Memcomputing with membrane memcapacitive systems
This work addresses the challenge of realizing memcomputing with passive devices, potentially advancing solid-state computing, but it is incremental as it builds on existing memcomputing concepts.
The paper tackles the problem of performing logic operations in a brain-like, massively parallel manner by proposing networks of membrane memcapacitive systems, showing theoretically that they can execute a complete set of logic gates without altering network topology.
We show theoretically that networks of membrane memcapacitive systems -- capacitors with memory made out of membrane materials -- can be used to perform a complete set of logic gates in a massively parallel way by simply changing the external input amplitudes, but not the topology of the network. This polymorphism is an important characteristic of memcomputing (computing with memories) that closely reproduces one of the main features of the brain. A practical realization of these membrane memcapacitive systems, using, e.g., graphene or other 2D materials, would be a step forward towards a solid-state realization of memcomputing with passive devices.