Rational Design of Conductive Pathways in Flexible Tactile Sensors via Indirect 3D-Printing of Liquid Metal for High-Precision Monitoring and Recognition

Highly sensitive and conformal sensors are essentialfor the implementationof human-machine interfaces, health monitoring, and rehabilitationprostheses. The proper adjustment of conductive pathways in the sensingmaterials is essential for their sensitive transduction of mechanicalstimuli into electrical signals. However, the rational, precise, andwide-range control of electrical networks within traditional conductivecomposites is difficult due to the randomly distributed fillers. Herein,we adopt an indirect 3D-printing method to fabricate pressure sensorswith various microchannels for liquid metal (LM) to form consistentand tunable conductive pathways. LM is highly conductive, fluidic,and incompressible at ambient conditions, which guarantees the reliableregulation and function of our pressure sensor. Additive manufacturingprovides a facile way to construct complicated microchannels withdifferent lengths, different orientations, cross-sectional sizes,depth-width ratios, and shapes, which can effectively modulate thesensitivity and the sensing range. Under the optimized structuralconfigurations, our sensor achieves a high sensitivity of 1.139 kPa(-1), a detection range of 0-68 kPa (loading process),and stability of over 5000 cycles, whose sensing performance is betterthan most microchannel-filled LM sensors. It can achieve high-accuracymonitoring of pulse, speaking and gestures, and exhibit a full recognitionof objects under the assistance of machine learning. This work canprovide new ideas on the design of conductive pathways in flexibleelectronics and expand the application of recyclable LM in human-machineinterfaces.