Quantum researchers at Purdue are advancing an approach that could improve the resolution of nuclear magnetic resonance (NMR) spectroscopy to the atomic scale and may also have applications in developing quantum computing and quantum communications.

Discover how cutting-edge food processing technologies are transforming staple crops into nutrient-rich superfoods! A new study in Engineering explores microwave, ultrasound, and fermentation techniques that boost nutritional value and reduce waste. Learn how these innovations could revolutionize our diets and tackle global food challenges.

Ever wondered how lakes change over centuries? A new study in Engineering uses ancient DNA from lake sediments to reveal how urbanization and nutrient pollution have transformed aquatic plant and cyanobacteria communities in China’s Donghu Lake over nearly 200 years. Discover how these changes impact water quality and biodiversity!

In addressing the challenges encountered during the design of multi-pass cell (MPC) with dense spot pattern, the research team from Harbin Institute of Technology (HIT) has, for the first time, integrated the parallel non-dominated sorting genetic algorithm II (PNSGA-II) with the mathematical model of MPCs. This innovation has enabled the development of a high-performance multi-pass cell that simultaneously achieves long optical path length and high ratio of optical path length to volume — two key performance metrics that are often mutually restrictive.

Furthermore, the team constructed a light-induced thermoelectric spectroscopy (LITES) sensing system by incorporating a self-designed, high-performance round-head quartz tuning fork (QTF). Leveraging this integrated system, they successfully realized ultra-high sensitivity trace gas detection, with a minimum detection limit (MDL) reaching the ppt (10^-12) level.

Underwater optical imaging plays an irreplaceable role in fields such as marine exploration, resource development, environmental monitoring, and underwater archaeology. However in the underwater environment, light is affected by scattering and absorption, which not only leads to blurred image details and reduced contrast, but also severely limits the imaging range, and further makes it difficult for traditional technologies to acquire scene depth information. Since underwater scattered light inherently exhibits partial polarization characteristics, polarization technology can separate the target light and reflected light by analyzing the polarization state of light, thereby effectively suppressing the scattering effect of turbid water. Nevertheless, existing polarization underwater imaging methods mostly focus on "enhancing image clarity" and neglect the hidden depth cues in polarization images. Although binocular imaging is suitable for underwater 3D perception due to its simple hardware and low energy consumption, in turbid water, objects with low texture are prone to failure in feature point matching, resulting in wrong depth information. To address this, this study focus on the depth cues contained in underwater polarization imaging, integrates polarization features into the binocular imaging framework, and improves the accuracy and stability of depth estimation in turbid water, filling the research gap of polarization in underwater three-dimensional imaging utilizing polarization imaging technology.