Memory in a Droplet: Collections of Brain-Inspired Biomolecular Elements

University Of Georgia Research Foundation Inc, Athens GA

Investigators

Abstract

The development of alternative computing approaches is urgently needed as artificial intelligence methods become prevalent, requiring greater resources for their execution. One approach to alternative computing draws inspiration directly from the brain itself, reconstructing aspects of conventional circuitry through combinations of the ionic transport and selective membranous barriers present in living tissues. These approaches require low power consumption through collocating memory and processing units, building memory into the structure of the material itself. This project builds networks of lipid-coated droplets as model neurons capable of adapting their properties in response to the signals they transmit. This ability to tune the exchange across the model synapses is a crucial component of neuromorphic architectures, and this project explores controlling the exchanges using emergent mechanics in networks of interconnected synthetic cells through a combination of mathematical predictions and experimental observations. Completion of the project will provide a foundation for dynamic synthetic tissues capable of chemical computation and able to interface both with conventional electronics and biochemical signals. In addition, the project provides interdisciplinary training for future scientists and enhances the development of the STEM workforce by recruiting and training undergraduate and high school students. This research provides a new approach to droplet-based neuromorphic materials, expanding them to larger multidimensional networks of reconfigurable elements. Investigating these networks of neuromorphic compartments has demonstrated how the internal droplet states (such as accumulation of charge) may be exploited as a form of memory. The selected approach recognizes that droplet interface bilayers may be viewed through the lens of viscoelasticity/viscoplasticity in soft materials, enabling metastable behaviors. A novel multiphysics model will be created for simulating adhesive droplet mechanics by combining the electrical and chemical activities. This model will then be used to explore complex electrowetting events in collections of biological membranes, guiding the design of biomolecular neuromorphic materials. Model predictions will be validated experimentally, and the model will be gradually expanded to study emergent mechanics present in larger collections of biomolecular elements operating in unison. This new approach to the brain-inspired material provides long term synaptic plasticity and the ability to permanently retain changes in the membranous structure through voltage signals. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.