Learning about material integrity from statistical data

Feb 07, 2012
With chemical imaging data, scientists can better predict the molecular behavior of materials that must handle harsh environments, such as those found in space or in nuclear reactors.

Whether it protects space satellites or sequesters nuclear waste, scientists want to understand tiny features that could significantly alter how a material behaves. Locating microscopic defects can be done with powerful microscopes, but scientists want more. They want to use the microscopes to locate and understand the very molecules involved in the defects. Describing the location of the molecules and atoms in images often relies on statistics that can be inaccurate and expensive. The trick is to pick the statistical approach that accurately and economically describes the situation. Pick the wrong one, and the mathematical description won't match the microscope's image.

At Pacific Northwest National Laboratory, a team of scientists analyzed several statistical descriptors, different mathematical options that explain the distribution of items in an image, to help researchers select the right . They found that the simpler descriptions were inexpensive, but inaccurate. The more detailed, mathematically complex approaches gave higher accuracy, but used more computational time at greater cost.

"Get the right descriptor and you get the right, accurate, and true information," said Dr. Louis Terminello, Director of the Initiative at Pacific Northwest National Laboratory. "Next, the challenge is to make that accurate, expensive version more accurate and less expensive."

Using accurate and effective statistical descriptors lets scientists gather complex data from images. With this data, scientists can better predict the behavior of materials at the molecular level. If they know how a material will respond, they can select the properties they want and design the materials for them, reducing the need for expensive and time-consuming trial and error.

At Pacific Northwest National Laboratory, scientists analyzed statistical descriptors, different mathematical options that explain the distribution of items in an image, to help researchers select the right statistical information.

The structural information of some materials can be obtained from micrographs alone, but obtaining a representative image of complex and heterogeneous materials can be challenging. The team used two statistical descriptors to investigate microscopic images of the glass form and determined which gave the most accurate representation. They used the two-point correlation function, a statistic used to describe the distribution of particles in a microstructure, and lineal path functions.

"Our findings will enable scientists to predict the behavior of complex material systems," said Dr. Dongsheng Li, the PNNL scientist who led the study for the Laboratory's Chemical Imaging Initiative. "Scientists will be able to predict properties based on the ‘whole picture,' not just a small ‘typical' part anymore," Li added. 

The next steps will be to integrate this work into computer models that predict material properties based on multiple scale modeling and microstructure reconstruction. Data fusion and image enhancement will be combined with microstructure reconstruction to integrate different chemical imaging instrumentation.

Explore further: New process can convert human-generated waste into fuel in space

More information: Li DS, et al. 2012. "Comparison of Reconstructed Spatial Microstructure Images Using Different Statistical Descriptors." Computational Materials Science 51(1):437-444. doi:10.1016/j.commatsci.2011.07.056

add to favorites email to friend print save as pdf

Related Stories

World record in 3d-imaging of porous rocks

Oct 24, 2011

A team of physicists headed by Prof. Rudolf Hilfer at the Institute for Computational Physics (ICP) of the University of Stuttgart has established a world record in the field of three-dimensional imaging of porous materials. ...

Down-and-dirty details of climate modeling

May 04, 2011

For the first time, researchers have developed a comprehensive approach to look at aerosols—those fine particles found in pollution—and their effect on clouds and climate. Scientists from Pacific ...

The proof is in the clouds

Jan 26, 2012

For most people, clouds are just an indication of whether it's a "good" or "bad" day. A team of scientists from Pacific Northwest National Laboratory found that certain clouds hold the key to climate behavior ...

Computational actinide chemistry: Are we there yet?

Aug 21, 2007

Ever since the Manhattan project in World War II, actinide chemistry has been essential for nuclear science and technology. Yet scientists still seek the ability to interpret and predict chemical and physical ...

A better look at the brain

Aug 23, 2011

The challenge of Dr. Mark Ellisman's life is understanding how the brain works. He wants to know how the interplay of structural, chemical, and electrical signals in and between cells of nervous tissue gives rise to behavior. To ...

Recommended for you

Electronic switches on the molecular scale

Nov 25, 2014

A molecular electronic switch is a junction created from individual molecules that can alternate between two or more stable states, making the switch act as a conductor or an insulator. These switches show ...

Mimicking photosynthesis with man-made leaves

Nov 25, 2014

Scientists have long been trying to emulate the way in which plants harvest energy from the sun through photosynthesis. Plants are able to absorb photons from even weak sunlight using light antennae made ...

User comments : 0

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.