Physical Reservoir Computing using a Cellulose Nanofiber Hydrogel for Intelligent Green Electronics

Cellulose nanofibers (CNFs) are attractive materials for green electronics, but their use as the computational core of intelligent devices remains largely unexplored. Here, a hydrogel made of CNFs and water is examined as a physical computational resource, i.e., a physical reservoir, for electronic time‐series processing, based on a square‐gel measurement platform with three identical input and 13 readout electrodes. The dynamics depend on pulse width, where a slower relaxation branch becoming increasingly relevant at longer pulses. Increasing pulse width shifts the reservoir from a linear‐memory‐rich regime toward a more contractive and more nonlinear regime, where more contractive means that the same input drive suppresses differences between neighboring states more strongly. Useful functionality is retained for more than 3.5 h after being exposed to an ambient drying environment: sub‐millisecond conditions favor a benchmark for nonlinear memory capability (NARMA2), whereas node emulation, the restoration of outputs from a missing node by available ones, is advantageous for longer pulse widths. These results establish bare CNF hydrogel as a degradable physical reservoir with drying robustness.