Retina-Inspired Carbon Nitride-Based Photonic Synapses for Selective Detection of UV Light

Photonic synapses combine sensing and processing in a single device, so they are promising candidates to emulate visual perception of a biological retina. However, photonic synapses with wavelength selectivity, which is a key property for visual perception, have not been developed so far. Herein, organic photonic synapses that selectively detect UV rays and process various optical stimuli are presented. The photonic synapses use carbon nitride (C3N4) as an UV-responsive floating-gate layer in transistor geometry. C3N4 nanodots dominantly absorb UV light; this trait is the basis of UV selectivity in these photonic synapses. The presented devices consume only 18.06 fJ per synaptic event, which is comparable to the energy consumption of biological synapses. Furthermore, in situ modulation of exposure to UV light is demonstrated by integrating the devices with UV transmittance modulators. These smart systems can be further developed to combine detection and dose-calculation to determine how and when to decrease UV transmittance for preventive health care.

Flexible Neuromorphic Electronics for Computing, Soft Robotics, and Neuroprosthetics

© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, WeinheimFlexible neuromorphic electronics that emulate biological neuronal systems constitute a promising candidate for next-generation wearable computing, soft robotics, and neuroprosthetics. For realization, with the achievement of simple synaptic behaviors in a single device, the construction of artificial synapses with various functions of sensing and responding and integrated systems to mimic complicated computing, sensing, and responding in biological systems is a prerequisite. Artificial synapses that have learning ability can perceive and react to events in the real world; these abilities expand the neuromorphic applications toward health monitoring and cybernetic devices in the future Internet of Things. To demonstrate the flexible neuromorphic systems successfully, it is essential to develop artificial synapses and nerves replicating the functionalities of the biological counterparts and satisfying the requirements for constructing the elements and the integrated systems such as flexibility, low power consumption, high-density integration, and biocompatibility. Here, the progress of flexible neuromorphic electronics is addressed, from basic backgrounds including synaptic characteristics, device structures, and mechanisms of artificial synapses and nerves, to applications for computing, soft robotics, and neuroprosthetics. Finally, future research directions toward wearable artificial neuromorphic systems are suggested for this emerging area.

Organic flexible memristor with reduced operating voltage and high stability by interfacial control of conductive filament growth

This work was supported in part through the BK21 Program funded by Ministry of Education of Korea.Herein, the underlying mechanisms for the growth of conductive filaments (CFs) at a metal–polymer electrolyte interface through ion migration in organic electrochemical metallization (ECM) memristor are presented. It is observed that the free volume of voids (nanopores) in the polymer electrolyte serves as the pathways of metal‐cations whereas the interfacial topography between an active electrode and a polymer electrolyte determines the nucleation sites of the CFs. The growth kinetics of the CFs and the resultant resistive memory are found to vary with the molecular weight of the polymer electrolyte and the metal protrusions at the interface. Our direct observations show that the free volume of voids of the polymer electrolyte, varied with the molecular weight, dictates the ion transport for the growth and the disruption of the CFs. Our organic ECM‐based memristor with a hetero‐electrolyte exhibits high mechanical flexibility, low switching voltages reduced by about three times compared to those of conventional devices, and stable memory retention for longer than 104 s under repeated cycles of bending.PostprintPeer reviewe

Topography-Guided Spreading and Drying of 6,13-bis(triisopropylsilylethynyl)-pentacene Solution on a Polymer Insulator for the Field-Effect Mobility Enhancement

We report on the enhancement of the field-effect mobility of solution-processed 6,13-bis(triisopropylsilylethynyl)-pentacene (TIPS-pentacene) by unidirectional topography (UT) of an inkjet-printed polymer insulator. The UT leads to anisotropic spreading and drying of the TIPS-pentacene droplet and enables to spontaneously develop the ordered structures during the solvent evaporation. The mobility of the UT-dictated TIPS-pentacene film (0.202 ± 0.012 cm2/Vs) is found to increase by more than a factor of two compared to that of the isotropic case (0.090 ± 0.032 cm2/Vs). The structural arrangement of the TIPS-pentacene molecules in relation to the mobility enhancement is described within an anisotropic wetting formalism. Our UT-based approach to the mobility enhancement is easily applicable to different classes of soluble organic field-effect transistors by adjusting the geometrical parameters such as the height, the width, and the periodicity of the UT of an inkjet-printed insulator

Organic and perovskite memristors for neuromorphic computing

Organic and perovskite memristors have superior characteristics both in material and structural perspectives, and therefore have been evaluated for possible integration as bio-realistic components of artificial intelligent hardware systems. This application will require the brain-inspired integrated systems that can process and memorize large amounts of complex information; requirements include highly uniform and reliable memristors that can be operated at low energy and integrated at high density. Here, we review the progress in development of organic and perovskite memristors to obtain various synaptic behaviors, with focus on material and underlying mechanism aspects. Then we address various approaches to meet the needs for constructing applications of neuromorphic computing, including low energy consumption, high uniformity and reliability of the memristors, and high-density integration. Lastly, we suggest future research directions toward realizing neuromorphic computing.

