On Boolean gates in fungal colony

Advancing Molecular-Scale Logic Devices through Multistage Switching in a Luminescent Bimetallic Ru(II)-Terpyridine Complex

Stimuli-responsive multistep switching phenomena of a luminescent bimetallic Ru(II) complex are employed herein to fabricate multiple configurable logic devices. The complex exhibits "off-on" and "on-off" emission switching upon alternative treatment with visible and UV light. Additionally, remarkable augmentation of the rate as well as quantum yield of photoisomerization was achieved via the use of a chemical oxidant (Ce4+) as well as a reductant (metallic sodium). Upon exploiting the emission spectral response of the complex, several advanced Boolean logic functions, including IMPLICATION as well as 2-input 2-output and 3-input 2-output complex combinational logic gates, are successfully implemented. Additionally, by utilizing the vast efficacy of Python, a novel "logic_circuit" model is devised that is capable of making accurate decisions under the influence of various input combinations. This model transcends traditional Boolean logic gates, offering flexibility and intuition to design logical functions tailored to specific chemical contexts. By integrating principles of logic circuits with chemical processes, this innovative approach enables structure determination of the chemical states based on input conditions, thereby unlocking avenues for exploring intricate interactions and reactions beyond conventional Boolean logic paradigms.

Logical circuits in colloids

Colloid-based computing devices offer remarkable fault tolerance and adaptability to varying environmental conditions due to their amorphous structure. An intriguing observation is that a colloidal suspension of ZnO nanoparticles in dimethylsulfoxide (DMSO) exhibits reconfiguration when exposed to electrical stimulation and produces spikes of electrical potential in response. This study presents a novel laboratory prototype of a ZnO colloidal computer, showcasing its capability to implement various Boolean functions featuring two, four and eight inputs. During our experiments, we input binary strings into the colloid mixture, where a logical 'True' state is represented by an impulse of an electrical potential. In contrast, the absence of the electrical impulse denotes a logical 'False' state. The electrical responses of the colloid mixture are recorded, allowing us to extract truth tables from the recordings. Through this methodological approach, we demonstrate the successful implementation of a wide range of logical functions using colloidal mixtures. We provide detailed distributions of the logical functions discovered and offer speculation on the potential impacts of our findings on future and emerging unconventional computing technologies. This research highlights the exciting possibilities of colloid-based computing and paves the way for further advancements.

Human brain-inspired chemical artificial intelligence tools for the analysis and prediction of the anion-sensing characteristics of an imidazole-based luminescent Os(II)-bipyridine complex

Neural network and decision tree-based soft computing techniques are implemented in this work for the thorough analysis of the multichannel anion-sensing characteristics of an Os(II)-bipyridine complex derived from imidazole-4,5-bis(benzimidazole) ligand. With the aid of three imidazole NH protons in its outer coordination sphere, a substantial change in the spectral response as well as Os^II/Os^III potential is made possible upon treating with anions of varying basicity. Initial hydrogen bonding between NH protons and anions and thereafter complete proton transfer from the complex backbone probably take place in the process. The deprotonation of the complex by specific anions and restoration to its original form by acid is also reversible. The responsiveness of the new compound is complex enough to imitate multiple sophisticated binary and ternary Boolean logic (BL) functions (NOT logic, combinational logic, traffic signal, set-reset flip-flop logic, and ternary NOR logic) by employing its spectral and redox outputs upon the action of suitable anions and acid in a proper sequence. Executing sensing investigations on altering the amount of the anions within a widespread range is often time-consuming and tedious. To overcome the lacuna, we implemented multiple soft computing techniques, viz., fuzzy logic (FL), artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS), and decision tree (DT) regression, for the thorough analysis and prediction of the experimentally observed results. The outcomes obtained from different techniques were compared among themselves as well as with the experimental data and utilized for the proper modeling of the anion-sensing behaviors of the complex.

Electrical response of fungi to changing moisture content

Mycelium-bound composites are potential alternatives to conventional materials for a variety of applications, including thermal and acoustic building panels and product packaging. If the reactions of live mycelium to environmental conditions and stimuli are taken into account, it is possible to create functioning fungal materials. Thus, active building components, sensory wearables, etc. might be created. This research describes the electrical sensitivity of fungus to changes in the moisture content of a mycelium-bound composite. Trains of electrical spikes initiate spontaneously in fresh mycelium-bound composites with a moisture content between [Formula: see text] 95% and [Formula: see text] 65%, and between [Formula: see text] 15% and [Formula: see text] 5% when partially dried. When the surfaces of mycelium-bound composites were partially or totally encased with an impermeable layer, increased electrical activity was observed. In fresh mycelium-bound composites, electrical spikes were seen both spontaneously and when induced by water droplets on the surface. Also explored is the link between electrical activity and electrode depth. Future designs of smart buildings, wearables, fungi-based sensors, and unconventional computer systems may benefit from fungi configurations and biofabrication flexibility.

