This grant supports a two-year project to develop an automated serial grinder and image analysis system capable of rapid and high resolution 3-D imaging of small (cm scale) calcareous fossils imbedded within carbonate facies. Given the lack of suitable density contrast in such fossiliferous rocks, x-ray computed tomography will not work, neither will dissolution or disaggregation techniques, and standard manual serial sectioning polishing and subsequent photographing to ultimately build a 3-D image of the fossil morphology is extremely time consuming and greatly limits progress in studying such fossil remains. The PIs recent research has focused on manual examination of Neoproterozoic fossils which appear to be sponges found in stromatolitic facies of the Flinders Range of southeastern Australia and which appear to have survived throughout the so-called Snowball Earth time period where isotopic evidence from contemporaneous rocks suggest a global glaciation. A major outstanding question is how such organisms might have persisted in such an environment. The availability of a rapid method for study of early life forms from the Neoproterozoic would shed light on this question and the system would also be useful for study of other early life forms where the fossil remains and the host matrix offers little to no density contrast.
The development involves mating an imaging system to a commercially available serial grinder and developing the machine code and imaging routines to allow for automated serial grinding and 3-D fossil image construction and visualization. The project will involve a postdoc at Princeton, the PI and a colleague from the Princeton computational sciences department with expertise in image analysis. The project will also include a partnership with a private firm, SITU Research, that specializes in digital design and manufacturing. They will be responsible for the development of the machine code to mate the grinder with the imaging system. Undergraduate students will be engaged in sample preparation work for machine testing.
