Memristor-based adaptive neuromorphic perception in unstructured environments.

Efficient operation of control systems in robotics or autonomous driving targeting real-world navigation scenarios requires perception methods that allow them to understand and adapt to unstructured environments with good accuracy, adaptation, and generality, similar to humans. To address this need, we present a memristor-based differential neuromorphic computing, perceptual signal processing, and online adaptation method providing neuromorphic style adaptation to external sensory stimuli. The adaptation ability and generality of this method are confirmed in two application scenarios: object grasping and autonomous driving. In the former, a robot hand realizes safe and stable grasping through fast ( ~ 1 ms) adaptation based on the tactile object features with a single memristor. In the latter, decision-making information of 10 unstructured environments in autonomous driving is extracted with an accuracy of 94% with a 40×25 memristor array. By mimicking human low-level perception mechanisms, the electronic neuromorphic circuit-based method achieves real-time adaptation and high-level reactions to unstructured environments.

Highly Conductive PEDOT:PSS: Ag Nanowire-Based Nanofibers for Transparent Flexible Electronics.

Highly conductive, transparent, and easily available materials are needed in a wide range of devices, such as sensors, solar cells, and touch screens, as alternatives to expensive and unsustainable materials such as indium tin oxide. Herein, electrospinning was employed to develop fibers of PEDOT:PSS/silver nanowire (AgNW) composites on various substrates, including poly(caprolactone) (PCL), cotton fabric, and Kapton. The influence of AgNWs, as well as the applied voltage of electrospinning on the conductivity of fibers, was thoroughly investigated. The developed fibers showed a sheet resistance of 7 Ω/sq, a conductivity of 354 S/cm, and a transmittance value of 77%, providing excellent optoelectrical properties. Further, the effect of bending on the fibers' electrical properties was analyzed. The sheet resistance of fibers on the PCL substrate increased slightly from 7 to 8 Ω/sq, after 1000 bending cycles. Subsequently, as a proof of concept, the nanofibers were evaluated as electrode material in a triboelectric nanogenerator (TENG)-based energy harvester, and they were observed to enhance the performance of the TENG device (78.83 V and 7 µA output voltage and current, respectively), as compared to the same device using copper electrodes. These experiments highlight the untapped potential of conductive electrospun fibers for flexible and transparent electronics.

Out-of-Plane Electronics on Flexible Substrates Using Inorganic Nanowires Grown on High-Aspect-Ratio Printed Gold Micropillars.

Out-of-plane or 3D electronics on flexible substrates are an interesting direction that can enable novel solutions such as efficient bioelectricity generation and artificial retina. However, the development of devices with such architectures is limited by the lack of suitable fabrication techniques. Additive manufacturing (AM) can but often fail to provide high-resolution, sub-micrometer 3D architectures. Herein, the optimization of a drop-on-demand (DoD), high-resolution electrohydrodynamic (EHD)-based jet printing method for generating 3D gold (Au) micropillars is reported. Libraries of Au micropillar electrode arrays (MEAs) reaching a maximum height of 196 µm and a maximum aspect ratio of 52 are printed. Further, by combining AM with the hydrothermal growth method, a seedless synthesis of zinc oxide (ZnO) nanowires (NWs) on the printed Au MEAs is demonstrated. The developed hybrid approach leads to hierarchical light-sensitive NW-connected networks exhibiting favorable ultraviolet (UV) sensing as demonstrated via fabricating flexible photodetectors (PDs). The 3D PDs exhibit an excellent omnidirectional light-absorption ability and thus, maintain high photocurrents over wide light incidence angles (±90°). Lastly, the PDs are tested under both concave and convex bending at 40 mm, showing excellent mechanical flexibility.

Printed n- and p-Channel Transistors using Silicon Nanoribbons Enduring Electrical, Thermal, and Mechanical Stress.

Printing technologies are changing the face of electronics with features such as resource-efficiency, low-cost, and novel form factors. While significant advances have been made in terms of organic electronics, the high-performance and stable transistors by printing, and their large-scale integration leading to fast integrated circuits remains a major challenge. This is because of the difficulties to print high-mobility semiconducting materials and the lack of high-resolution printing techniques. Herein, we present silicon based printed n- and p-channel transistors to demonstrate the possibility of developing high-performance complementary metal-oxide-semiconductor (CMOS) computing architecture. The direct roll transfer printing is used here for deterministic assembly of high-mobility single crystal silicon nanoribbons arrays on a flexible polyimide substrate. This is followed by high-resolution electrohydrodynamic printing to define source/drain/gate electrodes and to encapsulate, thus leading to printed devices. The printed transistors show effective peak mobilities of 15 cm2/(V s) (n-channel) and 5 cm2/(V s) (p-channel) at low 1 V drain bias. Furthermore, the effect of electrical, mechanical, and thermal stress on the performance and stability of the encapsulated transistors is investigated. The transistors showed stable transfer characteristics even after: (i) continuous 4000 transfer cycles, (ii) excruciating 10000 bending cycles at different bending radii (40, 25, and 15 mm), and (iii) between 15 and 60 °C temperatures.