Responsive fungal insoles for pressure detection

Mycelium bound composites are promising materials for a diverse range of applications including wearables and building elements. Their functionality surpasses some of the capabilities of traditionally passive materials, such as synthetic fibres, reconstituted cellulose fibres and natural fibres. Thereby, creating novel propositions including augmented functionality (sensory) and aesthetic (personal fashion). Biomaterials can offer multiple modal sensing capability such as mechanical loading (compressive and tensile) and moisture content. To assess the sensing potential of fungal insoles we undertook laboratory experiments on electrical response of bespoke insoles made from capillary matting colonised with oyster fungi Pleurotus ostreatus to compressive stress which mimics human loading when standing and walking. We have shown changes in electrical activity with compressive loading. The results advance the development of intelligent sensing insoles which are a building block towards more generic reactive fungal wearables. Using FitzHugh-Nagumo model we numerically illustrated how excitation wave-fronts behave in a mycelium network colonising an insole and shown that it may be possible to discern pressure points from the mycelium electrical activity.

Neural network and decision tree-based machine learning tools to analyse the anion-responsive behaviours of emissive Ru(ii)–terpyridine complexes

Artificial neural network, adaptive neuro-fuzzy inference and decision tree regression are implemented to analyse the anion-responsive behaviours of emissive Ru(ii)–terpyridine complexes.

Mining logical circuits in fungi

Living substrates are capable for nontrivial mappings of electrical signals due to the substrate nonlinear electrical characteristics. This property can be used to realise Boolean functions. Input logical values are represented by amplitude or frequency of electrical stimuli. Output logical values are decoded from electrical responses of living substrates. We demonstrate how logical circuits can be implemented in mycelium bound composites. The mycelium bound composites (fungal materials) are getting growing recognition as building, packaging, decoration and clothing materials. Presently the fungal materials are passive. To make the fungal materials adaptive, i.e. sensing and computing, we should embed logical circuits into them. We demonstrate experimental laboratory prototypes of many-input Boolean functions implemented in fungal materials from oyster fungi P. ostreatus. We characterise complexity of the functions discovered via complexity of the space-time configurations of one-dimensional cellular automata governed by the functions. We show that the mycelium bound composites can implement representative functions from all classes of cellular automata complexity including the computationally universal. The results presented will make an impact in the field of unconventional computing, experimental demonstration of purposeful computing with fungi, and in the field of intelligent materials, as the prototypes of computing mycelium bound composites.

Neuro-Fuzzification Architecture for Modeling of Electrochemical Ion-Sensing Data of Imidazole-Dicarboxylate-Based Ru(II)-Bipyridine Complex

Anion- and pH-sensing behaviors of an imidazole-dicarboxylate-based Ru(II)-bipyridine complex possessing a number of dissociable protons in its secondary coordination sphere are employed here for the creation of multiple Boolean and fuzzy logic systems. The absorption, emission, and electrochemical behaviors of the metalloreceptor were significantly modulated upon the influence of basic anions (such as F^-, AcO^-, and H₂PO₄^-) as well as by altering the pH of the solution. Interestingly, the deprotonation of the metalloreceptor by selected anions or by alkaline pH, followed by its restoration to its original form by acid or acidic pH is reversible and could be repeated many times. The metalloreceptor is capable to demonstrate several advanced Boolean functions, namely, three-input OR gate, set-reset flip-flop logic, and traffic signal, by employing its electrochemical responses through proper use of different inputs. Administering exhaustive sensing experiments by changing the analyte concentration within a wide range is usually tedious as well as exorbitantly costly. To get rid of these difficulties, we employed here several soft computing approaches such as artificial neural networks (ANN), fuzzy logic systems (FLS), or adaptive neuro-fuzzy inference system (ANFIS) to foresee the experimental sensing data and to appropriately model the protonation-deprotonation behaviors of the metalloreceptor. Reasonably good correlation between the experimental and model output data is also reflected in their tested root-mean-square error values (0.115961 and 0.118894 for the ANFIS model).

