Proteinoids, or thermal proteins, are inorganic entities formed by heating amino acids to their melting point and commencing polymerisation to form polymeric chains. Typically, their diameters range from 1μm to 10μm. Some amino acids incorporated into proteinoid chains are more hydrophobic than others, leading proteinoids to cluster together when they are present in aqueous solutions at specific concentrations, allowing them to grow into microspheres. The peculiar structure of proteinoids composed of linked amino acids endows them with unique properties, including action-potential like spiking of electrical potential. These unique properties make ensembles of proteinoid microspheres a promising substrate for designing future artificial brains and unconventional computing devices. To evaluate a potential of proteinoid microspheres for unconventional electronic devices we measure and analyse the data-transfer capacities of proteinoid microspheres. In experimental laboratory conditions we demonstrate that the transfer function of proteinoids microspheres is a nontrivial phenomenon, which might be due to the wide range of proteinoid shapes, sizes, and structures.

Proteinoids (thermal proteins) are produced by heating amino acids to their melting point and initiation of polymerisation to produce polymeric chains. Amino acid-like molecules, or proteinoids, can condense at high temperatures to create aggregation structures called proteinoid microspheres, which have been reported to exhibit strong electrical oscillations. When the amino acids L-glutamic acid (L-Glu) and L-aspartic acid (L-Asp) were combined with electric fields of varying frequencies and intensities, electrical activity resulted. We recorded electrical activity of the proteinoid microspheres’ ensembles via a pair of differential electrodes. This is analogous to extracellular recording in physiology or EEG in neuroscience but at micro-level. We discovered that the ensembles produce spikes of electrical potential, an average duration of each spike is 26 min and average amplitude is 1 mV. The spikes are typically grouped in trains of two spikes. The electrical activity of the ensembles can be tuned by external stimulation because ensembles of proteinoid microspheres can generate and propagate electrical activity when exposed to electric fields.

Proteinoids are thermal proteins which swell into microspheres in aqueous solution. Ensembles of proteinoids produce electrical spiking activity similar to that of neurons. We introduce a novel method for implementing logical gates in the ensembles of proteinoid microspheres using chronoamperometry. Chronoamperometry is a technique that involves applying a voltage pulse to proteinoid microspheres and measuring their current response. We have observed that proteinoids exhibit distinct current patterns that align with various logical outputs. We identify four types of logical gates: AND, OR, XOR, and NAND. These gates are determined by the current response of proteinoid microspheres. Additionally, we demonstrate that proteinoid microspheres have the ability to modify their current response over time, which is influenced by their previous exposure to voltage. This indicates that they possess a capacity for learning and are capable of adapting to their environment. Our research showcases the ability of proteinoid microspheres to perform logical operations and computations through their inherent electrical properties.

Proteinoids are synthetic polymers that have structural similarities to natural proteins, and their formation is achieved through the application of heat to amino acid combinations in a dehydrated environment. The thermal proteins, initially synthesised by Sidney Fox during the 1960s, has the ability to undergo self-assembly, resulting in the formation of microspheres that resemble cells. These microspheres have fascinating biomimetic characteristics. In recent studies, substantial advancements have been made in elucidating the electrical signalling phenomena shown by proteinoids, hence showcasing their promising prospects in the field of neuro-inspired computing. This study demonstrates the advancement of experimental prototypes that employ proteinoids in the construction of fundamental neural network structures. The article provides an overview of significant achievements in proteinoid systems, such as the demonstration of electrical excitability, emulation of synaptic functions, capabilities in pattern recognition, and adaptability of network structures. This study examines the similarities and differences between proteinoid networks and spontaneous neural computation. We examine the persistent challenges associated with deciphering the underlying mechanisms of emergent proteinoid-based intelligence. Additionally, we explore the potential for developing bio-inspired computing systems using synthetic thermal proteins in forthcoming times. The results of this study offer a theoretical foundation for the advancement of adaptive, self-assembling electronic systems that operate using artificial bio-neural principles.

Low power gas sensors with high sensitivity and selectivity are desired for many practical applications. Devices based on organic field effect transistors are promising because they can be fabricated at modest cost and are low power devices. Organic field effect transistors fabricated in bottom-gate bottom-contact configuration using the organic semiconductor [2,5-(2-octyldodecyl)-3,6-diketopyrrolopyrrole-alt-5,5-(2,5-di(thien-2-yl)thieno] [3,2-b]thiophene) (DPP-T-TT) were systematically investigated to determine the response characteristics to a series of alkylamines and ammonia. The highest sensitivity was to dibutylamine with a limit of detection of 0.025 ppb, followed by n-butylamine, 0.056 ppb, and ammonia, 2.17 ppb. A model was constructed based on the Antoine equation that successfully allows the empirical prediction of the sensitivity and selectivity of the gas sensor to various analytes including amines and alcohols based on the Antoine C parameter and the heat of the vaporization of the analyte.

Proteinoids, or thermal proteinoids, are produced by heating amino‐acids. When placed in water, proteinoids swell into microspheres which produce neuron‐like spikes of electrical potential. This study combines proteinoid microspheres with Emiliania huxleyi algae to create advanced bioelectronic signal processing systems with neuromorphic characteristics. The morphologies of L‐Glu:L‐Phe proteinoid microspheres and their interactions with algae are studied using scanning electron microscopy, revealing complex structures with budding forms and traits of self‐assembly. Electrical measurements demonstrate that both pure algae and algae‐proteinoid mixtures generate spontaneous oscillations with unique amplitude and frequency patterns across different recording channels. The algae‐proteinoid mixture exhibits a broad range of oscillatory dynamics with amplitudes varying from 25.49 to 191.42 mV and periods ranging from 251.92 to 5471.01 s. These oscillatory behaviors are utilized to perform Boolean logic operations, through post‐processing of biological signals rather than autonomous computing, with pure algae systems showing superior performance for direct gates (AND, OR) while the mixture excels at inverse gates (NAND, NOR). Temperature and pH emerge as critical factors controlling oscillatory dynamics. The findings indicate that algae‐proteinoid electrochemical systems represent a step toward biohybrid computing and offer a sustainable and biocompatible alternative for unconventional computing, providing enhanced signal stability, environmental resilience, and more effective information processing compared to traditional electronic systems while acknowledging current limitations in autonomous learning capabilities.