Triboelectric Nanogenerators as Power Sources for Chemical Sensors and Biosensors.

The recent advances of portable sensors in flexible and wearable form factors are drawing increasing attention worldwide owing to their requirement applications ranging from health monitoring to environment monitoring. While portability is critical for these applications, real-time data gathering also requires a reliable power supply-which is largely met with batteries. Besides the need for regular charging, the use of toxic chemicals in batteries makes it difficult to rely on them, and as a result different types of energy harvesters have been explored in recent years. Among these, triboelectric nanogenerators (TENGs) provide a promising platform for harnessing ambient energy and converting it into usable electric signals. The ease of fabrication and possibility to develop TENGs with a diverse range of easily available materials also make them attractive. This review focuses on the TENG technology and its efficient use as a power source for various types of chemical sensors and biosensors. The paper describes the underlying mechanism, various modes of working of TENGs, and representative examples of their utilization as power sources for sensing a multitude of analytes. The challenges associated with their adoption for commercial solutions are also discussed to stimulate further advances and innovations.

Real-time noise cancellation with deep learning.

Biological measurements are often contaminated with large amounts of non-stationary noise which require effective noise reduction techniques. We present a new real-time deep learning algorithm which produces adaptively a signal opposing the noise so that destructive interference occurs. As a proof of concept, we demonstrate the algorithm's performance by reducing electromyogram noise in electroencephalograms with the usage of a custom, flexible, 3D-printed, compound electrode. With this setup, an average of 4dB and a maximum of 10dB improvement of the signal-to-noise ratio of the EEG was achieved by removing wide band muscle noise. This concept has the potential to not only adaptively improve the signal-to-noise ratio of EEG but can be applied to a wide range of biological, industrial and consumer applications such as industrial sensing or noise cancelling headphones.

Skin-Inspired Thermoreceptors-Based Electronic Skin for Biomimicking Thermal Pain Reflexes.

Electronic systems possessing skin-like morphology and functionalities (electronic skins [e-skins]) have attracted considerable attention in recent years to provide sensory or haptic feedback in growing areas such as robotics, prosthetics, and interactive systems. However, the main focus thus far has been on the distributed pressure or force sensors. Herein a thermoreceptive e-skin with biological systems like functionality is presented. The soft, distributed, and highly sensitive miniaturized (≈700 µm2 ) artificial thermoreceptors (ATRs) in the e-skin are developed using an innovative fabrication route that involves dielectrophoretic assembly of oriented vanadium pentoxide nanowires at defined locations and high-resolution electrohydrodynamic printing. Inspired from the skin morphology, the ATRs are embedded in a thermally insulating soft nanosilica/epoxy polymeric layer and yet they exhibit excellent thermal sensitivity (-1.1 ± 0.3% °C-1 ), fast response (≈1s), exceptional stability (negligible hysteresis for >5 h operation), and mechanical durability (up to 10 000 bending and twisting loading cycles). Finally, the developed e-skin is integrated on the fingertip of a robotic hand and a biological system like reflex is demonstrated in response to temperature stimuli via localized learning at the hardware level.

Printed synaptic transistor-based electronic skin for robots to feel and learn.

An electronic skin (e-skin) for the next generation of robots is expected to have biological skin-like multimodal sensing, signal encoding, and preprocessing. To this end, it is imperative to have high-quality, uniformly responding electronic devices distributed over large areas and capable of delivering synaptic behavior with long- and short-term memory. Here, we present an approach to realize synaptic transistors (12-by-14 array) using ZnO nanowires printed on flexible substrate with 100% yield and high uniformity. The presented devices show synaptic behavior under pulse stimuli, exhibiting excitatory (inhibitory) post-synaptic current, spiking rate-dependent plasticity, and short-term to long-term memory transition. The as-realized transistors demonstrate excellent bio-like synaptic behavior and show great potential for in-hardware learning. This is demonstrated through a prototype computational e-skin, comprising event-driven sensors, synaptic transistors, and spiking neurons that bestow biological skin-like haptic sensations to a robotic hand. With associative learning, the presented computational e-skin could gradually acquire a human body-like pain reflex. The learnt behavior could be strengthened through practice. Such a peripheral nervous system-like localized learning could substantially reduce the data latency and decrease the cognitive load on the robotic platform.

