Sensitivity Enhancement of Soft Capacitive Pressure Sensors Using a Solvent Evaporation-Based Porosity Control Technique

Soft pressure sensors play a significant role in developing &#34;man-machine&#34; tactile sensation in soft robotics and haptic interfaces. Specifically, ...

Zhejiang University

Bottom-up self-assembly of components, inspired by hierarchically self-regulating aggregation of small subunits observed in nature, provides a strategy for constructing two- or three-dimensional intriguing biomimetic materials via the spontaneous combination of discrete building blocks. Herein, we report the methods of ultrasonic wave energy-assisted, fast, two- and three-dimensional mesoscale well-ordered self-assembly of microfabricated building blocks (100 μm in size). Mechanical vibration energy-driven self-assembly of microplatelets at the water-air interface of inverted water droplets is demonstrated, and the real-time formation process of the patterned structure is dynamically explored. 40 kHz ultrasonic wave is transferred into microplatelets suspended in a water environment to drive the self-assembly of predesigned well-ordered structures. Two-dimensional self-assembly of microplatelets inside the water phase with a large patterned area is achieved. Stable three-dimensional multi-layered self-assembled structures are quickly formed at the air-water interface. These demonstrations aim to open distinctive and effective ways for new two-dimensional surface coating technology with autonomous organization strategy, and three-dimensional complex hierarchical architectures built by the bottom-up method and commonly found in nature (such as nacre, bone or enamel, etc.).

Quick self-assembly of bio-inspired multi-dimensional well-ordered structures induced by ultrasonic wave energy.

Species-specific monitoring activities represent fundamental tools for natural resource management and conservation but require techniques that target species-specific traits or markers. Sea lamprey, a destructive invasive species in the Laurentian Great Lakes and conservation target in North America and Europe, is among very few fishes that possess and use oral suction, yet suction has not been exploited for sea lamprey control or conservation. Knowledge of specific characteristics of sea lamprey suction (e.g., amplitude, duration, and pattern of suction events; hereafter 'suction dynamics') may be useful to develop devices that detect, record, and respond to the presence of sea lamprey at a given place and time. Previous observations were limited to adult sea lampreys in static water. In this study, pressure sensing panels were constructed and used to measure oral suction pressures and describe suction dynamics of juvenile and adult sea lampreys at multiple locations within the mouth and in static and flowing water. Suction dynamics were largely consistent with previous descriptions, but more variation was observed. For adult sea lampreys, suction pressures ranged from -0.6 kPa to -26 kPa with 20 s to 200 s between pumps at rest, and increased to -8 kPa to -70 kPa when lampreys were manually disengaged. An array of sensors indicated that suction pressure distribution was largely uniform across the mouths of both juvenile and adult lampreys; but some apparent variation was attributed to obstruction of sensing portal holes by teeth. Suction pressure did not differ between static and flowing water when water velocity was lower than 0.45 m/s. Such information may inform design of new systems to monitor behavior, distribution and abundance of lampreys.

Measurement of suction pressure dynamics of sea lampreys, Petromyzon marinus.

As the initial stage in the formation of human intelligence, the sensory-memory system plays a critical role for human being to perceive, interact, and evolve with the environment. Electronic implementation of such biological sensory-memory system empowers the development of environment-interactive artificial intelligence (AI) that can learn and evolve with diversified external information, which could potentially broaden the application of the AI technology in the field of human-computer interaction. Here, we report a multimodal artificial sensory-memory system consisting of sensors for generating biomimetic visual, auditory, tactile inputs, and flexible carbon nanotube synaptic transistor that possesses synapse-like signal processing and memorizing behaviors. The transduction of physical signals into information-containing, presynaptic action potentials and the synaptic plasticity of the transistor in response to single and long-term action potential excitations have been systematically characterized. The bioreceptor-like sensing and synapse-like memorizing behaviors have also been demonstrated. On the basis of the memory and learning characteristics of the sensory-memory system, the well-known psychological model describing human memory, the "multistore memory" model, and the classical conditioning experiment that demonstrates the associative learning of brain, "Pavlov's dog's experiment", have both been implemented electronically using actual physical input signals as the sources of the stimuli. The biomimetic intelligence demonstrated in this neurological sensory-memory system shows its potential in promoting the advancement in multimodal, user-environment interactive AI.

Multimodal Artificial Neurological Sensory-Memory System Based on Flexible Carbon Nanotube Synaptic Transistor.

In wearable or implantable biomedical devices that typically rely on battery power for diagnostics or operation, the development of flexible piezoelectric nanogenerators (NGs) that enable mechanical-to-electrical energy harvesting is finding promising applications. Here, we present the construction of a flexible piezoelectric nanogenerator using a thin film of room temperature deposited nanocrystalline aluminium nitride (AlN). On a thin layer of aluminium (Al), the AlN thin film was grown using pulsed laser deposition (PLD). The room temperature grown AlN film was composed of crystalline columnar grains oriented in the (100)-direction, as revealed in images from transmission electron microscopy (TEM) and X-ray diffraction (XRD). Fundamental characterization of the AlN thin film by piezoresponse force microscopy (PFM) indicated that its electro-mechanical energy conversion metrics were comparable to those of c-axis oriented AlN and zinc oxide (ZnO) thin films. Additionally, the AlN-based flexible piezoelectric NG was encapsulated in polyimide to further strengthen its mechanical robustness and protect it from some corrosive chemicals.

Yunqi Cao

State Key Laboratory of Industrial Control Technology,
College of Control Science and Engineering,
State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering

Zhejiang University

Sensitivity Enhancement of Soft Capacitive Pressure Sensors Using a Solvent Evaporation-Based Porosity Control Technique

Yunqi Cao

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}State Key Laboratory of Industrial Control Technology,College of Control Science and Engineering,State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering

Zhejiang University

Sensitivity Enhancement of Soft Capacitive Pressure Sensors Using a Solvent Evaporation-Based Porosity Control Technique

State Key Laboratory of Industrial Control Technology,
College of Control Science and Engineering,
State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering