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Building-up relations between intra- and intermolecular interactions, miscibility, and performance for low-cost, efficient fully non-fused acceptor-based organic solar cells
No full textAlthough the molecular electronic forces (e.g., intra- and intermolecular interactions) within active layers largely govern the device performance of organic solar cells (OSCs), they are complicated and less understood. In this study, we have synthesized two low-cost isomeric non-fused acceptors (TT-Naph1 and TT-Naph2) with 1-naphthyl and 2-naphthyl aromatic chains, respectively and quantified the molecular interaction-photovoltaic performance relationship. Benefiting from the enhanced dipole moment, TT-Naph2 possesses a strong dipole-dipole intermolecular interaction, while the improved backbone planarity endows TT-Naph1 with a strengthened intramolecular charge-transfer effect, which can regulate the desired blend morphology with the D18 donor polymer as a result of its low miscibility with D18. Less miscible nanostructures are more pronounced in the layer-by-layer (LBL) systems than bulk heterojunction (BHJ) ones, increasing the power conversion efficiencies (PCEs) in the sequence of TT-Naph2 BHJ < TT-Naph1 BHJ < TT-Naph2 LBL < TT-Naph1 LBL. Notably, a ternary LBL OSC based on TT-Naph1 achieved remarkable PCE of 18.41%, one of the top values for LBL-type OSCs. Our findings provide insights into the controlling effect of intra- and intermolecular interactions on the active layers for efficient non-fused acceptor-based OSCs
A deep learning-based framework for battery reusability verification: one-step state-of-health estimation of pack and constituent modules using a generative algorithm and graphical representation
No full textAs the electric vehicle market continues to surge, the proper assessment of used batteries has become increasingly important. However, current technologies for assessing used batteries, which involve separately estimating the State-of-Health (SoH) of the pack and its individual modules, require multiple times of cycling tests and lead to time inefficiency and power consumption. The proposed DeepSUGAR, a deep learning-based framework for SoH estimation using a generative algorithm based on graphical representation techniques to reveal individual module health, offers the advantage of estimating the status of internal modules replying on battery pack SoH. The cycling profiles of a simultaneously measured 14S7P pack and its constituent modules were analyzed, and a convolutional neural network (CNN) was trained by spatializing cycling curves to estimate SoH. DeepSUGAR, trained on pack data, showed outstanding performance with an RMSE of 5.31 x 10-3 and its applicability was validated by testing with module data, resulting in an RMSE of 7.38 x 10-3. Furthermore, the generated module cycling profiles from pack SoH using the deep generative model were fed into the trained CNN and showed a remarkable performance with an RMSE of 8.38 x 10-3. DeepSUGAR can significantly reduce power consumption, processing cost, and carbon dioxide emissions by integrating module-level diagnosis within the pack-level assessment process. A non-invasive approach to reveal the health of individual modules, replying on the state-of-health of the battery pack, is achieved through generative adversarial networks (GAN) with spatialized battery pack cycling profiles
First High???Speed Video Camera Observations of a Lightning Flash Associated With a Downward Terrestrial Gamma???Ray Flash
No full textIn this paper, we present the first high???speed video observation of a cloud???to???ground lightning flash and its associated downward???directed Terrestrial Gamma???ray Flash (TGF). The optical emission of the event was observed by a high???speed video camera running at 40,000 frames per second in conjunction with the Telescope Array Surface Detector, Lightning Mapping Array, interferometer, electric???field fast antenna, and the National Lightning Detection Network. The cloud???to???ground flash associated with the observed TGF was formed by a fast downward leader followed by a very intense return stroke peak current of ???154??kA. The TGF occurred while the downward leader was below cloud base, and even when it was halfway in its propagation to ground. The suite of gamma???ray and lightning instruments, timing resolution, and source proximity offer us detailed information and therefore a unique look at the TGF phenomena.</jats:p>
Multi-Channel Current to Digital Read-out Integrated Interface for Electrochemical Sensor and FET Type Sensor
No full textUnsupervised machine learning techniques for exploring tropical coamoeba, brane tilings and Seiberg duality
No full textWe introduce unsupervised machine learning techniques in order to identify toric phases of 4d N ?? 1 supersymmetric gauge theories corresponding to the same toric Calabi-Yau 3-fold. These 4d N ?? 1 supersymmetric gauge theories are world volume theories of a D3-brane probing a toric Calabi-Yau 3-fold and are realized in terms of a type IIB brane configuration known as a brane tiling. It corresponds to the skeleton graph of the coamoeba projection of the mirror curve associated to the toric Calabi-Yau 3-fold. When we vary the complex structure moduli of the mirror Calabi-Yau 3-fold, the coamoeba and the corresponding brane tilings change their shape, giving rise to different toric phases related by Seiberg duality. We illustrate that by employing techniques such as principal component analysis and t-distributed stochastic neighbor embedding, we can project the space of coamoeba labeled by complex structure moduli down to a lower-dimensional phase space with phase boundaries corresponding to Seiberg duality. In this work, we illustrate this technique by obtaining a 2-dimensional phase diagram for brane tilings corresponding to the cone over the zeroth Hirzebruch surface F0
