Soft robots are prized for their agility and gentle touch, which makes them ideal for traversing delicate or enclosed spaces to perform various tasks, from cultivating baby corals in laboratories to inspecting industrial pipes in chemical plants. However, achieving embodied intelligence in such systems, where sensing, movement and power supply work together in an untethered configuration, remains a challenge.

Flexible materials can deform and adapt, but their power sources are unable to do so. Conventional batteries often stiffen the robot’s body, drain quickly, or degrade under strain, all of which leave soft robots tethered or with a short lifespan.

Assistant Professor Wu Changsheng and his team from the Department of Materials Science and Engineering and the Department of Ele...

Imagine biting into a crisp, garden-fresh salad and savoring juicy strawberries for dessert. But instead of your backyard, you’re gazing out at a stark lunar landscape, Earth hanging like a precious blue marble in the inky sky.

Sound like far-fetched sci-fi? Think again.

This cosmic cuisine scenario is fast becoming our reality, thanks to research led by University of Melbourne scientists belonging to the Australian Research Council Centre of Excellence in Plants for Space (P4S, 2024-2030), in partnership with NASA and other space scientists.

A global dream team of over 40 scientists in 11 countries and seven space agencies have united to produce a roadmap for plant science breakthroughs crucial for long-term human life on the moon and Mars.

And...

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language translation. A quantum counterpart—known as a quantum convolutional neural network (QCNN)—could process information more efficiently by using quantum states instead of classical bits.

Photons are fast, stable, and easy to manipulate on chips, making photonic systems a promising platform for QCNNs. However, photonic circuits typically behave linearly, limiting the flexible operations that neural networks need.

Adaptive state injection in photonic QCNNs
In a study published in Advanced Photonic...

In the early 1930s, Swiss astronomer Fritz Zwicky observed galaxies in space moving faster than their mass should allow, prompting him to infer the presence of some invisible scaffolding—dark matter—holding the galaxies together. Nearly 100 years later, NASA’s Fermi Gamma-ray Space Telescope may have provided direct evidence of dark mattner, allowing the invisible matter to be “seen” for the very first time.

The elusive nature of ...