Engineering the Summer is an annual series following molecular engineering students as they embark on summer internships and industry experiences.
For many researchers, the inception of their scientific career can be traced back to singular pique of curiosity—a surprising observation, an unusual encounter, an unignorable question. For Chuting Deng, the path to materials engineering began with food.
Deeply inquisitive as a child, Deng remembers being transfixed by the seemingly commonplace transformation of raw ingredients into food; how a little heat could turn freshly cracked eggs into a hearty breakfast. That simple chemical reaction led Deng to study materials science, an interdisciplinary field that leverages those same types of reactions—albeit more complex—to help solve many of today’s pressing issues across healthcare, sustainability, and water security.
Deng is now a 5th-year PhD student at the Pritzker School of Molecular Engineering, where she’s working on advanced materials such as better lithium-ion batteries and molecules that can capture phosphate from contaminated water. This summer, she’s bringing her expertise to molecular simulations and material informatics as a 3M data science intern.
What about materials science continues to fascinate you?
To me, the most intriguing part of materials science is the magical bridge between molecular design and material properties. Different materials can exhibit different functionalities such as thermal, mechanical, optical, or electrical. The design space of molecules is vast and diverse, but the bridge between them is always drawn from a set of fundamental physical principles—you just need to find out which are the most relevant to your problem. To me, this is the best form of puzzle-solving.
Was there a crystalizing moment in your life when you understood you wanted to study materials science?
I took advanced thermodynamics and statistical mechanics in my senior year, and that class showed me the beauty in how a unified formulation bridges between micro- and macroscopic quantities. It was already my last year in college, but that experience made me realize I had only just discovered a field I was truly interested in. Because of that, I decided to pursue it in graduate school.
Now you’re interning at one of the most prolific companies in the field. Tell us about that experience?
I am working as a data science intern at 3M, where I’m doing a mix of molecular simulation and material informatics. I employ high-throughput simulation pipeline to generate data, which are later used to predict target properties and find the optimal material design.
The lab I work in here is a very collaborative research atmosphere, which reminds me a lot of PME. However, project management here has some nuances. 3M employs a project management framework that ensures every team member is making steady progress and keeping up-to-date with their colleagues. The whole team moves and exchanges ideas and tasks quite frequently. At school, the projects are generally more explorative and have a different pace because people manage their projects in their own way.
How does that relate to your work at PME? Can you talk a bit about your research here?
I work on computational material design. My projects at PME involve a diverse range of materials, all under the theme of sustainable technologies.
I’ve worked on solid polymer electrolytes for Li-ion battery applications; peptide amphiphile micelles for phosphate recovery and water treatment; polymer transport in hydrocracking catalysts for plastic upcycling; and vapor deposited glass of organic semiconductors.
So far, my studies are theory-informed, and they investigate design principles based on fundamental, mechanistic understandings. My goal is to perform more efficient material discovery by seeking the synergy between theory-informed and data-driven approaches.
How has the environment at PME influenced your work?
The interdisciplinary culture and collaborative environment at PME are unseen elsewhere. And they are the key reason why I can be exposed to diverse projects and why these projects can be carried out efficiently in parallel.
How do you see your field growing in the coming years?
Rapidly. In computational material design, we have seen work on material informatics bloom. Artificial intelligence and machine learning are proving to be powerful tools for property prediction and automatic material discovery, though not all materials can benefit from them. Polymer research, for example, still faces several barriers before it can take advantage of this type of material discovery.
There are a lot of existing research problems that could readily benefit from artificial intelligence and machine learning, but we have yet to employ them.
Theoretically-informed fundamental studies that provide mechanistic understanding will continue to be integral to the field, as they are the keys to pushing generations of data-driven discoveries.
PME is at the forefront of engineering and science related to materials systems, addressing challenges and technological issues that have a major impact on humanity and quality of life.
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