Bio-inspired Systems Research Articles

Electroactive Bistable Actuators with Tunable Snap‐through Performances and Adjustable Mechanical Bending Modes for Ultrafast Bioinspired Systems

Shape memory alloy (SMA) actuators typically exhibit limited response speed owing to the long duration required for the alloy to cool down and return to its natural shape and compliance after electrical thermal actuation. Herein, a generic design principle for harnessing the mechanical instability of the bistable mechanism to improve the response properties and output force of SMA actuators is proposed. The SMA actuator presented herein is constructed by combining spring‐based bistable linkages and SMA springs as “skeletal spine” and “skeletal muscles,” respectively. Most existing SMA actuators are designed as inherently and unimodally stable, whereas the working performance of the design suggests that it rapidly stores and releases energy within tens of milliseconds by regulating the bistable mechanism. Furthermore, a highly dynamic SMA actuator that can generate a force of ≈3.4 N is demonstrated, bends through 60° in 0.05 s, and achieves periodic deformation under the alternating actuation of two SMA springs. Furthermore, two representative demonstrations of dynamic impact excitation and jumping are verified. Owing to these properties, the actuator can pave a new path toward constructing next‐generation, high‐performance smart actuators with multiple scales and functionalities. It can be applied to next‐generation high‐performance robotic or actuation systems with multifunctional characteristics.

Shaping the future of tunneling with data and emerging technologies

Abstract The increase in global population and urbanization is presenting significant challenges to society: space is becoming increasingly scarce, demand is exceeding capacity for deteriorating infrastructure, transportation is fraught with congestion, and environmental impacts are accelerating. Underground space, and particularly tunnels, has a key role to play in tackling these challenges. However, the cost, risk, uncertainty, and complexity of the tunneling process have impeded its growth. In this paper, we envision several technological advancements that can potentially innovate and transform the mechanized tunneling industry, including artificial intelligence (AI), autonomous, and bio-inspired systems. The proliferation of AI may assist human engineers and operators in making informed decisions systematically and quantitatively based on massive real-time data during tunneling. Autonomous tunneling systems may enable precise and predictable tunneling operations with minimal human intervention and facilitate the construction of massive and large-scale underground infrastructure projects that were previously challenging or unfeasible using conventional methods. Bio-inspired systems may provide valuable references and strategies for more efficient tunneling design and construction concepts. While these technological advancements can offer great promise, they also face considerable challenges, such as improving accessibility to and shareability of tunneling data, developing robust, reliable, and explainable machine learning systems, as well as scaling the mechanics and ensuring the applicability of bio-inspired systems from the prototype level to real-world applications. Addressing these challenges is imperative to ensure the successful implementation of these innovations for future tunneling.

Stimuli-responsive and biomimetic delivery systems for sepsis and related complications.

Sepsis, a consequence of an imbalanced immune response to infection, is currently one of the leading causes of death globally. Despite advances in the discoveries of potential targets and nanotechnology, sepsis still lacks effective drug delivery systems for optimal treatment. Stimuli-responsive and biomimetic nano delivery systems, specifically, are emerging as advanced bio-inspired nanocarriers for enhancing the treatment of sepsis. Herein, we present a critical review of different stimuli-responsive systems, including pH-; enzyme-; ROS- and toxin-responsive nanocarriers, reported in the delivery of therapeutics for sepsis. Biomimetic nanocarriers, utilizing natural pathways in the inflammatory cascade to optimize sepsis therapy, are also reviewed, in addition to smart, multifunctional vehicles. The review highlights the nanomaterials designed for constructing these systems; their physicochemical properties; the mechanisms of drug release; and their potential for enhancing the therapeutic efficacy of their cargo. Current challenges are identified and future avenues for research into the optimization of bio-inspired nano delivery systems for sepsis are also proposed. This review confirms the potential of stimuli-responsive and biomimetic nanocarriers for enhanced therapy against sepsis and related complications.

