Eric Freeman
University of Georgia, GA·Engineering
Artificial intelligence demands ever more computing power, so new, energy-efficient ways to compute are needed. The brain offers a model: it stores memory and processes information in the same place, using ions moving across thin selective membranes.
- Fields
Engineering
Materials Science
Biophysics
- Topics
neuromorphic computing
neuromorphic materials
droplet interface bilayers
- Grants
- 1 known grant, through Aug 2027
What they work on
- Build networks of lipid-coated droplets, joined by droplet interface bilayers that act as model synapses, that adapt their connections in response to the signals they transmit.
- Create a multiphysics model of sticky droplet mechanics that combines electrical and chemical activity, and use it to simulate electrowetting events, where voltage reshapes droplet contacts, in collections of membranes.
- Validate model predictions experimentally, treating the membranes as viscoelastic or viscoplastic soft materials whose metastable states can store memory.
- Expand the model to larger multidimensional droplet networks to study emergent mechanics and achieve long-term synaptic plasticity retained through voltage signals.
More about the research
This project builds soft, brain-inspired materials from lipid-coated droplets. These droplets act like simple model neurons that can change their properties in response to the signals they pass, which is a basic requirement for neuromorphic (brain-like) computing.
Why it matters
Brain-inspired materials that combine memory and processing could lower the power needed for computing as artificial intelligence grows. This work lays groundwork for dynamic synthetic tissues that compute chemically and could connect both with conventional electronics and with biochemical signals, which may eventually inform low-power computing hardware and interfaces between electronics and biology.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Eric Fullerton
University of California-San Diego, CA·Materials Science
Fabricate new quantum materials and characterize their properties with advanced techniques to understand and control their behavior for non-volatile memory.
Tania Roy
Duke University, NC·Engineering·Early-career
Develop in-pixel computing circuits using optoelectronic synaptic devices made from 2D materials, sensing several wavelengths, that maximize each pixel's fill factor and form the first layer of a convolutional neural network.
Gül Zerze
University of Houston, TX·Engineering·Early-career
Identify the role of mesoscale clusters, small intermediate molecular groupings, in nonclassical nucleation of liquid-like condensates, using free energy methods to map their stability and find metastable states.
The school
University of Georgia: 27 labs on PI Pages, $628M a year on research, 598 research doctorates a year.
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