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Advances in flexible electronic devices and robotic software require that sensors and controllers be virtually devoid of traditional electronic components, be deformable and stretch‐resistant. Liquid electronic devices that mimic biological synapses would make an ideal core component for flexible liquid circuits. This is due to their unbeatable features such as flexibility, reconfiguration, fault tolerance. To mimic synaptic functions in fluids we need to imitate dynamics and complexity similar to those that occurring in living systems. Mimicking ionic movements are considered as the simplest platform for implementation of neuromorphic in material computing systems. We overview a series of experimental laboratory prototypes where neuromorphic systems are implemented in liquids, colloids and gels.

The next generation of wearable electronics for internet of things (IoT) systems, and green energy harvesting require electrically conductive materials with high flexibility, conductivity, and being environmentally friendly. In this study, three biopolymers, cow's milk, soy milk, and egg white liquid, are investigated and compared as spin‐coated positive layers in triboelectric nanogenerators (TENGs). Superior results are obtained using egg white liquid as a novel liquid conductor with comparable conductivity and high transparency. After investigating various disposable polymers as substrates, sandpaper is used to improve the output performance of the proposed egg white liquid based TENG (EW‐TENG). The maximum output power density, voltage, and current of the EW‐TENG are 328.84 mW cm−2, 1720 V, and 16.05 mA, respectively. The fabricated EW‐TENG, with an area of 4 × 4 cm2, can directly illuminate 55 high‐power blue LEDs and can adequately perform an electrophoretic deposition of ZnO nanoparticles on copper layers without microcracks. The potential distribution of the EW‐TENG obtained by COMSOL Multiphysics software is consistent with the experimental results. Herein, an eco‐environmentally friendly, flexible, and lightweight electronic device for energy harvesting and electrophoretic deposition applications is proposed.

Colloids submitted to electrical stimuli exhibit a reconfiguration that could be used to store information and, potentially compute. We investigated learning, memorization, and time and stimulation's voltage dependence of conductive network formation in a colloidal suspension of ZnO nanoparticles in DMSO. Relations between critical resistance and stimulation time were reconstructed. The critical voltage, i.e. the stimulation voltage necessary for dropping the resistance, was shown to decrease in response to an increase in stimulation time. We characterized a dispersion of conductive ZnO nanoparticles in the DMSO polymeric matrix using FESEM and UV-visible absorption spectrum.

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