Computing with Printed and Flexible Electronics

Printed and flexible electronics (PFE) have emerged as the ubiquitous solution for application domains at the extreme edge, where the demands for low manufacturing and operational cost cannot be met by silicon-based computing. Built on mechanically flexible substrates, printed and flexible devices offer unparalleled advantages in terms of form factor, bio-compatibility and sustainability, making them ideal for emerging and uncharted applications, such as wearable healthcare products or fast-moving consumer goods. Their desirable attributes stem from specialized fabrication technologies, e.g., Pragmatic's FlexIC, where advancements like ultra-thin substrates and specialized printing methods expand their hardware efficiency, and enable penetration to previously unexplored application domains. In recent years, significant focus has been on machine learning (ML) circuits for resource-constrained on-sensor and near-sensor processing, both in the digital and analog domains, as they meet the requirements of target applications by PFE. Despite their advancements, challenges like reliability, device integration and efficient memory design are still prevalent in PFE, spawning several research efforts towards cross-layer optimization and co-design, whilst showing promise for advancing printed and flexible electronics to new domains.