An ultralow power wearable vital sign sensor using an electromagnetically reactive near field
No full textDespite coronavirus disease 2019, cardiovascular disease, the leading cause of global death, requires timely detection and treatment for a high survival rate, underscoring the 24 h monitoring of vital signs. Therefore, telehealth using wearable devices with vital sign sensors is not only a fundamental response against the pandemic but a solution to provide prompt healthcare for the patients in remote sites. Former technologies which measured a couple of vital signs had features that disturbed practical applications to wearable devices, such as heavy power consumption. Here, we suggest an ultralow power (100 mu W) sensor that collects all cardiopulmonary vital signs, including blood pressure, heart rate, and the respiration signal. The small and lightweight (2 g) sensor designed to be easily embedded in the flexible wristband generates an electromagnetically reactive near field to monitor the contraction and relaxation of the radial artery. The proposed ultralow power sensor measuring noninvasively continuous and accurate cardiopulmonary vital signs at once will be one of the most promising sensors for wearable devices to bring telehealth to our lives
Distributed swarm system with hybrid-flocking control for small fixed-wing UAVs: Algorithms and flight experiments
No full textThis paper presents a distributed swarm system for small fixed-wing unmanned aerial vehicles (UAVs). In particular, to perform various missions with multiple UAVs that are densely gathered and collision free, a hybrid-flocking control algorithm is synthesized by using three types of control protocols: vector field guidance (for path following/loitering), augmented Cucker-Smale (ACS) model (for collective flocking behavior), and potential field (for collision avoidance). In particular, to address the issue of conflicts between different control protocols, the adaptive ACS model is proposed and the optimization problem is formulated to determine the suitable mixing weights of control protocols. We also design the transition of multiple operation modes and communication architecture for the swarm system. The system is evaluated using the proposed hybrid-flocking control algorithm by proof-of-concept real flight experiments using 18 small fixed-wing UAVs as well as extensive numerical simulations. Flight experiments are successfully performed for multiple consecutive tasks including the individual task, circular path loitering and elliptical path loitering while avoiding collisions among UAVs
Write-Once-Read-Many-Times Memory Characteristics with a Large Memory Window Operating at a Low Voltage by Li-Ion Incorporation from the LiCoO x Ion-Supplying Layer into the InGaZnO Channel of a Thin-Film Transistor
No full textWrite-once-read-many-times (WORM)memory characteristicswith alarge memory window are demonstrated in a thin-film transistor (TFT)composed of an indium-gallium-zinc oxide (IGZO) channel and a lithium-cobaltoxide (LiCoO x ) ion-supplying layer inthe gate oxide. While the device with a thicker (5 nm) tunneling oxideshowing a threshold voltage shift (Delta V (T)) of about 5 V by electron charging upon positive gate voltage (V (GS)) sweep to +25 V, the device with a 2 nm-thicktunneling oxide exhibits a large memory window with Delta V (T) > 20 V by Li-ion migration from LiCoO x to IGZO channel, which can be controlledas multilevel states with respect to the V (GS) amplitude. Incorporation of Li ions into the IGZO channel actingas p-type dopants reduces carrier concentration in the channel andconsequently increases V (T). The increased V (T) and the consequently reduced drain currentare not instantly restored back by applying negative V (GS), featuring WORM memory characteristics. Although thedevice undergoes partial retention loss, the retention remains upto about 90% after 100 min of retention time. These results verifyWORM memory operations in the IGZO TFTs through gate voltage-drivenLi-ion incorporation into the IGZO channel to modify its conductivestates instead of using a typical electrical charging route
Self-Healable Conductive Hydrogels with High Stretchability and Ultralow Hysteresis for Soft Electronics
No full textStretchable sensors based on conductive hydrogels haveattractedconsiderable attention for wearable electronics. However, their practicalapplications have been limited by the low sensitivity, high hysteresis,and long response times of the hydrogels. In this study, we developedhigh-performance poly-(vinyl alcohol) (PVA)/poly-(3,4-ethylenedioxythiophene):poly-(styrenesulfonate)(PEDOT:PSS) based hydrogels post-treated with NaCl, which showed excellentmechanical properties, fast electrical response, and ultralow hysteresisproperties. The hydrogels also demonstrated excellent self-healingproperties with electrical and mechanical properties comparable tothose of the original hydrogel and more than 150% elongation at breakafter the self-healing process. The high performance of the optimizedhydrogels was attributed to the enhanced intermolecular forces betweenthe PVA matrix and PEDOT:PSS, the favorable conformational changeof the PEDOT chains, and an increase in localized charges in the hydrogelnetworks. The hydrogel sensors were capable of tracking large humanmotion and subtle muscle action in real time with high sensitivity,a fast response time (0.88 s), and low power consumption (<180 mu W). Moreover, the sensor was able to monitor human respirationdue to chemical changes in the hydrogel. These highly robust, stretchable,conductive, and self-healing PVA/PEDOT:PSS hydrogels, therefore, showgreat application potential as wearable sensors for monitoring humanactivity
