New Ecofriendly Spectrophotometric Method Boosts Accuracy in Veterinary Drug Analysis
A recent study showcases a cost-effective, ecofriendly UV spectrophotometric method enhanced with dimension reduction algorithms to accurately quantify veterinary drugs dexamethasone and prednisolone, offering a sustainable alternative to traditional analysis techniques.
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.
New Imaging Techniques Explored to Assess Quality of Sustainable Fertilizers
Researchers from Cranfield University and partners from industry demonstrated the feasibility of using advanced, non-destructive imaging techniques to analyze and standardize organo-mineral fertilizers.
Mediterranean Origins of Red Coral Artifacts in Xinjiang Reveal Ancient Silk Road Trade Links
A new study published in Minerals reveals that red coral artifacts unearthed in Xinjiang’s Shengjindian cemetery originated from the western Mediterranean, highlighting early Silk Road trade and long-distance cultural exchange during the Han Dynasty.
Polystyrene and UVC Sterilization Tested with Spectroscopy and Luminescence Tools
June 25th 2025A team of researchers from Spanish institutions has found that polystyrene used in healthcare packaging shows strong resistance to UVC sterilization, with minimal chemical degradation detected using FT-IR and Raman spectroscopy.
Combining AI and NIR Spectroscopy to Predict Resistant Starch (RS) Content in Rice
A new study published in the journal Food Chemistry by lead authors Qian Zhao and Jun Huang from Zhejiang University of Science and Technology unveil a new data-driven framework for predicting resistant starch content in rice