How can you employ science to construct a greater gingerbread house?
Miranda Schwacke has considered this for a very long time. The MIT graduate within the Department of Materials Science and Engineering (DMSE) is an element of Kitchen mattersa bunch of graduate students who use food and kitchen equipment to clarify scientific concepts through short videos and outreach events. Previous topics have included why chocolate “freezes” or is difficult to work with when melted (spoiler: water gets in) and learn how to make isomalt, the sugar glass that stunt performers jump through in motion movies.
Two years ago when the group made a video learn how to construct a structurally sound gingerbread houseSchwacke searched cookbooks for a variable that may make the most important difference within the cookies.
“I examine what determines the feel of cookies after which tried several recipes in my kitchen until I had two gingerbread recipes that I used to be comfortable with,” Schwacke says.
She focused on butter, which comprises water that turns into steam at high baking temperatures, creating air pockets in cookies. Schwacke predicted that reducing the quantity of butter would end in denser gingerbread cookies that may be strong enough to carry together as a house.
“This hypothesis is an example of how changing structure can affect the properties and performance of materials,” Schwacke said within the eight-minute video.
The same curiosity about material properties and performance drives her research into the high energy costs of computing, particularly for artificial intelligence. Schwacke is developing recent materials and devices for neuromorphic computing, which mimics the brain by processing and storing information in the identical place. She studies electrochemical ion synapses – tiny devices that may be “tuned” to regulate conductivity, just like neurons, which strengthen or weaken connections within the brain.
“If you have a look at AI specifically – to coach these really large models – that uses plenty of energy. And in case you compare that to the quantity of energy we use as humans after we're learning things, the brain uses loads less energy,” says Schwacke. “This led to the concept of finding more brain-inspired and energy-efficient ways to implement AI.”
Her advisor, Bilge Yildiz, underscores the purpose: One reason the brain is so efficient is that there is no such thing as a have to move data backwards and forwards.
“In the brain, we process information through the connections between our neurons, called synapses. This is where signal transmission takes place. It is processed, programmed and in addition stored in the identical place,” says Yildiz, Breene M. Kerr (1951), professor within the Department of Nuclear Science and Engineering and DMSE. Schwacke's devices aim to breed this efficiency.
Scientific roots
As the daughter of a marine biologist and an electrical engineer, Schwacke was involved in science from a young age. Science has “at all times been a component of my understanding of the world.”
“I used to be obsessive about dinosaurs. As a baby I desired to be a paleontologist,” she says. But her interests expanded. At her middle school in Charleston, South Carolina, she entered a FIRST Lego League robotics competition and built robots to perform tasks similar to pushing or pulling objects. “My parents, especially my father, were very involved in the varsity team and helped us design and construct our little robot for the competition.”
Her mother, meanwhile, was studying how pollution affects dolphin populations for the National Oceanic and Atmospheric Administration. That had a long-lasting effect.
“This was an example of how science may be used to grasp the world and in addition learn how we will improve it,” says Schwacke. “And that’s what I at all times desired to do with science.”
Her interest in materials science later emerged through her highschool magnet program. There she was introduced to the interdisciplinary subject, a combination of physics, chemistry and engineering that studies the structure and properties of materials and uses that knowledge to design recent materials.
“I've at all times liked that it goes from this very basic science where we study how atoms organize themselves to those solid materials that we interact with in our each day lives – and the way that offers them their properties that we will see and play with,” Schwacke says.
As an undergraduate, she participated in a thesis research program 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 how we will move from light to energy that we will use – and in addition seeing how that might help us use more renewable energy sources,” says Schwacke.
After highschool, she moved across the country to Caltech. “I desired to try a totally recent place,” she says, where she studied materials science, including nanostructured materials which are a thousand times thinner than a human hair. She focused on material properties and microstructure – the tiny internal structure that determines the behavior of materials – which led her to electrochemical systems similar to batteries and fuel cells.
AI energy challenge
At MIT she continued to work on energy technologies. She met Yildiz during a Zoom meeting during 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 similar to fuel cells, batteries and electrolyzers.
