Printable and Stretchable Conductive Elastomers for Monitoring Dynamic Strain with High Fidelity

Printable and stretchable conductive elastomers have promising applications for epidermal and wearable electronics, soft robotics, etc. However, these conductive materials usually present poor performances in monitoring dynamic strains. The monitored signals are distorted and lose key physical signs, which limit their practical applications. Through investigating kinetic behaviors of conductive pathways along longitudinal and transverse directions in these conductive materials, the physical mechanism of signal distortion under dynamic strains is interpreted. To overcome this strain sensing problem, an Ag‐Ecoflex‐polydimethylsiloxane (PDMS) elastomer by printing Ag‐filler‐Ecoflex‐matrix ink on PDMS is proposed. Compared to other conductive materials, the Ag‐Ecoflex‐PDMS elastomer has preferable dynamic performances, embodying smaller overshoot response, higher strain sensitivity, and lower hysteresis. A deep‐learning‐based dynamic calibration method is proposed to successfully correct the sensing signals and eliminate the hysteresis error to 0.1%. Moreover, the proposed Ag‐Ecoflex‐PDMS elastomers gain high electrical conductivities owing to thermal expansion and contraction of PDMS substrate during the thermosetting of conductive ink, and thus can be both excellent stretchable sensors and stretchable conductors. Demonstrations of monitoring knee motion with high fidelity and human–robot collaborative playing ping‐pong validate superior accuracy and robustness of the Ag‐Ecoflex‐PDMS elastomers for monitoring human dynamic activities, human‐machine collaboration, virtual reality, etc. Performances of stretchable conductive elastomers in monitoring dynamic strains are improved by printing Ag‐filler‐Ecoflex‐matrix ink on polydimethylsiloxane substrate with deep‐learning‐based calibration. Smaller overshoot response, higher strain sensitivity, lower hysteresis, and higher electrical conductivity are achieved. Demonstrations of monitoring knee motion with high fidelity and human–robot collaborative playing ping‐pong validate superior accuracy and robustness of the proposed material and fabrication.