Analyzing memcapacitive capabilities of lipid and polymer bilayers for use in smart materials

Neuromorphic engineering involves designing artificial neural systems that mimic the way neuron circuits in the brain process information and make computations. It took the fourth most powerful computer in the world (with 705,024 processor cores and 1.4 million GB of RAM) 40 minutes to simulate just one second of human brain activity. This shows a clear difference of energy use in the human brain versus modern computers; neuromorphic engineering could be how we mimic the computing power of the brain to create energy-efficient, neuron-based computers. Memristors and memcapacitors are proposed circuit elements with memory components. Memristors have been extensively studied in the past and have already been used in artificial neural networks. However, much less research has been done with memcapacitors. We have studied static lipid and polymer bilayers in the past, but our goal with this experiment is to dynamically test bilayers of different lipid or polymer makeup in various oils and then to compare which combinations exhibit the best memcapacitive capabilities. Bilayers will be tested using AC voltage and analyzed based on resulting current. With the combinations that exhibit strong memory capability, the next step will be determining how to incorporate these bilayer systems into soft smart materials.