A Review on the Motion of Magnetically Actuated Bio-Inspired Microrobots

Nature consists of numerous solutions to overcome challenges in designing artificial systems. Various actuation mechanisms have been implemented in microrobots to mimic the motion of microorganisms. Such bio-inspired designs have contributed immensely to microscale developments. Among the actuation mechanisms, magnetic actuation is widely used in bio-inspired microrobotic systems and related propulsion mechanisms used by microrobots to navigate inside a magnetic field and are presented in this review. In addition, the considered robots are in microscale, and they can swim inside a fluidic environment with a low Reynolds number. In relation to microrobotics, mimicry of bacteria flagella, sperm flagella, cilia, and fish are significant. Due to the fact that these biological matters consist of different propulsion mechanisms, the effect of various parameters was investigated in the last decade and the review presents a summary that enhances understanding of the working principle of propulsion mechanisms. In addition, the effect of different parameters on the various speeds of the existing microrobots was analyzed to identify their trends. So, the swimming speeds of the microrobots show an upward trend with increasing body length, frequency, magnetic flux density, and helix angle. Microfabrication techniques play a significant role in the microscale because the device designs are highly dependent on the availability of the techniques. The presented microrobots were manufactured by 3D/4D photolithography and rapid prototyping techniques. Proper materials enable effective fabrication of microrobots using the mentioned techniques. Therefore, magnetically active material types, matrix materials, biocompatible and biodegradable materials are presented in this study. Utilizing biocompatible and biodegradable materials avoids adverse effects to the organs that could occur otherwise. In addition, magnetic field generation is significant for the propulsion of such microrobots. We conclude the review with an overview of the biomimicry of microrobots and magnetically actuated robot propulsion.

Efficient autonomous navigation for terrestrial insect-machine hybrid systems

While bio-inspired and biomimetic systems draw inspiration from living materials, biohybrid systems incorporate them with synthetic devices, allowing the exploitation of both organic and artificial advantages inside a single entity. In the challenging development of centimeter-scaled mobile robots serving unstructured territory navigations, biohybrid systems appear as a potential solution in the forms of terrestrial insect-machine hybrid systems, which are the fusion of living ambulatory insects and miniature electronic devices. Although their maneuver can be deliberately controlled via artificial electrical stimulation, these hybrid systems still inherit the insects’ outstanding locomotory skills, orchestrated by a sophisticated central nervous system and various sensory organs, favoring their maneuvers in complex terrains. However, efficient autonomous navigation of these hybrid systems is challenging. The struggle to optimize the stimulation parameters for individual insects limits the reliability and accuracy of navigation control. This study overcomes this problem by implementing a feedback control system with an insight into tunable navigation control for an insect-machine hybrid system based on a living darkling beetle. Via a thrust controller for acceleration and a proportional controller for turning, the system regulates the stimulation parameters based on the instantaneous status of the hybrid robot. While the system can provide an overall success rate of ∼ 71% for path-following navigations, fine tuning its control parameters could further improve the outcome’s reliability and precision to up to ∼ 94% success rate and ∼ 1/2 body length accuracy, respectively. Such tunable performance of the feedback control system provides flexibility to navigation applications of insect-machine hybrid systems.

Review of Bioinspired Vision-Tactile Fusion Perception (VTFP): From Humans to Humanoids

Humanoid robots are designed and expected to resemble humans in structure and behavior, showing increasing application potentials in various fields. Like their biological counterparts, their environmental perception ability is fundamental. In particular, the visual and tactile perception are the two main sensory modes that humanoids use to understand and interact with the environment. Vision-Tactile Fusion Perception (VTFP) has shown multiple possibilities for better sensing understanding in challenging conditions, causing new research interests and questions. The overlap between visual and tactile perception in humanoids is continually growing. This work has reviewed the current state of the art of VTFP. It starts with the physiological basis of biological vision and tactile systems as well as the VTFP mechanisms as inspirations for humanoid perception. Then, the bioinspired visual-tactile fusion systems for humanoids are reviewed as the emphasis. After the survey on the vision and tactile sensors of robots, seven currently publicly available VTFP datasets are introduced. They are the data sources for several studies on neural network-inspired fusion algorithms. Furthermore, the applications of VTFP on humanoids are summarized. Finally, the challenges and future work are discussed. This review aims to provide several references for further exploitation of VTFP and its applications on humanoids.

Band-type resonance: non-discrete energetically optimal resonant states

Structural resonance involves the absorption of inertial loads by a tuned structural elasticity: a process playing a key role in a wide range of biological and technological systems, including many biological and bio-inspired locomotion systems. Conventional linear and nonlinear resonant states typically exist at specific discrete frequencies and specific symmetric waveforms. This discreteness can be an obstacle to resonant control modulation: deviating from these states, by modulating waveform asymmetry or drive frequency, generally leads to losses in system efficiency. Here, we demonstrate a new strategy for achieving these modulations at no loss of energetic efficiency. Leveraging fundamental advances in nonlinear dynamics, we characterise a new form of structural resonance: band-type resonance, describing a continuous band of energetically optimal resonant states existing around conventional discrete resonant states. These states are a counterexample to the common supposition that deviation from a linear (or nonlinear) resonant frequency necessarily involves a loss of efficiency. We demonstrate how band-type resonant states can be generated via a spectral shaping approach: with small modifications to the system kinematic and load waveforms, we construct sets of frequency- and asymmetry-modulated resonant states that show equal energetic optimality to their conventional discrete analogues. The existence of these non-discrete resonant states in a huge range of oscillators—linear and nonlinear, in many different physical contexts—is a new dynamical systems phenomenon. It has implications not only for biological and bio-inspired locomotion systems but for a constellation of forced oscillator systems across physics, engineering, and biology.

Emulation of bio-synaptic behaviours in copper-doped zinc oxide memristors: A nanoscale scanning probe microscopic study

Memristors emulating biological synapses to perform memory and learning functions are crucial for realizing bio-inspired neuromorphic systems. However, to meet the increasing demand for high-speed operation, low power consumption, and large integration density in neuromorphic architectures, the synaptic functions must be achieved at nanometer scale and with ultra-low write current. This report evidences electronic synapses realized in Cu-doped ZnO (CZO) memristors by nanoscale scanning probe microscopic techniques. In this process, the device can be downsized all the way up to the size of the probe, offering ultra-high density (>109 devices/mm2) of electronic synapses. The essential bio-synaptic functions in the memristor are accomplished with ultra-low write current (∼10 nA) and in a forming-free approach that marks their potential in building power-efficient computing systems. The modulation in device conductivity is elucidated on the basis of charged defect migration, forming conducting bridges across the thickness or locally within the CZO layer. In addition, the influence of Cu-doping in controlling nanoscale neuromorphic and memristive performances of the device is explored. The present study, therefore, demonstrates a novel approach to decipher oxide-based synaptic-memristors and highlights CZO as a promising candidate to fabricate ultra high-density power-efficient neuromorphic devices.

Effect of the Structural Characteristics on Attachment-Detachment Mechanics of a Rigid-Flexible Coupling Adhesive Unit.

The terminal toes of adhesive animals are characterized by rigid-flexible coupling, and their structure–function relationship is an urgent problem to be solved in understanding bioinspired adhesive systems and the design of biomimetic adhesive units. In this paper, inspired by the rigid-flexible coupling adhesive system of the gecko toe, a rigid-flexible coupling adhesive unit was designed, the interface strength of the adhesives under different preloads was tested, and the model and analysis method of the compression and peeling process of the rigid-flexible coupling adhesive unit was established. Meanwhile, combined with the experimental test, the effect of the coupling mechanism of the rigid-flexible structure on the interfacial stress and the final peeling force during the compression and peeling process of the adhesive unit was studied. The research found that the length of the adhesive unit L has no apparent effect on the normal peel force of the system within a specific range, and the normal peeling force increases linearly with the increase in the compression force P; while the influence of the inclination angle θ0 of the adhesive unit and the thickness of the rigid backing layer hb on the final normal peeling force of the system presents nonlinear characteristics, when the inclination angle θ0 of the adhesive unit is 5°, and the thickness of the rigid backing layer hb is 0.2 mm or 0.3 mm, the normal peel force and the ratio of adhesion force to preload the system reaches its maximum value. Compared with the flexible adhesive unit, the compressed zone formed by the rigid-flexible coupling adhesive unit during the same compression process increased by 6.7 times, while under the same peeling force, the peel zone increased by 8 times, and the maximum normal tensile stress at the peeling end decreased by 20 times. The rigid-flexible coupling mechanics improves the uniformity of the contact stress during the compression and peeling process. The research results provide guidelines for the design of the rigid-flexible coupling adhesive unit, further providing the end effector of the bionic wall-climbing robot with a rigid-flexible coupled bionic design.