Organic electronic synapses with low energy consumption

A SUMMARY The von Neumann computing architecture consists of separated processing and memory elements; it is too bulky and energy-intensive to be implemented in the upcoming artificial intelligence age. In contrast, neurons and synapses in a brain perform learning and memory in an integrated manner and function energy- efficiently by analog adjustment of synaptic strengths in response to stimulation. Organic artificial synapses provide good emulation of the functions and structures of biological synapses and are easily fabricated and therefore can be applied to various neuromorphic electronic devices. In particular, organic artificial synapses that consume energy at a level comparable to that of a biological synapse show great promise for use in future low-energy neuromorphic devices. Here, we review the trends of energy consumption of organic artificial synapses and how it is affected by the structure, materials, and operation mechanism. We also present a strategy to decrease the energy consumption of organic neuromorphic devices. Our review will help the development of versatile low-energy organic neuromorphic electronics.

Site-Specific Difference of Bone Geometry Indices in Hypoparathyroid Patients

BackgroundHypoparathyroid patients often have a higher bone mineral density (BMD) than the general population. However, an increase in BMD does not necessarily correlate with a solid bone microstructure. This study aimed to evaluate the bone microstructure of hypoparathyroid patients by using hip structure analysis (HSA).MethodsNinety-five hypoparathyroid patients >20 years old were enrolled and 31 of them had eligible data for analyzing bone geometry parameters using HSA. And among the control data, we extracted sex-, age-, and body mass index-matched three control subjects to each patient. The BMD data were reviewed retrospectively and the bone geometry parameters of the patients were analyzed by HSA.ResultsThe mean Z-scores of hypoparathyroid patients at the lumbar spine, femoral neck, and total hip were above zero (0.63±1.17, 0.48±1.13, and 0.62±1.10, respectively). The differences in bone geometric parameters were site specific. At the femoral neck and intertrochanter, the cross-sectional area (CSA) and cortical thickness (C.th) were higher, whereas the buckling ratio (BR) was lower than in controls. However, those trends were opposite at the femoral shaft; that is, the CSA and C.th were low and the BR was high.ConclusionOur study shows the site-specific effects of hypoparathyroidism on the bone. Differences in bone components, marrow composition, or modeling based bone formation may explain these findings. However, further studies are warranted to investigate the mechanism, and its relation to fracture risk

Organic synaptic transistors for flexible and stretchable artificial sensory nerves

This article reviews artificial nerve electronics (nervetronics), an emerging field in which the goal is to develop bioinspired electronics that implement biological sensory functions. An artificial synapse is a fundamental core technology of artificial sensory nerves that can emulate functional properties of a biological synapse. Use of artificial synapses reduces the energy consumption and increases the sensitivity of low-level perception in artificial sensory nerves. Wearable and implantable devices require artificial sensory nerves that are flexible and stretchable. Therefore, development of organic artificial synapses that have these qualities is a central focus in nervetronics. Here, we review the concept and mechanism of organic artificial synapses for use as basic elements of flexible and stretchable artificial nerves. Next, we outline the research direction of the flexible and stretchable artificial sensory nerves so far, and finally, identify challenges of artificial sensory nerves that must be solved to enable actual application of this developing technology.

Organic Synaptic Transistors for Bio-Hybrid Neuromorphic Electronics

© 2021 Wiley-VCH GmbHNeuromorphic electronics that emulate biological synapses and nerves can provide a solution to overcome the limitation in energy efficiency of von Neumann computing systems. With increasing demands on bio-medical applications such as healthcare monitoring and neuroprosthetic devices, bio-hybrid neuromorphic electronics are evaluated as ways to process biological information and replace biological systems. Successful realization of bio-hybrid neuromorphic systems requires replication of various synaptic properties in a single device, along with other characteristics such as biomimetic neural functionality, biocompatibility, soft mechanical properties, and low energy consumption. To satisfy these requirements, organic synaptic transistors (OSTs) are widely investigated as essential components of these applications. If the requirements can be met, bio-hybrid neuromorphic systems that use OSTs can be compatible with biological systems, and can operate stably at bio-electronic interfaces. Here, fundamentals of the OSTs emulating biological synapses and nerves are presented followed by a discussion of the requirements of the neuromorphic device/systems for bio-hybrid application. Finally, recent research on implementations of bio-hybrid neuromorphic devices and systems with future research directions, are reviewed.N