ABSTRACT
The emergence of the Internet-of-Things is anticipated to create a vast market for what are known as smart edge devices, opening numerous opportunities across countless domains, including personalized healthcare and advanced robotics. Leveraging 3D integration, edge devices can achieve unprecedented miniaturization while simultaneously boosting processing power and minimizing energy consumption. Here, we demonstrate a back-end-of-line compatible optoelectronic synapse with a transfer learning method on health care applications, including electroencephalogram (EEG)-based seizure prediction, electromyography (EMG)-based gesture recognition, and electrocardiogram (ECG)-based arrhythmia detection. With experiments on three biomedical datasets, we observe the classification accuracy improvement for the pretrained model with 2.93% on EEG, 4.90% on ECG, and 7.92% on EMG, respectively. The optical programming property of the device enables an ultra-low power (2.8 × 10-13 J) fine-tuning process and offers solutions for patient-specific issues in edge computing scenarios. Moreover, the device exhibits impressive light-sensitive characteristics that enable a range of light-triggered synaptic functions, making it promising for neuromorphic vision application. To display the benefits of these intricate synaptic properties, a 5 × 5 optoelectronic synapse array is developed, effectively simulating human visual perception and memory functions. The proposed flexible optoelectronic synapse holds immense potential for advancing the fields of neuromorphic physiological signal processing and artificial visual systems in wearable applications.
ABSTRACT
The charge-trapping mechanism in conjugated polymers is a performance obstacle in many optoelectronic devices harnessed for non-volatile memory applications. Herein, a carbonyl-decorated organic 2D-polymer (TpDb)-based charge-trapping memory device has been developed with a wide memory window (3.2 V) with low programming and erasing voltages of +3/-2 and -3/+2. The TpDb was synthesized by a potentially scalable solid-state aldol condensation reaction. The inherent structural defects and the semi-conjugated nature of the enone network in TpDb offer effective charge-trapping through the localization of charges in specific functional groups (CîO). The interlayer hydrogen bonding enhances the packing density of the 2D-polymer layers thereby improving the memory storage properties of the material. Furthermore, the TpDb exhibits excellent features for non-volatile memory applications including over 10 000 cycles of write/read endurance and a prolonged retention performance of 104 seconds at high temperatures (100 °C).
ABSTRACT
Four-dimensional (4D) printing has attracted significant attention, because it enables structures to be reconfigured based on an external stimulus, realizing complex architectures that are useful for different applications. Nevertheless, most previously reported 4D-printed components have focused on actuators, which are just one part of a full soft robotic system. In this study, toward achieving fully 4D-printed systems, the design and direct ink writing of sensors with a straining mechanism that mimics the 4D effect are explored. Solution-processable carbon nanotubes (CNTs) were used as the sensing medium, and the effect of a heat-shrinkable shape-memory polymer-based substrate (i.e., potential 4D effect) on the electronic and structural properties of CNTs was assessed, followed by their application in various sensing devices. Herein, we reveal that substrate shrinking affords a more porous yet more conductive film owing to the compressive strain experienced by CNTs, leading to an increase in the carrier concentration. Furthermore, it improves the sensitivity of the devices without the need for chemical functionalization. Interestingly, the results show that, by engineering the potential 4D effect, the selectivity of the sensor can be tuned. Finally, the sensors were integrated into a fully 4D-printed flower structure, exhibiting their potential for different soft robotic applications.
ABSTRACT
Ultraviolet (UV) exposure overdose can cause health issues such as skin burns or other skin damage. In this work, a UV and temperature sensor smartwatch is developed, utilizing a multimaterial 3D printing approach via a vat photopolymerization-digital light processing technique. Photochromic (PC) pigments with different UV sensitivities, UVA (315-400 nm) and UVB (315-280 nm), were utilized to cover a wider range of UV exposure and were mixed in transparent resin, whereas the smartwatch was printed with controlled thickness gradients. A multifunctional sensor was next fabricated by adding a thermochromic (TC) material to PC, which is capable of sensing UV and temperature change. Colorimetric measurements assisted by a smartphone-based application provided instantaneous as well as cumulative UV exposure from sunlight. The mechanical properties of the device were also measured to determine its durability. The prototype of the wearable watch was prepared by fixing the 3D-printed dial to a commercially available silicon wristband suitable for all age groups. The 3D-printed watch is water-resistant and easily removable, allowing for its utilization in multiple outdoor activities. Thus, the developed wearable UV sensor alerts the user to the extent of their UV exposure, which can help protect them against overexposure.
