How can you use science to make better gingerbread houses?
This was something that Miranda Schwacke spent a lot of time thinking about. MIT graduate students in the Department of Materials Science and Engineering (DMSE) are part of Kitchen Matters, a group of graduate students who use food and kitchen appliances to explain scientific concepts through short videos and outreach programs. Previous topics have included why chocolate “seizes”, or becomes difficult to work with when melted (spoiler: water gets in), and how to make isomalt, the glass of sugar that stunt performers jump into in action movies.
Two years ago, when the group was making a video about building structurally sound gingerbread houses, Schweke discovered a variable in the cookbook that would make the most dramatic difference in the cookies.
“I was reading about what determines the texture of cookies, and then I tried several recipes in my kitchen until I found two gingerbread recipes I was happy with,” says Schwecke.
They focused on butter, which contains water that turns to steam at high baking temperatures, creating air pockets in the cookies. Schwecke predicted that reducing the amount of butter would result in a denser gingerbread, strong enough to hold together as a house.
“This hypothesis is an example of how changes in structure can affect the properties and performance of materials,” Schwake said in the eight-minute video.
The same curiosity about the properties and performance of materials motivates his research into the high energy costs of computing, especially artificial intelligence. Schwacke has developed new materials and tools for neuromorphic computing, which mimics the brain by processing and storing information in a single location. She studies electrochemical ionic synapses – tiny devices that can be “tuned” to adjust conductance, much like neurons strengthening or weakening connections in the brain.
“If you look at AI specifically—to train these really large models—that consumes a lot of energy. And if you compare it to the amount of energy we consume as humans when we’re learning things, the brain consumes a lot less energy,” Schwake says. “That’s why the idea of finding more brain-inspired, energy-efficient ways of doing AI came about.”
His advisor, Bilge Yildiz, underlines this: One reason the brain is so efficient is that it doesn’t need to move data back and forth.
“In the brain, the connections between our neurons, called synapses, are where we process information. Signal transmission happens there. It is processed, programmed, and even stored in the same place,” says Yildiz, the Breen M. Kerr (1951) Professor in the Department of Nuclear Science and Engineering and DMSE. Schwake’s devices aim to replicate that efficiency.
scientific roots
The daughter of a marine biologist mother and an electrical engineer father, Schwake was immersed in science from a young age. Science “was always part of how I understood the world.”
“I was obsessed with dinosaurs. I wanted to be a paleontologist when I grew up,” she says. But his interests broadened. At her middle school in Charleston, South Carolina, she joined the FIRST Lego League robotics competition, building robots to complete tasks such as pushing or pulling objects. “My parents, especially my father, joined the school team and were helping us design and build our little robots for the competition.”
Meanwhile, his mother studied for the National Oceanic and Atmospheric Administration how pollution affects dolphin populations. It had a lasting impact.
“It was an example of how science can be used to understand the world, and to figure out how we can make the world better,” says Schwecke. “And that’s what I always wanted to do with science.”
His interest in materials science came later in his high school magnet program. There, he was introduced to an interdisciplinary subject, a blend of physics, chemistry and engineering that studies the structure and properties of materials and uses that knowledge to design new ones.
“I always liked that it comes from this very basic science, where we’re studying how atoms are arranged, to these solid materials that we interact with in our everyday lives – and how that gives them their properties that we can observe and play with,” says Schwake.
As a senior, he 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 absorb light and generate electricity.
“What really inspired me to understand is how we go from light to energy that we can use — and also looking at how that can help us have more renewable energy sources,” says Schweke.
After high school, she moved across the country to Caltech. “I wanted to try a completely new space,” she says, where she studied materials science, including nanostructured materials thousands of times thinner than a human hair. He focused on the properties and microstructure of materials – the tiny internal structures that control how materials behave – which led him toward electrochemical systems such as batteries and fuel cells.
