Memristor Circuits for Colloidal Robotics: Temporal Access to Memory, Sensing, and Actuation
Abstract
Micrometer‐scale robots capable of navigating enclosed spaces and remote locations are approaching reality. However, true autonomy remains an open challenge despite substantial progress made with externally supervised and manipulated systems. To accelerate the development of autonomous microrobots, alternatives to conventional top‐down lithography are sought. Such additive technologies like printing, coating, and colloidal self‐assembly allow for rapid prototyping and access to novel materials, such as polymers, bio‐ and nanomaterials. On the basis of recent experimental findings that memristive networks can be rapidly printed and lifted off as electronic microparticles, an alternative design paradigm is introduced based on arrays of two‐terminal memristive elements, which enables real‐time use of memory, sensing, and actuation in microrobots. Several memristor‐based designs are validated, each representing a key building block toward robotic autonomy: tracking elapsed time, timestamping a rare event, continuously cataloguing time‐indexed data, and accessing the collected information for a feedback‐controlled response as in a robotic glucose‐responsive insulin. The computational results establish an actionable framework for microrobotic design—tasks normally requiring complex circuits can now be achieved with self‐assembled and printed memristor arrays within microparticles.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Dec 23, 2021
- Source ID
- 10.1002/aisy.202100205
Entities
People
- Albert Tianxiang Liu
- Allan M. Brooks
- Ge Zhang
- Jing Yang
- Michael Strano
- Sungyun Yang
- Thomas A Berrueta
- Todd D Murphey
- Volodymyr B Koman
- Xun Gong
Organizations
- Massachusetts Institute of Technology
- MathWorks
- Northwestern University
- Stanford University
- University of Michigan