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Categories: Chemistry: Thermodynamics, Engineering: Robotics Research

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SuperLimbs, a system of wearable robotic limbs, can physically support an astronaut and lift them back on their feet after a fall, helping them conserve energy for other essential tasks.

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A team of researchers has developed a drone that flies autonomously using neuromorphic image processing and control based on the workings of animal brains. Animal brains use less data and energy compared to current deep neural networks running on GPUs (graphic chips). Neuromorphic processors are therefore very suitable for small drones because they don't need heavy and large hardware and batteries. The results are extraordinary: during flight the drone's deep neural network processes data up to 64 times faster and consumes three times less energy than when running on a GPU. Further developments of this technology may enable the leap for drones to become as small, agile, and smart as flying insects or birds.

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Researchers have developed a new method that can lead to significant energy savings in buildings. The team identified 28 major heat loss regions in a multi-unit residential building with the most severe ones being at wall intersections and around windows. A potential energy savings of 25 per cent is expected if 70 per cent of the discovered regions are fixed.

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Research could pave the way for a prosthetic hand and robot to be able to feel touch like a human hand. The technology could also be used to help restore lost functionality to patients after a stroke.

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Researchers have leveraged deep learning techniques to enhance the image quality of a metalens camera. The new approach uses artificial intelligence to turn low-quality images into high-quality ones, which could make these cameras viable for a multitude of imaging tasks including intricate microscopy applications and mobile devices.

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Instead of burning fossil fuels to smelt steel and cook cement, researchers in Switzerland want to use heat from the sun. The proof-of-concept study uses synthetic quartz to trap solar energy at temperatures over 1,000 C (1,832 F), demonstrating the method's potential role in providing clean energy for carbon-intensive industries.

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Researchers are using artificial intelligence to perfect the design of the vessels surrounding the super-hot plasma, optimize heating methods and maintain stable control of the reaction for increasingly long periods. A new article explains how a researcher team used machine learning to avoid magnetic perturbations, or disruptions, which destabilize fusion plasma.

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Would you trust a robot to look after your cat? New research suggests it takes more than a carefully designed robot to care for your cat, the environment in which they operate is also vital, as well as human interaction.

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A research team has demonstrated that a simple stack of thermoelectric and magnetic material layers can exhibit a substantially larger transverse thermoelectric effect -- energy conversion between electric and heat currents that flow orthogonally to each other within it -- than existing magnetic materials capable of exhibiting the anomalous Nernst effect. This mechanism may be used to develop new types of thermoelectric devices useful in energy harvesting and heat flux sensing.

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Physicists and computer scientists have recently expanded the modern theory of the thermodynamics of computation. By combining approaches from statistical physics and computer science, the researchers introduce mathematical equations that reveal the minimum and maximum predicted energy cost of computational processes that depend on randomness, which is a powerful tool in modern computers.

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A research team has demonstrated that an iron-based amorphous alloy, widely used as a soft magnetic material in transformers and motors, can be transformed into a 'transverse' thermoelectric conversion material that converts electric and thermal currents in orthogonal directions, with just a short period of heat treatment. This is the first example that highlights the importance of microstructure engineering in the development of transverse thermoelectric conversion materials, and provides new design guidelines for materials development to realize environmentally friendly power generation and thermal management technologies using magnetic materials.

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A new machine-learning technique can train and control a reconfigurable soft robot that can dynamically change its shape to complete a task. The researchers also built a simulator that can evaluate control algorithms for shape-shifting soft robots.

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Researchers have developed a robotic feeding system that uses computer vision, machine learning and multimodal sensing to safely feed people with severe mobility limitations, including those with spinal cord injuries, cerebral palsy and multiple sclerosis.

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Walking and running is notoriously difficult to recreate in robots. Now, a group of researchers has overcome some of these challenges by creating an innovative method that employs central pattern generators -- neural circuits located in the spinal cord that generate rhythmic patterns of muscle activity -- with deep reinforcement learning. The method not only imitates walking and running motions but also generates movements for frequencies where motion data is absent, enables smooth transition movements from walking to running, and allows for adapting to environments with unstable surfaces.

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When old food packaging, discarded children's toys and other mismanaged plastic waste break down into microplastics, they become even harder to clean up from oceans and waterways. These tiny bits of plastic also attract bacteria, including those that cause disease. Researchers describe swarms of microscale robots (microrobots) that captured bits of plastic and bacteria from water. Afterward, the bots were decontaminated and reused.

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Engineers created a catapillar-shaped robot that splits into segments and reassembles, hauls cargo, and crawls through twisting courses.

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A stretchy electronic skin could equip robots and other devices with the same softness and touch sensitivity as human skin, opening up new possibilities to perform tasks that require a great deal of precision and control of force.

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New algorithm encourages robots to move more randomly to collect more diverse data for learning. In tests, robots started with no knowledge and then learned and correctly performed tasks within a single attempt. New model could improve safety and practicality of self-driving cars, delivery drones and more.

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Scientists have dramatically reduced the time and energy required to chill materials to temperatures near absolute zero. Their prototype refrigerator could prove a boon for the burgeoning quantum industry, which widely uses ultracold materials.

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Common household products containing nanoparticles -- grains of engineered material so miniscule they are invisible to the eye -- could be contributing to a new form of indoor air pollution, according to a new study.