Neuro-inspired electronic skin for robots.

Touch is a complex sensing modality owing to large number of receptors (mechano, thermal, pain) nonuniformly embedded in the soft skin all over the body. These receptors can gather and encode the large tactile data, allowing us to feel and perceive the real world. This efficient somatosensation far outperforms the touch-sensing capability of most of the state-of-the-art robots today and suggests the need for neural-like hardware for electronic skin (e-skin). This could be attained through either innovative schemes for developing distributed electronics or repurposing the neuromorphic circuits developed for other sensory modalities such as vision and audio. This Review highlights the hardware implementations of various computational building blocks for e-skin and the ways they can be integrated to potentially realize human skin-like or peripheral nervous system-like functionalities. The neural-like sensing and data processing are discussed along with various algorithms and hardware architectures. The integration of ultrathin neuromorphic chips for local computation and the printed electronics on soft substrate used for the development of e-skin over large areas are expected to advance robotic interaction as well as open new avenues for research in medical instrumentation, wearables, electronics, and neuroprosthetics.

Self-Powered Active Sensing Based on Triboelectric Generators.

The demand for portable and wearable chemical or biosensors and their expeditious development in recent years has created a scientific challenge in terms of their continuous powering. As a result, mechanical energy harvesters such as piezoelectric and triboelectric generators (TEGs) have been explored recently either as sensors or harvesters to store charge in small, but long-life, energy-storage devices to power the sensors. The use of energy harvesters as sensors is particularly interesting, as with such multifunctional operations it is possible to reduce the number devices needed in a system, which also helps overcome the integration complexities. In this regard, TEGs are promising, particularly for energy autonomous chemical and biological sensors, as they can be developed with a wide variety of materials, and their mechanical energy to electricity conversion can be modulated by various analytes. This review focuses on this interesting dimension of TEGs and presents various self-powered active chemical and biological sensors. A brief discussion about the development of TEG-based physical, magnetic, and optical sensors is also included. The influence of environmental factors, various figures of merit, and the significance of TEG design are explained in context with the active sensing. Finally, the key applications, challenges, and future perspective of chemical and biological detection via TEGs are discussed with a view to drive further advances in the field of self-powered sensors.

Graphite-Based Bioinspired Piezoresistive Soft Strain Sensors with Performance Optimized for Low Strain Values.

This paper presents the custom-made graphite-based piezoresistive strain sensor with gecko foot-inspired macroscopic features realized using a Velcro tape on Ecoflex substrate. The Velcro-based design provides an inexpensive and easy approach for the development of soft sensors with appreciable improvement in the performance even at low strain values. The sensor demonstrated excellent response (sensitivity of ∼16 500%, gauge factor of ∼3800) for 24% linear strain. The fabricated device showed a high gauge factor (>100) even for very low strain values. The sensor has been extensively characterized with a view to potentially use in soft robotics applications where high performance is needed at lower strain values. It is observed that the piezoresistive behavior of strain sensors is governed by several factors such as the supporting elastic medium, architecture of the strain sensor, material properties, strain rate and deformation sequence, and direction.

Correction: Development of a highly controlled system for large-area, directional printing of quasi-1D nanomaterials.

[This corrects the article DOI: 10.1038/s41378-021-00314-6.].

Development of a highly controlled system for large-area, directional printing of quasi-1D nanomaterials.

Printing is a promising method for the large-scale, high-throughput, and low-cost fabrication of electronics. Specifically, the contact printing approach shows great potential for realizing high-performance electronics with aligned quasi-1D materials. Despite being known for more than a decade, reports on a precisely controlled system to carry out contact printing are rare and printed nanowires (NWs) suffer from issues such as location-to-location and batch-to-batch variations. To address this problem, we present here a novel design for a tailor-made contact printing system with highly accurate control of printing parameters (applied force: 0-6 N ± 0.3%, sliding velocity: 0-200 mm/s, sliding distance: 0-100 mm) to enable the uniform printing of nanowires (NWs) aligned along 93% of the large printed area (1 cm2). The system employs self-leveling platforms to achieve optimal alignment between substrates, whereas the fully automated process minimizes human-induced variation. The printing dynamics of the developed system are explored on both rigid and flexible substrates. The uniformity in printing is carefully examined by a series of scanning electron microscopy (SEM) images and by fabricating a 5 × 5 array of NW-based photodetectors. This work will pave the way for the future realization of highly uniform, large-area electronics based on printed NWs.