ABSTRACT
Wearable electronics demand high adhesion properties through various skin conditions. Here, 3D-printed porous skin patches with octopus-like suckers of different geometries are presented. Experimental and theoretical studies are investigated to show an enhanced, low-cost 3D-printed bioinspired patches that successfully obtain biosignals comparable to commercial electrodes.Clinical Relevance- This work establishes low-cost, highly-adhesive skin patches that are irritation- and contamination-free with effortless peel-off technique for biosignal measurement.
Subject(s)
Octopodiformes , Wearable Electronic Devices , Animals , Adhesives , Skin , ElectronicsABSTRACT
There is a growing interest in new semiconductor nanostructures for future high-density high-performance flexible electronic devices. Two-dimensional conjugated microporous polymers (2D-CMPs) are promising candidates because of their inherent optoelectronic properties. Here, we are reporting a novel donor-acceptor type 2D-CMP based on Pyrene and Isoindigo (PI) for a potential nano-scale charge-trapping memory application. We exfoliated the PI polymer into ~ 2.5 nm thick nanoparticles (NPs) and fabricated a Metal-Insulator-Semiconductor (MIS) device with PI-NPs embedded in the insulator. Conductive AFM (cAFM) is used to examine the confinement mechanism as well as the local charge injection process, where ultrathin high-κ alumina supplied the energy barrier for confining the charge carrier transport. We have achieved a reproducible on-and-off state and a wide memory window (ΔV) of 1.5 V at a relatively small reading current. The device displays a low operation voltage (V < 1 V), with good retention (104 s), and endurance (103 cycles). Furthermore, a theoretical analysis is developed to affirm the measured charge carriers' transport and entrapment mechanisms through and within the fabricated MIS structures. The PI-NPs act as a nanoscale floating gate in the MIS-based memory with deep trapping sites for the charged carriers. Moreover, our results demonstrate that the synthesized 2D-CMP can be promising for future low-power high-density memory applications.
ABSTRACT
Being renowned for operating with visible-light pulses and electrical signals, optoelectronic memristive synaptic devices have excellent potential for neuromorphic computing systems and artificial visual information processing. Here, a flexible back-end-of-line-compatible optoelectronic memristor based on a solution-processable black phosphorus/HfOx bilayer with excellent synaptic features, toward biomimetic retinas is presented. The device shows highly stable synaptic features such as long-term potentiation (LTP) and long-term depression (LTD) for repetitive 1000 epochs, having 400 conductance pulses, each. The device presents advanced synaptic features in terms of long-term memory (LTM)/short term memory (STM), as well as learning-forgetting-relearning when visible light is induced on it. These advanced synaptic features can improve the information processing abilities for neuromorphic applications. Interestingly, the STM can be converted into LTM by adjusting the intensity of light and illumination time. Using the light-induced characteristics of the device, a 6 × 6 synaptic array is developed to exhibit possible use in artificial visual perception. Moreover, the devices are flexed using a silicon back-etching process. The resulting flexible devices demonstrate stable synaptic features when bent down to 1 cm radius. These multifunctional features in a single memristive cell make it highly suitable for optoelectronic memory storage, neuromorphic computing, and artificial visual perception applications.
Subject(s)
Light , Visual Perception , Cognition , Phosphorus , SynapsesABSTRACT
Optoelectronic devices are advantageous in in-memory light sensing for visual information processing, recognition, and storage in an energy-efficient manner. Recently, in-memory light sensors have been proposed to improve the energy, area, and time efficiencies of neuromorphic computing systems. This study is primarily focused on the development of a single sensing-storage-processing node based on a two-terminal solution-processable MoS2 metal-oxide-semiconductor (MOS) charge-trapping memory structure-the basic structure for charge-coupled devices (CCD)-and showing its suitability for in-memory light sensing and artificial visual perception. The memory window of the device increased from 2.8 V to more than 6 V when the device was irradiated with optical lights of different wavelengths during the program operation. Furthermore, the charge retention capability of the device at a high temperature (100 °C) was enhanced from 36 to 64% when exposed to a light wavelength of 400 nm. The larger shift in the threshold voltage with an increasing operating voltage confirmed that more charges were trapped at the Al2O3/MoS2 interface and in the MoS2 layer. A small convolutional neural network was proposed to measure the optical sensing and electrical programming abilities of the device. The array simulation received optical images transmitted using a blue light wavelength and performed inference computation to process and recognize the images with 91% accuracy. This study is a significant step toward the development of optoelectronic MOS memory devices for neuromorphic visual perception, adaptive parallel processing networks for in-memory light sensing, and smart CCD cameras with artificial visual perception capabilities.
