The following overview is excerpted from: Hanna, R.D., and Ketcham, R.A. (2017) X-ray computed tomography of planetary materials: a primer and review of recent studies. Chemie der Erde – Geochemistry, 77, 547-572.
MuCalc is a Microsoft Excel workbook that can be used to compare the X-ray attenuation of various minerals. A mineral’s X-ray attenuation is primarily determined by its chemical formula and density, and the key to distinguishing between different minerals in a rock using XCT is to image at an energy where each mineral has a different X-ray attenuation (if possible). This workbook allows a user to determine if the various minerals in their sample will be distinguishable in the XCT data, and if there is an optimal energy at which to image in order to maximize their relative differences in attenuation. Within the workbook, the user selects the constituent minerals from a drop-down list and their X-ray attenuation versus energy (up to 500keV) are plotted together on a graph (see Figure for an example). The mass X-ray attenuation coefficients for the minerals in the workbook were retrieved using the NIST XCOM database, and the coefficients are multiplied by the mineral’s common density to obtain the final X-ray attenuation values.
The workbook currently contains a list of ∼250 common terrestrial and extraterrestrial minerals and native elements but detailed instructions are included on how to add a new mineral or element. In addition, there is a solid solution tool that can be used to define a new solid solution mineral out of existing minerals in the work- book and to add this to the permanent mineral list.
Papers Utilizing MuCalc
Cappuccio, F. (2021) Image analysis of x-ray computed tomographic datasets, quantification of porosity, and applications to understanding fracturing of rock masses. Ph.D. dissertation, The University of Otago, Geology, 158p.
Cooperdock, E.H.G., Hofman, F., Tibbetts, R.M.C., Carrera, A., Takase, A., and Celestian, A.J. (2022) Technical note: Rapid phase identification of apatite and zircon grains for geochronology using X-ray micro-computed tomography. Geochronology, 4, 501-515.
Ferraz da Costa, M., Kyle, J.R., Lobato, L.M. Ketcham, R.A., Figueiredo e Silva, R.C., and Fernandes, R.C. (2022) Orogenic gold ores in three-dimensions: A case study of distinct mineralization styles at the world-class Cuiabá deposit, Brazil, using high-resolution X-ray computed tomography on gold particles. Ore Geology Reviews, 140, 104584.
Howarth, G.H., Sobolev, N.V., Pernet-Fisher, J.F., Ketcham, R.A., Maisano, J.A., Pokhilenko, L.N., Taylor, D., and Taylor, L.A. (2015) 3-D X-ray tomography of diamondiferous mantle eclogite xenoliths, Siberia: A review. Journal of Asian Earth Sciences, 101, 39-67.
Liu, X., Yan, J., Zhang, X., Zhang, L., Ni, H., Zhao, W., Wei, B., Li, C., and Fu., L.-F. (2021) Numerical upscaling of multi-mineral digital rocks: Electrical conductivities of tight sandstones. Journal of Petroleum Science and Engineering, 201, 108530.
Louis, L. (2018) Integration of rock images and laboratory data through the lens of a new discipline. 52nd U.S. Rock Mechanics/Geomechanics Symposium, 17-20 June, Seattle, Washington.
Ma, L., Fauchille, A.L., Dowey, P.J., Pilz, F.F., Courtois, L., Taylor, K.G., and Lee, P.D. (2017) Correlative multi-scale imaging of shales: a review and future perspectives. Geological Society, London, Special Publications, 454, SP454-11.
Nwaila, G.T., Manzi, M.S.D., Zhang, S.E., Bourdeau, J.E., Bam, L.C., Rose, D.H., Maselela, K., Reid, D.L., Ghorbani, Y., and Durrheim, R.J. (2022) Constraints on the geometry and gold distribution in the Black Reef Formation of South Africa using 3D reflection seismic data and micro-X-ray computed tomography. Natural Resources Research, 31, 1225-1244.
Manzari, P., Mele, D., Tempesta, G., Agrosì, G (2023) New insights on the porosity and grain features of Al Haggounia 001, an impact-melt meteorite. Lithos, 438-439, 107015.
Никулин, И. И., Михайлова, Ю. А., Калашников, А. О., Грошев, Н. Ю.,Степенщиков, Д. Г., Пахомовский, Я. А., and Кадыров Р. И. (2023) Структурно-текстурные и вещественные свойства сульфидных медно-никелевых руд. ГЕОЛОГИЧЕСКИЙ ИНСТИТУТ КОЛЬСКОГО НАУЧНОГО ЦЕНТРА РОССИЙСКОЙ АКАДЕМИИ НАУК, 82p.
Pressley, L.A. (2022) Defects by design enhancing synthesis and characterization of quantum materials. Ph.D. dissertation, The Johns Hopkins University, Chemistry, 112p.
Pressley, L.A., Edey, D. Hanna, R., Chae, S. Heron, J.T., Khan, M.A., and McQueen, T. (2022) Informing quantum materials discovery and synthesis using X-ray micro-computed tomography. npj Quantum Materials, 7, 121
Rowe, T. B., Luo, Z. X., Ketcham, R. A., Maisano, J. A., & Colbert, M. W. (2016) X-ray computed tomography datasets for forensic analysis of vertebrate fossils. Scientific data, 3, 160040.
Saur, H. (2022) Microstructure investigation by means of X-ray computed tomography: Application to fine-grained clastic rocks. Ph.D. dissertation. Université de Pau et des Pays de l’Adour, Geosciences, 211p.
Штырляева, А. А., & Журавлев, А. В. (2016) Увеличение разрешающей способности рентгеновской микротомографии. Вестник института геологии Коми научного центра Уральского отделения РАН, 6.
Wilbur, Z.E., Udry, A., McCubbin, F.M., vander Kaaden, K.E., DeFelice, C., Ziegler, K., Ross, D.K., McCoy, T.J., Gross, J., Barnes, J.J., Dygert, N., Zeigler, R., Turrin, B.D., and McCoy, C. (2022) The effects of highly reduced magmatism revealed through aubrites. Meteoritics & Planetary Science, 57, 1387-1420
Zhang, M., Clark, B., King, A.J., Russell, S.S. ,and Lin, Y. (2021) Shape and porosity of refractory inclusions in CV3 chondrites: A micro-computed tomography (µCT) study. Meteoritics & Planetary Science, 56, 500-514