More than 400 underwater sites in the United States are potentially contaminated with unexploded ordnance — weapons that did not explode upon deployment. Connor Hodges studies the changes in the acoustic characteristics of these UXOs after they have been subject to corrosion and biofouling to help detect them underwater and will discuss the use of acoustics for corroded UXO recovery on Monday, May 19, at the 188th ASA Meeting.

A research team from ct.qmat, in a collaboration with an international team, has detected optical quasiparticles on the surface of an antiferromagnetic quantum material for the very first time. Previously, scientists only knew that these excitons could form inside these materials. The breakthrough results have been published in Nature Materials.

This article examines the potential of Artificial Intelligence-driven Distributed Acoustic Sensing (AI+DAS) technology in engineering applications. Based on fiber optic monitoring, DAS enables real-time acoustic signal monitoring by detecting disturbances along the fiber, offering long measurement distances, high spatial resolution, and a large dynamic range. The article outlines the basic principles and demodulation methods of DAS using Φ-OTDR technology, highlighting AI's role in data processing and event recognition. By integrating AI algorithms, DAS systems enhance monitoring accuracy and reliability. Additionally, the article reviews AI+DAS applications across various fields, including engineering and geology, and discusses challenges such as model complexity and resource demands. Overall, it aims to foster interdisciplinary collaboration and support digital transformation in industrial scenarios.