Generation and Aerobic Oxidative Catalysis of a Cu(II) Superoxo Complex Supported by a Redox-Active Ligand.

Cu systems feature prominently in aerobic oxidative catalysis in both biology and synthetic chemistry. Metal ligand cooperativity is a common theme in both areas as exemplified by galactose oxidase and by aminoxyl radicals in alcohol oxidations. This has motivated investigations into the aerobic chemistry of Cu and specifically the isolation and study of Cu-superoxo species that are invoked as key catalytic intermediates. While several examples of complexes that model biologically relevant Cu(II) superoxo intermediates have been reported, they are not typically competent aerobic catalysts. Here, we report a new Cu complex of the redox-active ligand tBu,TolDHP (2,5-bis((2-t-butylhydrazono)(p-tolyl)methyl)-pyrrole) that activates O2 to generate a catalytically active Cu(II)-superoxo complex via ligand-based electron transfer. Characterization using ultraviolet (UV)-visible spectroscopy, Raman isotope labeling studies, and Cu extended X-ray absorption fine structure (EXAFS) analysis confirms the assignment of an end-on κ1 superoxo complex. This Cu-O2 complex engages in a range of aerobic catalytic oxidations with substrates including alcohols and aldehydes. These results demonstrate that bioinspired Cu systems can not only model important bioinorganic intermediates but can also mediate and provide mechanistic insight into aerobic oxidative transformations.

A Tunable, Simplified Model for Biological Latch Mediated Spring Actuated Systems.

We develop a model of latch-mediated spring actuated (LaMSA) systems relevant to comparative biomechanics and bioinspired design. The model contains five components: two motors (muscles), a spring, a latch, and a load mass. One motor loads the spring to store elastic energy and the second motor subsequently removes the latch, which releases the spring and causes movement of the load mass. We develop freely available software to accompany the model, which provides an extensible framework for simulating LaMSA systems. Output from the simulation includes information from the loading and release phases of motion, which can be used to calculate kinematic performance metrics that are important for biomechanical function. In parallel, we simulate a comparable, directly actuated system that uses the same motor and mass combinations as the LaMSA simulations. By rapidly iterating through biologically relevant input parameters to the model, simulated kinematic performance differences between LaMSA and directly actuated systems can be used to explore the evolutionary dynamics of biological LaMSA systems and uncover design principles for bioinspired LaMSA systems. As proof of principle of this concept, we compare a LaMSA simulation to a directly actuated simulation that includes either a Hill-type force-velocity trade-off or muscle activation dynamics, or both. For the biologically-relevant range of parameters explored, we find that the muscle force-velocity trade-off and muscle activation have similar effects on directly actuated performance. Including both of these dynamic muscle properties increases the accelerated mass range where a LaMSA system outperforms a directly actuated one.

Self-organized rod undulations on pre-stretched textiles

Textile technology is a traditional approach to additive manufacturing based on one-dimensional yarn. Printing solid rods onto pre-stretched textiles creates internal stresses upon relaxation of the pre-stretch, which leads to buckling-induced out-of-plane deformation of the textile. Similar behaviours are well known to occur also in biological systems where differential growth leads to internal stresses that are responsible for the folding or wrinkling of leaves, for example. Our goal was to get a quantitative understanding of this wrinkling by a systematic experimental and numerical investigation of parallel rods printed onto a pre-stretched textile. We vary rod thickness and spacing to obtain wavelength and phase coherence of the wrinkles as a function of these parameters. We also derive a simple analytical description to rationalize these observations. The result is a simple analytical estimate for the phase diagram of behaviours that may be used for design purposes or to describe wrinkling phenomena in biological or bioinspired systems.

