Quantum Engineering for Machine Learning

The QUEFORMAL project proposes a radical vision of a new integrated circuit technology for machine learning where low-voltage field-effect transistors and non-volatile memories are integrated next to each other exploiting quantum engineering of heterostructures of two-dimensional materials (2DMs), i.e. the atom-by-atom design and fabrication of devices, which combine vertical and lateral heterostructures of 2DMs. Our vision is based on the insight that heterostructures of 2D materials (in particular Transition Metal Dichalcogenides) provide a unique opportunity to engineer new materials almost atom by atom, essentially eliminating the boundary between electronic materials and devices