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microphotonics

Serving scientific and industrial research for over 27 years

Covid-19 Update – We will continue to offer our micro-CT support services remotely during this time. Check our additional resources here.

Micro-CT Scanners

MICRO-CT SCANNERS

Explore our range of quality Micro-CT scanners. 20+ years of market experience in meeting and supporting research needs. Learn More

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Graphene

GRAPHENE

High quality graphene production from large sheets to roll to roll production. Learn More

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Laue Diffraction

ALL PRODUCTS

Explore our range of QCM, Laue Diffraction Systems, and Vacuum Components. Learn More

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LEARNING CENTER

A complete resource learning center for all of your project needs.Learn More

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microphotonics

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HOW TO CHOOSE THE RIGHT MICRO-CT SCANNER

A step-by-step guide to finding the best Micro CT scanner for your facility.

“Purchasing a micro-CT has redefined our research opportunities, making it a great investment for our research environment”.
Dr. Alan Carlson
UPDATES & NEWS

Micro-CT Applications for Product Development

3D Micro-CT scan of a polyelectrolyte complex (PEC) film used as an excipient for the formulation of active agents in drug delivery systems.…

Customer Feature: Micro-CT for Personal Hygiene Product Development

Micro-CT has been found to be an effective tool for studying and contributing to improvements of consumer hygiene products such as tampons.  Tampons…

Micro-CT Examination of a Tree Mushroom

Polypores are a group of fleshy fungi with pores or tubes underneath. Taxonomically, the polypores are complicated and not completely understood, with an…

MICRO-CT NEWS, ARTICLES, AND INFORMATION

3-D reconstructions and visualizations based on micro-CT imagery of a Hericium coralloides basidioma sample. A.Fixed and critical-point dried sample. Three histo-anatomical features can be recognized on the optical image (Pallua et al.2014): basal branch (1), side branches (2), and end branch structures (3). B. 3-D surface rendered image of the micro-CT-dataset processed by a connected component algorithm to ignore irrelevant structure such as small pieces caused by the inherent image noise. C. 3-D surface rendered image of the spatial thickness distribution (0–357mm). Credit: Pallua, Johannes D., et al, Mycologia, 20 Jan 2017.

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