News EPFL

A new device for early diagnosis of degenerative eye disorders

Published:28.10.22 — Researchers at an EPFL lab have developed an ophthalmological device that can be used to diagnose some degenerative eye disorders long before the onset of the first symptoms. In early clinical trials, the prototype was shown to produce images with a sufficient degree of precision in just five seconds.

"Grätzel" solar cells achieve a new record

Published:27.10.22 — Scientists at EPFL have increased the power conversion efficiency of dye-sensitized solar cells ("Grätzel cells") beyond 15% in direct sunlight and 30% in ambient light conditions.

Education plays an essential role in research integrity

Published:26.10.22 — Ambrogio Fasoli, EPFL’s Associate Vice President for Research and Director of the Swiss Plasma Center, and Caroline Vandevyver, the Head of EPFL’s Research Office, spoke with us about the importance of research integrity, the challenges in this area and EPFL’s positions on the issues.

How a key immune protein is regulated in the cell

Published:25.10.22 — Scientists at EPFL have determined how a protein that is critical in our first line of immune defense is regulated in the cell to prevent autoinflammatory diseases.

Flexible surgical needle offers enhanced precision

Published:21.10.22 — Engineers from EPFL and INSA Strasbourg have developed an innovative surgical needle whose trajectory can be corrected on the fly, thanks to a flexible tip controlled with a simple button. Intended for use in image-guided surgery, the needle offers greater precision in surgeon’s movements and reduces the risk for patients.

Femtech, taboo-breaking innovations

Published:17.10.22 — Femtech is a term used to describe technologies and applications that focus on women’s health. While this new market offers immense growth potential, taboos around sexuality, periods and menopause continue to hamper progress. Here, we take a deep dive into the latest developments — at EPFL and beyond.

Machine learning predicts heat capacities of MOFs

Published:18.10.22 — Chemical engineers at EPFL have developed a machine-learning model that can accurately predict the heat capacity of the versatile metal-organic framework materials. The work shows that the overall energy costs of carbon-capture processes could be much lower than expected.