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Vision-based tactile sensor design using physically based rendering

High-resolution tactile sensors are very helpful to robots for fine-grained perception and manipulation tasks, but designing those sensors is challenging. This is because the designs are based on the compact integration of multiple optical elements, and it is difficult to understand the correlation between the element arrangements and the sensor accuracy by trial and error. In this work, we introduce the digital design of vision-based tactile sensors using a physically accurate light simulator. The framework modularizes the design process, parameterizes the sensor components, and contains an evaluation metric to quantify a sensor’s performance. We quantify the effects of sensor shape, illumination setting, and sensing surface material on tactile sensor performance using our evaluation metric. The proposed optical simulation framework can replicate the tactile image of the real vision-based tactile sensor prototype without any prior sensor-specific data. Using our approach we can substantially improve the design of a fingertip GelSight sensor. This improved design performs approximately 5 times better than previous state-of-the-art human-expert design at real-world robotic tactile embossed text detection. Our simulation approach can be used with any vision-based tactile sensor to produce a physically accurate tactile image. Overall, our approach enables the automatic design of sensorized soft robots and opens the door for closed-loop co-optimization of controllers and sensors for dexterous manipulation.

Advanced electrode processing for lithium-ion battery manufacturing

Lithium-ion batteries (LIBs) need to be manufactured at speed and scale for their use in electric vehicles and devices. However, LIB electrode manufacturing via conventional wet slurry processing is energy-intensive and costly, challenging the goal to achieve sustainable, affordable and facile manufacturing of high-performance LIBs. In this Review, we discuss advanced electrode processing routes (dry processing, radiation curing processing, advanced wet processing and 3D-printing processing) that could reduce energy usage and material waste. Maxwell-type dry processing is a scalable alternative to conventional processing and has relatively low manufacturing cost and energy consumption. Radiation curing processing could enable high-throughput manufacturing, but binder selection is limited to certain radiation curable chemistries. 3D-printing processing can produce electrodes with diverse architectures and improved rate performance, but scalability is yet to be demonstrated. 3D-printing processing is good for special applications where throughput and cost can be compromised for performance.

Sustainable solutions for water scarcity: a review of electrostatic fog harvesting technology

Amid global climate change and population growth, traditional water acquisition methods face challenges. Electrostatic fog harvesting technology offers a novel solution for arid regions, leveraging space charges and electric fields to convert fog into usable water. This article explores the fundamental processes, structure, and enhancement methods of electrostatic fog collectors (EFC), focusing on recent research progress. We offer a prospective perspective on the future research of electrostatic fog harvesting technology, with the aim of facilitating the transition of this technology from scientific research to practical application.

On-chip solar power source for self-powered smart microsensors in bulk CMOS process

Enhancing the photoelectric conversion efficiency of on-chip solar cells is crucial for advancing solar energy harvesting in self-powered smart microsensors for Internet of Things applications. Here we show that adopting a center electrode (CE) layout instead of a ring electrode (RE) effectively reduces the shadowing effect of surface electrodes. Using a standard 0.18 μm CMOS process, we fabricated a 0.01 mm² segmented triple-well on-chip solar cell with CEs and highly doped interconnections. Measurements demonstrate a photoelectric conversion efficiency of 25.79% under solar simulator illumination, a 17.49% improvement over conventional designs. This on-chip solar cell is used for on-chip energy harvesting, achieving a maximum end-to-end conversion efficiency of 10.20%, referring to the overall efficiency from incident light power to load power output. The proposed energy harvesting system reliably provides a stable 1 V output to the load, even under varying illumination and load conditions.

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