Programmable Morphing Hydrogels for Soft Actuators and Robots: From Structure Designs to Active Functions.

Nature provides abundant inspiration and elegant paradigms for the development of smart materials that can actuate, morph, and move on demand. One remarkable capacity of living organisms is to adapt their shapes or positions in response to stimuli. Programmed deformations or movements in plant organs are mainly driven by water absorption/dehydration of cells, while versatile motions of mollusks are based on contraction/extension of muscles. Understanding the general principles of these morphing and motion behaviors can give rise to disruptive technologies for soft robotics, flexible electronics, biomedical devices, etc. As one kind of intelligent material, hydrogels with high similarity to soft biotissues and diverse responses to external stimuli are an ideal candidate to construct soft actuators and robots.The objective of this Account is to give an overview of the fundamental principles for controllable deformations and motions of hydrogels, with a focus on the structure designs and responsive functions of the corresponding soft actuators and robots. This field has been rapidly developed in recent years with a growing understanding of working principles in natural organisms and a substantial revolution of manufacturing technologies to devise bioinspired hydrogel systems with desired structures. Diverse morphing hydrogels and soft actuators/robots have been developed on the basis of several pioneering works, ranging from bending and folding deformations of bilayer hydrogels to self-shaping of non-Euclidean hydrogel surfaces, and from thermoactuated bilayer gel "hands" to electrodriven polyelectrolyte gel "worms". These morphing hydrogels have demonstrated active functions and versatile applications in biomedical and engineering fields.In this Account, we discuss recent progress in morphing hydrogels and highlight the design principles and relevant applications. First, we introduce the fundamentals of basic deformation modes, together with generic structure features, actuation strategies, and morphing mechanisms. The advantages of in-plane gradient structures are highlighted for programmable deformations by harnessing the out-of-plane buckling with bistability nature to obtain sophisticated three-dimensional configurations. Next, we give an overview of soft actuators and robots based on morphing hydrogels and focus on the working principles of the active systems with different structure designs. We discuss the advancements of hydrogel-based soft robots capable of swift locomotion with different gaits and emphasize the significances of structure control and dynamic actuation. Then we summarize versatile applications of hydrogel-based actuators and robots in biomedicines, cargo delivery, soft electronics, information encryption, and so forth. Some hydrogel robots with a built-in feedback loop and self-sensing system exhibit collaborative functions and advanced intelligence that are informative for the design of next-generation hydrogel machines. Finally, concluding remarks are given to discuss future opportunities and remaining challenges in this field. For example, miniature hydrogel-based actuators/robots with therapeutic or diagnostic functions are highly desired for biomedical applications. The morphing mechanisms summarized in this Account should be applicable to other responsive materials. We hope that this Account will inspire more scientists to be involved in this emerging area and make contributions to reveal novel working principles, design multifunctional soft machines, and explore applications in diverse fields.

Chemically Modified Extracellular Vesicles and Applications in Radiolabeling and Drug Delivery.

Extracellular vesicles (EVs) have been exploited as bio-inspired drug delivery systems (DDS) in the biomedical field. EVs have more advantages than synthetic nanoparticles: they are naturally equipped to cross extra- and intra-cellular barriers. Furthermore, they can deliver functional biomolecules from one cell to another even far away in the body. These advantages, along with obtained promising in vivo results, clearly evidenced the potential of EVs in drug delivery. Nevertheless, due to the difficulties of finding a chemical approach that is coherent with EVs’ rational clinical therapeutic use, those in the drug delivery community are expecting more from EVs’ use. Therefore, this review gathered knowledge of the current chemical approaches dealing with the conjugation of EVs for drugs and radiotracers.

Green Synthesis of Nanoparticles Using Bio-Inspired Systems and Electrically Conductive Pattern Fabrication through Laser-Direct Writing.

