Category Physics

MilliMobile is a Tiny, Self-driving Robot Powered only by Light and Radio Waves

MilliMobile is a tiny, self-driving robot powered only by light and radio waves
Researchers at the University of Washington have created MilliMobile, a tiny, self-driving robot powered only by surrounding light or radio waves. It’s about the size of a penny and can run indefinitely on harvested energy. Credit: Mark Stone/University of Washington

Small mobile robots carrying sensors could perform tasks like catching gas leaks or tracking warehouse inventory. But moving robots demands a lot of energy, and batteries, the typical power source, limit lifetime and raise environmental concerns. Researchers have explored various alternatives: affixing sensors to insects, keeping charging mats nearby, or powering the robots with lasers. Each has drawbacks: Insects roam, chargers limit range, and lasers can burn people’s eyes.

Researchers at the University of Washington ...

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Thermal MagIC: Digging into the Details of an Ambitious New ‘Thermometry Camera’

Diagram of the series of tiny wells and the magnetic particle image itself
Left: Diagram of the series of tiny wells, in clusters of fours, filled with solution. Each well in a foursome is spaced away from the other wells by a certain amount, anywhere from 0.1 mm (very close together) to 1 mm (further apart). Right: The magnetic particle image itself, showing distinctions between the wells spaced farther apart but not between the wells spaced close together. The dashed red circle in both images shows the foursome of wells spaced 0.5 mm apart.
Credit: NIST

Thermometers can do a lot of things: Measure the temperature at the center of your perfectly braised chicken or tell you whether to keep your child home from school due to illness. But because of their size, traditional thermometers’ uses are still limited.

“How do you non-invasively measure a temperature...

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Machine Learning Models can produce Reliable Results even with Limited Training Data

Machine learning models can produce reliable results even with limited training data
Elliptic PDE learning methods can be data-efficient. Credit: Proceedings of the National Academy of Sciences (2023). DOI: 10.1073/pnas.2303904120

Researchers have determined how to build reliable machine learning models that can understand complex equations in real-world situations while using far less training data than is normally expected.

The researchers, from the University of Cambridge and Cornell University, found that for partial differential equations—a class of physics equations that describe how things in the natural world evolve in space and time—machine learning models can produce reliable results even when they are provided with limited data.

Their results, reported in the Proceedings of the National Academy of Sciences, could be useful for constructing more t...

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Golden Future for Thermoelectrics

Three men stand in front of a blackboard, with a periodic table of the elements in the background.
Michael Parzer, Fabian Garmroudi and Andrej Pustogow (from left), in the background a periodic table showing the electronic structure of all solid elements.

Researchers discover excellent thermoelectric properties of nickel-gold alloys. These can be used to efficiently convert heat into electrical energy. Thermoelectrics enable the direct conversion of heat into electrical energy – and vice versa. This makes them interesting for a range of technological applications. In the search for thermoelectric materials with the best possible properties, a research team at TU Wien investigated various metallic alloys. A mixture of nickel and gold proved particularly promising. The researchers recently published their results in the journal Science Advances.

Using thermoelectrics to generate el...

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