MnOx-Electrodeposited Fabric-Based Stretchable Supercapacitors with Intrinsic Strain Sensing.

The increasing number of devices needed by wearable systems to bring radical advances in healthcare, robotics, and human-machine interfaces is a threat to their growth if the integration and energy-related challenges are not managed. A natural solution is to reduce the number of devices while retaining the functionality or simply using multifunctional devices, as demonstrated here through a stretchable supercapacitor (SSC) with intrinsic strain sensing. The presented SSC was obtained by electrodeposition of nanoflower MnOx on fabric (as a pseudocapacitive electrode) and three-dimensional conductive wrapping of poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) to boost the performance. Among fabricated devices, the stretchable PEDOT:PSS/MnOx/PEDOT:PSS supercapacitor (SPMP-SC) showed the best performance (specific capacitance of 580 mF·cm-2 (108.1 F·g-1); energy density of 51.4 µWh·cm-2 at 0.5 mA). The stretchability (0-100%; 1000 cycles) analysis of SPMP-SC with Ecoflex encapsulation showed high capacitance retention (>90% for 40% stretch). The intrinsic strain sensing of the SSC was confirmed by the linear variation of capacitance (sensitivity -0.4%) during stretching. Finally, as a proof-of-concept, the application of SSC with intrinsic sensing was demonstrated for health monitoring through volumetric expansion of a manikin during ventilator operation and in robotics and by measuring the joint angle of a robotic hand.

Energy Autonomous Sweat-Based Wearable Systems.

The continuous operation of wearable electronics demands reliable sources of energy, currently met through Li-ion batteries and various energy harvesters. These solutions are being used out of necessity despite potential safety issues and unsustainable environmental impact. Safe and sustainable energy sources can boost the use of wearables systems in diverse applications such as health monitoring, prosthetics, and sports. In this regard, sweat- and sweat-equivalent-based studies have attracted tremendous attention through the demonstration of energy-generating biofuel cells, promising power densities as high as 3.5 mW cm-2 , storage using sweat-electrolyte-based supercapacitors with energy and power densities of 1.36 Wh kg-1 and 329.70 W kg-1 , respectively, and sweat-activated batteries with an impressive energy density of 67 Ah kg-1 . A combination of these energy generating, and storage devices can lead to fully energy-autonomous wearables capable of providing sustainable power in the µW to mW range, which is sufficient to operate both sensing and communication devices. Here, a comprehensive review covering these advances, addressing future challenges and potential solutions related to fully energy-autonomous wearables is presented, with emphasis on sweat-based energy storage and energy generation elements along with sweat-based sensors as applications.

Textile-Based Stretchable Microstrip Antenna with Intrinsic Strain Sensing.

This paper presents a textile-based stretchable microstrip patch antenna with intrinsic strain for e-textiles with seamlessly integrated multifunctional devices. Several microstrip antennas have been developed with the patch alone (stretchable up to 40%) or both the patch and the ground plane (stretchable up to 100%) meshed by using rectangular serpentine units. The changes in the resonant frequency of the meshed antennas, as a result of stretching, have been exploited to demonstrate the intrinsic uniaxial strain sensing. The obtained results indicate that resonant frequency decreases linearly with increasing applied strain, suggesting that the designed antennas can also be used as strain sensors with stretchability up to 100% and a sensitivity of 0.25. The results were validated through full-wave electromagnetic simulations and a two-dimensional digital image correlation (DIC) technique to model the antenna deformations during the tensile tests. In terms of stretchability, the meshed textile patch antenna on a solid ground plane showed more than a 2-fold improvement compared to a meshed gold patch antenna, showing a linear frequency shift. As potential applications, we demonstrate the use of a highly deformable fully meshed textile antenna as a strain sensor capable of measuring joint angles of a human limb. To do that, a microwave readout circuit based on RF to DC rectifier was realized. The rectifier obtained a peak conversion efficiency of 71% at 10 dBm input power overload resistor of 3 kΩ.

Biodegradable Materials for Sustainable Health Monitoring Devices.