Mem-fractive properties of mushrooms

Memristors close the loop forI-Vcharacteristics of the traditional, passive, semi-conductor devices. A memristor is a physical realisation of the material implication and thus is a universal logical element. Memristors are getting particular interest in the field of bioelectronics. Electrical properties of living substrates are not binary and there is nearly a continuous transitions from being non-memristive to mem-fractive (exhibiting a combination of passive memory) to ideally memristive. In laboratory experiments we show that living oyster mushroomsPleurotus ostreatusexhibit mem-fractive properties. We offer a piece-wise polynomial approximation of theI-Vbehaviour of the oyster mushrooms. We also report spiking activity, oscillations in conduced current of the oyster mushrooms.

Risk assessment of fungal materials

Sustainable fungal materials have a high potential to replace non-sustainable materials such as those used for packaging or as an alternative for leather and textile. The properties of fungal materials depend on the type of fungus and substrate, the growth conditions and post-treatment of the material. So far, fungal materials are mainly made with species from the phylum Basidiomycota, selected for the mechanical and physical properties they provide. However, for mycelium materials to be implemented in society on a large scale, selection of fungal species should also be based on a risk assessment of the potential to be pathogenic, form mycotoxins, attract insects, or become an invasive species. Moreover, production processes should be standardized to ensure reproducibility and safety of the product.

Fungal electronics

Fungal electronics is a family of living electronic devices made of mycelium bound composites or pure mycelium. Fungal electronic devices are capable of changing their impedance and generating spikes of electrical potential in response to external control parameters. Fungal electronics can be embedded into fungal materials and wearables or used as stand alone sensing and computing devices.

Stimulating Fungi Pleurotus ostreatus with Hydrocortisone

Fungi cells can sense extracellular signals via reception, transduction, and response mechanisms, allowing them to communicate with their host and adapt to their environment. They feature effective regulatory protein expressions that enhance and regulate their response and adaptation to various triggers such as stress, hormones, physical stimuli such as light, and host factors. In our recent studies, we have shown that Pleurotus oyster fungi generate electrical potential impulses in the form of spike events in response to their exposure to environmental, mechanical, and chemical triggers, suggesting that the nature of stimuli may be deduced from the fungal electrical responses. In this study, we explored the communication protocols of fungi as reporters of human chemical secretions such as hormones, addressing whether fungi can sense human signals. We exposed Pleurotus oyster fungi to hydrocortisone, which was directly applied to the surface of a fungal-colonized hemp shavings substrate, and recorded the electrical activity of the fungi. Hydrocortisone is a medicinal hormone replacement that is similar to the natural stress hormone cortisol. Changes in cortisol levels released by the body indicate the presence of disease and can have a detrimental effect on physiological process regulation. The response of fungi to hydrocortisone was also explored further using X-rays to reveal changes in the fungi tissue, where receiving hydrocortisone by the substrate can inhibit the flow of calcium and, as a result, reduce its physiological changes. This research could open the way for future studies on adaptive fungal wearables capable of detecting human physiological states and biosensors built of living fungi.

Exploring the symbol processing 'time interval' parametric constraint in a Belousov-Zhabotinsky operated chemical Turing machine

Chemical reactions are powerful molecular recognition machines. This power has been recently harnessed to build actual instances of each class of experimentally realizable computing automata, using exclusively small-molecule chemistry (i.e. without requiring biomolecules). The most powerful of them, a programmable Turing machine, uses the Belousov-Zhabotinsky oscillatory chemistry, and accepts/rejects input sequences through a dual oscillatory and thermodynamic output signature. The time interval between the aliquots representing each letter of the input is the parameter that determines the time it takes to run the computation. Here, we investigate this critical performance parameter, and its effect not only on the computation speed, but also on the robustness of the accept/reject oscillatory and thermodynamic criteria. Our work demonstrates that the time interval is a non-trivial design parameter, whose choice should be made with great care. The guidelines we provide can be used in the optimization of the speed, robustness, and energy efficiency of chemical automata computations.

Reactive fungal wearable

Smart wearables sense and process information from the user's body and environment and report results of their analysis as electrical signals. Conventional electronic sensors and controllers are commonly, sometimes augmented by recent advances in soft electronics. Organic electronics and bioelectronics, especially with living substrates, offer a great opportunity to incorporate parallel sensing and information processing capabilities of natural systems into future and emerging wearables. Nowadays fungi are emerging as a promising candidate to produce sustainable textiles to be used as ecofriendly biowearables. To assess the sensing potential of fungal wearables we undertook laboratory experiments on electrical response of a hemp fabric colonised by oyster fungi Pleurotus ostreatus to mechanical stretching and stimulation with attractants and repellents. We have shown that it is possible to discern a nature of stimuli from the fungi electrical responses. The results paved a way towards future design of intelligent sensing patches to be used in reactive fungal wearables.