ABSTRACT
Motion sensors are an essential component of many electronic systems. However, the development of inertial motion sensors based on fatigue-free soft proof mass has not been explored extensively in the field of soft electronics. Nontoxic gallium-based liquid metals are an emerging class of material that exhibit attractive electromechanical properties, making them excellent proof mass materials for inertial sensors. Here, we propose and demonstrate a fully soft laser-induced graphene (LIG) and liquid metal-based inertial sensor integrated with temperature, humidity, and breathing sensors. The inertial sensor design confines a graphene-coated liquid metal droplet inside a fluidic channel, rolling over LIG resistive electrode. The proposed sensor architecture and material realize a highly mobile proof mass and a vibrational space for its oscillation. The inertial sensor exhibits a high sensitivity of 6.52% m-1 s2 and excellent repeatability (over 12â¯500 cycles). The platform is fabricated using a scalable, rapid laser writing technique and integrated with a programmable system on a chip (PSoC) to function as a stand-alone system for real-time wireless monitoring of movement patterns and the control of a robotic arm. The developed printed inertial platform is an excellent candidate for the next-generation of wearables motion tracking platforms and soft human-machine interfaces.
Subject(s)
Gallium , Graphite , Wearable Electronic Devices , Humans , Motion , VibrationABSTRACT
Wearing a face mask has become a necessity following the outbreak of the coronavirus (COVID-19) disease, where its effectiveness in containing the pandemic has been confirmed. Nevertheless, the pandemic has revealed major deficiencies in the ability to manufacture and ramp up worldwide production of efficient surgical-grade face masks. As a result, many researchers have focused their efforts on the development of low cost, smart and effective face covers. In this article, following a short introduction concerning face mask requirements, the different nanotechnology-enabled techniques for achieving better protection against the SARS-CoV-2 virus are reviewed, including the development of nanoporous and nanofibrous membranes in addition to triboelectric nanogenerators based masks, which can filter the virus using various mechanisms such as straining, electrostatic attraction and electrocution. The development of nanomaterials-based mask coatings to achieve virus repellent and sterilizing capabilities, including antiviral, hydrophobic and photothermal features are also discussed. Finally, the usability of nanotechnology-enabled face masks is discussed and compared with that of current commercial-grade N95 masks. To conclude, we highlight the challenges associated with the quick transfer of nanomaterials-enabled face masks and provide an overall outlook of the importance of nanotechnology in counteracting the COVID-19 and future pandemics.
Subject(s)
COVID-19/prevention & control , Masks , Nanotechnology , SARS-CoV-2/isolation & purification , COVID-19/epidemiology , COVID-19/transmission , Filtration , Humans , Hydrophobic and Hydrophilic Interactions , Nanofibers/chemistry , Nanostructures/chemistry , User-Centered DesignABSTRACT
Since the outbreak of the severe respiratory disease caused by the novel coronavirus (COVID-19), the use of face masks has become ubiquitous worldwide to control the rapid spread of this pandemic. As a result, the world is currently facing a face mask shortage, and some countries have placed limits on the number of masks that can be bought by each person. Although the surgical grade N95 mask provides the highest level of protection currently available, its filtration efficiency for sub-300 nm particles is around 85% due to its wider pore size (â¼300 nm). Because the COVID-19 virus shows a diameter of around 65-125 nm, there is a need for developing more efficient masks. To overcome these issues, we demonstrate the development of a flexible, nanoporous membrane to achieve a reusable N95 mask with a replaceable membrane and enhanced filtration efficiency. We first developed a flexible nanoporous Si-based template on a silicon-on-insulator wafer using KOH etching and then used the template as a hard mask during a reactive ion etching process to transfer the patterns onto a flexible and lightweight (<0.12 g) polymeric membrane. Pores with sizes down to 5 nm were achieved with a narrow distribution. Theoretical calculations show that airflow rates above 85 L/min are possible through the mask, which confirms its breathability over a wide range of pore sizes, densities, membrane thicknesses, and pressure drops. Finally, the membrane is intrinsically hydrophobic, which contributes to antifouling and self-cleaning as a result of droplets rolling and sliding on the inclined mask area.