The recent advent of biodegradable materials has offered huge opportunity to transform healthcare technologies by enabling sensors that degrade naturally after use. The implantable electronic systems made from such materials eliminate the need for extraction or reoperation, minimize chronic inflammatory responses, and hence offer attractive propositions for future biomedical technology. The eco-friendly sensor systems developed from degradable materials could also help mitigate some of the major environmental issues by reducing the volume of electronic or medical waste produced and, in turn, the carbon footprint. With this background, herein we present a comprehensive overview of the structural and functional biodegradable materials that have been used for various biodegradable or bioresorbable electronic devices. The discussion focuses on the dissolution rates and degradation mechanisms of materials such as natural and synthetic polymers, organic or inorganic semiconductors, and hydrolyzable metals. The recent trend and examples of biodegradable or bioresorbable materials-based sensors for body monitoring, diagnostic, and medical therapeutic applications are also presented. Lastly, key technological challenges are discussed for clinical application of biodegradable sensors, particularly for implantable devices with wireless data and power transfer. Promising perspectives for the advancement of future generation of biodegradable sensor systems are also presented.

Rapid Assessment of SARS-CoV-2 Transmission Risk for Fecally Contaminated River Water.

Following the outbreak of severe acute respiratory syndrome coronavirus (SARS-CoV-2), airborne water droplets have been identified as the main transmission route. Identifying and breaking all viable transmission routes are critical to stop future outbreaks, and the potential of transmission by water has been highlighted. By modifying established approaches, we provide a method for the rapid assessment of the risk of transmission posed by fecally contaminated river water and give example results for 39 countries. The country relative risk of transmission posed by fecally contaminated river water is related to the environment and the populations' infection rate and water usage. On the basis of in vitro data and using temperature as the primary controller of survival, we then demonstrate how viral loads likely decrease after a spill. These methods using readily available data suggest that sewage spills into rivers within countries with high infection rates could provide infectious doses of >40 copies per 100 mL of water. The approach, implemented in the supplementary spreadsheet, can provide a fast estimate of the upper and lower viral load ranges following a riverine spill. The results enable evidence-based research recommendations for wastewater epidemiology and could be used to evaluate the significance of fecal-oral transmission within freshwater systems.

Ultra-Thin Chips With ISFET Array for Continuous Monitoring of Body Fluids Ph.

This paper presents ISFET array based pH-sensing system-on-ultra-thin-chip (SoUTC) designed and fabricated in 350 nm CMOS technology. The SoUTC with the proposed current-mode active-pixel ISFET circuit array is desined to operate at 2 V and consumes 6.28 µW per-pixel. The presented SoUTC exhibits low sensitivity to process, voltage, temperature and strain-induced (PVTS) variations. The silicon area occupancy of each active-pixel is 44.9 × 33.5 µm2 with an ion-sensing area of 576 µm2. The design of presented ISFET device is analysed with finite element modeling in COMSOL Multiphysics using compact model parameters of MOSFET in 350 nm CMOS technology. Owing to thin (∼30 µm) Si-substrate the presented SoUTC can conform to curvilinear surfaces, allowing intimate contact necessary for reliable data for monitoring of analytes in body fluids such as sweat. Further, it can operate either in a rolling shutter fashion or in a pseudo-random pixel selection mode allowing the simultaneous detection of pH from different skin regions. Finally, the circuits have been tested in aqueous Dulbecco's Modified Eagle Medium (DMEM) culture media with 5-9 pH values, which mimics cellular environments, to demonstrate their potential use for continuous monitoring of body-fluids pH.

GlasVent-The Rapidly Deployable Emergency Ventilator.

As a result of the novel Coronavirus disease (COVID-19) outbreak, a surge is witnessed in the demand for mechanical ventilators needed for treating affected patients. With the rapidly virus spreading around the globe, the shortage of ventilators becomes a global challenge and numerus efforts are followed. While industry mobilizes toward producing medical grade equipment, a number of low-cost and less complex emergency ventilators have been developed, mainly through academic and open-source channels, with a hope to meet any temporary needs gap until medical grade ventilator provision becomes sufficient. Herein, the design and implementation of one such emergency ventilator called GlasVent is presented, which an automated version of manual resuscitator device, commonly known as big valve mask or artificial manual breathing unit bag and widely used prior to initiating the mechanical ventilation. GlasVent uses 3D printed mechanical parts, widely available materials and off-the-shelf electronic and sensing devices which can be fast assembled. Furthermore, it requires minimal training and can be operated manually by hands or legs, thus meeting the emergency requirements even in the low-resource settings or regions with less developed healthcare systems. Post-COVID-19, such ventilators can potentially find use in clinical care of a wider variety of patients with injury, pulmonary noncommunicable diseases, and severe asthma etc.