Category Technology/Electronics

Amid the many mysteries of quantum physics, subatomic particles don’t always follow the rules of the physical world. They can exist in two places at once, pass through solid barriers and even communicate across vast distances instantaneously. These behaviors may seem impossible, but in the quantum realm, scientists are exploring an array of properties once thought impossible.

In a new study, physicists at Brown University have now observed a novel class of quantum particles called fractional excitons, which behave in unexpected ways and could significantly expand scientists’ understanding of the quantum realm.

“Our findings point toward an entirely new class of quantum pa...

Scientists have successfully achieved a quantum collective behavior of macroscopic mechanical oscillators, unlocking new possibilities in quantum technology.

Quantum technologies are radically transforming our understanding of the universe. One emerging technology are macroscopic mechanical oscillators, devices that are vital in quartz watches, mobile phones, and lasers used in telecommunications. In the quantum realm, macroscopic oscillators could enable ultra-sensitive sensors and components for quantum computing, opening new possibilities for innovation in various industries.

Controlling mechanical oscillators at the quantum level is essential for developing future technologies in quantum computing and ultra-precise sensing...

A joint research effort has developed a high-performance self-charging energy storage device capable of efficiently storing solar energy. The research team has dramatically improved the performance of existing supercapacitor devices by utilizing transition metal-based electrode materials and proposed a new energy storage technology that combines supercapacitors with solar cells.

The paper is published in the journal Energy.

The research team designed the electrodes using a nickel-based carbonate and hydroxide composite material and maximized the conductivity and stability of the electrodes by ...

Researchers at the Indian Institute of Science (IISc), with collaborators at University College London, have developed machine learning-based methods to predict material properties even with limited data. This can aid in the discovery of materials with desired properties, such as semiconductors.

In recent years, materials engineers have turned to machine learning models to predict which types of materials can possess specific properties such as electronic band gaps, formation energies, and mechanical properties, in order to design new materials. However, data on material properties—which is needed to train these models—is limited because testing materials is expensive and time consuming.

This prompted researchers led by Sai Gautam Gopalakrishnan, Assistant Professor at the D...