Systems existing in nature have evolved to operate efficiently over a long period of time, enabling efficient material transformation and processing. These natural systems provide hints for the synthesis of metal nanoparticles through efficient electron generation and transport towards metal ions for the reduction process. In this study, based on the efficient electron transfer mechanism between tryptophan (Trp) in the living body, the possibility of advanced silver patterning on flexible substrates has been presented through laser-direct writing. Irradiation of a low-power laser on the precursor induces the reduction of silver ions to nanoparticles. The sintering of these generated nanoparticles induces a silver conductive pattern by a photothermal/chemical reaction. The method of this study has strength as it supports the possibility of conductive pattern fabrication on various substrates (e.g., glass and PDMS) using a silver-based organic ink with low laser power compared to the conventional nanoparticle-based sintering method. It also suggests its suitability to various applications in terms of sophisticated pattern fabrication with minimized substrate denaturation.

Escaping the Labyrinth of Bioinspiration: Biodiversity as Key to Successful Product Innovation

AbstractNature provides an infinite source of inspiration for innovative designs that may be required to tackle the social, economic, and environmental challenges the world faces. Despite the surging popularity and prevalence, the discipline of bioinspiration is limited in unleashing its full potential by the inadequate understanding of biological and evolutionary concepts, often leading to suboptimal solutions and a lack of further development toward successful products. Here, the constraints and limitations that pose potential pitfalls for bioinspiration, but are generally overlooked by most practitioners of bioinspiration, are discussed. It is highlighted that an awareness of biodiversity is key to address this issue, and ultimately to the successful application of bioinspiration in general. Furthermore, a practical approach to the analysis of biodiversity information is provided and attention is drawn to opportunities for improving the translation of biological knowledge into innovative solutions. Primary emphasis is placed on direct bioinspired product innovations, though many of the concepts central to the ideas are applicable to the wider domain of bioinspired materials science, chemical, and systems engineering, among others. With this perspective, the guiding thread that will enable to escape the labyrinth of bioinspiration and follow the right track to successful innovation is brought back.

2022 ACS National Award winners —Part III

ACS Award in Pure Chemistry: Gabriela S. Schlau-Cohen Sponsor: Alpha Chi Sigma fraternity and the Alpha Chi Sigma Educational Foundation Citation: For elucidating structural and energetic dynamics of biological and bio-inspired systems, particularly membrane proteins Current position: Associate chemistry professor, Massachusetts Institute of Technology Education: ScB, chemical physics, Brown University; PhD, chemistry, University of California, Berkeley Schlau-Cohen on a global challenge she hopes her research will help solve: “Like many of us, I’m scared about climate change and what it’ll mean for my daughter. I hope that our studies of photosynthesis may one day guide the development of affordable and scalable solar energy devices or help make biofuels a feasible renewable energy source. Although this may be a long time off, we need both short-term and long-term solutions for climate change.” What Schlau-Cohen’s colleagues say: “Gabriela is, in my opinion, one of the top experimental physical chemists of her generation.

Application of Neuromorphic Olfactory Approach for High-Accuracy Classification of Malts.

Current developments in artificial olfactory systems, also known as electronic nose (e-nose) systems, have benefited from advanced machine learning techniques that have significantly improved the conditioning and processing of multivariate feature-rich sensor data. These advancements are complemented by the application of bioinspired algorithms and architectures based on findings from neurophysiological studies focusing on the biological olfactory pathway. The application of spiking neural networks (SNNs), and concepts from neuromorphic engineering in general, are one of the key factors that has led to the design and development of efficient bioinspired e-nose systems. However, only a limited number of studies have focused on deploying these models on a natively event-driven hardware platform that exploits the benefits of neuromorphic implementation, such as ultra-low-power consumption and real-time processing, for simplified integration in a portable e-nose system. In this paper, we extend our previously reported neuromorphic encoding and classification approach to a real-world dataset that consists of sensor responses from a commercial e-nose system when exposed to eight different types of malts. We show that the proposed SNN-based classifier was able to deliver 97% accurate classification results at a maximum latency of 0.4 ms per inference with a power consumption of less than 1 mW when deployed on neuromorphic hardware. One of the key advantages of the proposed neuromorphic architecture is that the entire functionality, including pre-processing, event encoding, and classification, can be mapped on the neuromorphic system-on-a-chip (NSoC) to develop power-efficient and highly-accurate real-time e-nose systems.

