Carmen Lilley
University of Illinois Chicago, IL·Materials Science
Materials only one atom thick, called two-dimensional (2D) materials, are promising for flexible electronics and batteries. Joining two different atomic sheets side by side forms a lateral heterostructure.
- Fields
Materials Science
Engineering
Computer Science
- Topics
two-dimensional materials
2D materials
lateral heterostructures
- Grants
- 1 known grant, through Dec 2027
What they work on
- Develop a machine-learning workflow that predicts elastic properties, stress-strain behavior and fracture strength of 2D lateral heterostructures with interface defects, at accuracy comparable to density functional theory (DFT).
- Automate the search for defects where two atomic sheets meet, using geometry optimization to find stable atomic arrangements at the interface.
- Automate data clustering to build training sets for the algorithms, creating a materials-agnostic workflow that can support future inverse design of 2D materials.
More about the research
The seam between the sheets often contains defects, and these change how stiff and how strong the material is. Predicting those properties with standard quantum-mechanical simulation is slow and costly, which makes it hard to design new 2D materials.
Why it matters
The work could speed up the development of atomically thin materials for devices such as flexible electronics and batteries. It would let researchers predict stiffness, stress-strain behavior and breaking strength quickly rather than through costly simulations. Over time, it could support designing new 2D materials directly from the properties a device needs.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Yingchao Yang
University of Missouri-Columbia, MO·Materials Science·Early-career
Synthesize single-layer and multilayer two-dimensional high entropy materials containing at least five elements, using solid-state reaction and chemical vapor deposition.
Lan Li
Boise State University, ID·Materials Science
Generate dye structure-property datasets using density functional theory (DFT) and time-dependent DFT, which simulate molecules and their light-excited states.
Yubo Qi
University of Alabama at Birmingham, AL·Physics
Develop a deep-learning-based, multifunctional computational method that reproduces density functional theory predictions of electron behavior while scaling to systems far larger than direct calculations allow.
The school
University of Illinois Chicago: 42 labs on PI Pages, $532M a year on research, 359 research doctorates a year.
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