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Ecole Polytechnique Fédérale de Lausanne


Robotic interface masters a soft touch

EPFL researchers have developed a haptic device called SORI that can accurately recreate the softness of various materials, from marshmallows to beating hearts. This technology has potential applications in medicine, such as training medical students to detect cancerous tumors and providing sensory feedback to surgeons using robots.

SourceEcole Polytechnique Fédérale de Lausanne·JournalProceedings of the National Academy of Sciences·TypeExperimental study·DateMar 11, 2024

Nanodevices can produce energy from evaporating tap or seawater

EPFL researchers have discovered that nanoscale devices harnessing the hydroelectric effect can harvest electricity from the evaporation of fluids with higher ion concentrations than purified water. This breakthrough reveals a wide range of applications for hydrovoltaic devices, including powering sensors and generating clean water.

SourceEcole Polytechnique Fédérale de Lausanne·JournalDevice·TypeExperimental study·DateMar 6, 2024

A new theoretical development clarifies water's electronic structure

Researchers from EPFL have made significant strides in deciphering the electronic structure of water using computational methods that go beyond current approaches. The study accurately determines water's ionization potential, electron affinity, and band gap, essential for understanding its interactions with light and substances.

SourceEcole Polytechnique Fédérale de Lausanne·JournalProceedings of the National Academy of Sciences·DateFeb 26, 2024

AI-driven method helps improve quality assurance for wind turbines

Researchers have developed an AI-driven method to detect possible anomalies beneath the surface of wind turbine blades using patented radar technology. The non-destructive approach supports agile data acquisition and analysis, enabling faster detection of manufacturing defects and improved overall quality assurance.

SourceEcole Polytechnique Fédérale de Lausanne·JournalMechanical Systems and Signal Processing·TypeComputational simulation/modeling·DateFeb 22, 2024

Training algorithm breaks barriers to deep physical neural networks

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, decreasing energy consumption and eliminating the need for a digital twin. This approach is more biologically plausible and shows improved speed, robustness, and reduced power consumption compared to other methods.

SourceEcole Polytechnique Fédérale de Lausanne·JournalScience·TypeExperimental study·DateDec 7, 2023

Laser additive manufacturing: Listening for defects as they happen

A team of researchers at EPFL has successfully challenged the reliability of acoustic monitoring for detecting defects in laser additive manufacturing. By analyzing shifts in the acoustic signal during regime transitions, they identified defects in real-time, providing a cost-effective solution to improve product quality and integrity.

SourceEcole Polytechnique Fédérale de Lausanne·JournalNature Communications·TypeExperimental study·DateDec 5, 2023

First 2D semiconductor with 1000 transistors developed at EPFL Switzerland: Redefining energy efficiency in data processing

EPFL researchers have developed the world's first large-scale in-memory processor using 2D semiconductor materials, which could substantially cut the ICT sector's energy footprint. The processor combines data processing and storage onto a single device, reducing energy waste and improving efficiency.

SourceEcole Polytechnique Fédérale de Lausanne·JournalNature Electronics·DateNov 13, 2023

From chaos to light

A team of researchers from EPFL has found a way to harness the unique features of chaotic frequency combs to implement unambiguous and interference-immune massively parallel laser ranging. This innovative approach offers significant advantages over conventional methods, enabling hundreds of multicolor independent optical carriers.

SourceEcole Polytechnique Fédérale de Lausanne·JournalNature Photonics·TypeExperimental study·DateJul 20, 2023