X-ray and AFM Study of Volcanic Ash Particles Produces Risk-Assessment Protocol
A paper published by a joint Icelandic and Danish team in the journal, Proceedings of the National Academy of Sciences (April 25, 2011), provides evidence that a move to ground European aircraft was justified after an April 14, 2010, volcanic event allowed meltwaters from the Eyjafjallaökull glacier to mix with hot magma from the volcanic site, sending fine ash into the jet stream.
A paper published by a joint Icelandicand Danish team in the journal,Proceedings of the National Academyof Sciences (April 25, 2011), providesevidence that a move to groundEuropean aircraft was justifiedafter an April 14, 2010, volcanicevent allowed meltwaters from theEyjafjallaökull glacier to mix withhot magma from the volcanic site,sending fine ash into the jet stream.The team used X-ray photoelectronspectroscopy and atomic forcemicroscopy to assess toxicity risk andto determine the composition of theindividual ash particles.
The study involved taking a uniqueset of dry ash samples collectedimmediately after the explosive eventand comparing the samples withfresh ash from a later, more typicaleruption. Using nanotechniquescustom-designed for studying naturalmaterials, the team explored thephysical and chemical nature of theash to determine if fears about healthand safety were justified. Additionally,they developed a protocol that willserve for assessing risks during afuture event.
AI and Dual-Sensor Spectroscopy Supercharge Antibiotic Fermentation
June 30th 2025Researchers from Chinese universities have developed an AI-powered platform that combines near-infrared (NIR) and Raman spectroscopy for real-time monitoring and control of antibiotic production, boosting efficiency by over 30%.
Toward a Generalizable Model of Diffuse Reflectance in Particulate Systems
June 30th 2025This tutorial examines the modeling of diffuse reflectance (DR) in complex particulate samples, such as powders and granular solids. Traditional theoretical frameworks like empirical absorbance, Kubelka-Munk, radiative transfer theory (RTT), and the Hapke model are presented in standard and matrix notation where applicable. Their advantages and limitations are highlighted, particularly for heterogeneous particle size distributions and real-world variations in the optical properties of particulate samples. Hybrid and emerging computational strategies, including Monte Carlo methods, full-wave numerical solvers, and machine learning (ML) models, are evaluated for their potential to produce more generalizable prediction models.
