Have you ever wished you could travel inside a stone? It may seem more like magic than science, but Princeton scientists have discovered a way to make it (almost) true.

With an industrial grinder plus a super-high-resolution camera, Princeton geoscientists Adam Maloof and Akshay Mehra can deconstruct stone samples and make three-dimensional electronic versions that scientists are able to look at from any angle. In addition, they’ve developed software which enables the computer to segment images and isolate objects without human bias.

Using this technology in combination with detailed field observations, they analyzed a thin-shelled creature that lived over a lot of the planet about 545 million years back, Cloudina, generally agreed to be the first “biomineralizer,” an organism which can produce a shell or bones along with soft tissue.

While preceding researchers had argued that Cloudina were reef builders, Maloof and Mehra managed to utilize their 3-D reconstruction of their animals’ delicate tube-like structures to conclude that the fossils had been transported from other areas, suggesting that Cloudina played only a minor role in the earliest reef systems.

“I thought going in we would learn all sorts about this amazing first biomineralizer and first reef builder, but Cloudina turned out to be more like a reef dweller,” said Maloof, an associate professor of geosciences.

Meet GIRI

Almost five years ago, Maloof a nd Situ Studio collaborator Brad Samuels assembled the technology to create what he now calls “flipbooks,” digital renderings that move through more than a thousand wafer-thin slices through a rock.

Known as “GIRI” or “the grinder,” the Princeton Grinding Imaging and Reconstruction Instrument is an answer to geologists’ longstanding urge to understand what stones look like on the interior.

“Forever – since Darwin – people have tried to figure out how fossils look in 3-D, when they’re embedded in rock and it’s hard to get them out,” Maloof said.

“People did serial sections just like this way back then – but perhaps not at this scale – where they would grind away a little rock, draw it, grind a little more, draw it. … It can be incredibly time-consuming.”

Enter GIRI, that can cut pieces as thin as a few microns (less than one per cent of a millimeter) and may operate 24 hours a day for weeks on end. As every piece takes approximately 90 minutes to cut and picture, researchers need to choose between scale and speed. Most of the specimens Maloof and Mehra have imaged are cut into 30-micron pieces, about a third the thickness of a human hair. A typical inch-thick, 1,500-slice sample takes approximately a day and a half to grind and picture; during that time, the operator should replace machine fluids and clean the wipers (which clear the surface after every cut) just once.

“The process is destructive,” Maloof said.

“Dinosaur bones, lunar samples – there are certain specimens that people are less likely to give us. It hasn’t really stopped us, because most samples are not precious. Cloudina, there are zillions of them – we could never grind them all.”

GIRI can generate a 3-D rendering of any solid item, whether it has the density differences required for successful X-ray computed microtomography (generally called X-ray CT or Micro CT). In addition, as you are taking a super-high-resolution photo with each piece, you are constantly seeing the stone itself, not only the density model that remote sensing could provide.

“It’s destructive of course, that’s the disadvantage, but what’s so nice is that you get to see photographs and make direct observations,” Maloof. “That’s what’s been so life-changing to me: I love that it’s not a model. You can just see it. On any given slice, if you find something great, you can just find the slice and say, ‘What did it look like?’ …We’re on a virtual tour inside, rather than looking at waveforms and trying to interpret them.”

And while GIRI does pulverize the sample, it preserves every detail in its own high-resolution pictures, Maloof stated, which arguably makes it less harmful than other procedures. It also preserves the structural information which shows how the rocks formed. “When people have attempted to get 3-D information from rocks like this that are opaque to X-rays, they’ve always tried to dissolve the material out. But then you lose all the in-situ information. You don’t know how they grew. They have no relationship to each other. And you don’t know how they are related to perhaps smaller or less resilient parts. You may preferentially dissolve the ornamentation or other key details. So this is a way to keep them in their habitat while still trying to figure out what they looked like.”

In the years since Maloof constructed GIRI, he and his research group have made physical progress. These include redesigning and replacing the camera housing in addition to the mechanism for wiping and preparing the stone surface for photographing after every grind. They’ve additionally installed screens for humidity and temperature to document conditions during each photograph. The researchers also decrease the grind period per piece in seven minutes to 90 seconds. The biggest changes, however, have been advancing software to run the device and examine the output.

Using a group of interactive MATLAB scripts and Applescript works, the management computer is now able to send and receive signals from your grinder, activate the camera, and confirm image capture, while GIRI is in operation, Mehra stated.

“From the ground up, Akshay has designed machine-learning solutions to make the process of image segmentation – differentiating fossils from matrix, cement, etc., in every slice – automated and reliable,” stated Maloof. “He has developed techniques that ultimately will be important for any tomographic applications, including X-ray CT. Akshay also has developed ways to make quantitative measurements in the reconstructed 3-D volumes. You’d be surprised how much 3-D modeling out there only leads to visualization and qualitative interpretation, whereas Akshay actually measures the size, shape and 3-D orientation of these critters.”

Using the applications he has developed, “We can directly measure these Cloudina specimens,” stated Mehra. “We can directly measure what directions the tubes are bending, what their diameters are, what their curvatures are – none of them are actually straight – and based on that information, we can determine whether they are in situ or not in situ.”

Mehra has also made neural networks to detect rock types by only their visual attributes: colour and texture. After the consumer defines which “classes” exist in a small number of pictures from the stack – fossil versus matrix, for instance, or the crucial minerals in a metamorphic stone – the system can then predict if a pixel belongs to a given class with larger than 90 percentage precision.

And with all of that, he said, graduate and undergraduate students can typically be trained to run GIRI in roughly a day.

Scientists from across the world have reached out to Maloof and Mehra to request virtual, visual excursions within their particular specimens. Paleontologists are expecting to inspect the delicate structures from the first life on Earth, the massive assortment of early shelled creatures, the very first fish, the very first land creatures, the inner structure of ammonites and other creatures with inner buoyancy systems, and even dinosaur bones. Planetary scientists have started analyzing meteorites using GIRI to check at tiny grains known as chondrules that contain traces to how the planets formed. Engineers are analyzing possible reservoir rocks for carbon sequestration and grinding graphite batteries to inspect the 3-D structure of porosity inside the carbon.

There’s no limit to the contributions GIRI can make, stated Maloof. “This represents five years of work. It’s the only instrument in the world like it.”

Journal Reference:

1. Akshay Mehra, Adam Maloof. Multiscale strategy shows thatCloudinaaggregates are detritus rather than in situ reef structures. Proceedings of those National Academy of Sciences, 2018; 201719911 DOI: 10.1073/pnas.1719911115