Introducing the Metrohm TacticID-1064 ST
TacticID-1064 ST is a reliable partner, designed to keep up with the work, no matter how challenging the environment.
Metrohm is proud to introduce the new TacticID-1064 ST, an innovative device for material identification using see-through Raman technology. 1064 nm laser technology combines with dedicated sampling accessories and advanced data algorithms to analyze substances through many containers. By quickly separating the signature of the container from its contents, the Metrohm TacticID-1064 ST delivers accurate results and reduces operator exposure to potentially harmful materials.
Designed for optimized and efficient measurements, the TacticID-1064 ST is compact and user-friendly – eliminating the need to set up complicated methods. An innovative accessory recognition feature ensures seamless operation and minimizes operator training. This handheld device provides reliable results at the sample contact point, guaranteeing faster outcomes, reduced downtime, and heightened confidence in the material identification process.
Chemical identification in quality control, forensics, hazmat, and customs checkpoints demands precise material identification. With its extensive Raman library and onboard guides, the TacticID-1074 ST is designed to handle a wide range of substances during an extended shift or at the site of a dangerous chemical spill. It delivers accurate results when it matters most.
Metrohm
www.metrohm.com/en_us.html
Remembering Engineering Pioneer Sir David McMurtry
December 16th 2024The world of engineering and innovation mourns the loss of a towering figure with the passing of Sir David McMurtry, CBE, RDI, FREng, FRS, CEng, FIMechE, co-founder and Non-Executive Director of Renishaw. Known for his brilliance, humility, and groundbreaking contributions to metrology and manufacturing, McMurtry leaves a legacy that has profoundly shaped modern engineering.
New Fluorescent Raman Technique Enhances Detection of Microplastics in Seawater
November 19th 2024A novel method using fluorescence labeling and differential Raman spectroscopy claims to offer a more efficient, accurate approach to detect microplastics in seawater. Developed by researchers at the Ocean University of China, this method improves both the speed and precision of microplastic identification, addressing a key environmental issue affecting marine ecosystems.
How Raman Spectroscopy Could Transform Hematology Diagnostics
November 5th 2024A leading-edge review highlights the potential of Raman spectroscopy for fast, non-invasive diagnostics in hematology and oncology. By mapping biochemical fingerprints, this technology could one day help detect cancers, monitor treatments, and even predict immune responses.
FT-NIR and Raman Spectroscopic Methods Enhance Food Quality Control
October 28th 2024A recent study showcases the potential of Fourier transform near-infrared (FT-NIR) spectroscopy and spatially offset Raman spectroscopy (SORS) in detecting raw material defects in hazelnuts caused by improper storage conditions. FT-NIR spectroscopy proved especially effective, while SORS offered complementary insights in certain scenarios. These spectroscopic methods could modernize the speed and accuracy of hazelnut inspections in the food industry.
Breakthrough in Amino Acid Differentiation with Enhanced Raman Technology
October 8th 2024Researchers from the Shanghai Institute of Technology have developed a leading-edge method using surface-enhanced Raman scattering (SERS) to accurately differentiate between amino acid enantiomers. This breakthrough could revolutionize applications in pharmaceutical synthesis, disease diagnosis, and quality control of chiral compounds.
Next-Gen Mineral Identification: Fusing LIBS and Raman Spectroscopy with Machine Learning
September 17th 2024A pioneering study integrates laser-induced breakdown spectroscopy (LIBS) with Raman spectroscopy (RS) and applies machine learning (ML) to achieve exceptional accuracy in mineral identification. The combined approach not only leverages the strengths of both techniques but also enhances classification precision, achieving up to 98.4% accuracy.