Subject(s)
Betacoronavirus , Coronavirus Infections/prevention & control , Masks , Nanopores , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Air Microbiology , Betacoronavirus/ultrastructure , COVID-19 , Coronavirus Infections/transmission , Equipment Design , Humans , Hydrophobic and Hydrophilic Interactions , Membranes, Artificial , Microscopy, Electron, Scanning , Nanopores/ultrastructure , Pneumonia, Viral/transmission , Polymers , Porosity , SARS-CoV-2 , SiliconABSTRACT
Microfluidics is a continuously growing field with potential not only in the fields of medical, chemical, and bioanalysis, but also in the domains of optics and information technology. Here, a pressure-driven 3D microfluidic chip is demonstrated with multiple logic Boolean functions. The presence and absence of fluid at the output of the gates represent the binary signals 1 and 0, respectively. Therefore, the logic gates do not require a specially functionalized liquid to operate. The chip is based on a multilevel of poly(methyl methacrylate) (PMMA)-based polymeric sheets with aligned microchannels while a flexible polyimide-based sheet with a cantilever-like structure is embedded to enable a one-directional flow of the liquid. Several Boolean logic functions are realized (AND, OR, and XOR) using different fluids in addition to a half adder digital microfluidic circuit. The outputs of the logic gates are designed to be at different heights within the 3D chip to enable different pressure drops. The results show that the logic gates are operational for a specific range of flow rates, which is dependent on the microchannel dimensions, surface roughness, and fluid viscosity and therefore on their hydraulic resistance. The demonstrated approach enables simple cascading of logic gates for large-scale microfluidic computing systems.
ABSTRACT
Flexible solar cells have received growing attention recently because of their ever-increasing range of applications. Here, the development of ultraflexible, lightweight, and high efficiency (19%) monocrystalline silicon solar cells with excellent reliability, mechanical resilience, and thermal performance is demonstrated by applying a corrugation method combined with laser patterning. The flexing mechanism converts large-scale rigid photovoltaic cells with interdigitated back contacts (IBCs) into a flexible version with a preserved efficiency. The corrugation technique is based on the formation of patterned grooves in active silicon to achieve ultraflexibility. As a result, islands of silicon with different shapes are obtained which are interconnected through the IBCs. Multiple corrugation patterns such as linear, honeycomb, and octagonal designs are studied, each resulting in different flexing capabilities in terms of flexing directionality and minimum bending radius, in addition to providing an atypical appearance with an aesthetic appeal. The corrugation method is shown to improve thermal dissipation (14.6% lower temperature) and to relieve the thermal mismatch challenge compared to the rigid cells because of the finlike architecture. Finally, encapsulation using a transparent polymeric material enables a robust performance of the flexible cells when exposed to different environmental conditions such as acid rain, snow, and mechanical shocks.
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Among major food production sectors, world aquaculture shows the highest growth rate, providing more than 50% of the global seafood market. However, water pollution in fish farming ponds is regarded as the leading cause of fish death and financial losses in the market. Here, an Internet of Things system based on a cubic multidimensional integration of circuit (MD-IC) is demonstrated for water and food security applications in fish farming ponds. Both faces of the silicon substrate are used for thin-film-based device fabrication. The devices are interconnected via through-silicon-vias, resulting in a bifacial complementary metal-oxide-semiconductor-compatible electronics system. The demonstrated cubic MD-IC is a complete, small, and lightweight system that can be easily deployed by farmers with no need for specialists. The system integrates on its outer sides simultaneous air and water quality monitoring devices (temperature, electrical conductivity, ammonia, and pH sensors), solar cells for energy-harvesting, and antenna for real-time data-transfer, while data-management circuitry and a solid-state battery are integrated on its internal faces. Microfluidic cooling technology is used for thermal management in the MD-IC. Finally, a biofriendly polymeric encapsulation is used to waterproof the embedded electronics, improve the mechanical robustness, and allow the system to float on the surface of the water.
Subject(s)
Aquaculture , Food Security , Ponds , Water Quality , Animals , Aquaculture/instrumentation , Aquaculture/methods , Electric Power Supplies , Fisheries , Food Security/methodsABSTRACT
According to the World Health Organization, one quarter of the world's population suffers from various neurological disorders ranging from depression to Alzheimer's disease. Thus, understanding the operation mechanism of the brain enables us to help those who are suffering from these diseases. In addition, recent clinical medicine employs electronic brain implants, despite the fact of being invasive, to treat disorders ranging from severe coronary conditions to traumatic injuries. As a result, the deaf could hear, the blind could see, and the paralyzed could control robotic arms and legs. Due to the requirement of high data management capability with a power consumption as low as possible, designing nanoscale transistors as essential I/O electronics is a complex task. Herein, we review the essential design criteria for such nanoscale transistors, progress and prospect for implantable brain-machine-interface electronics. This article also discusses their technological challenges for practical implementation.