AI Energy Challenge
At MIT, he continued exploring energy technologies. She met Yildiz during a Zoom meeting in her first year of graduate school in the fall of 2020, when the campus was still operating under strict COVID-19 protocols. Yildiz’s laboratory studies how charged atoms, or ions, move through materials in technologies such as fuel cells, batteries and electrolyzers.
The lab’s research into brain-inspired computing sparked Schwake’s imagination, but she was equally attracted to Yildiz’s way of talking about science.
“It was not based on jargon and emphasized a very basic understanding of what was going on – that ions are going here, and electrons are going here – to basically understand what is happening in the system,” says Schwake.
That mindset shaped his approach to research. Their initial projects focused on the properties these devices need to work well – fast operation, low energy use, and compatibility with semiconductor technology – and using magnesium ions instead of hydrogen, which can escape into the environment and make the devices unstable.
His current project, the focus of his PhD thesis, focuses on understanding how the insertion of magnesium ions into tungsten oxide, a metal oxide whose electrical properties can be precisely tuned, changes its electrical resistance. In these devices, tungsten oxide acts as a channel layer, where resistance controls signal strength, just as synapses control signals in the brain.
“I’m trying to understand how these devices change channel conductance,” says Schwake.
Schwake’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 such as MATLAB or Simulink in their work; Schwake applied MATLAB for important data analysis and visualization.
Yildiz described Schwake’s research as a novel step toward solving one of AI’s biggest challenges.
“This is electrochemistry for brain-inspired computing,” says Yildiz. “This is a new context for electrochemistry, but also with energy implications, because the energy consumption of computing is constantly increasing. We need to find new ways to do computing with much less energy, and this is one way that can help us move in that direction.”
Like any pioneering work, it comes with challenges, especially in connecting concepts between electrochemistry and semiconductor physics.
“Our group comes from a solid-state chemistry background, and when we started working on magnesium, no one had used magnesium in these types of devices before,” says Schwake. “So we were looking at the magnesium battery literature for inspiration and different materials and strategies we could use. When I started this, I wasn’t just learning the language and standards for one area – I was trying to learn it for two areas, and also translate between the two.”
She also grapples with a challenge familiar to all scientists: how to make sense of dirty data.
“The main challenge is to be able to take my data and know that I’m interpreting it correctly, and that I understand exactly what it means,” says Schwake.
She overcomes obstacles by collaborating with colleagues in diverse fields, including neuroscience and electrical engineering, and sometimes by making small changes to her experiments and seeing what happens next.
community matters
Schwake isn’t just active in the lab. At Kitchen Matters, she and her fellow DMSE graduate students set up booths at local events such as the Cambridge Science Fair and Steam It Up, an after-school program with hands-on activities for children.
“We did ‘Food with Food’ with pH spelling out ‘fun’, so we had cabbage juice as a pH indicator,” says Schweke. “We let the kids test the pH of lemon juice, vinegar, and dish soap, and they had a lot of fun mixing the different liquids and seeing all the different colors.”
He has also served as 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 the sciences, and assisted students in applying for the school’s summer graduate research fellowships.
For Schwake, these experiences sharpened her ability to explain science to diverse audiences, a skill she finds important whether she is presenting at a children’s fair or a research conference.
“I always think, where is my audience starting from, and what do I need to explain before they can engage with what I’m doing so that it all makes sense to them?” She says.
Schwake views the ability to communicate as central to building community, which she sees as an important part of conducting research. “It helps to spread ideas. It always helps to get a new perspective on what you’re working on,” she says. “I also think it keeps us healthy during our PhD.”
Yildiz sees Schwake’s community involvement as an important part of her resume. “She is doing all these activities to inspire the broader community to do research, to get interested in science, to advance science and technology, but this ability will also help her make progress in her own research and academic endeavors.”
Following her PhD, Schwake wants to take her ability to communicate to academia, where she hopes to inspire the next generation of scientists and engineers. Yildiz has no doubts that she will succeed.
“I think he’s a perfect fit,” says Yildiz. “She’s talented, but talent in itself is not enough. She’s determined, resilient. You really need those people on top of that.”
