Enabling On-Demand Conformal Zn-Ion Batteries on Non-Developable Surfaces

Conventional power sources encounter difficulties in achieving structural unitization with complex-shaped electronic devices because of their fixed form factors. Here, it is realized that an on-demand conformal Zn-ion battery (ZIB) on non-developable surfaces uses direct ink writing (DIW)-based nonplanar 3D printing. First, ZIB component (manganese oxide-based cathode, Zn powder-based anode, and UV-curable gel composite electrolyte) inks are designed to regulate their colloidal interactions to fulfill the rheological requirements of nonplanar 3D printing, and establish bi-percolating ion/electron conduction pathways, thereby enabling geometrical synchronization with non-developable surfaces, and ensuring reliable electrochemical performance. The ZIB component inks are conformally printed on arbitrary curvilinear substrates to produce embodied ZIBs that can be seamlessly integrated with complicated 3D objects (including human ears). The conformal ZIB exhibits a high fill factor (i.e., areal coverage of cells on underlying substrates, ≈100%) that ensures high volumetric energy density (50.5 mWh cm_cell⁻³), which exceeds those of previously-reported shape-adaptable power sources.     

3D Printable One-Part Carbon Nanotube-Elastomer Ink for Health Monitoring Applications

3D printing of conductive elastomers is a promising route to personalized health monitoring applications due to its flexibility and biocompatibility. Here, a one-part, highly conductive, flexible, stretchable, 3D printable carbon nanotube (CNT)-silicone composite is developed and thoroughly characterized. The one-part nature of the inks: i) enables printing without prior mixing and cures under ambient conditions; ii) allows direct dispensing at ≈100 µm resolution printability on nonpolar and polar substrates; iii) forms both self-supporting and high-aspect-ratio structures, key aspects in additive biomanufacturing that eliminate the need for sacrificial layers; and iv) lends efficient, reproducible, and highly sensitive responses to various tensile and compressive stimuli. The high electrical and thermal conductivity of the CNT-silicone composite is further extended to facilitate use as a flexible and stretchable heating element, with applications in body temperature regulation, water distillation, and dual temperature sensing and Joule heating. Overall, the facile fabrication of this composite points to excellent synergy with direct ink writing and can be used to prepare patient-specific wearable electronics for motion detection and cardiac and respiratory monitoring devices and toward advanced personal health tracking and bionic skin applications.     

Room-Temperature-Processable Highly Reliable Resistive Switching Memory with Reconfigurability for Neuromorphic Computing and Ultrasonic Tissue Classification

Reversible metal-filamentary mechanism has been widely investigated to design an analog resistive switching memory (RSM) for neuromorphic hardware-implementation. However, uncontrollable filament-formation, inducing its reliability issues, has been a fundamental challenge. Here, an analog RSM with 3D ion transport channels that can provide unprecedentedly high reliability and robustness is demonstrated. This architecture is realized by a laser-assisted photo-thermochemical process, compatible with the back-end-of-line process and even applicable to a flexible format. These superior characteristics also lead to the proposal of a practical adaptive learning rule for hardware neural networks that can significantly simplify the voltage pulse application methodology even with high computing accuracy. A neural network, which can perform the biological tissue classification task using the ultrasound signals, is designed, and the simulation results confirm that this practical adaptive learning rule is efficient enough to classify these weak and complicated signals with high accuracy (97%). Furthermore, the proposed RSM can work as a diffusive-memristor at the opposite voltage polarity, exhibiting extremely stable threshold switching characteristics. In this mode, several crucial operations in biological nervous systems, such as Ca²⁺ dynamics and nonlinear integrate-and-fire functions of neurons, are successfully emulated. This reconfigurability is also exceedingly beneficial for decreasing the complexity of systems—requiring both drift- and diffusive-memristors.     

Analysis of issues in gate recess etching in the InAlAs/InGaAs HEMT manufacturing process

We have developed an InAlAs/InGaAs metamorphic high electron mobility transistor device fabrication process where the gate length can be tuned within the range of 0.13 μm–0.16 μm to suit the intended application. The core processes are a two-step electron-beam lithography process using a three-layer resist and gate recess etching process using citric acid. An electron-beam lithography process was developed to fabricate a T-shaped gate electrode with a fine gate foot and a relatively large gate head. This was realized through the use of three-layered resist and two-step electron beam exposure and development. Citric acid-based gate recess etching is a wet etching, so it is very important to secure etching uniformity and process reproducibility. The device layout was designed by considering the electrochemical reaction involved in recess etching, and a reproducible gate recess etching process was developed by finding optimized etching conditions. Using the developed gate electrode process technology, we were able to successfully manufacture various monolithic microwave integrated circuits, including low noise amplifiers that can be used in the 28 GHz to 94 GHz frequency range.     

Real-time 3D multi-pedestrian detection and tracking using 3D LiDAR point cloud for mobile robot

Mobile robots are used in modern life; however, object recognition is still insufficient to realize robot navigation in crowded environments. Mobile robots must rapidly and accurately recognize the movements and shapes of pedestrians to navigate safely in pedestrian-rich spaces. This study proposes real-time, accurate, three-dimensional (3D) multi-pedestrian detection and tracking using a 3D light detection and ranging (LiDAR) point cloud in crowded environments. The pedestrian detection quickly segments a sparse 3D point cloud into individual pedestrians using a lightweight convolutional autoencoder and connected-component algorithm. The multi-pedestrian tracking identifies the same pedestrians considering motion and appearance cues in continuing frames. In addition, it estimates pedestrians' dynamic movements with various patterns by adaptively mixing heterogeneous motion models. We evaluate the computational speed and accuracy of each module using the KITTI dataset. We demonstrate that our integrated system, which rapidly and accurately recognizes pedestrian movement and appearance using a sparse 3D LiDAR, is applicable for robot navigation in crowded spaces.     

Joint frame rate adaptation and object recognition model selection for stabilized unmanned aerial vehicle surveillance

We propose an adaptive unmanned aerial vehicle (UAV)-assisted object recognition algorithm for urban surveillance scenarios. For UAV-assisted surveillance, UAVs are equipped with learning-based object recognition models and can collect surveillance image data. However, owing to the limitations of UAVs regarding power and computational resources, adaptive control must be performed accordingly. Therefore, we introduce a self-adaptive control strategy to maximize the time-averaged recognition performance subject to stability through a formulation based on Lyapunov optimization. Results from performance evaluations on real-world data demonstrate that the proposed algorithm achieves the desired performance improvements.     

Almost linearity of -bi-Lipschitz maps between real Banach spaces

Let and be real Banach spaces. A map between and is called an -bi-Lipschitz map if for all . In this note we show that if is an -bi-Lipschitz map with from onto , then is almost linear. We also show that if is a surjective -bi-Lipschitz map with , then there exists a linear isomorphism such that

where as and .