Bio-inspired sensory systems with integrated capabilities of sensing, data storage, and processing

<sec>In current sensing-computing systems, sensors are used to acquire information from environments, such data are normally analogue, unstructured and even redundant. After the analogue-to-digital conversion (ADC), the data are transferred into digital computers for processing. In computers with the von Neumann architecture, memories and central processing units (CPUs) are physically separated. Such a separation of sensing terminals, memories and CPUs yields serious problems, such as high energy consumption, long response time, huge data storage, and stringent requirements for the communication bandwidth and security. However, time- and energy-efficient ways are urgently required to process information at where data are generated. On the other hand, biological sensory organs respond to external stimuli in real-time with high efficiency due to the integrated capabilities of sensing, memory and computing. Therefore, the problem of separated sensing units, memories and processing units can be solved by emulating biological sensory organs.</sec><sec>In this work, we propose bio-inspired sensory systems with integrated capabilities of sensing, data storage and processing. In such a system, different sensors are used to capture the environmental signals from e.g. gases, light, audio and pressure, then the sensory signals are processed by an analogue signal processor, so that the energy-consuming ADC is avoided, afterwards the sensory signals are processed by a brain-inspired chip which consists of neuron-synapse cores based on memristors. In the neuron-synapse cores, leaky integrate-and-fire (LIF) neurons can be implemented by memristors and capacitors, and adaptive LIF neurons are developed from the LIF neurons to realize unsupervised learning algorithms. The synapses are realized by memristor arrays which can also perform the in-memory computing. By changing the connection between the neurons, the brain-inspired chip can realize different spiking neural networks (SNNs), such as fully connected SNN, convolutional SNN, and recurrent SNN. The synaptic weight in SNNs can be updated according to the spike-timing dependent plasticity (STDP) or the spike-rate dependent plasticity (SRDP). As an example, a bio-inspired olfactory system is demonstrated. In a artificial olfactory system, a sensor array detects and transforms the chemical information about gas molecules into electrical sensory signals. Then the sensory signals are processed by the analogue signal processing unit. After pre-processing, the brain-inspired chip classifies gases by constructing a fully connected SNN with two layers. Such a bio-inspired olfactory system emulates the function of a biological nose, overcoming the low efficiency caused by the frequent sampling, data conversion, transfer and storage under the current sensing-computing architecture. More importantly, the approach of this work can be used to emulate almost all the biological perceptions, such as touch, sight, hearing and taste, through the integration with different types of sensors., Therefore, this work offers a brand new approach to realizing the artificial intelligence (AI).</sec>

Dynamic Self-Rectifying Liquid Metal-Semiconductor Heterointerfaces: A Platform for Development of Bioinspired Afferent Systems.

The assembly of geometrically complex and dynamically active liquid metal/semiconductor heterointerfaces has drawn extensive attention in multidimensional electronic systems. In this study the chemovoltaic driven reactions have enabled the microfluidity of hydrophobic galinstan into a three-dimensional (3D) semiconductor matrix. A dynamic heterointerface is developed between the atomically thin surface oxide of galinstan and the TiO2-Ni interface. Upon the growth of Ga2O3 film at the Ga2O3-TiO2 heterointerface, the partial reduction of the TiO2 film was confirmed by material characterization techniques. The conductance imaging spectroscopy and electrical measurements are used to investigate the charge transfer at heterointerfaces. Concurrently, the dynamic conductance in artificial synaptic junctions is modulated to mimic the biofunctional communication characteristics of multipolar neurons, including slow and fast inhibitory and excitatory postsynaptic responses. The self-rectifying characteristics, femtojoule energy processing, tunable synaptic events, and notably the coordinated signal recognition are the main characteristics of this multisynaptic device. This novel 3D design of liquid metal-semiconductor structure opens up new opportunities for the development of bioinspired afferent systems. It further facilitates the realization of physical phenomena at liquid metal-semiconductor heterointerfaces.