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We study the emergence of chemical intelligence in proteinoid–ZnO nanocomposites through their interaction with visible light. When these novel materials are exposed to light, they display electrical spiking behaviour that is similar to the action potentials of neurons. We examine the influence of various light conditions, such as wavelength, intensity, and duration, on the photo-response of these nanocomposites. The results indicate that higher light intensity and longer duration are associated with increased frequency and amplitude of voltage spikes. Furthermore, blue light is more effective than red light in this regard. This light-dependent behaviour indicates a form of chemical intelligence, in which the material learns and responds to external stimuli. The results of our research emphasise the potential of proteinoid–ZnO nanocomposites to develop bio-inspired, light-sensitive systems, which can lead to advancements in areas such as photocatalysis, unconventional computing, and adaptive materials. This study enhances the understanding of chemical intelligence and how it is demonstrated in synthetic nanomaterials. [ABSTRACT FROM AUTHOR]

Two bio-friendly and photoactive triboelectric nanogenerators (TENG) are introduced, employing sustainable and biocompatible materials as functional components. The TENGs utilize corn husk and coconut coir fibers as the positive layers and incorporate two-dimensional graphitic carbon nitride (g-C3N4) nanosheets as negative layers. Upon simple biomechanical forces, the optimized devices fabricated from corn husk and coconut fibers produce a maximum output voltage of 630 V and 581 V, respectively. Under short-circuit conditions, the measured current was approximately 0.79 mA for corn husk-TENG and 11.47 mA for coconut fibers-TENG. Also, the maximum output power of 131 mW and 1980 mW were achieved over a 2 × 2 cm2 area of corn husk-TENG and coconut fibers-TENG. The TENGs were also tested under blue commercial lights and UV light, and an increase of approximately 1.5 times was observed in the output voltages of both TENGs under UV light. These g-C3N4-based TENGs perform superior under UV illumination and can be used as nanogenerators and active photosensors. This paper proposes two eco-environmentally friendly and robust electronic devices for energy harvesting and photo-sensing applications based on two agricultural wastes, corn husk, and coconut coir fibers. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The colloid cellular automata do not imitate the physical structure of colloids but are governed by logical functions derived from them. We analyze the space-time complexity of Boolean circuits derived from the electrical responses of colloids-specifically ZnO (zinc oxide, an inorganic compound also known as calamine or zinc white, which naturally occurs as the mineral zincite), proteinoids (microspheres and crystals of thermal abiotic proteins), and their combinations in response to electrical stimulation. To extract Boolean circuits from colloids, we send all possible configurations of two-, four-, and eight-bit binary strings, encoded as electrical potential values, to the colloids, record their responses, and infer the Boolean functions they implement. We map the discovered functions onto the cell-state transition rules of cellular automata-arrays of binary state machines that update their states synchronously according to the same rule-creating the colloid cellular automata. We then analyze the phenomenology of the space-time configurations of the automata and evaluate their complexity using measures such as compressibility, Shannon entropy, Simpson diversity, and expressivity. A hierarchy of phenomenological and measurable space-time complexity is constructed., (© 2024. The Author(s).)

We report on the synthesis and characterization of a colloidal graphitic carbon nitride (g-C_{3}N_{4}) system exhibiting complex memfractance behavior. The g-C_{3}N_{4} colloid was prepared through thermal polymerization of urea, followed by dispersion in deionized water. X-ray diffraction and scanning electron microscopy confirmed the successful synthesis of g-C_{3}N_{4}. Electrical characterization revealed nonpinched hysteresis loops in current-voltage curves, indicative of memristive behavior with additional capacitive components. The device demonstrated stable resistive switching between high (∼50kΩ) and low (∼22kΩ) impedance states over 500 cycles, as well as synaptic plasticity-like conductance modulation. To capture these complex dynamics, we employed a generalized memfractance model that interpolates between memristive, memcapacitive, and second-order memristive elements. This model, employing fractional-order derivatives, accurately fitted the experimental data, revealing the device's memory effects. The emergence of memfractance in this colloidal system opens new avenues for neuromorphic computing and unconventional information processing architectures, leveraging the unique properties of liquid-state memory devices.