CrystalView CPCI

CrystalView CPCI

CrystalView CPCI Overview

The ultimate extension of polarized-light microscopy (PLM), AOT's CrystalView CPCI ushers in a new era of non-destructive testing of crystallographic structure.  CrystalView CPCI allows visualization of material microstructural properties correlated with failure and corrosion probabilities in high-strength and high-performance parts for aerospace, energy, architectural, and medical applications.  CrystalView CPCI works in air and, as a parallel imaging technique, at much higher speeds and fields-of-view than scanning alternatives.

Benefits

CrystalView CPCI is a fast and affordable sensor that allows users to spend more time analyzing images and less time preparing samples

Measure Non-Destructively

Visualize crystallographic microstructure without cutting your parts

Expand Field-of-View

Easily collect crystallographic orientation images 1" x 1" and larger

Simplify Sample Preparation

CrystalView CPCI is more tolerant of surface imperfections and suffers fewer non-indexed pixels than EBSD

Reduce Cost

Reduce sample preparation and labor costs

Applications

Applications 

CrystalView CPCI systems offer non-destructive, low-cost orientation imaging for grain-boundary & microtexture analysis, process development, quality control, failure analysis, and other applications with non-cubic metals including beryllium, magnesium, titanium, cobalt, zinc, tin, zirconium, and most of their alloys.  Systems can also be customized for oriented non-metals including fiber composites, textiles, and plastics.

Crystallographic Non-Destructive Testing Additive Manufacturing

Crystallographic polarization classificcation imaging (CPCI)

Sandia Lab News: Titanium Imaging Advances

Sandia materials scientist Joseph Michael was paired with AOT for the project and conducted a test using a scanning-electron microscope, current technology that can be difficult for small businesses to access because the microscopes are large, expensive and require experts to run. Metals characterization is one of Sandia's strengths -- we have been doing this for many years, Michael said.  "It's been energizing to me to see other techniques that can do some of the things that we do in the lab in a faster, higher-throughput way," he said. "It's been more than neat -- it's been exciting to see it all happen. If you can generate data that gets you 90% of the solution and do it quickly from an unprepared sample, that's a great place to be."

This excerpt is from Sandia National Laboratories's website regarding
CrystalView CPCI - Read the full article here.

CPCI Statistics

Gain Process Insight Through Machine Learning

Clusters PSTi Features ABC

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