The lab's research into brain-inspired computing captured 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 happening—that ions go here and electrons go here—to fundamentally understand what was happening within the system,” Schwacke says.
This attitude shaped her research approach. Their early projects focused on the features these devices have to work well—fast operation, low power consumption, and compatibility with semiconductor technology—and on using magnesium ions as a substitute of hydrogen, which might leach into the environment and make devices unstable.
Her current project, which is the main target of her doctoral thesis, focuses on understanding how incorporating magnesium ions into tungsten oxide, a metal oxide whose electrical properties may be precisely tuned, changes its electrical resistance. In these devices, tungsten oxide serves as a channel layer during which resistance controls signal strength, just like how synapses regulate signals within the brain.
“I’m trying to grasp exactly how these devices change channel conductivity,” says Schwacke.
Schwacke's research was recognized with a MathWorks grant from the School of Engineering in 2023 and 2024. The scholarship supports doctoral students who use tools similar to MATLAB or Simulink of their work; Schwacke used MATLAB to research and visualize critical data.
Yildiz describes Schwacke's research as a novel step towards solving considered one of the most important challenges in AI.
“This is electrochemistry for brain-inspired computing,” says Yildiz. “It's a brand new context for electrochemistry, but additionally with energy implications, since the energy consumption of computers is increasing unsustainably. We need to search out recent ways to run computers with much less energy, and that is a method that might help us move in that direction.”
Like any pioneering work, it brings with it challenges, particularly in linking the concepts between electrochemistry and semiconductor physics.
“Our group has a background in solid-state chemistry, and after we began studying magnesium, nobody had used magnesium in devices of this kind before,” says Schwacke. “So we looked to the magnesium battery literature for inspiration and different materials and techniques we could use. When I began doing this, I not only learned the language and standards for one area, but tried to learn them for 2 areas and in addition translated between the 2.”
She also struggles with a challenge familiar to all scientists: learn how to make sense of messy data.
“The biggest challenge is to be confident in my data that I’m interpreting it accurately and understanding what it actually means,” says Schwacke.
She overcomes hurdles by working closely with colleagues from diverse fields, including neuroscience and electrical engineering, and sometimes by making only small changes to her experiments and watching what happens next.
Community is very important
Schwacke just isn’t only energetic within the laboratory. In Kitchen Matters, she and her DMSE colleagues arrange booths at local events similar to the Cambridge Science Fair and Steam It Up, an after-school program with hands-on activities for youngsters.
“We did 'pHun with Food,' where 'fun' was spelled with a pH value, so we had cabbage juice as a pH indicator,” says Schwacke. “We had the children test the pH of lemon juice, vinegar and dish soap they usually had plenty of fun mixing different liquids and searching at different colours.”
She also served as social chair and treasurer of DMSE's graduate student group, the Graduate Materials Council. As an undergraduate at Caltech, she led science and technology workshops for Robogals, a student-run group that encourages young women to pursue careers in science, and helped students apply for the varsity's Summer Undergraduate Research Fellowships.
For Schwacke, these experiences have sharpened her ability to clarify science to diverse audiences, a skill she considers crucial whether she is presenting at a children's fair or a research conference.
“I at all times think: Where does my audience start and what do I would like to clarify before I get into what I’m doing in order that all the pieces is smart to them?” she says.
Schwacke sees the power to speak as central to constructing a community, which she sees as a very important a part of research. “It helps spread ideas. It at all times helps to get a brand new perspective on what you're working on,” she says. “I also think it keeps us mentally healthy during our doctoral studies.”
For Yildiz, Schwacke's social commitment is a very important a part of her CV. “She is doing all of those activities to motivate the broader community to do research, to be thinking about science, to pursue science and technology, but this ability may also help her advance in her own research and academic endeavors.”
After completing her doctorate, Schwacke would really like to transfer these communication skills into science, where she would really like to encourage the following generation of scientists and engineers. Yildiz has little question that she will probably be successful.
“I feel she’s an ideal fit,” Yildiz says. “She's good, but brilliance alone isn't enough. She's persistent and resilient. You actually need that on top of that.”
