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Sunday, August 20, 2017

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UH, NASA study 4.4 billion-year-old moon samples


Using the Micro CT Machine and special computer software, UH professors were able to study the internal structure of the lunar sample without causing damage. | Isabel Pen/The Cougar

Inside a machine the size of a refrigerator, a 3.6 millimeter rock sat on the head of a nail, hundreds of thousands of miles away from its home on the moon.

On Friday at UH’s Energy Research Park, Professors Lori Hathon and Michael Myers examined lunar samples collected from the Apollo missions in hopes of gaining new insight into the formation of the moon.

With their recently purchased Micro CT machine, they were able to examine the internal structures of the rock without causing damage. The machine, which is usually used to examine pore structures of oil reservoir core samples, uses X-ray microscopy to penetrate the layers of rock and create a 3-D computer reconstruction.

“Without having to destroy the sample, we can look at a region of interest at an extremely high resolution,” said Hathon, an assistant professor of petroleum engineering. “You look at this tiny sample and you have no idea, but you can interrogate the interior of it with this tool.”

Their findings provide an inside look at not only the composition of the moon, but also the story of how the moon came to be.

“This scan gives us clues to the violent history of the formation of the moon,” said Daniel Coleff, a Ph.D. student and NASA employee who orchestrated the collaboration. “The presence or absence of certain structures, like bubbles or patchworks of high and low density rock in a sample can provide a lot of information about the fashion and environment in which the rocks were formed.”

Hathon hopes to receive permission to analyze NASA’s samples using a transmitted light microscope to gain further insight into the moon’s composition.

“If we were to scan the sample at different energies, we could unravel the mineral composition, understand how these phases are distributed in three dimensions and build a model for predicting properties of the moon,” Hathon said.

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