Subject(s)
Brain-Computer Interfaces , Brain/physiology , Nanostructures/chemistry , Transistors, Electronic , Animals , Graphite/chemistry , Humans , Prostheses and Implants , Silicon/chemistry , Spatio-Temporal AnalysisABSTRACT
The manipulation of matter at the nanoscale enables the generation of properties in a material that would otherwise be challenging or impossible to realize in the bulk state. Here, we demonstrate growth of zirconia nano-islands using atomic layer deposition on different substrate terminations. Transmission electron microscopy and Raman measurements indicate that the nano-islands consist of nano-crystallites of the cubic-crystalline phase, which results in a higher dielectric constant (κ â¼ 35) than the amorphous phase case (κ â¼ 20). X-ray photoelectron spectroscopy measurements show that a deep quantum well is formed in the Al2O3/ZrO2/Al2O3 system, which is substantially different to that in the bulk state of zirconia and is more favorable for memory application. Finally, a memory device with a ZrO2 nano-island charge-trapping layer is fabricated, and a wide memory window of 4.5 V is obtained at a low programming voltage of 5 V due to the large dielectric constant of the islands in addition to excellent endurance and retention characteristics.
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Low-dimensional semiconductor nanostructures are of great interest in high performance electronic and photonic devices. ZnO is considered to be a multifunctional material due to its unique properties with potential in various applications. In this work, 3-nm ZnO nanoislands are deposited by Atomic Layer Deposition (ALD) and the electronic properties are characterized by UV-Vis-NIR Spectrophotometer and X-ray Photoelectron Spectroscopy. The results show that the nanostructures show quantum confinement effects in 1D. Moreover, Metal-Oxide-Semiconductor Capacitor (MOSCAP) charge trapping memory devices with ZnO nanoislands charge storage layer are fabricated by a single ALD step and their performances are analyzed. The devices showed a large memory window at low operating voltages with excellent retention and endurance characteristics due to the additional oxygen vacancies in the nanoislands and the deep barrier for the trapped holes due to the reduction in ZnO electron affinity. The results show that the ZnO nanoislands are promising in future low power memory applications.
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ZnO nanoparticles (NPs) have attracted considerable interest from industry and researchers due to their excellent properties with applications in optoelectronic devices, sunscreens, photocatalysts, sensors, biomedical sciences, etc. However, the agglomeration of NPs is considered to be a limiting factor since it can affect the desirable physical and electronic properties of the NPs. In this work, 1-5 nm ZnO NPs deposited by spin- and dip-coating techniques are studied. The electronic and physical properties of the resulting agglomerations of NPs are studied using UV-vis-NIR spectroscopy, atomic force microscopy (AFM), and transmission electron microscopy (TEM), and their application in metal-oxide-semiconductor (MOS) memory devices is analyzed. The results show that both dip- and spin-coating techniques lead to agglomerations of the NPs mostly in the horizontal direction. However, the width of the ZnO clusters is larger with dip-coating which leads to 1D quantum confinement, while the smaller ZnO clusters obtained by spin-coating enable 3D quantum confinement in ZnO. The ZnO NPs are used as the charge-trapping layer of a MOS-memory structure and the analysis of the high-frequency C-V measurements allow further understanding of the electronic properties of the ZnO agglomerations. A large memory window is achieved in both devices which confirms that ZnO NPs provide large charge-trapping density. In addition, ZnO confined in 3D allows for a larger memory window at lower operating voltages due to the Poole-Frenkel charge-emission mechanism.
ABSTRACT
In this work, we demonstrate a non-volatile metal-oxide semiconductor (MOS) memory with Quattro-layer graphene nanoplatelets as charge storage layer with asymmetric Al2O3/HfO2 tunnel oxide and we compare it to the same memory structure with 2.85-nm Si nanoparticles charge trapping layer. The results show that graphene nanoplatelets with Al2O3/HfO2 tunnel oxide allow for larger memory windows at the same operating voltages, enhanced retention, and endurance characteristics. The measurements are further confirmed by plotting the energy band diagram of the structures, calculating the quantum tunneling probabilities, and analyzing the charge transport mechanism. Also, the required program time of the memory with ultra-thin asymmetric Al2O3/HfO2 tunnel oxide with graphene nanoplatelets storage layer is calculated under Fowler-Nordheim tunneling regime and found to be 4.1 ns making it the fastest fully programmed MOS memory due to the observed pure electrons storage in the graphene nanoplatelets. With Si nanoparticles, however, the program time is larger due to the mixed charge storage. The results confirm that band-engineering of both tunnel oxide and charge trapping layer is required to enhance the current non-volatile memory characteristics.