed across the country to Caltech. “I desired to try a very recent place,” she says, where she studied materials science, including nanostructured materials hundreds of times thinner than a human hair. She focused on materials properties and microstructure — the tiny internal structure that governs how materials behave — which led her to electrochemical systems like batteries and fuel cells.
AI energy challenge
At MIT, she continued exploring energy technologies. She met Yildiz during a Zoom meeting in her first 12 months of graduate school, in fall 2020, when the campus was still operating under strict Covid-19 protocols. Yildiz’s lab studies how charged atoms, or ions, move through materials in technologies like fuel cells, batteries, and electrolyzers.
The lab’s research into brain-inspired computing fired Schwacke’s imagination, but she was equally drawn to Yildiz’s way of talking about science.
“It wasn’t based on jargon and emphasized a really basic understanding of what was occurring — that ions are going here, and electrons are going here — to grasp fundamentally what’s happening within the system,” Schwacke says.
That mindset shaped her approach to research. Her early projects focused on the properties these devices have to work well — fast operation, low energy use, and compatibility with semiconductor technology — and on using magnesium ions as an alternative of hydrogen, which may escape into the environment and make devices unstable.
Her current project, the main target of her PhD thesis, centers on understanding how the insertion of magnesium ions into tungsten oxide, a metal oxide whose electrical properties will be precisely tuned, changes its electrical resistance. In these devices, tungsten oxide serves as a channel layer, where resistance controls signal strength, very similar to synapses regulate signals within the brain.
“I’m trying to grasp exactly how these devices change the channel conductance,” Schwacke says.
Schwacke’s research was recognized with a MathWorks Fellowship from the School of Engineering in 2023 and 2024. The fellowship supports graduate students who leverage tools like MATLAB or Simulink of their work; Schwacke applied MATLAB for critical data evaluation and visualization.
Yildiz describes Schwacke’s research as a novel step toward solving certainly one of AI’s biggest challenges.
“That is electrochemistry for brain-inspired computing,” Yildiz says. “It’s a brand new context for electrochemistry, but additionally with an energy implication, since the energy consumption of computing is unsustainably increasing. We have now to search out recent ways of doing computing with much lower energy, and that is a technique that may also help us move in that direction.”
Like several pioneering work, it comes with challenges, especially in bridging the concepts between electrochemistry and semiconductor physics.
“Our group comes from a solid-state chemistry background, and after we began this work looking into magnesium, nobody had used magnesium in these sorts of devices before,” Schwacke says. “So we were taking a look at the magnesium battery literature for inspiration and different materials and methods we could use. After I began this, I wasn’t just learning the language and norms for one field — I used to be attempting to learn it for 2 fields, and in addition translate between the 2.”
She also grapples with a challenge familiar to all scientists: the right way to make sense of messy data.
“The foremost challenge is with the ability to take my data and know that I’m interpreting it in a way that’s correct, and that I understand what it actually means,” Schwacke says.
She overcomes hurdles by collaborating closely with colleagues across fields, including neuroscience and electrical engineering, and sometimes by just making small changes to her experiments and watching what happens next.
Community matters
Schwacke will not be just lively within the lab. In Kitchen Matters, she and her fellow DMSE grad students arrange booths at local events just like the Cambridge Science Fair and Steam It Up, an after-school program with hands-on activities for youths.
“We did ‘pHun with Food’ with ‘fun’ spelled with a pH, so we had cabbage juice as a pH indicator,” Schwacke says. “We let the children test the pH of lemon juice and vinegar and dish soap, they usually had a whole lot of fun mixing the various liquids and seeing all the various colours.”
She has also served because the social chair and treasurer for DMSE’s graduate student group, the Graduate Materials Council. As an undergraduate at Caltech, she led workshops in science and technology for Robogals, a student-run group that encourages young women to pursue careers in science, and assisted students in applying for the varsity’s Summer Undergraduate Research Fellowships.
For Schwacke, these experiences sharpened her ability to elucidate science to different audiences, a skill she sees as vital whether she’s presenting at a kids’ fair or at a research conference.
“I all the time think, where is my audience ranging from, and what do I would like to elucidate before I can get into what I’m doing in order that it’ll all make sense to them?” she says.
Schwacke sees the power to speak as central to constructing community, which she considers a vital a part of doing research. “It helps with spreading ideas. It all the time helps to get a brand new perspective on what you’re working on,” she says. “I also think it keeps us sane during our PhD.”
Yildiz sees Schwacke’s community involvement as a vital a part of her resume. “She’s doing all these activities to motivate the broader community to do research, to be thinking about science, to pursue science and technology, but that ability will help her also progress in her own research and academic endeavors.”
After her PhD, Schwacke desires to take that ability to speak together with her to academia, where she’d wish to encourage the subsequent generation of scientists and engineers. Yildiz has little question she’ll thrive.
“I believe she’s an ideal fit,” Yildiz says. “She’s sensible, but brilliance by itself will not be enough. She’s persistent, resilient. You really want those on top of that.”