Solid-State Ionics Synaptic Transistors for Neuromorphic Computing

Objective

Neuromorphic computing will revolutionize artificial intelligence for applications such as autonomous driving, smart diagnosis or natural-language understanding by emulating the operation of efficient biological neural networks. The main challenge in this field is the substitution of conventional transistors for synaptic transistors able to learn in ways similar to a neural synapse, i.e. the development of multistate non-volatile transistors. However, currently existing synaptic transistors have been developed using electrolytes that are by nature unstable and difficult to integrate such as ionic liquids or proton conducting polymers.

TRANSIONICS will deliver highly stable (non-volatile), silicon-compatible and scalable solid state synaptic transistors by exploiting the first-ever room temperature oxide-ionic electrolyte developed in the ERC CoG grant (ULTRASOFC) held by the PI. TRANSIONICS transistors are able to modulate its channel properties with external stimulus like real neurons by reducing/oxidizing a mixed ionic-electronic conductor unveiled at ULTRASOFC. Additionally, TRANSIONICS is compatible with mainstream microelectronics fabrication technology, which makes it ideal for developing high density brain-like computer chips.

The goals of the TRANSIONICS project are i) to evaluate the technical feasibility for the fabrication of unique all-solid-oxide synaptic transistors with lateral architecture; ii) to assess the silicon- compatibility and scalability of the TRANSIONICS transistors; iii) to define an IPR strategy for technology transfer; iv) to build a value proposition for a startup company and to identify customer segments with industrial partners. To achieve these goals, the PI has joined around the project team that combines applied research, technology transfer and market uptake expertise.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.

• natural sciences chemical sciences polymer sciences
• natural sciences physical sciences electromagnetism and electronics microelectronics
• natural sciences chemical sciences inorganic chemistry metalloids

Host institution

Beneficiaries (1)