Project description
Neuromorphic brain 'health': enhancing the performance of memristors
Memristors, or memory resistors, were first proposed nearly half a century ago as the fourth fundamental building block of electrical circuits along with resistors, capacitors and inductors. However, it was not clear how they could be built. Their first demonstration came in 2008 thanks to the electrical properties of certain nanoscale devices. With their tuneable-on-a-continuum resistance values, which they "remember" even when power is turned off, they can act as both synapses and store "memories." Even though they have the potential to become the enabling technology for neuromorphic computing, they need a technological boost. The EU-funded COFFEE project is optimising the physical and functional properties of memristors made of conductive filaments to perform computational tasks in neural networks.
Objective
With modern data demands and computational burdens rapidly expanding, technology must quickly move beyond the traditional von Neumann architecture that has driven computational advances since the 20th century. Taking its inspiration from the remarkable plasticity and power efficiency of the human brain, neuromorphic computing offers a promising approach to overcome the fundamental limitations imposed by the von Neumann architecture and the imminent demise of Moore’s Law. One notable formulation of neuromorphic hardware relies on analog memory elements called memristors (resistive switching devices). While resistive switching is a well-known phenomenon, its implementation in neuromorphic computing currently suffers from several serious issues, including significant device-to-device variations, binary (as opposed to analog) switching and cycle-to-cycle variability. In COFFEE (Controlling and Observing Filaments For Enhanced memristive Elements), we seek to overcome these shortcomings by studying the fundamental materials physics of conductive filaments as well as through iterative and targeted device optimization efforts. We will utilize novel experimental techniques, including in operando transmission electron microscopy (TEM) and scanning thermal microscopy (SThM), to visualize the formation and behavior of conductive filaments in practical devices. Insights gained from filament visualization experiments will be used to modify device design through geometric, chemical, and electrode engineering in the hopes of improving device performance. Improved memristors will be used for the fabrication of cross-bar arrays to perform benchmark computational tasks in neural network hardware and for neural network simulations. Through the study of conductive filaments and targeted engineering efforts, the performance of filamentary memristors can likely be dramatically improved and their implementation in viable neuromorphic technologies can move closer to reality.
Fields of science
Programme(s)
Funding Scheme
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinator
8803 Rueschlikon
Switzerland