Since its inception, CRAIC has specialized in optical tools for the ultraviolet, visible, and near-infrared regions. Products include microspectrophotometers (also known as microspectrometers or microscope spectrometers) that is able to take spectra of samples smaller than a micron. CRAIC has also designed and built UV-visible-NIR range microscopes. Full spectral range fluorescence, transmission, and reflectance spectra and images can be acquired from any microscopic sample non-destructively and without contact with these tools. CRAIC manufactures both scientific grade systems in addition to specialized systems for industries such as semiconductor inspection and pharmaceutical metrology. CRAIC also makes NIST Traceable Standards, the only ones in the world specifically designed for microspectrophotometers, and specialized software packages.
CRAIC specializes in the following micro-analytical techniques:
FLEX PRO™ from CRAIC Technologies: Flexible Microspectroscopy
GeoImage™: Fast and Accurate Energy Grading of Coal, Kerogen and Petroleum Source Rock from CRAIC Technologies
CRAIC Technologies UVM-1 Ultraviolet Microscope
The TheiaVu™ Series is a range of benchtop inspection systems that allow the user to take a wide variety of measurements, and to record repeatable, reliable data to improve processes.
KLA’s Filmetrics F40 allows you to transform your benchtop microscope into an instrument to measure thickness and refractive index.
This product profile describes the properties and applications of the ProMetric® I-SC Solution Imaging Colorimeter.
Dr. David Dung
We spoke with University of Bonn spin-off Midel Photonics, a start-up company whose laser beam shaping technology is hoping to sharpen up the laser industry.
Matthias Sachsenhauser, Ph.D.
Following Laser World of Photonics 2022, we spoke with Matthias Sachsenhauser from Hamamatsu Photonics about the role of laser-driven light sources in the future of the photonics sector.
Dr. Keith Paulsen
AZoOptics speaks to Dr. Keith Paulsen about the importance of breast cancer detection and the introduction of his team's deep-learning algorithm that associates spatial images of tissue optical properties with optical signal patterns measured during an imaging experiment or patient exam.